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Análisis de sangre de la reacción en cadena de la polimerasa para el diagnóstico de la aspergilosis invasiva en pacientes inmunocomprometidos

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Resumen

Antecedentes

Esta es una actualización de la revisión original publicada en la Cochrane Database of Systematic Reviews Número 10, 2015.

La aspergilosis invasiva (AI) es la micosis invasiva oportunista potencialmente mortal más frecuente en los pacientes inmunocomprometidos. El diagnóstico temprano de la AI y la administración inmediata del tratamiento antimicótico apropiado son críticos para la supervivencia de los pacientes con AI. Los fármacos antimicóticos se pueden administrar como profilaxis o como tratamiento empírico, iniciados sobre la base de una estrategia de diagnóstico (el enfoque preventivo) o para tratar la enfermedad establecida. En consecuencia, existe una necesidad urgente de investigar tanto las nuevas herramientas de diagnóstico como las estrategias de tratamiento farmacológico. Cada vez se investigan más métodos nuevos como la reacción en cadena de la polimerasa (RCP) para detectar ácidos nucleicos fúngicos.

Objetivos

Proporcionar un resumen general de la exactitud diagnóstica de los análisis de RCP en especímenes sanguíneos para el diagnóstico de la AI en pacientes inmunocomprometidos.

Métodos de búsqueda

Se hicieron búsquedas en MEDLINE (1946 hasta junio 2015) y en EMBASE (1980 hasta junio 2015). También se hicieron búsquedas en LILACS, DARE, Health Technology Assessment, Web of Science y en Scopus hasta junio 2015. Se verificaron las listas de referencias de todos los estudios identificados por los métodos anterioromente descritos y se contactó con autores e investigadores relevantes en este campo. Para esta actualización de la revisión se actualizaron las búsquedas electrónicas del Registro Cochrane Central de Ensayos Controlados (Cochrane Central Register of Controlled Trials) (CENTRAL; 2018, número 3) en la Cochrane Library; MEDLINE a través de Ovid (junio de 2015 a marzo de la semana 2 de 2018); y Embase a través de Ovid (junio de 2015 a 2018 la semana 12).

Criterios de selección

Se incluyeron estudios que: i) compararon los resultados de los análisis de RCP en sangