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Pronóstico global de los diagnósticos de trastorno del espectro autista en edad preescolar

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Referencias

Referencias de los estudios incluidos en esta revisión

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Anderson 2009 {published data only}10.1007/s10802-009-9326-0

Anderson DK, Lord C, Risi S, DiLavore PS, Shulman C, Thurm A, et al. Patterns of growth in verbal abilities among children with autism spectrum disorder. Journal of Consulting and Clinical Psychology 2007;75(4):594-604. CENTRAL [DOI: 10.1037/0022-006X.75.4.594] [PMID: 17663613]
Anderson DK, Oti RS, Lord C, Welch K. Patterns of growth in adaptive social abilities among children with autism spectrum disorders. Journal of Abnormal Child Psychology 2009;37(7):1019-34. CENTRAL [DOI: 10.1007/s10802-009-9326-0] [PMCID: PMC2893550] [PMID: 19521762]
Bedford R, Pickles A, Lord C. Early gross motor skills predict the subsequent development of language in children with autism spectrum disorder. Autism Research 2016;9(9):993-1001. CENTRAL [DOI: 10.1002/aur.1587] [PMCID: PMC5031219] [PMID: 26692550]
Gotham K, Pickles A, Lord C. Trajectories of autism severity in children using standardized ADOS scores. Pediatrics 2012;130(5):e1278-84. CENTRAL [DOI: 10.1542/peds.2011-3668] [PMCID: PMC3483889] [PMID: 23090336]
Gotham KO. Defining and quantifying severity of impairment in autism spectrum disorders across the lifespan. Doctoral Dissertation, The University of Michigan 2011;71(11-B):1-171. CENTRAL
Hus V, Taylor A, Lord C. Telescoping of caregiver report on the Autism Diagnostic Interview - Revised. Journal of Child Psychology and Psychiatry 2011;52(7):753-60. CENTRAL [DOI: 10.1111/j.1469-7610.2011.02398.x] [PMCID: PMC3549439] [PMID: 21410473]
Lord C, Luyster R, Guthrie W, Pickles A. Patterns of developmental trajectories in toddlers with autism spectrum disorder. Journal of Consulting and Clinical Psychology 2012;80(3):477-89. CENTRAL [DOI: 10.1037/a0027214] [PMID: 22506796] [PMID: PMC3365612]
Lord C, Shulman C, DiLavore P. Regression and word loss in autistic spectrum disorders. Journal of Child Psychology and Psychiatry 2004;45(5):936-55. CENTRAL [DOI: 10.1111/j.1469-7610.2004.t01-1-00287.x] [PMID: 15225337]
Lord C. Follow-up of two-year-olds referred for possible autism. Journal of Child Psychology and Psychiatry 1995;36(8):1365-82. CENTRAL [DOI: 10.1111/j.1469-7610.1995.tb01669.x] [PMID: 8988272]
Luyster R, Qui S, Lopez K, Lord C. Predicting outcomes of children referred for autism using the MacArthur-Bastes Communicative Development Inventory. Journal of Speech, Language, and Hearing Research 2007;50(3):667-81. CENTRAL [DOI: 10.1044/1092-4388(2007/047)] [PMID: 17538108]
Pickles A, Anderson DK, Lord C. Heterogeneity and plasticity in the development of language: a 17‐year follow‐up of children referred early for possible autism. Journal of Child Psychology and Psychiatry 2014;55(12):1354-62. CENTRAL [DOI: 10.1111/jcpp.12269] [PMID: 24889883]
Richler J, Huerta M, Bishop SL, Lord C. Developmental trajectories of restricted and repetitive behaviors and interests in children with autism spectrum disorders. Developmental Psychopathology 2010;22(1):55-69. CENTRAL [DOI: 10.1017/S0954579409990265] [PMCID: PMC2893549] [PMID: 20102647]
Thurm A, Lord C, Lee L-C, Newschaffer C. Predictors of language acquisition in preschool children with autism spectrum disorders. Journal of Autism and Developmental Disorders 2007;37(9):1721-34. CENTRAL [DOI: 10.1007/s10803-006-0300-1] [PMID: 17180717]

Baghdadli 2012 {published data only}

Baghdadli A, Assouline B, Sonié S, Pernon E, Darrou C, Michelon C, et al. Developmental trajectories of adaptive behaviors from early childhood to adolescence in a cohort of 152 children with autism spectrum disorders. Journal of Autism and Developmental Disorders 2012;42(7):1314-25. CENTRAL [PMID: 10.1007/s10803-011-1357-z] [PMID: 21928042]
Baghdadli A, Michelon C, Pernon E, Picot M C, Miot S, Sonie S, Rattaz C, Mottron L. Adaptive trajectories and early risk factors in the autism spectrum: A 15-year prospective study. Autism Research 2018;11(11):1455-1467. CENTRAL
Baghdadli A, Picot MC, Michelon C, Bodet J, Pernon E, Burstezjn C, et al. What happens to children with PDD when they grow up? Prospective follow-up of 219 children from preschool age to mid-childhood. Acta Psychiatrica Scandinavica 2007;115(5):403-12. CENTRAL [DOI: 10.1111/j.1600-0447.2006.00898.x] [PMID: 17430419]
Baghdadli A, Picot MC, Pry R, Michelon C, Burzstejn C, Lazartigues A, et al. What factors are related to a negative outcome of self-injurious behaviour during childhood in pervasive developmental disorders? Journal of Applied Research in Intellectual Disabilities 2008;21(2):142-9. CENTRAL [DOI: 10.1111/j.1468-3148.2007.00389.x]
Darrou C, Pry R, Pernon E, Michelon C, Aussilloux C, Baghdadli A. Outcome of young children with autism: does the amount of intervention influence developmental trajectories? Autism 2010;14(6):663-77. CENTRAL [DOI: 10.1177/1362361310374156] [PMID: 21149421]
Pry R, Petersen AF, Baghdadli A. In search of prediction factors for autism spectrum disorders: an impossible task? Psychology 2012;3(11):997-1003. CENTRAL [DOI: 10.4236/psych.2012.311150]
Pry R, Petersen AF, Baghdadli AM. On general and specific markers of lexical development in children with autism from 5 to 8 years of age. Research in Autism Spectrum Disorders 2011;5(3):1243-52. CENTRAL [DOI: 10.1016/j.rasd.2011.01.014]

Benedetto 2021 {published data only}

Benedetto L, Cucinotta F, Maggio R, Germano E, De Raco R, Alquino A, et al. One-year follow-up diagnostic stability of autism spectrum disorder diagnosis in a clinical sample of children and toddlers. Brain Sciences 2021;11(1):1-15. CENTRAL

Bopp 2006 {published data only}

Bopp KD, Mirenda P, Zumbo BD. Behavior predictors of language development over 2 years in children with autism spectrum disorders. Journal of Speech, Language, and Hearing Research 2009;52(5):1106-20. CENTRAL [DOI: 10.1044/1092-4388(2009/07-0262)] [PMID: 19797136]
Bopp KD. Behaviour predictors of child development and parenting stress trajectories of children with autism [Doctoral dissertation]. Vancouver (BC): University of British Columbia, 2006. CENTRAL
Smith V, Mirenda P, Zaidman-Zait A. Predictors of expressive vocabulary growth in children with autism. Journal of Speech, Language, and Hearing Research 2007;50(1):149-60. CENTRAL [DOI: 10.1044/1092-4388(2007/013)] [PMID: 17344556]

Brian 2016 {published data only}

Brian J, Bryson SE, Smith IM, Roberts W, Roncadin C, Szatmari P, et al. Stability and change in autism spectrum disorder diagnosis from age 3 to middle childhood in a high-risk sibling cohort. Autism 2016;20(7):888-92. CENTRAL [DOI: 10.1177/1362361315614979] [PMID: 26685198]

Chu 2017 {published data only}

Chu C-L, Chiang C-H, Wu C-C, Hou Y-M, Liu J-H. Service system and cognitive outcomes for young children with autism spectrum disorders in a rural area of Taiwan. Autism 2017;21(5):581-91. CENTRAL [DOI: 10.1177/1362361316664867] [PMID: 28610539]

Demb 1989 {published data only}

Demb HB, Weintraub AG. A five-year follow-up of preschool children diagnosed as having an atypical pervasive developmental disorder. Journal of Developmental & Behavioral Pediatrics 1989;10(6):292-8. CENTRAL [PMID: 2600185]

DeWaay 2010 {published data only}

DeWaay RJ. Parents' perceptions of treatment effectiveness in a DIR/Floortime home intervention [Doctoral dissertation]. Pasadena (CA): Fuller Theological Seminary, 2010. CENTRAL [UMI NUMBER: 3485984]

Dietz 2007 {published data only}

Dietz C, Swinkels SH, Buitelaar JK, Van Daalen E, Van Engeland H. Stability and change of IQ scores in preschool children diagnosed with autistic spectrum disorder. European Child & Adolescent Psychiatry 2007;16(6):405-10. CENTRAL [DOI: 10.1007/s00787-007-0614-3] [PMID: 7401607]

Eaves 2004 {published data only}

Eaves LC, Ho HH. The very early identification of autism: outcome to age 4 1/2-5. Journal of Autism and Developmental Disorders 2004;34(4):367-78. CENTRAL [DOI: 10.1023/b:jadd.0000037414.33270.a8] [PMID: 15449513]

Elmose 2014 {published data only}

Elmose M, Trillingsgaard A, Jørgensen M, Nielsen A, Bruhn SS, Sørensen EU. Follow-up at mid-school age (9-13 years) of children assessed for autism spectrum disorder before the age of four. Nordic Journal of Psychiatry 2014;68(5):362-8. CENTRAL [DOI: 10.3109/08039488.2013.846411] [PMID: 24199947]

Flanagan 2010 {published data only}

Flanagan HE, Perry A, Freeman NL. Effectiveness of large-scale community-based intensive behavioral intervention: a waitlist comparison study exploring outcomes and predictors. Research in Autism Spectrum Disorders 2012;6(2):673-82. CENTRAL [DOI: 10.1016/j.rasd.2011.09.011]
Flanagan HE. The Impact of Community-Based Intensive Behavioural Intervention [PhD thesis]. Toronto (ON): York University, 2010. CENTRAL

Freeman 2004 {published data only}

Freeman LJ. Functional Impairment in PDD-NOS: Predicting Outcome at a Two-Year Follow-up [PhD thesis]. Windsor (ON): University of Windsor, 2004. CENTRAL

Gabriels 2007 {published data only}

Gabriels RL, Ivers BJ, Hill DE, Agnew JA, McNeill J. Stability of adaptive behaviors in middle-school children with autism spectrum disorders. Research in Autism Spectrum Disorders 2007;1(4):291-303. CENTRAL [DOI: 10.1016/j.rasd.2006.11.004]

Gillberg 1990 {published data only}

Gillberg C, Ehlers S, Schaumann H, Jakobsson G, Dahlgren SO, Lindblom R, et al. Autism under age 3 years: a clinical study of 28 cases referred for autistic symptoms in infancy. Journal of Child Psychology and Psychiatry 1990;31(6):921-34. CENTRAL [DOI: 10.1111/j.1469-7610.1990.tb00834.x] [PMID: 2246342]

Giserman‐Kiss 2020 {published data only}

Giserman-Kiss I, Carter AS. Stability of autism spectrum disorder in young children with diverse backgrounds. Journal of Autism & Developmental Disorders 2020;50(9):3263-75. CENTRAL
Giserman-Kiss I. Diagnostic stability of autism spectrum disorder in young children with diverse backgrounds [Doctoral Dissertation]. Boston: University of Massachusetts, 2018. CENTRAL [PROQUEST NUMBER: 10743610]

Gonzalez 1993 {published data only}

Gonzalez NM, Alpert M, Shay J, Campbell M, Small AM. Autistic children on follow up - change of diagnosis. Psychopharmacology Bulletin 1993;29(3):353-8. CENTRAL [PMID: 8121963]

Haglund 2020 {published data only}

Haglund N, Dahlgren S, Rastam M, Gustafsson P, Kallen K. Improvement of autism symptoms after comprehensive intensive early interventions in community settings. Journal of the American Psychiatric Nurses Association 2020;00(0):1-13. CENTRAL [DOI: 10.1177/1078390320915257]

Hinnebusch 2017 {published data only}

Hinnebusch AJ, Miller LE, Fein DA. Autism spectrum disorders and low mental age: diagnostic stability and developmental outcomes in early childhood. Journal of Autism and Developmental Disorders 2017;47(12):3967-82. CENTRAL [DOI: 10.1007/s10803-017-3278-y] [PMCID: PMC5845818] [PMID: 28861732]

Kim 2016 {published data only}

Kim SH, Macari S, Koller J, Chawarska K. Examining the phenotypic heterogeneity of early autism spectrum disorder: subtypes and short-term outcomes. Journal of Child Psychology and Psychiatry 2016;57(1):93-102. CENTRAL [DOI: 10.1111/jcpp.12448] [PMID: 26264996] [PMID: PMC6852790]

Klintwall 2015 {published data only}

Klintwall L, Macari S, Eikeseth S, Chawarska K. Interest level in 2-year-olds with autism spectrum disorder predicts rate of verbal, nonverbal, and adaptive skill acquisition. Autism 2015;19(8):925-33. CENTRAL [DOI: 10.1177/1362361314555376] [PMCID: PMC4878117] [PMID: 25398893]

Lombardo 2015 {published data only}

Lombardo MV, Pierce K, Eyler LT, Carter Barnes C, Ahrens-Barbeau C, Solso S, et al. Different functional neural substrates for good and poor language outcome in autism. Neuron 2015;86(2):567-77. CENTRAL [DOI: 10.1016/j.neuron.2015.03.023] [PMID: 25864635] [PMID: PMC4610713]

Malhi 2011 {published data only}

Malhi P, Singhi P. Follow up of children with autism spectrum disorders: stability and change in diagnosis. Indian Journal of Pediatrics 2011;78(8):941-5. CENTRAL [DOI: 10.1007/s12098-011-0370-8] [PMID: 21318394]

Martin‐Borreguero 2021 {published data only}

Martin-Borreguero P, Gomez-Fernandez AR, De La Torre-Aguilar MJ, Gil-Campos M, Flores-Rojas K, Perez-Navero JL. Children with autism spectrum disorder and neurodevelopmental regression present a severe pattern after a follow-up at 24 months. Frontiers in Psychiatry 2021;12:644324. CENTRAL

Moore 2003 {published data only}

Moore V, Goodson S. How well does early diagnosis of autism stand the test of time? Follow-up study of children assessed for autism at age 2 and development of an early diagnostic service. Autism 2003;7(1):47-63. CENTRAL [DOI: 10.1177/1362361303007001005] [PMID: 12638764]

Moss 2008 {published data only}

Magiati I, Charman T, Howlin P. A two-year prospective follow-up study of community-based early intensive behavioural intervention and specialist nursery provision for children with autism spectrum disorders. Journal of Child Psychology and Psychiatry 2007;48(8):803-12. CENTRAL [DOI: 10.1111/j.1469-7610.2007.01756.x] [PMID: 17683452]
Magiati I, Moss J, Charman T, Howlin P. Patterns of change in children with autism spectrum disorders who received community based comprehensive interventions in their pre-school years: a seven year follow-up study. Research in Autism Spectrum Disorders 2011;5(3):1016-27. CENTRAL [DOI: 10.1016/j.rasd.2010.11.007]
Magiati I, Moss J, Yates R, Charman T, Howlin P. Is the Autism Treatment Evaluation Checklist a useful tool for monitoring progress in children with autism spectrum disorders? Journal of Intellectual Disability Research 2011;55(3):302-12. CENTRAL [DOI: 10.1111/j.1365-2788.2010.01359.x] [PMID: 21199043]
Moss J, Magiati I, Charman T, Howlin P. Stability of the Autism Diagnostic Interview - revised from pre-school to elementary school age in children with autism spectrum disorders. Journal of Autism and Developmental Disorders 2008;38(6):1081-91. CENTRAL [DOI: 10.1007/s10803-007-0487-9] [PMID: 18058215]

Naigles 2016 {published data only}

Naigles LR, Cheng M, Rattansone NX, Tek S, Khetrapal N, Fein D, et al. "You're telling me!" The prevalence and predictors of pronoun reversals in children with autism spectrum dsorders and typical development. Research in Autism Spectrum Disorders 2016;27:11-20. CENTRAL [PMCID: PMC4834724] [PMID: 10.1016/j.rasd.2016.03.008] [PMID: 27103941]

Neuhaus 2016 {published data only}

Neuhaus E, Jones EJ, Barnes K, Sterling L, Estes A, Munson J, et al. The relationship between early neural responses to emotional faces at age 3 and later autism and anxiety symptoms in adolescents with autism. Journal of Autism and Developmental Disorders 2016;46(7):2450-63. CENTRAL [DOI: 10.1007/s10803-016-2780-y] [PMCID: PMC5305034] [PMID: 27055415]

Ozonoff 2015 {published data only}

Ozonoff S, Young GS, Landa RJ, Brian J, Bryson S, Charman T, et al. Diagnostic stability in young children at risk for autism spectrum disorder: a baby siblings research consortium study. Journal of Child Psychology and Psychiatry 2015;56(9):988-98. CENTRAL [DOI: 10.1111/jcpp.12421] [PMCID: PMC4532646] [PMID: 25921776]

Paul 2008 {published data only}

Paul R, Chawarska K, Cicchetti D, Volkmar F. Language outcomes of toddlers with autism spectrum disorders: a two year follow-up. Autism Research 2008;1(2):97-107. CENTRAL [DOI: 10.1002/aur.12] [PMCID: PMC2946084] [PMID: 19360656]

Qian 2018 {published data only}

Ke X, Qian L. Alteration of hub organization in the white matter structural network in toddlers with autism spectrum disorder: a two-year follow-up study. Journal of the American Academy of Child and Adolescent Psychiatry 2017;56(10):S260. CENTRAL
Li Y, Zhou Z, Chang C, Qian L, Li C, Xiao T, et al. Anomalies in uncinate fasciculus development and social defects in preschoolers with autism spectrum disorder. BMC Psychiatry 2019;19(1):399. CENTRAL [DOI: 10.1016/j.neurenf.2012.04.383]
Qian L, Wang Y, Chu K, Li Y, Xiao C, Xiao T, et al. Alterations in hub organization in the white matter structural network in toddlers with autism spectrum disorder: A 2-year follow-up study. Autism Research 2018;11(9):1218-28. CENTRAL

Rivard 2019 {published data only}

Mello C, Rivard M Terroux A, Mercier C. Differential responses to early behavioural intervention in young children with autism spectrum disorders as a function of features of intellectual disability. Journal on Developmental Disabilities 2018;23(3):5-17. CENTRAL
Rivard M, Morin M, Mello C, Terroux A, Mercier C. Follow-Up of children with autism spectrum disorder 1 year after early behavioraliIntervention. Behavior Modification 2019;43(4):490-517. CENTRAL

Robain 2020 {published data only}

Robain F, Franchini M, Kojovic N, Wood de Wilde Hi, Schaer M. Predictors of treatment outcome in preschoolers with autism spectrum disorder: an observational study in the greater Geneva area, Switzerland. Journal of Autism & Developmental Disorders 2020;50(11):3815-30. CENTRAL

Santocchi 2012 {published data only}

Santocchi E, Prosperi M, Tancredi R, Muratori F. Diagnostic stability of autism in preschooler age. Conference: 20th World Congress of the International Association for Child and Adolescent Psychiatry and Allied Professions 2012;60(5):S198. CENTRAL [DOI: 10.1016/j.neurenf.2012.04.383]

Sheinkopf 1998 {published data only}

Sheinkopf SJ, Siegel B. Home-based behavioral treatment of young children with autism. Journal of Autism and Developmental Disorders 1998;28(1):15-23. CENTRAL [DOI: 10.1023/a:1026054701472] [PMID: 9546298]

Smith 2019 {published data only}

Smith D P, Hayward D W, Gale C M, Eikeseth S, Klintwall L. Treatment gains from early andi intensive behavioral intervention (EIBI) are maintained 10 years later. Behavior Modification 2019;45(4):581-601. CENTRAL [DOI: .o0r.g1/107.171/0771/405145445451591988822895]

Soke 2011 {published data only}

Soke GN, Philofsky A, Diguiseppi C, Lezotte D, Rogers S, Hepburn S. Longitudinal changes in scores on the Autism Diagnostic Interview - Revised (ADI-R) in pre-school children with autism: Iimplications for diagnostic classification and symptom stability. Autism 2011;15(5):545-62. CENTRAL [DOI: 10.1177/1362361309358332] [PMCID: PMC4426200] [PMID: 21586639]

Solomon 2014 {published data only}

Mahoney G, Solomon R. Mechanism of developmental change in the PLAY Project Home Consultation program: evidence from a randomized control trial. Journal of Autism and Developmental Disorders 2016;46(5):1860-71. CENTRAL [DOI: 10.1007/s10803-016-2720-x] [PMID: 26830414]
Solomon R, Van Egeren LA, Mahoney G, Quon Huber MS, Zimmerman P. PLAY Project Home Consultation intervention program for young children with autism spectrum disorders: a randomized controlled trial. Journal of Developmental & Behavioral Pediatrics 2014;35(8):475-85. CENTRAL [DOI: 10.1097/DBP.0000000000000096] [PMCID: PMC4181375] [PMID: 25264862]

Solomon 2016 {published data only}

Solomon M, Iosif A-M, Nordahl C, Libero L, Li D, Ghetti S, et al. W33. IQ-based developmental phenotypes of autism spectrum disorder in early childhood and their correlates. Neuropsychopharmacology 2016;41:S476. CENTRAL [DOI: 10.1038/npp.2016.242] [URL: www.nature.com/articles/npp2016242.pdf]
Solomon M, Iosif AM, Reinhardt VP, Libero LE, Nordahl CW, Ozonoff S, et al. What will my child's future hold? phenotypes of intellectual development in 2-8-year-olds with autism spectrum disorder. Autism Research 2018;11(1):121-32. CENTRAL
Waizbard-Bartov E, Ferrer E, Young GS, Heath B, Rogers S, Wu Nordahl C, et al. Trajectories of autism symptom severity change during early childhood. Journal of Autism & Developmental Disorders 2021;51(1):227-42. CENTRAL

Spjut Jansson 2016 {published data only}

Spjut Jansson B, Miniscalco C, Westerlund J, Kantzer A-K, Fernell E, Gillberg C. Children who screen positive for autism at 2.5 years and receive early intervention: a prospective naturalistic 2-year outcome study. Neuropsychiatric Disease and Treatment 2016;12:2255-63. CENTRAL [DOI: 10.2147/NDT.S108899] [PMCID: PMC5012621] [PMID: 27621636]

Sullivan 2010 {published data only}

Sullivan A. Developmental trajectories of young children with autism enrolled in an intensive behaviour intervention program: what the ablls can tell us about their progress [Doctoral dissertation]. Toronto (ON): York University, 2010. CENTRAL [IBSN: 978-0-494-64911-4]

Szatmari 2021 {published data only}

Baribeau DA, Vigod S, Pullenayegum E, Kerns CM, Mirenda P, Smith IM, et al. Co-occurring trajectories of anxiety and insistence on sameness behaviour in autism spectrum disorder. British Journal of Psychiatry 2021;218(1):20-7. CENTRAL
Baribeau DA, Vigod S, Pullenayegum E, Kerns CM, Mirenda P, Smith IM, et al. Repetitive behavior severity as an early indicator of risk for elevated anxiety symptoms in autism spectrum disorder. Journal of the American Academy of Child & Adolescent Psychiatry 2020;59(7):890-9. CENTRAL
Bennett TA, Szatmari P, Georgiades K, Hanna S, Janus M, Georgiades S, et al. Do reciprocal associations exist between social and language pathways in preschoolers with autism spectrum disorders? Journal of Child Psychology and Psychiatry 2015;56(8):874-83. CENTRAL [DOI: 10.1111/jcpp.12356] [PMID: 25376440]
Bennett TA, Szatmari P, Georgiades K, Hanna S, Janus M, Georgiades S, et al. Language impairment and early social competence in preschoolers with autism spectrum disorders: a comparison of DSM-5 profiles. Journal of Autism and Developmental Disorders 2014;44(11):2797-808. CENTRAL [DOI: 10.1007/s10803-014-2138-2] [PMID: 24865586]
Courchesne, V, Bedford R, Pickles A, Duku E, Kerns C, Mirenda P, et al, Pathways Team. Non-verbal IQ and change in restricted and repetitive behavior throughout childhood in autism: a longitudinal study using the Autism Diagnostic Interview-Revised. Molecular Autism 2021;12(1):10. CENTRAL [DOI: https://doi.org/10.1186/s13229-021-00461-7]
Georgiades S, Boyle M, Szatmari P, Hanna S, Duku E, Zwaigenbaum L, et al. Modeling the phenotypic architecture of autism symptoms from time of diagnosis to age 6. Journal of Autism and Developmental Disorders 2014;44(12):3045-55. CENTRAL [DOI: 10.1007/s10803-014-2167-x] [PMID: 24958435]
Georgiades S, Tait PA, McNicholas PD, Duku E, Zwaigenbaum L, Smith I M, et al. Trajectories of symptom severity in children with autism: variability and turning points through the transition to school. Journal of Autism and Developmental Disorders. 2021;Epub ahead of print:no pagiation. CENTRAL [DOI: 0.1007/s10803-021-04949-2]
Szatmari P, Cost KT, Duku E, Bennett T, Elsabbagh M, Georgiades S, et al. Association of child and family attributes with outcomes in children with autism. JAMA Network Open 2021;4(3):e212530. CENTRAL
Szatmari P, Georgiades S, Duku E, Bennett TA, Bryson S, Fombonne E, et al. Developmental trajectories of symptom severity and adaptive functioning in an inception cohort of preschool children with autism spectrum disorder. JAMA Psychiatry 2015;72(3):276-83. CENTRAL [DOI: 10.1001/jamapsychiatry.2014.2463] [PMID: 25629657]

Takeda 2007 {published data only}

Takeda T, Koyama T, Kurita H. Comparison of developmental/intellectual changes between autistic disorder and pervasive developmental disorder not otherwise specified in preschool years. Psychiatry and Clinical Neurosciences 2007;61(6):684-6. CENTRAL [DOI: 10.1111/j.1440-1819.2007.01740.x] [PMID: 18081633]

Thomas 2009 {published data only}

Thomas CJ. Analyses of five years of results from project data (developmentally appropriate treatment for autism), a high-quality early childhood special education program for students with autism spectrum disorders [Doctoral dissertation]. Washington (DC): University of Washington, 2009. CENTRAL [UMI NUMBER: 3393990]

Venker 2014 {published data only}

Davidson Mm, Ellis Weismer S. A discrepancy in comprehension and production in early language development in ASD: is it clinically relevant? Journal of Autism AND Developmental Disorders 2017;47(7):2163-75. CENTRAL [DOI: 10.1007/s10803-017-3135-z] [PMCID: PMC5812677] [PMID: 28447305]
Ellis Weismer S, Kover ST. Preschool language variation, growth, and predictors in children on the autism spectrum. Journal of Child Psychology and Psychiatry 2015;56(12):1327-37. CENTRAL [DOI: 10.1111/jcpp.12406] [PMCID: PMC4565784] [PMID: 25753577]
Ray-Subramanian CE, Ellis Weismer S. Receptive and expressive language as predictors of restricted and repetitive behaviors in young children with autism spectrum disorders. Journal of Autism and Developmental Disorders 2012;42(10):2113-20. CENTRAL [DOI: 10.1007/s10803-012-1463-6] [PMCID: PMC3422597] [PMID: 22350337]
Venker CE, Kover ST, Ellis Weismer S. Brief report: fast mapping predicts differences in concurrent and later language abilities among children with ASD. Journal of Autism and Developmental Disorders 2016;46(3):1118-23. CENTRAL [DOI: 10.1007/s10803-015-2644-x] [PMCID: PMC4747812] [PMID: 26572655]
Venker CE, Ray-Subramanian CE, Bolt DM, Ellis Weismer S. Trajectories of autism severity in early childhood. Journal of Autism and Developmental Disorders 2014;44(3):546-63. CENTRAL [DOI: 10.1007/s10803-013-1903-y] [PMCID: PMC3909724] [PMID: 23907710]

Wu 2016 {published data only}

Wu Y-T, Maenner MJ, Wiggins LD, Rice CE, Bradley CC, Lopez ML, et al. Retention of autism spectrum disorder diagnosis: the role of co-occurring conditions in males and females. Research in Autism Spectrum Disorders 2016;25:76-86. CENTRAL [DOI: 10.1016/j.rasd.2016.02.001] [PMCID: PMC5603237] [PMID: 28936232]

Zappella 1990 {published data only}

Zappella M. Young autistic children treated with ethologically oriented family therapy. Family Systems Medicine 1990;8(1):14-27. CENTRAL [DOI: 10.1037/h0089267]

Zappella 2010 {published data only}

Zappella M. Autistic regression with and without EEG abnormalities followed by favourable outcome. Brain & Development 2010;32(9):739-45. CENTRAL [DOI: 10.1016/j.braindev.2010.05.004] [PMID: 20708360]

Zwaigenbaum 2015 {published data only}

Zwaigenbaum L, Bryson SE, Brian J, Smith IM, Roberts W, Szatmari P, et al. Stability of diagnostic assessment for autism spectrum disorder between 18 and 36 months in a high-risk cohort. Autism Research 2016;9(7):790-800. CENTRAL [DOI: 10.1002/aur.1585] [PMID: 26613202]

Referencias de los estudios excluidos de esta revisión

Ir a:

Bacon 2018 {published data only}

Bacon EC, Courchesne E, Barnes CC, Cha D, Pence S, Schreibman L, et al. Rethinking the idea of late autism spectrum disorder onset. Development and Psychopathology 2018;30(2):553-69. CENTRAL [DOI: 10.1017/S0954579417001067] [PMID: 28803559]
Bacon EC, Moore A, Lee Q, Carter BC, Courchesne E, Pierce K. Identifying prognostic markers in autism spectrum disorder using eye tracking. Autism: The International Journal of Research & Practice 2020;24(3):658-69. CENTRAL
Pierce K, Gazestani VH, Bacon E, Barnes CC, Cha D, Nalabolu S, et al. Evaluation of the diagnostic stability of the early autism spectrum disorder phenotype in the general population starting at 12 months. JAMA Pediatrics 2019;173(6):578-87. CENTRAL

Bal 2019 {published data only}

Bal VH, Kim SH, Fok M, Lord C. Autism spectrum disorder symptoms from ages 2 to 19 years: Implications for diagnosing adolescents and young adults. Autism Research 2019;12(1):89-99. CENTRAL

Berry 2009 {published data only}

Berry LN. Early treatments associated with optimal outcome in children with autism spectrum disorders [Doctoral dissertation). Connecticut, New England: University of Connecticut, 2009. CENTRAL [UMI NUMBER: 3377035]
Boorstein HC. Regressive and early onset autism spectrum disorders: a comparison of developmental trajectories, autistic behaviors, and medical histories [Doctorial dissertation]. Connecticut, New England: University of Connecticut, 2010. CENTRAL [UMI NUMBER: 3475517]
Kleinman JM, Ventola PE, Pandey J, Verbalis AD, Barton M, Hodgson S, et al. Diagnostic stability in very young children with autism spectrum disorders. Journal of Autism and Developmental Disorders 2008;38(4):606-15. CENTRAL [DOI: 10.1007/s10803-007-0427-8] [PMCID: PMC3625643] [PMID: 17924183]
Miller LE, Burke JD, Troyb E, Knoch K, Herlihy LE, Fein DA. Preschool predictors of school-age academic achievement in autism spectrum disorder. Clinical Neuropsychologist 2017;31(2):382-403. CENTRAL [DOI: 10.1080/13854046.2016.1225665] [PMCID: PMC5464727] [PMID: 27705180]
Moulton E, Barton M, Robins DL, Abrams DN, Fein D. Early characteristics of children with ASD who demonstrate optimal progress between age two and four. Journal of Autism and Developmental Disorders 2016;46(6):2160-73. CENTRAL [DOI: 10.1007/s10803-016-2745-1] [PMCID: PMC4860351] [PMID: 26895327]
Verbalis AD. Longitudinal changes in the expression of autism spectrum disorders in girls and boys [Doctoral dissertation]. Connecticut, New England: University of Connecticut, 2010. CENTRAL [UMI NUMBER: 3451418]

Canal‐Bedia 2016 {published data only}

Canal-Bedia R, Magan-Maganto M, Bejarano-Martin A, De Pablos-De la Morena A, Bueno-Carrera G, Manso-De Dios S, et al. Early detection and stability of diagnosis in autism spectrum disorders. Revista de Neurología 2016;62(Suppl 1):S15-20. CENTRAL [PMID: 26922953]

Charman 2005 {published data only}

Charman T, Taylor E, Drew A, Cockerill H, Brown J-A, Baird G. Outcome at 7 years of children diagnosed with autism at age 2: predictive validity of assessments conducted at 2 and 3 years of age and pattern of symptom change over time. Journal of Child Psychology and Psychiatry 2005;46(5):500-13. CENTRAL [DOI: 10.1111/j.1469-7610.2004.00377.x] [PMID: 15845130]
Cox A, Klein K, Charman, T, Baird G, Baron-Cohen S, Swettenham J, et al. Autism spectrum disorders at 20 and 42 months of age: Stability of clinical and ADI-R diagnosis.. Journal of Child Psychology and Psychiatry 1999;40(5):719–32. CENTRAL [DOI: https://doi.org/10.1111/1469-7610.00488]
Drew A, Baird G, Baron‐CohenvS, Cox A, Slonims V, Wheelwright S, et al. A pilot randomised control trial of a parent training intervention for pre‐school children with autism: Preliminary findings and methodological challenges. European Child and Adolescent Psychiatry 2002;11:266–72. CENTRAL [DOI: doi: 10.1007/s00787-002-0299-6.]

Chawarska 2007 {published data only}

Chawarska K, Klin A, Paul R, Macari S, Volkmar F. A prospective study of toddlers with ASD: short-term diagnostic and cognitive outcomes. Journal of Child Psychology and Psychiatry 2009;50(10):1235-45. CENTRAL [DOI: 10.1111/j.1469-7610.2009.02101.x] [PMCID: PMC4878113] [PMID: 19594835]
Chawarska K, Klin A, Paul R, Volkmar F. Autism spectrum disorder in the second year: stability and change in syndrome expression. Journal of Child Psychology and Psychiatry 2007;48(2):128-38. CENTRAL [DOI: 10.1111/j.1469-7610.2006.01685.x] [PMID: 17300551]
Chawarska K, Paul R, Klin A, Hannigen S, Dichtel LE, Volkmar F. Parental recognition of developmental problems in toddlers with autism spectrum disorders. Journal of Autism and Developmental Disorders 2007;37(1):62-72. CENTRAL [DOI: 10.1007/s10803-006-0330-8] [PMID: 17195921]

Clark 2017 {published data only}

Barbaro J, Dissanayake C. Diagnostic stability of autism spectrum disorder in toddlers prospectively identified in a community-based setting: behavioural characteristics and predictors of change over time. Autism 2017;21(7):830-40. CENTRAL [DOI: 10.1177/1362361316654084] [PMID: 27474118]
Clark ML, Barbaro J, Dissanayake C. Continuity and change in cognition and autism severity from toddlerhood to school age. Journal of Autism and Developmental Disorders 2017;47(2):328-39. CENTRAL [DOI: 10.1007/s10803-016-2954-7] [PMID: 27848051]
Clark ML, Vinen Z, Barbaro J, Dissanayake C. School age outcomes of children diagnosed Eerly and later with autism spectrum disorder. Journal of Autism and Developmental Disorders 2018;48(1):92-102. CENTRAL [DOI: 10.1007/s10803-017-3279-x] [PMID: 28905160]

De Giacomo 2009 {published data only}

De Giacomo A, Lamanna AL, Lafortezza E, Lecce P, Martinelli D, Margari L. Diagnostic stability and early developmental trajectory of pervasive developmental disorder using the Autism Diagnostic Interview - Revised. Italian Journal of Psychopathology 2009;15(4):336-42. CENTRAL

Guthrie 2013 {published data only}

Guthrie W, Swineford LB, Nottke C, Wetherby AM. Early diagnosis of autism spectrum disorder: stability and change in clinical diagnosis and symptom presentation. Journal of Child Psychology and Psychiatry 2013;54(5):582-90. CENTRAL [DOI: 10.1111/jcpp.12008] [PMCID: PMC3556369] [PMID: 23078094]

Hedvall 2014 {published data only}

Barnevik Olsson M, Lundström S, Westerlund J, Giacobini MB, Gillberg C, Fernell E. Preschool to school in autism: neuropsychiatric problems 8 years after diagnosis at 3 years of age. Journal of Autism and Developmental Disorders 2016;46(8):2749-55. CENTRAL [DOI: 10.1007/s10803-016-2819-0] [PMID: 27230761]
Fernell E, Hedvall A, Westerlund J, Hoglund Carlsson L, Eriksson M, Barnevik Olsson M, et al. Early intervention in 208 Swedish preschoolers with autism spectrum disorder. A prospective naturalistic study. Research in Developmental Disabilities 2011;32(6):2092-101. CENTRAL [DOI: 10.1016/j.ridd.2011.08.002] [PMID: 21985993]
Hedvall A, Westerlund J, Fernell E, Holm A, Gillberg C, Billstedt E. Autism and developmental profiles in preschoolers: stability and change over time. Acta Paediatrica 2014;103(2):174-81. CENTRAL [DOI: 10.1111/apa.12455] [PMID: 24237479]
Hedvall A, Westerlund J, Fernell E, Norrelgen F, Kjellmer L, Olsson MB, et al. Preschoolers with autism spectrum disorder followed for 2 years: those who gained and those who lost the most in terms of adaptive functioning outcome. Journal of Autism and Developmental Disorders 2015;45(11):3624-33. CENTRAL [DOI: 10.1007/s10803-015-2509-3] [PMID: 26123008]
Norrelgen F, Fernell E, Eriksson M, Hedvall A, Persson C, Sjölin M, et al. Children with autism spectrum disorders who do not develop phrase speech in the preschool years. Autism 2015;19(8):934-43. CENTRAL [DOI: 10.1177/1362361314556782] [PMID: 25488002]

Jónsdóttir 2007 {published data only}

Jónsdóttir SL, Saemundsen E, Asmundsdóttir G, Hjartardóttir S, Asgeirsdóttir BB, Smáradóttir HH, et al. Follow-up of children diagnosed with pervasive developmental disorders: stability and change during the preschool years. Journal of Autism and Developmental Disorders 2007;37(7):1361-74. CENTRAL [DOI: 10.1007/s10803-006-0282-z] [PMID: 17146706]

Kadam 2021 {published data only}

Kadam A, Patni B, Pandit A, Patole S. Stability of the initial diagnosis of autism spectrum disorder by DSM-5 in children: a short-term follow-up study. Journal of Tropical Pediatrics 2020;00(0):1-6. CENTRAL [DOI: 10.1093/tropej/fmaa104]

Kantzer 2018 {published data only}

Kantzer A-K, Fernell E, Westerlund J, Hagberg B, Gillberg C, Miniscalco C. Young children who screen positive for autism: stability, change and "comorbidity" over two years. Research in Developmental Disabilities 2018;72:297-307. CENTRAL [DOI: 10.1016/j.ridd.2016.10.004] [PMID: 27818061]
Thompson L, Gillberg C, Landberg S, Kantzer AK, Miniscalco C, Barnevik OM, et al. Autism with and without regression: a two-year prospective longitudinal study in two population-derived Swedish cohorts. Journal of Autism & Developmental Disorders 2019;49(6):2281-290. CENTRAL

Ozonoff 2018 {published data only}

Ozonoff S, Young GS, Brian J, Charman T, Shephard E, Solish A, et al. Diagnosis of uutism spectrum disorder after age 5 in children evaluated longitudinally since infancy. Journal of the American Academy of Child & Adolescent Psychiatry 2018;57(11):849-57. CENTRAL

Shumway 2012 {published data only}

Shumway S, Farmer C, Thurm A, Joseph L, Black D, Golden C. The ADOS calibrated severity score: relationship to phenotypic variables and stability over time. Autism Research 2012;5(4):267-76. CENTRAL [DOI: 10.1002/aur.1238] [PMCID: PMC3422401] [PMID: 22628087]

Stone 1999 {published data only}

Stone WL, Lee EB, Ashford L, Brissie J, Hepburn SL, Coonrod EE, et al. Can autism be diagnosed accurately in children under 3 years? Journal of Child Psychology and Psychiatry 1999;40(2):219-26. CENTRAL [PMID: 10188704]
Turner LM, Stone WL, Pozdol SL, Coonrod EE. Follow-up of children with autism spectrum disorders from age 2 to age 9. Autism 2006;10(3):243-65. CENTRAL [DOI: 10.1177/1362361306063296] [PMID: 16682397]
Turner LM, Stone WL. Variability in outcome for children with an ASD diagnosis at age 2. Journal of Child Psychology and Psychiatry 2007;48(8):793-802. CENTRAL [DOI: 10.1111/j.1469-7610.2007.01744.x] [PMID: 17683451]

Sutera 2010 {published data only}

Sutera S, Pandey J, Esser EL, Rosenthal MA, Wilson LB, Barton M, et al. Predictors of optimal outcome in toddlers diagnosed with autism spectrum disorders. Journal of Autism and Developmental Disorders 2007;37(1):98-107. CENTRAL [DOI: 10.1007/s10803-006-0340-6]
Sutera S. Predictors of optimal outcome in children with an autism spectrum disorder. Dissertation Abstracts International: Section B: The Sciences and Engineering 2010;70(9-B):5849. CENTRAL

Thurm 2015 {published data only}

Farmer C, Swineford L, Swedo SE, Thurm A. Classifying and characterizing the development of adaptive behavior in a naturalistic longitudinal study of young children with autism. Journal of Neurodevelopmental Disorders 2018;10(1):No pagiation reported. CENTRAL [DOI: 10.1186/s11689-017-9222-9]
Thurm A, Manwaring SS, Swineford L, Farmer C. Longitudinal study of symptom severity and language in minimally verbal children with autism. Journal of Child Psychology and Psychiatry 2015;56(1):97-104. CENTRAL [DOI: 10.1111/jcpp.12285] [PMCID: PMC4581593] [PMID: 24961159]

Tunc 2021 {published data only}

Tunc B, Pandey J, St John T, Meera SS, Maldarelli J E, Zwaigenbaum L, et al. Diagnostic shifts in autism spectrum disorder can be linked to the fuzzy nature of the diagnostic boundary: a data-driven approach. Journal of Child Psychology and Psychiatry 2021;62(10):1236-45. CENTRAL [DOI: 10.1111/jcpp.13406]

Van Daalen 2009 {published data only}

Van Daalen E, Kemner C, Dietz C, Swinkels SH, Buitelaar JK, Van Engeland H. Inter-rater reliability and stability of diagnoses of autism spectrum disorder in children identified through screening at a very young age. European Child & Adolescent Psychiatry 2009;18(11):663-74. CENTRAL [DOI: 10.1007/s00787-009-0025-8] [PMCID: PMC2762529] [PMID: 19421728]

Venter 1992 {published data only}

Venter A, Lord C, Schopler E. A follow-up study of high functioning autistic children. Journal of Child Psychology and Psychiatry 1992;33(3):489-507. CENTRAL [DOI: 10.1111/j.1469-7610.1992.tb00887.x] [PMID: 1577895]

Referencias de los estudios en espera de evaluación

Ir a:

Anglim 2012 {published data only}

Anglim M, Ackermann P, Barry M, Kashif M, Moran A, O'Connell A, et al. Stability and change in a clinical sample of preschool children with autistic spectrum disorder. Neuropsychiatrie de l'Enfance et de l'Adolescence. Conference Abstract: 20th World Congress of the International Association for Child and Adolescent Psychiatry and Allied Professions, IACAPAP 2012. Paris France. 2012;60(5 Supplement):S215-S216. CENTRAL [DOI: 10.1016/j.neurenf.2012.04.472]

Boi 2017 {published data only}

Boi J, Donno F, Petza S, Cera F, Balia C, Carucci S, Zuddas A. Medium-term efficacy data of medications in children and adolescents with autism spectrum disorder: An 18 months retrospective follow up study. European Neuropsychopharmacology 2017;27 (Supplement 4):S1112. CENTRAL

Brown 1997 {published data only}

Brown H M, N Amer Riding Handicapped Assoc. Post-therapy follow up of the effects on autism of equine-based therapy. Denver: North American Riding Handicapped Association Inc, 1997. CENTRAL

Chang 2017 {published data only}

Chang Tzu-Ling, Chen Chia-ling, Chung Chia-Ying. Poster 135: Developmental Outcomes in Children with Autism Spectrum Disorder of Different Cognitive Functions. Physical Medicine and Rehabilitation 2017;9:S176-S177. CENTRAL [DOI: 10.1016/j.pmrj.2017.08.078]

Chang 2017a {published data only}

Chang C, Qiu NN, Xiao T, Xiao X, Chu KK, Li Y, et al. [Structural change of the corpus callosum fibers in toddlers with autism spectrum disorder: two-year follow-up]. Zhonghua Er Ke Za Zhi 2017;55(12):920-5. CENTRAL

Da Silva 2003 {published data only}

Da Silva PC, Eira C, Pombo J, Silva A, Da Silva LC, Martins F, et al. Clinical program for treatment of difficulties with relating and communicating, based on the D.I.R. Model. Analise Psicoloica 2003;21(1):3139. CENTRAL

Eapen 2019 {published data only}

Eapen V, Mathew N, Mazzoni A. Subtyping autism: can we predict treatment response in Autism Spectrum Disorder? IBRO Reports 2019;6 (Supplement):S358. CENTRAL

Faroghizadeh 2021 {published data only}

Faroghizadeh K, Ziaian T. Effectiveness of applied behavioral analysis method on autism symptoms. International Journal of Pharmaceutical Research 2021;13(1):5710-6. CENTRAL

Gabis 2011 {published data only}

Gabis V L, Maayan M, Rivka S, Aya SH, Marcy Y. Preschool diagnostic process and changes in diagnosis of autism spectrum disorder. Annals of Neurology. Conference: 40th Annual Child Neurology Society Meeting Scientific Program. Savannah, GA United States 2011;70(15):S132. CENTRAL

Ghamari Kivi 2012 {published data only}

Ghamari Kivi H, Agh A, Nasoudi R. Efficacy of applied behavioral analysis in reducing symptoms of stereotyped behavior, interaction and communicational problems in autistic children. Iranian Journal of Psychiatry. Supplement Abstracts of the 5th International Congress of Iranian Association of Child and Adolescents Psychiatry. 2012;7(4):106-7. CENTRAL

Jimenez‐Martinez 2018 {published data only}

Jimenez-Martinez M, Nunez-Rodriguez A, Guzman G. Analysis of applied behavior treatment for children with autism spectrum disorder. European Psychiatry 2018;48 (Supplement 1):S473. CENTRAL

Melville 1987 {published data only}

Melville LC. Douglass Developmental Disabilities Center: A Follow-Up Study [PhD thesis]. New Brunswick (NJ): Rutgers University, 1987. CENTRAL

Millikovsky‐Ayalon 2012 {published data only}

Millikovsky-Ayalon M, Sofrin R, Raz R, Shilon-Hadass A, Yehuda M, Mukamel M, et al. Preschool diagnostic process and changes in diagnosis of autism spectrum disorder. Harefuah 2012;151(3):150-4, 190. CENTRAL [PMID: 22519262]

Mohanta 2019 {published data only}

Mohanta A, Mittal V K, Ieee. Acoustic features for characterizing speech of childrenaffected with ASD. 2019 IEEE 16th India Council International Conference 2019;00(0):1-4. CENTRAL [DOI: 10.1109/INDICON47234.2019.9029043]

Mosconi 2009 {published data only}

Mosconi MW, Cody-Hazlett H, Poe MD, Gerig G, Gimpel-Smith R, Piven J. Longitudinal study of amygdala volume and joint attention in 2- to 4-year-old children with autism. Archives of General Psychiatry 2009;66(5):509-16. CENTRAL [DOI: 10.1001/archgenpsychiatry.2009.19] [PMCID: PMC3156446] [PMID: 19414710]
Mosconi MW, Reznick JS, Mesibov G, Piven J. The Social Orienting Continuum and Response Scale (SOC-RS): a dimensional measure for preschool-aged children. Journal of Autism & Developmental Disorders 2009;39(2):24-50. CENTRAL [DOI: 10.1007/s10803-008-0620-4]

Muratori 2002 {published data only}

Muratori F, Dini P, Cosenza A, Parrini B, Fascetti L, Vanni F. A controlled study on therapeutic effects of day-hospital for autistic children [Studio controllato sugli effetti terapeutici del day-hospital nell'autismo infantile]. Imago 2002;9(2):133-42. CENTRAL [URL: Available at www.scopus.com/record/display.uri?eid=2-s2.0-0036322970&origin=inward&txGid=089debeeb957531e3d1767500217fd76]

Ozyurt 2020 {published data only}

Ozyurt G, Elikucuk C D. Augmentative and alternative communication for children with autism spectrum disorder: a randomised study of awareness and developmental language interventions. Hong Kong Journal of Paediatrics 2020;25(2):79-88. CENTRAL

Perucchini 2005 {published data only}

Perucchini P, Muratori F, Parrini B. Theory of mind, gesture and autism. Giornale Italiano di Psicologia 2005;32(4):799-817. CENTRAL

Selvakumar 2018 {published data only}

Selvakumar L, Malhi P, Singhi P. Stability and change in Diagnosis of Autism Spectrum Disorder over time among toddlers. International Journal of Medical Research & Health Sciences 2018;7(3):4045. CENTRAL

Takesada 1992 {published data only}

Takesada M, Naruse H, Nagahata M, Kazamatsuri H, Nakane Y, Yamazaki K, t al. An Open Clinical-Study of Apropterin Hydrochloride (R-Tetrahydrobiopterin, R-Thbp)iIn Infantile-Autism - Clinical Effects and Long-Term Follow-Up. 965 edition. Amsterdam: Elsevier Science Publ B V, 1992. CENTRAL

Zhang 2019 {published data only}

Zhang L, Liu Y, Zhou Z, Wei Y, Wang J, Yang Ji, et al. A follow-up study on the long-term effects of rehabilitation in children with autism spectrum disorders. NeuroRehabilitation 2019;44(1):1-7. CENTRAL

Zirakashvili 2018 {published data only}

Zirakashvili M, Gabunia M, Tatishvili N, Lomidze G, Janelidze M. Predictors of better outcome in children with autism spectrum disorders: a pilot study in Georgia. Developmental Medicine and Child Neurology 2018;60 (Supplement 2):23-4. CENTRAL

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APA 2000

American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Washington (DC): American Psychiatric Association, 2000.

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American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 5th edition. (DSM-5). Arlington (VA): American Psychiatric Publishing, 2013.

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Barbaro J, Dissanayake C. Diagnostic stability of autism spectrum disorder in toddlers prospectively identified in a community-based setting: behavioural characteristics and predictors of change over time. Autism 2016 Jul 28 [Epub ahead of print]. [DOI: 10.1177/1362361316654084] [PMID: 27474118]

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Buescher AV, Cidav Z, Knapp M, Mandell DS. Costs of autism spectrum disorder in the United Kingdom and the United States. JAMA Pediatrics 2014;168(8):721-8. [DOI: 10.1001/jamapediatrics.2014.210] [PMID: 24911948]

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Corsello CM, Akshoomoff N, Stahmer AC. Diagnosis of autism spectrum disorders in 2-year-olds: a study of community practice. Journal of Child Psychology and Psychiatry 2013;54(2):178-85. [DOI: 10.1111/j.1469-7610.2012.02607.x] [PMC3505251] [PMID: 22905987]

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Daniels AM, Rosenberg RE, Law JK, Lord C, Kaufmann WE, Law PA. Stability of initial autism spectrum disorder diagnoses in community settings. Journal of Autism and Developmental Disorders 2011;41(1):110-21. [DOI: 10.1007/s10803-010-1031-x] [PMID: 20473589]

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Gilliam JE. Gilliam Autism Rating Scale. Austin (TX): Pro-Ed, 1995.

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Goin-Kochel RP, Myers BJ, Mackintosh VH. Parental reports on the use of treatments and therapies for children with autism spectrum disorders. Research in Autism Spectrum Disorders 2007;1(3):195-209. [DOI: http://dx.doi.org/10.1016/j.rasd.2006.08.006]

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Green VA, Pituch KA, Itchon J, Choi A, O'Reilly M, Sigafoos J. Internet survey of treatments used by parents of children with autism. Research in Developmental Disabilities 2006;27(1):70-84. [DOI: 10.1016/j.ridd.2004.12.002] [PMID: 15919178]

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Hansen SN, Schendel DE, Parner ET. Explaining the increase in the prevalence of autism spectrum disorders: the proportion attributable to changes in reporting practices. JAMA Pediatrics 2015;169(1):56-62. [DOI: 10.1001/jamapediatrics.2014.1893] [PMID: 25365033]

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Hayden JA, Wilson MN, Riley RD, Iles R, Pincus T, Ogilvie R. Individual recovery expectations and prognosis of outcomes in non‐specific low back pain: prognostic factor review. Cochrane Database of Systematic Reviews 2019, Issue I1. Art. No: CD011284. [DOI: 10.1002/14651858.CD011284.pub2]

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Horlin C, Falkmer M, Parsons R, Albrecht MA, Falkmer T. The cost of autism spectrum disorders. PLoS One 2014;9(9):e106552. [DOI: 10.1371/journal.pone.0106552]

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National Institute for Health and Care Excellence. Autism spectrum disorder in under 19s: recognition, referral and diagnosis (CG128). www.nice.org.uk/guidance/cg128/resources/autism-in-under-19s-recognition-referral-and-diagnosis-35109456621253 (accessed 20 May 2015).

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Schopler 1980

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Referencias de otras versiones publicadas de esta revisión

Ir a:

Brignell 2017

Brignell A, Albein‐Urios N, Woolfenden S, Hayen A, Iorio A, Williams K. Overall prognosis of preschool autism spectrum disorder diagnoses. Cochrane Database of Systematic Reviews 2017, Issue 8. Art. No: CD012749. [DOI: 10.1002/14651858.CD012749]

Characteristics of studies

Characteristics of included studies [ordered by study ID]

Ir a:

Anderson 2009

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical, drawn from broad community base
Location (country): USA
Length of follow‐up (years): 11 (seen at 2, 3, 5, 9 & 13 years)
Diagnostic tool (multidisciplinary or not): DSM‐IV (N)

Population

Sample size (% male): 192 (84)
Diagnosis type: autism, PDD‐NOS and non‐spectrum developmental delay
Mean age at baseline (years): 2.4 (0.43)
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: not reported
Note(s): sample included children without a diagnosis of ASD and we were unable to extract data on the children with ASD separately as we were unable to obtain this information from study authors

Baghdadli 2012

Study characteristics

Methods

Design: retrospective
Setting: cohort study
Sample: clinical
Location (country): France
Length of follow‐up (years): 3.0
Diagnostic tool (multidisciplinary or not): ICD‐10 & CARS (Y)

Population

Sample size (% male): 152 (82)
Diagnosis type: ASD
Mean age at baseline (years): 4.9
IQ (mean standard score): < 70
Language (mean standard score): < 70
Adaptive behaviour (mean standard score): < 70

Notes

Conflict of interest: not reported
Funding: Programme Hospitalier de Recherche Clinique (PHRC) and Orange Foundation, France
Note(s): none

Benedetto 2021

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical with broad community base
Location (country): Italy
Length of follow‐up (years): 1
Diagnostic tool (multidisciplinary or not): DSM‐5 and ADOS (Y)

Population

Sample size (% male): 147 (80)
Diagnosis type: ASD
Mean age at baseline (years): 2.3
IQ (mean standard score): ‐
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: the authors declared they have no COI.
Funding: no funding
Note(s):

Bopp 2006

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): Canada
Length of follow‐up (years): 2.0
Diagnostic tool (multidisciplinary or not): CARS (U)

Population

Sample size (% male): 70 (83)
Diagnosis type: ASD
Mean age at baseline (years): 4.2
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): < 70

Notes

Conflict of interest: not reported
Funding: not reported
Note(s): none

Brian 2016

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): Canada
Length of follow‐up (years): 6.4
Diagnostic tool (multidisciplinary or not): ADOS and DSM‐IV (N)

Population

Sample size (% male): 18 (72)
Diagnosis type: ASD
Mean age at baseline (years): 3.2
IQ (mean standard score): > 70
Language (mean standard score): > 70
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: Canadian Institutes of Health Research; Autism Speaks; Autism Speaks Canada; NeuroDevNet; and the Simons Foundation
Note(s): none

Chu 2017

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): Taiwan
Length of follow‐up (years): 1.5
Diagnostic tool (multidisciplinary or not): DSM‐IV‐TR and ADOS Social and Communication subset (N)

Population

Sample size (% male): 35 (89)
Diagnosis type: ASD
Mean age at baseline (years): 2.5
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: National Science Council in Taiwan (NSC‐96‐2413‐H‐004‐021‐MY3 and MOST 102‐2410‐ H‐004 ‐044 ‐MY3)
Note(s): none

Demb 1989

Study characteristics

Methods

Design: retrospective, with whole cohort considered
Setting: cohort study
Sample: clinical, from broad community base
Location (country): USA
Length of follow‐up (years): 5.0
Diagnostic tool (multidisciplinary or not): DSM‐III and DSM‐III‐R (N)

Population

Sample size (% male): 12 (75)
Diagnosis type: ASD
Mean age at baseline (years): 4.5
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: not reported
Note(s): none

DeWaay 2010

Study characteristics

Methods

Design: prospective
Setting: intervention trial, with one treatment arm
Sample: clinical
Location (country): USA
Length of follow‐up (years): 1.5
Diagnostic tool (multidisciplinary or not): GARS/GARS2 (U)

Population

Sample size (% male): 13 (77)
Diagnosis type: ASD
Mean age at baseline (years): 4.3
IQ (mean standard score): ‐
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: not reported
Note(s): none

Dietz 2007

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: population based
Location (country): the Netherlands
Length of follow‐up (years): 1.5
Diagnostic tool (multidisciplinary or not): DSM‐IV (N)

Population

Sample size (% male): 14 (66). Note, data were only provided for the full sample (n = 39), which includes children without ASD.
Diagnosis type: ASD
Mean age at baseline (years): 2.1
IQ (mean standard score): < 70
Language (mean standard score): < 70
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding:quote: "This study was supported by grants 940‐38‐045 and 940‐38‐014 (Chronic Disease Program), by grant 28.3000‐2of the Praeventiefonds‐ZONMW, by the Netherlands Organisationfor Scientific Research (NWO), by a grant from the Dutch Ministryof Health, Welfare and Culture, and by grants from Cure AutismNow, and the Korczak Foundation."
Note(s): children were assessed at two time points for ASD using the ADI‐R, but only the stability results from IQ tests at two time points are presented. Unable to obtain required data from the study authors

Eaves 2004

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: population based
Location (country): Canada
Length of follow‐up (years): 2.3
Diagnostic tool (multidisciplinary or not): CARS, DSM‐IV, MDT (Y)

Population

Sample size (% male): 43 (80)
Diagnosis type: ASD
Mean age at baseline (years): 2.8
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): < 70

Notes

Conflict of interest: not reported
Funding: Vancouver Foundation, British Columbia Medical Services Association
Note(s): none

Elmose 2014

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: unclear how sample drawn
Location (country): Denmark
Length of follow‐up (years): 8.3
Diagnostic tool (multidisciplinary or not): ADOS & ICD‐10 (Y)

Population

Sample size (% male): 23 (78)
Diagnosis type: ASD
Mean age at baseline (years): 3.1
IQ (mean standard score): ‐
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: the authors declared they have no COI.
Funding: not reported
Note(s): none

Flanagan 2010

Study characteristics

Methods

Design: prospective
Setting: control group (wait list of a community intervention)
Sample: clinical, from a broad community base
Location (country): Canada
Length of follow‐up (years): 1.4
Diagnostic tool (multidisciplinary or not): CARS (N)

Population

Sample size (% male): 67 (82)
Diagnosis type: ASD
Mean age at baseline (years): 3.6
IQ (mean standard score): ‐
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): < 70

Notes

Conflict of interest: not reported
Funding: Canadian Institutes of Health Research (Canada Graduate Scholarship) and the Canadian Institutes of Health Research/National Alliance for Autism Research (Interdisciplinary Training Program in Autism Spectrum Disorders)
Note(s): none

Freeman 2004

Study characteristics

Methods

Design: retrospective
Setting: cohort study
Sample: clinical, from a broad community base
Location (country): Canada
Length of follow‐up (years): 2.2
Diagnostic tool (multidisciplinary or not): DSM IV (N)

Population

Sample size (% male): 59 (81)
Diagnosis type: ASD
Mean age at baseline (years): 4
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: not reported (thesis)
Note(s): none

Gabriels 2007

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): USA
Length of follow‐up (years): 5.3
Diagnostic tool (multidisciplinary or not): DSM‐IV and ADOS (N)

Population

Sample size (% male): 17 (71)
Diagnosis type: ASD
Mean age at baseline (years): 5.7
IQ (mean standard score): > 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): > 70

Notes

Conflict of interest: not reported
Funding: not reported
Note(s): none

Gillberg 1990

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical, from a broad community base
Location (country): Sweden
Length of follow‐up (years): 4.0
Diagnostic tool (multidisciplinary or not): DSM‐III‐R (N)

Population

Sample size (% male): 25 (68)
Diagnosis type: ASD
Mean age at baseline (years): 1.1
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: Child Neuropsychiatry Centre, Goteborg, Sweden
Note(s): none

Giserman‐Kiss 2020

Study characteristics

Methods

Design: prospective
Setting: cohort study where all received intervention
Sample: clinical
Location (country): USA
Length of follow‐up (years): 1.98
Diagnostic tool (multidisciplinary or not): ADOS (N)

Population

Sample size (% male): 60 (87)
Diagnosis type: ASD
Mean age at baseline (years): 2.31
IQ (mean standard score): < 70
Language (mean standard score): < 70
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: the authors declared they have no COI.
Funding: HRSA (R40MC26195), NIMH (R01MH104400), Autism Speaks, the UMB Office of Graduate Studies, and the UMB Graduate Student Assembly.
Note(s): none

Gonzalez 1993

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): USA
Length of follow‐up (years): 1.0
Diagnostic tool (multidisciplinary or not): DSM‐III, DSM‐III‐R, DSM‐IV & ICD‐10 (N)

Population

Sample size (% male): 30 (73)
Diagnosis type: ASD
Mean age at baseline (years): 4.5
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: supported, in part, by USPHS Grants MH‐18915 (Drs Gonzalez, Shay, and Campbell), MH‐32212 (Dr Campbell), and P01 MH‐47200 (DSM‐IV Autism/Pervasive Developmental Disorder Field Trial ‐ American Psychiatric Association) from the National Institute of Mental Health; the Stallone Fund for Autism Research; the Hirschell E and Deanna E Levine Foundation; and the Marion 0 and Maximilian E Hoffman Foundation, Inc
Note(s): none

Haglund 2020

Study characteristics

Methods

Design: prospective
Setting: intensive intervention in a community setting
Sample: clinical from broad community base
Location (country): Sweden
Length of follow‐up (years): 3.2
Diagnostic tool (multidisciplinary or not): ADOS (N)

Population

Sample size (% male): 27 (81.5)
Diagnosis type: ASD
Mean age at baseline (years): 4.9
IQ (mean standard score): both
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: the author(s) declared no potential COI with respect to the research, authorship, and/or publication of the article.
Funding: the author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by ALF Foundation, Region Skåne, and the Lindhaga Foundation.
Note(s): none

Hinnebusch 2017

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: unclear how sample was drawn
Location (country): USA
Length of follow‐up (years): 2.2
Diagnostic tool (multidisciplinary or not): DSM‐IV, ADOS, CARS (N)

Population

Sample size (% male): 219 (81)
Diagnosis type: ASD
Mean age at baseline (years): 2.13
IQ (mean standard score): both
Language (mean standard score): < 70
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: Deborah Fein is part owner of M‐CHAT‐R, LLC, which receives royalties from companies that incorporate the M‐CHAT‐R into commercial products and charge for its use. Data reported in the current paper are from the freely available paper versions of the M‐CHAT and M‐CHAT‐R. Alexander Hinnebusch and Lauren Miller declared that they had no COI.
Funding: this study was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (Grant number R01HD039961) and the Maternal and Child Health Bureau (Grant number R40MC00270).
Note(s): none

Kim 2016

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): USA
Length of follow‐up (years): 1.3
Diagnostic tool (multidisciplinary or not): ADOS (Y)

Population

Sample size (% male): 100 (84)
Diagnosis type: ASD
Mean age at baseline (years): 1.8
IQ (mean standard score): > 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): both

Notes

Conflict of interest: the authors declared they have no COI.
Funding: IMH grant #P50MH081756‐0 awarded to Fred Volkmar, Ami Klin,Rhea Paul, and KC, NIMH grant #1R03MH086732 awarded to SM, and the Associates of Child Study Center
Note(s): none

Klintwall 2015

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): USA
Length of follow‐up (years): 1.4
Diagnostic tool (multidisciplinary or not): ADOS, ADOS‐T (U)

Population

Sample size (% male): 70 (89)
Diagnosis type: ASD
Mean age at baseline (years): 1.8
IQ (mean standard score): > 70
Language (mean standard score): < 70
Adaptive behaviour (mean standard score): > 70

Notes

Conflict of interest: not reported
Funding: NIMH P50 MH081756 (Project 2, PI: KC), NIMH R01 MH087554 (PI: KC), and NICHD P01 HD003008 (Project 1, PI: KC)
Note(s): none

Lombardo 2015

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical, drawn from broad community base (well baby 1 year check and community referral)
Location (country): USA
Length of follow‐up (years): 1.1 (ASD poor language outcome) and 1 (ASD good language outcome)
Diagnostic tool (multidisciplinary or not): ADOS (N)

Population

Sample size (% male): 24 (79) ASD poor and 36 (78) ASD good
Diagnosis type: ASD
Mean age at baseline (years): 2.0 (ASD poor) and 1.78 (ASD good)
IQ (mean standard score): both
Language (mean standard score): both
Adaptive behaviour (mean standard score): both

Notes

Conflict of interest: not reported
Funding: this work was supported by NIMH Autism Center of Excellence grant P50‐MH081755 (EC), NIMH R01‐MH080134 (KP), NFAR grant (KP), NIMH R01‐MH036840 (EC), and fellowships from Jesus College, Cambridge and the British Academy (MVL).
Note(s): contacted authors to request the required data. Authors responded quote: "we didn't compute a calibrated ADOS severity score, so unfortunately cannot provide that data". ADOS data had not been transformed to be able to be used. Authors reported that all children in the study retained their diagnosis at follow‐up because that was a requirement for inclusion, so it is unclear how many from baseline may have no longer retained their diagnosis

Malhi 2011

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): India
Length of follow‐up (years): 1.7
Diagnostic tool (multidisciplinary or not): CARS (Y)

Population

Sample size (% male): 77 (83)
Diagnosis type: ASD
Mean age at baseline (years): 2.5
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: the authors declared they have no COI.
Funding: none (self‐funded ‐ Department of Pediatrics, Post Graduate Institute of Medical Education and Research, Sector 12, Chandigarh)
Note(s): none

Martin‐Borreguero 2021

Study characteristics

Methods

Design: retrospective with whole cohort considered
Setting: cohort study
Sample: clinical
Location (country): Spain
Length of follow‐up (years): 2
Diagnostic tool (multidisciplinary or not): DSM‐5, CARS and ADOS but CARS repeated several times (Y)

Population

Sample size (% male): 52 (82‐85)
Diagnosis type: ASD
Mean age at baseline (years): Between 2‐6 years. Categorical data provided with no overall mean.
IQ (mean standard score): ‐
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: the authors declared they have no COI.
Funding: Spanish Society of Paediatrics and SPAOYEX
Note(s): none

Moore 2003

Study characteristics

Methods

Design: retrospective
Setting: cohort study
Sample: clinical, from a broad community base
Location (country): UK
Length of follow‐up (years): 1.6
Diagnostic tool (multidisciplinary or not): ADOS (N)

Population

Sample size (% male): 19 (80)
Diagnosis type: ASD
Mean age at baseline (years): 2.8
IQ (mean standard score): > 70
Language (mean standard score): < 70
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: not reported
Note(s): none

Moss 2008

Study characteristics

Methods

Design: prospective
Setting: intervention trial, with treatment and control arms
Sample: clinical, from a broad community base
Location (country): UK
Length of follow‐up (years): 7.0
Diagnostic tool (multidisciplinary or not): ADI‐R (N)

Population

Sample size (% male): 35 (91)
Diagnosis type: ASD
Mean age at baseline (years): 3.5
IQ (mean standard score): < 70
Language (mean standard score): < 70
Adaptive behaviour (mean standard score): < 70

Notes

Conflict of interest: not reported. This was a publication of a PhD thesis. There was no information included in the paper about COI.
Funding: Action Research
Note(s): none

Naigles 2016

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical, drawn from broad community base
Location (country): USA
Length of follow‐up (years): 1.4
Diagnostic tool (multidisciplinary or not): ADOS (N)

Population

Sample size (% male): 15 (100)
Diagnosis type: ASD
Mean age at baseline (years): 2.6
IQ (mean standard score): ‐
Language (mean standard score): > 70
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: the authors declared they have no COI.
Funding: National Institute on Deafness and Other Communication Disorders grant to L Naigles (Grant number: R01 DC007428)
Note(s): unable to extract change in diagnosis over time based on data provided in the paper. Only change in ADOS scores at V1 and V5 provided. Unable to obtain required data from study authors

Neuhaus 2016

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical, drawn from broad community base
Location (country): USA
Length of follow‐up (years): 10.6
Diagnostic tool (multidisciplinary or not): ADOS‐G and ADI‐R (N)

Population

Sample size (% male): 26 (88)
Diagnosis type: ASD
Mean age at baseline (years): 3.7
IQ (mean standard score): > 70
Language (mean standard score): < 70
Adaptive behaviour (mean standard score): < 70

Notes

Conflict of interest: not reported
Funding: support for this project was provided by NICHD and NIDCD PO1HD34565, and an Autism Speaks Meixner Translational Postdoctoral Fellowship (Neuhaus)
Note(s): completed ADOS and ADI‐R at multiple time points but did not present scores or diagnostic status at each time point. Unable to obtain required data from study authors

Ozonoff 2015

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): USA
Length of follow‐up (years): 1.0
Diagnostic tool (multidisciplinary or not): ADI‐R, DSM‐IV, best clinical estimate (N)

Population

Sample size (% male): 79 (ND)
Diagnosis type: ASD
Mean age at baseline (years): 2.0
IQ (mean standard score): ‐
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: the authors declared they have no COI.
Funding: National Institutes of Health Grants, Canadian Institutes ofHealth Research, Autism Speaks Canada
Note(s): none

Paul 2008

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical, from a broad community base
Location (country): USA
Length of follow‐up (years): 1.1
Diagnostic tool (multidisciplinary or not): ADOS (Y)

Population

Sample size (% male): 37 (ND)
Diagnosis type: ASD
Mean age at baseline (years): 1.82
IQ (mean standard score): > 70
Language (mean standard score): < 70
Adaptive behaviour (mean standard score): > 70

Notes

Conflict of interest: not reported
Funding: National Institute of Mental Health (NIMH)P01‐03008, National Institute on Deafness and Other Communication Disorders (NIDCD)U54 MH66494, The National Institute of Environmental Health Sciences (NIEHS), The National Institute of Child Health and Human Development (NICHD), The National Institute of Neurological Disorders and Stroke (NINDS), NIDCDK24 HD045576, The National Alliance for Autism Research
Note(s): none

Qian 2018

Study characteristics

Methods

Design: retrospective
Setting: cohort study
Sample: clinical
Location (country): China
Length of follow‐up (years): 2
Diagnostic tool (multidisciplinary or not): CARS, ADI‐R (N)

Population

Sample size (% male): 37 (86)
Diagnosis type: ASD
Mean age at baseline (years): 2.57
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: Science Foundation of China (81771478), and the Jiangsu Provincial Key Research and Development Program (BE2016616) and the Major National Research and Development Program of China (2016YFC1306205)
Note(s): none

Rivard 2019

Study characteristics

Methods

Design: prospective
Setting: all had early behaviour intervention, no control arm
Sample: clinical
Location (country): Canada
Length of follow‐up (years): 1
Diagnostic tool (multidisciplinary or not): GARS and CARS but only GARS used at outcome (N)

Population

Sample size (% male): 32 (66)
Diagnosis type: ASD
Mean age at baseline (years): 3.9
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): <70

Notes

Conflict of interest: the author(s) declared the following potential COI with respect to the research, authorship, and/or publication of this article: Amélie Terroux declared to be an employee of the Centre de réadaptation en déficience intellectuelle et troubles envahissant du développement de la Montérégie‐Est. Marjorie Morin and Céline Mercier were also under contract for the same agency for the duration of the study.
Funding: the author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by grants by the Montérégie Health Agency and the Québec Ministry of Health and Social Services to Céline Mercier and Mélina Rivard.
Note(s): none

Robain 2020

Study characteristics

Methods

Design: prospective
Setting: intervention study (RCT with treatment and control arm)
Sample: clinical from broad community base
Location (country): Switzerland
Length of follow‐up (years): 1
Diagnostic tool (multidisciplinary or not): ADOS (not described)

Population

Sample size (% male): 60 (100)
Diagnosis type: ASD
Mean age at baseline (years): 3
IQ (mean standard score): > 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: the authors declared they have no COI.
Funding: this study was supported by the National Center of Competence in Research “Synapsy,” financed by the Swiss National Science Foundation (SNF, Grant Number: 51AU40_125759), by a SNF Grant to MS (#163859), and by the “Fondation Pôle Autisme” (https://www. pole‐autisme.ch). Martina Franchini was also supported by an individual fellowship from the SNF (#P2GEP1_171686)
Note(s): none

Santocchi 2012

Study characteristics

Methods

Design: not described
Setting: cohort study
Sample: not described
Location (country): Italy
Length of follow‐up (years): 1.75
Diagnostic tool (multidisciplinary or not): ADOS‐G and CARS (not described)

Population

Sample size (% male): 98 (‐)
Diagnosis type: ASD
Mean age at baseline (years): 3.25
IQ (mean standard score): ‐
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: not described
Note(s): conference abstract. We attempted to obtain the full text through multiple sources and contacted the study authors but did not receive a response so we have extracted as much data as possible from the abstract and have not been able to complete risk of bias assessment.

Sheinkopf 1998

Study characteristics

Methods

Design: prospective
Setting: intervention trial, with control arm
Sample: clinical, from a broad community base
Location (country): USA
Length of follow‐up (years): 1.5
Diagnostic tool (multidisciplinary or not): DSM III (Y)

Population

Sample size (% male): 11 (ND)
Diagnosis type: ASD
Mean age at baseline (years): 2.94
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: not reported
Note(s): none

Smith 2019

Study characteristics

Methods

Design: prospective
Setting: intervention arm with one treatment arm
Sample: clinical
Location (country): Norway
Length of follow‐up (years): 12.41
Diagnostic tool (multidisciplinary or not): ADI‐R (N)

Population

Sample size (% male): 19 (84)
Diagnosis type: ASD
Mean age at baseline (years): 2.92
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): <70

Notes

Conflict of interest: the authors declared they have no COI.
Funding:quote: "The author(s) received no financial support for the research, authorship, and/or publication of this article."
Note(s): none

Soke 2011

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): USA
Length of follow‐up (years): 2.1
Diagnostic tool (multidisciplinary or not): ADI‐R (Y)

Population

Sample size (% male): 28 (79)
Diagnosis type: AD
Mean age at baseline (years): 2.8
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported (Masters thesis)
Funding: Grant # U19HD35468 from the National Institute for Child Health and Human Development (NICHD)
Note(s): none

Solomon 2014

Study characteristics

Methods

Design: prospective
Setting: RCT, with control arm study
Sample: population based
Location (country): USA
Length of follow‐up (years): 1.0
Diagnostic tool (multidisciplinary or not): ADOS (U)

Population

Sample size (% male): 55 (84)
Diagnosis type: ASD
Mean age at baseline (years): 4.2
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: Small Business Innovation Research (SBIR) grants, sponsored by the NIMH, are administered through business entities to support research in technological innovation and dissemination. Therefore, all SBIR principle investigators if they are directly involved in the grant have a financial conflict of interest. R Solomon, the principle investigator of the study, was involved in the design of the study, wrote the first draft of the manuscript and was involved in the decision to submit the article. To limit his bias, R Solomon was assiduously excluded from evaluation of outcomes, data collection, or data analysis, all of which were done independently at MichiganState University under the auspices of LA Van Egeren, a senior level researcher and director of the Community Evaluation and Research Collaborative. The only involvement with data occurred when the data collected at Easter Seals sites were identified at the “central office” in Ann Arbor and sent on to Michigan State University for analysis. R Solomon received no other funds outside of the grant (such as honoraria, consultant fees, etc.) before or during the grant. G Mahoney received a fee for consulting as an original part of the grant protocol. The remaining authors declared no COI.
Funding: National Institute of Mental Health (NIMH) and Small Business Innovation Research (SBIR) grant (grant# 2 R44 MH078431‐02A)
Note(s): none

Solomon 2016

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical, from a broad community base
Location (country): USA
Length of follow‐up (years): 2.8
Diagnostic tool (multidisciplinary or not): ADOS (N)

Population

Sample size (% male): 102 (80)
Diagnosis type: ASD
Mean age at baseline (years): 2.9
IQ (mean standard score): > 70
Language (mean standard score): both
Adaptive behaviour (mean standard score): both

Notes

Conflict of interest: Drs Solomon, Iosif, Reinhardt, Libero, Nordahl, Ozon‐off, and Rogers reported no biomedical financial interests or conflicts of interest. Dr Amaral is on the Scientific Advisory Board of Stemina Biomaker Discovery and Axial Biotherapeutics.
Funding: Dr Solomon was supported by National Institutes of Health (NIH) grants R01MH106518 and R01MH103284. Dr Nordahl was supported by R01MH104438. Dr Amaral was supported by R01MH103371. Dr Reinhardt was supported by 5T32MH073124. Ana‐Maria Iosif, PhD provided statistical support as part of the MIND Institute Intellectual and Developmental Disabilities ResearchCenter (U54 HD079125).
Note(s): none

Spjut Jansson 2016

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): Sweden
Length of follow‐up (years): 2.0
Diagnostic tool (multidisciplinary or not): ADOS, DISCO, ADI‐R (Y)

Population

Sample size (% male): 71 (79)
Diagnosis type: ASD
Mean age at baseline (years): 3.0
IQ (mean standard score): both
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): both

Notes

Conflict of interest: the authors declared they have no COI.
Funding: Health & Medical Care Committee of the Regional Executive Board, Region Västra Götaland (BSJ)
Note(s): none

Sullivan 2010

Study characteristics

Methods

Design: prospective
Setting: All participants enrolled in a community intervention (IBI).
Sample: clinical, from a broad community base
Location (country): Canada
Length of follow‐up (years): 2.2
Diagnostic tool (multidisciplinary or not): CARS (N)

Population

Sample size (% male): 75 (83)
Diagnosis type: ASD
Mean age at baseline (years): 3.9
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): < 70

Notes

Conflict of interest: not reported
Funding: Provincial Centre of Excellence for Child and Youth Mental Health at CHEO, Social Sciences and Humanities Research Council of Canada, and the Canadian Institutes of Health Research/National Alliance for Autism Research (Interdisciplinary Training Program in Autism Spectrum Disorders)
Note(s): none

Szatmari 2021

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical
Location (country): Canada
Length of follow‐up (years): 7.36
Diagnostic tool (multidisciplinary or not): clinical consensus, ADOS and ADI‐R but ADOS scores reported twice (N)

Population

Sample size (% male): 272 (86)
Diagnosis type: ASD
Mean age at baseline (years): 3.39
IQ (mean standard score): both
Language (mean standard score): both
Adaptive behaviour (mean standard score): both

Notes

Conflict of interest: Dr Szatmari reported receiving grants from Canadian Institutes of Health Research (CIHR) during the conduct of this study. Dr Cost reported receiving grants from the CIHR during the conduct of the study. Dr Bennett reported receiving grants from CIHR and grants from Hamilton Health Sciences Foundation during the conduct of the study; and grants from Hamilton Health Sciences and Brain Canada outside the submitted work. Dr Smith reported receiving grants from the Centre for Addiction and Mental Health/CIHR as 1 of 5 study site principle investigators during the conduct of the study. Dr Zwaigenbaum reported receiving personal fees from Roche as a data monitoring board member outside the submitted work. No other disclosures were reported.
Funding: this study was supported by the Canadian Institutes of Health Research, Kids Brain Health Network, Autism Speaks, the Government of British Columbia, Alberta Innovates Health Solutions, and the Sinneave Family Foundation. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Note(s): none

Takeda 2007

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical, from a broad community base
Location (country): Japan
Length of follow‐up (years): 2.9
Diagnostic tool (multidisciplinary or not): ICD‐10, CARS (N)

Population

Sample size (% male): 126 (81)
Diagnosis type: ASD
Mean age at baseline (years): 2.62
IQ (mean standard score): < 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: not reported
Note(s): none

Thomas 2009

Study characteristics

Methods

Design: retrospective
Setting: cohort study (community intervention received over 5 years)
Sample: clinical, from a broad community base
Location (country): USA
Length of follow‐up (years): 5.0
Diagnostic tool (multidisciplinary or not): CARS (U)

Population

Sample size (% male): 69 (79)
Diagnosis type: ASD
Mean age at baseline (years): 4.4
IQ (mean standard score): ‐
Language (mean standard score): both
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported (thesis)
Funding: not reported (thesis)
Note(s): none

Venker 2014

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical, from a broad community base
Location (country): USA
Length of follow‐up (years): 5.9
Diagnostic tool (multidisciplinary or not): ADOS, DSM‐IV (Y)

Population

Sample size (% male): 129 (87)
Diagnosis type: ASD
Mean age at baseline (years): 2.8
IQ (mean standard score): > 70
Language (mean standard score): both
Adaptive behaviour (mean standard score): > 70

Notes

Conflict of interest: not reported
Funding: NIH R01DC007223‐05 (Ellis Weismer, PI; Gernsbacher, co‐PI); T32DC005359‐10 (Ellis Weismer, PI); P30HD003352‐46 (Seltzer, PI)
Note(s): none

Wu 2016

Study characteristics

Methods

Design: retrospective
Setting: cohort study
Sample: clinical
Location (country): USA
Length of follow‐up (years): 1.4
Diagnostic tool (multidisciplinary or not): DSM‐IV‐TR, file record review (N)

Population

Sample size (% male): 8564 (83)
Diagnosis type: ASD
Mean age at baseline (years): 3.7
IQ (mean standard score): ‐
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: the authors declared they have no COI.
Funding: the sponsor for the data collection of the Autism and Developmental Disabilities Monitoring (ADDM) Network is the US Centers for Disease
Control and Prevention (CDC).
Note(s): none

Zappella 1990

Study characteristics

Methods

Design: retrospective, with whole cohort considered
Setting: intervention trial, with one treatment arm
Sample: clinical, from a broad community base
Location (country): Italy
Length of follow‐up (years): 1.8
Diagnostic tool (multidisciplinary or not): DSM‐III (N)

Population

Sample size (% male): 15 (87)
Diagnosis type: AD
Mean age at baseline (years): 4.5
IQ (mean standard score): > 70
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): both

Notes

Conflict of interest: not reported
Funding: not reported
Note(s): none

Zappella 2010

Study characteristics

Methods

Design: retrospective
Setting: cohort study
Sample: clinical
Location (country): Italy
Length of follow‐up (years): 2.7
Diagnostic tool (multidisciplinary or not): DSM‐IV‐TR (U)

Population

Sample size (% male): 534 (84)
Diagnosis type: ASD
Mean age at baseline (years): 5.0
IQ (mean standard score): ‐
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): ‐

Notes

Conflict of interest: not reported
Funding: not reported
Note(s): none

Zwaigenbaum 2015

Study characteristics

Methods

Design: prospective
Setting: cohort study
Sample: clinical, from a broad community base
Location (country): Canada
Length of follow‐up (years): 1.5
Diagnostic tool (multidisciplinary or not): DSM‐IV‐TR (N)

Population

Sample size (% male): 23 (69)
Diagnosis type: ASD
Mean age at baseline (years): 1.5
IQ (mean standard score): ‐
Language (mean standard score): ‐
Adaptive behaviour (mean standard score): > 70

Notes

Conflict of interest: Dr Zwaigenbaum was supported by the Stollery Children’s Hospital Foundation Chair in Autism Research. Drs Bryson and Smith were supported by the Jack and Joan Craig Chair in Autism Research, Dr Szatmari was supported by the Chedoke Health Chair in Child Psychiatry, and Dr Vaillancourt was supported by a Canada Research Chair in Children’s Mental Health and Violence Protection.
Funding: Canadian Institutes of Health Research (grant numbers 62924 and 102665), Autism Speaks Canada and NeuroDevNet
Note(s): none

Mean scores (IQ, adaptive behaviour or language) for the cohort is < 70 or more than 70% are less than 70. If cohort evenly spread this is signified 'both'.

AD: autistic disorder; ADOS: Autism Diagnostic Observation Schedule; ADI: Autism Diagnostic Interview;ASD: autism spectrum disorder; CARS: Childhood Autism Rating Scale; COI: conflict of interest; DSM: Diagnostic Statistical Manual of Mental Disorders;ICD: International Classification of Diseases; IQ: intelligence quotient ;N: no, not multidisciplinary; NIH: National Institutes of Health; PDD‐NOS: pervasive developmental disorder; PI: principal investigator; RCT: randomised controlled trial; U: unclear; Y: yes, multidisciplinary; ‐: not reported by study

Characteristics of excluded studies [ordered by study ID]

Ir a:

Study

Reason for exclusion

Bacon 2018

Study only followed up those children who had consistent diagnosis at two time points and excluded those who moved off spectrum. Unable to obtain information on numbers that moved off spectrum from study authors.

Bal 2019

Did not use same diagnostic methods/tools at baseline and follow‐up

Berry 2009

Did not use same diagnostic methods/tools at baseline and follow‐up

Canal‐Bedia 2016

Did not use same diagnostic methods/tools at baseline and follow‐up

Charman 2005

Did not use same diagnostic methods/tools at baseline and follow‐up

Chawarska 2007

Did not use same diagnostic methods/tools at baseline and follow‐up

Clark 2017

Did not use same diagnostic methods/tools at baseline and follow‐up

De Giacomo 2009

Did not use same diagnostic methods/tools at baseline and follow‐up

Guthrie 2013

Did not use same diagnostic methods/tools at baseline and follow‐up.

Hedvall 2014

Did not use same diagnostic methods/tools at baseline and follow‐up

Jónsdóttir 2007

Did not use same diagnostic methods/tools at baseline and follow‐up

Kadam 2021

Did not use same diagnostic methods/tools at baseline and follow‐up

Kantzer 2018

Did not use same diagnostic methods/tools at baseline and follow‐up

Ozonoff 2018

No baseline diagnostic assessment

Shumway 2012

Did not use same diagnostic methods/tools at baseline and follow‐up

Stone 1999

Did not use same diagnostic methods/tools at baseline and follow‐up

Sutera 2010

Did not use same diagnostic methods/tools at baseline and follow‐up

Thurm 2015

Did not use same diagnostic methods/tools at baseline and follow‐up

Tunc 2021

Sample only included those diagnosed at baseline and follow‐up therefore unable to determine how many may have lost diagnosis at follow‐up.

Van Daalen 2009

Did not use same diagnostic methods/tools at baseline and follow‐up

Venter 1992

Did not use same diagnostic methods/tools at baseline and follow‐up

Characteristics of studies awaiting classification [ordered by study ID]

Ir a:

Anglim 2012

Notes

Conference abstract. May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Boi 2017

Notes

Conference abstract. May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Brown 1997

Notes

May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Chang 2017

Notes

Conference abstract. Appears to meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Chang 2017a

Notes

Appears to meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Da Silva 2003

Notes

May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Eapen 2019

Notes

Conference abstract. Appears to meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Faroghizadeh 2021

Notes

May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Gabis 2011

Notes

Conference abstract. May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data. Appears to have overlapping participants with Millikovsky‐Ayalon 2012 which is also awaiting classification.

Ghamari Kivi 2012

Notes

Conference abstract. May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Jimenez‐Martinez 2018

Notes

Conference abstract. May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Melville 1987

Notes

Dissertation. We requested a copy of the paper from numerous libraries, but given the date of the thesis, which is in hard copy (no digital copy), we were unable to access the full thesis.

Millikovsky‐Ayalon 2012

Notes

Study is in Hebrew. We contacted the authors for further information (an email was written to the authors in Hebrew) but we did not receive any response.

Mohanta 2019

Notes

Conference abstract. May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Mosconi 2009

Notes

Insufficient data to accurately classify as included or excluded. Contacted study authors for further data but did not receive a response

Muratori 2002

Notes

Study is in Italian. We had this article translated from Italian but require further information from the study authors to determine whether the study is eligible for inclusion. We emailed the authors and are awaiting a response.

Ozyurt 2020

Notes

May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Perucchini 2005

Notes

Study is in Italian. Article was translated in Italian but further information was required from the authors to determine whether the study was eligible for inclusion. We emailed the authors and are awaiting a response. Participants may overlap with Muratori 2002

Selvakumar 2018

Notes

Study meets eligibility criteria, however it may include the same participants as another included study by the same authorship group (Malhi 2011). We contacted the study authors several times to confirm whether the participants were the same/overlapping but did not receive a response.

Takesada 1992

Notes

May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Zhang 2019

Notes

May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Zirakashvili 2018

Notes

Conference abstract. May meet eligibility criteria. We attempted to obtain the full text through multiple sources and contacted the study authors but were unable to confirm eligibility for inclusion or obtain data.

Study flow diagram.

Figuras y tablas -
Figure 1

Study flow diagram.

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Risk of bias ratings on the QUIPS tool (40 studies). Green is low risk of bias, orange is moderate risk of bias and red is high risk of bias.Summary risk of bias ratings for provided for each QUIPS domain (i.e.study participation, study attrition, outcome measurement). See Appendix 9 for a figure showing all criteria that were rated for each domain. Studies were rated to have an overall low risk of bias if all three summary domains were rated low or moderate risk of bias. Studies were rated to have an overall high risk of bias if all three summary domains were rated low or moderate risk of bias.

Figuras y tablas -
Figure 2

Risk of bias ratings on the QUIPS tool (40 studies). Green is low risk of bias, orange is moderate risk of bias and red is high risk of bias.

Summary risk of bias ratings for provided for each QUIPS domain (i.e.study participation, study attrition, outcome measurement). See Appendix 9 for a figure showing all criteria that were rated for each domain. Studies were rated to have an overall low risk of bias if all three summary domains were rated low or moderate risk of bias. Studies were rated to have an overall high risk of bias if all three summary domains were rated low or moderate risk of bias.

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Risk of bias graph: review authors' judgements about each risk of bias item for each included study presented as percentages across all included studies (41 studies).

Figuras y tablas -
Figure 3

Risk of bias graph: review authors' judgements about each risk of bias item for each included study presented as percentages across all included studies (41 studies).

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Risk of bias ratings for each included study for each of the 18 criteria. Red indicates high, orange indicates moderate, green indicates low and yellow indicates unclear risk of bias.

Figuras y tablas -
Figure 4

Risk of bias ratings for each included study for each of the 18 criteria. Red indicates high, orange indicates moderate, green indicates low and yellow indicates unclear risk of bias.

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Forest plot of proportion of children that retained their autism diagnosisFootnote
CI: confidence interval; ES: effect size; N: number in sample

Figuras y tablas -
Figure 5

Forest plot of proportion of children that retained their autism diagnosis

Footnote
CI: confidence interval; ES: effect size; N: number in sample

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Age at baseline: < 2 years; 2 to 3 years; 4 to 6 years; 7 to 12; years; 13 to 17 yearsFootnote
CI: confidence interval; ES: effect size; N: number in sample

Figuras y tablas -
Figure 6

Age at baseline: < 2 years; 2 to 3 years; 4 to 6 years; 7 to 12; years; 13 to 17 years

Footnote
CI: confidence interval; ES: effect size; N: number in sample

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Age at follow up: 2 to 3 years; 4 to 6 years; 7 to 12 years; 13 to 18 yearsFootnote
CI: confidence interval; ES: effect size; N: number in sample

Figuras y tablas -
Figure 7

Age at follow up: 2 to 3 years; 4 to 6 years; 7 to 12 years; 13 to 18 years

Footnote
CI: confidence interval; ES: effect size; N: number in sample

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Duration of follow‐up: short‐term (up to 2 years), medium‐term (2 to 5 years), and long‐term (6 to 17 years) follow‐upFootnote
CI: confidence interval; ES: effect size; N: number in sample

Figuras y tablas -
Figure 8

Duration of follow‐up: short‐term (up to 2 years), medium‐term (2 to 5 years), and long‐term (6 to 17 years) follow‐up

Footnote
CI: confidence interval; ES: effect size; N: number in sample

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Decade of publication: 1960 to 1969; 1970 to 1979; 1980 to 1989; 1990 to 1999; 2000 to 2009; 2010 to 2019Footnote
CI: confidence interval; ES: effect size; N: number in sample

Figuras y tablas -
Figure 9

Decade of publication: 1960 to 1969; 1970 to 1979; 1980 to 1989; 1990 to 1999; 2000 to 2009; 2010 to 2019

Footnote
CI: confidence interval; ES: effect size; N: number in sample

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Intelligence: mean IQ 70; mean IQ > 70; or more than 70% of the cohort has IQ 70Footnote
CI: confidence interval; ES: effect size; IQ: intelligence quotient; N: number in sample

Figuras y tablas -
Figure 10

Intelligence: mean IQ 70; mean IQ > 70; or more than 70% of the cohort has IQ 70

Footnote
CI: confidence interval; ES: effect size; IQ: intelligence quotient; N: number in sample

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Language: > 70% verbal; > 70% non‐verbal (i.e. use < 15 words); mean standardised language score < 70; mean standardised language score 70; or > 70% of the cohort has mean language score < 70Footnote
CI: confidence interval; ES: effect size; N: number in sample

Figuras y tablas -
Figure 11

Language: > 70% verbal; > 70% non‐verbal (i.e. use < 15 words); mean standardised language score < 70; mean standardised language score 70; or > 70% of the cohort has mean language score < 70

Footnote
CI: confidence interval; ES: effect size; N: number in sample

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Adaptive behaviour: mean standard score 70; mean standard score > 70; or > 70% of the cohort has mean standard score 70Footnote
CI: confidence interval; ES: effect size; N: number in sample

Figuras y tablas -
Figure 12

Adaptive behaviour: mean standard score 70; mean standard score > 70; or > 70% of the cohort has mean standard score 70

Footnote
CI: confidence interval; ES: effect size; N: number in sample

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Multidisciplinary team used for diagnosis, Yes or NoFootnote
CI: confidence interval; ES: effect size; N: number in sample

Figuras y tablas -
Figure 13

Multidisciplinary team used for diagnosis, Yes or No

Footnote
CI: confidence interval; ES: effect size; N: number in sample

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Funnel Plot of included studies

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Figure 14

Funnel Plot of included studies

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Summary of findings 1. Summary of findings

Proportion of individuals who have a diagnosis of autism spectrum disorder at baseline and continue not meet diagnostic criteria at follow‐up one or more years later

Patient or population: children diagnosed with autism spectrum disorder

Settings: range of settings

Outcomes

Relative effect

(95% CI)

Number of participants

(studies)

Quality of the evidence
(GRADE)

Comments

Proportion with an autism spectrum disorder diagnosis at baseline and follow‐up

Follow‐up: > 12 months

0.92

(0.89 to 0.95)

11,105 (34 studies:

1 intervention trial with 1 arm;

1 RCTa;

2 non‐RCTsa;

30 TAU or in the community)

⊕⊕⊝⊝

Lowb,c

Limitations (ROB): seriousb

Inconsistency: seriousc

Indirectness: not serious

Imprecision: not serious

Publication/reporting bias: not serious

Effect size: N/A

Dose response gradient: N/A

Confirmatory evidence: N/A

See footnotes below.

Social communication at baseline and follow‐up (mean score)

Follow‐up: > 12 months

See comments

None of the included studies provided separate domain scores at baseline and follow‐up

Restricted and repetitive behaviours and interests at

baseline and follow‐up (mean score)

Follow‐up: > 12 months

See comments

None of the included studies provided separate domain scores at baseline and follow‐up

Defnitions of levels of evidence 

High: We are very confident that the true prognosis (probability of future events) lies close to that of the estimate

Moderate: We are moderately confident that the true prognosis (probability of future events) is likely to be close to the estimate, but there is a possibility that it is substantially different

Low: Our confidence in the estimate is limited: the true prognosis (probability of future events) may be substantially different from the estimate

Very low: We have very little confidence in the estimate: the true prognosis (probability of future events) is likely to be substantially different from the estimate

 

CI: Confidence intervals;N/A: Not applicable;RCT(s): Randomised controlled trial(s);ROB: Risk of bias; TAU: Treatment as usual.

aData were taken from the control arm of the study
bWe downgraded the quality of the evidence by one level for risk of bias due to high risk of bias across most studies: 85% of studies were rated moderate or high risk of bias in study participation, 68% were moderate or high risk of bias in study attrition and 88% were rated moderate or high risk of bias for outcome measurement. Only 5% of studies were rated low risk of bias across all three criteria.
cWe downgraded the quality of the evidence one level for inconsistency of results (large heterogeneity (I2 = 88.71%), P value (P < 0.01)). The forest plot showed significant variation between point estimates for studies and non‐overlapping confidence intervals across many studies. The least and most optimistic point estimates varied considerably (60% to 100%) and each of these estimates were likely to result in different conclusions about the stability of a diagnosis in autism spectrum disorder.

Figuras y tablas -
Summary of findings 1. Summary of findings
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Table 1. Changes to the classification systems over time

Year published

Classification system

Subgroups (as specified in the classification system)

1975

International Classification of Diseases, Ninth Revision, Clinical Modification (ICD‐9‐CM)

Autistic disorder

1980

Diagnostic and Statistical Manual of Mental Disorders, Third Edition (DSM‐III)

PDD: infantile autism, childhood onset PDD and atypical PDD

1987

Diagnostic and Statistical Manual of Mental Disorders, Third Edition, Revised (DSM‐III‐R)

PDD: autistic disorder, PDD‐not otherwise specified (PDD‐NOS)

1994 to 2000

Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM‐IV)

Asperger’s disorder, autistic disorder, PDD‐NOS

1996

International Classification of Diseases, Tenth Revision (ICD‐10)

Childhood autism, Asperger's syndrome, atypical autism, pervasive developmental disorder (PDD) ‐ unspecified

2000 to 2013

Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM‐IV‐TR)

Asperger’s disorder, autistic disorder, PDD‐NOS

2013 to current

Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM‐5)

Autism spectrum disorder

2018

International Classification of Diseases, Eleventh Revision (ICD‐11)

Autism spectrum disorder

PDD‐NOS: pervasive developmental disorder

Figuras y tablas -
Table 1. Changes to the classification systems over time
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Table 2. Studies that had multiple publications

Primary publication

Additional publications from the same study

Anderson 2009a

Anderson 2007, Bedford 2016, Gotham 2012, Gotham 2011, Hus 2011, Lord 1995, Lord 2004, Lord 2012, Luyster 2007, Pickles 2014, Richler 2010, Thurm 2007

Baghdadli 2012

Baghdadli 2018, Baghdadli 2008, Baghdadli 2007, Darrou 2010, Pry 2011, Pry 2012

Bopp 2006

Bopp 2009; Smith 2007

Flanagan 2010

Flanagan 2012

Giserman‐Kiss 2020

Giserman‐Kiss 2018

Moss 2008

Magiati 2007, Magiati 2011a, Magiati 2011b

Qian 2018

Ke 2017, Li 2019

Rivard 2019

Mello 2018

Solomon 2014

Mahoney 2016

Solomon 2016

Solomon 2018, Waizbard‐Bartov 2021

Szatmari 2021

Baribeau 2020, Baribeau 2021, Courchesne 2021, Bennett 2014, Bennett 2015, Georgiades 2014, Georgiades 2021, Szatmari 2015

Venker 2014

Ellis‐Weismer 2015, Davidson 2017, Ray‐Subramanian 2012, Venker 2016

aMet inclusion criteria but unable to extract data for synthesis as children without a diagnosis of autism spectrum disorder were also included in the cohort. Authors were contacted but we were unable to obtain required data.

Figuras y tablas -
Table 2. Studies that had multiple publications
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Table 3. Characteristics of individual studies included in synthesis (n = 34)

Study

Diagnosis type

N at baseline (% male)

IQ

(mean standard score)a

Adaptive behavior

(mean standard score)a

Language (mean

standard score)a

Age at baseline (years)

Follow‐up duration (years)

Diagnostic tool used at baseline (multidisciplinary or not)

Proportion who met diagnostic criteria at follow‐up

Baghdadli 2012

ASD

152 (82)

< 70

< 70

NR

4.90

3.00

ICD‐10 & CARS (Y)

1.0

Benedetto 2021

ASD

147 (80)

NR

NR

NR

2.3

1

DSM‐5 and ADOS (Y)

0.73

Brian 2016

ASD

18 (72)

> 70

NR

> 70

3.15

6.36

DSM‐IV‐TR & ADOS (N)

0.94

Demb 1989

ASD

12 (75)

< 70

NR

NR

4.50

5.00

DSM‐III & DSM‐III R (N)

0.83

Eaves 2004

ASD

43 (80)

< 70

< 70

NR

2.75

2.25

DSM‐IV, CARS, MDT (Y)

0.93

Elmose 2014

ASD

23 (78)

NR

NR

NR

3.10

8.30

ICD‐10, ADOS (Y)

1.00

Flanagan 2010

ASD

67 (82)

NR

< 70

NR

3.59

1.38

CARS (N)

0.81

Freeman 2004

ASD

59 (81)

< 70

NR

NR

4.00

2.2

DSM IV, CARS (N)

0.97

Gillberg 1990

ASD

25 (68)

< 70

NR

NR

1.13

4.04

DSM‐III‐R (N)

0.92

Giserman‐Kiss 2020

ASD

60 (87)

<70

NR

<70

2.31

1.98

ADOS

0.883

Gonzalez 1993

ASD

30 (73)

< 70

NR

NR

4.50

1.00

DSM‐III, DSM‐III‐R, DSM‐IV and ICD 10 (N)

0.97

Hinnebusch 2017

ASD

219 (81)

Both

NR

< 70

2.13

2.16

DSM‐IV, ADOS, CARS (N)

0.83

Kim 2016

ASD

100 (84)

> 70

Both

NR

1.80

1.30

ADOS (Y)

0.93

Klintwall 2015

ASD

70 (89)

> 70

> 70

< 70

1.83

1.36

ADOS G, ADOS T (U)

0.93

Malhi 2011

ASD

77 (83)

< 70

NR

NR

2.48

1.65

CARS (Y)

0.95

Moore 2003

ASD

19 (80)

> 70

NR

< 70

2.83

1.59

ADI‐R (Y)

1.00

Moss 2008

ASD

35 (91)

< 70

< 70

< 70

3.5

7.00

ADI‐R (N)

0.80

Ozonoff 2015

ASD

79 (NR)

NR

NR

NR

2

1

ADI‐R, DSM IV, best clinical estimate (N)

0.82

Paul 2008

ASD

37 (NR)

> 70

> 70

< 70

1.82

1.09

ADOS (Y)

1.00

Qian 2018

ASD

37 (86)

<70

NR

NR

2.57

2

DSM IV TR; CARS ADI‐R (N)

1.00

Robain 2020

ASD

60 (100)

>70

NR

NR

3

1

DSM 5 ADOS (N)

1.00

Santocchi 2012

ASD

98 (NR)

NR

NR

NR

3.25

1.75

ADOS, CARS

0.86

Sheinkopf 1998

ASD

11 (NR)

< 70

NR

NR

2.94

1.51

DSM‐III (Y)

1.00

Soke 2011

AD

28 (79)

< 70

NR

NR

2.75

2.08

ADI‐R (Y)

0.89

Solomon 2014

ASD

55 (84)

< 70

NR

NR

4.21

1.00

ADOS (U)

0.78

Solomon 2016

ASD

102 (80)

> 70

Both

Both

2.86

2.76

ADOS (N)

0.95

Spjut Jansson 2016

ASD

71 (79)

Both

Both

NR

3.03

2.00

ADOS, DISCO, ADI‐R (Y)

0.93

Sullivan 2010

ASD

75 (83)

< 70

< 70

NR

3.94

2.18

CARS (N)

0.53

Takeda 2007

ASD

126 (81)

< 70

NR

NR

2.62

2.90

ICD‐10, CARS (N)

1.00

Venker 2014

ASD

129 (87)

> 70

> 70

Both

2.80

5.85

DSM‐IV, ADOS (Y)

1.00

Wu 2016

ASD

8564 (83)

NR

NR

NR

3.67

1.43

DSM‐IV‐TR file record review (N)

0.91

Zappella 1990

AD

15 (87)

> 70

Both

NR

4.50

1.83

DSM‐III (N)

0.60

Zappella 2010

ASD

534 (84)

NR

NR

NR

5.00

2.67

DSM‐IV‐TR (U)

0.93

Zwaigenbaum 2015

ASD

23 (69)

NR

> 70

NR

1.50

1.50

DSM‐IV‐TR (N)

0.83

aMean score (IQ, adaptive behaviour or language) for the cohort is < 70 or more than 70% are less than 70. If cohort evenly spread this is signified 'both'.

AD: autistic disorder; ADI: Autism Diagnostic Interview;ADOS: Autism Diagnostic Observation Schedule; ASD: autism spectrum disorder; CARS: Childhood Autism Rating Scale; DISCO: Diagnostic Interview for Social and Communication Disorders; DSM: Diagnostic Statistical Manual of Mental Disorders; ICD: International Classification of Diseases; IQ: intelligence quotient; N: no; NR: not reported; PDD‐NOS: pervasive developmental disorder‐ not otherwise specified; U: unclear; Y: yes.

Figuras y tablas -
Table 3. Characteristics of individual studies included in synthesis (n = 34)
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Table 4. Prognostic factor analyses (eight comparisons), with effect sizes and confidence intervals

Domain

Relative effect (95% CIs)

No. of participants (studies)

I2

Age at baseline

0 to 2 years

0.94 (0.88 to 0.98)

251 (5 studies)

52.64%, P = 0.08

2 to 3 years

0.92 (0.88 to 0.95)

9989 (22 studies)

90.17%, P < 0.01

4 to 5 years

0.91 (0.76 to 0.99)

152 (5 studies)

90.48%, P < 0.01

5 to 6 years

0.93 (0.90 to 0.95)

534 (1 study)

‐

Age at follow‐up

< 4 years

0.89 (0.79 to 0.96)

443 (6 studies)

86.80%, P < 0.01

4 to 6 years

0.92 (0.88 to 0.95)

9794 (21 studies)

87.88%, P < 0.01

7 to 12 years

0.96 (0.89 to 1.00)

868 (7 studies)

88.18%, P < 0.01

Duration of follow‐up

1 to 2 years

0.91 (0.88 to 0.94)

10,745 (27 studies)

87.86%, P < 0.01

2 to 5 years

0.99 (0.92 to 1.00)

293 (4 studies)

78.16%, P < 0.01

6 to 17 years

0.92 (0.77 to 1.00)

67 (3 studies)

‐

Decade of publication

1980 to 1989

0.83 (0.55 to 0.95)

12 (1 studies)

‐

1990 to 1999

0.91 (0.74 to 1.00)

82 (4 studies)

73.16% P = 0.01

2000 to 2009

0.98 (0.93 to 1.00)

479 (7 studies)

80.57% P < 0.01

2010 to 2019

0.90 (0.87 to 0.93)

10,273 (19 studies)

86.84% P < 0.01

2020 to 2029

0.90 (0.68 to 1.00)

259 (3 studies)

‐

Intelligencea

< 70

0.93 (0.85 to 0.98)

793 (15 studies)

90.88%, P < 0.01

> 70

0.97 (0.92 to 1.00)

502 (9 studies)

77.54%, P < 0.01

Both < 70 and > 70

0.86 (0.81, 0.89)

289 (2 studies)

‐

Languagea

< 70

0.92 (0.84 to 0.98)

382 (6 studies)

79.65%, P < 0.01

> 70

0.94 (0.74 to 0.99)

18 (1 study)

‐

Both

0.98 (0.96 to 1.00)

205 (2 studies)

‐

Adaptive behavioura

< 70

0.85 (0.60 to 0.99)

300 (5 studies)

96.33%, P < 0.01

> 70

0.97 (0.8 to 1.00)

233 (4 studies)

83.28%, P < 0.01

Both

0.91 (0.82, 0.97)

283 (4 studies)

73.88%, P = 0.01

Multidisciplinary assessment

Yes

0.97 (0.91 to 1.00)

767 (13 studies)

87.97%, P < 0.01

No

0.88 (0.83 to 0.93)

9468 (16 studies)

89.46%, P < 0.01

aMean score (IQ, adaptive behaviour or language) for the cohort is < 70 or more than 70% are less than 70. If cohort was evenly spread this is signified 'both'.

CI: confidence interval;I2: a statistic that describes the percentage of variation across studies; No.: number.

Figuras y tablas -
Table 4. Prognostic factor analyses (eight comparisons), with effect sizes and confidence intervals
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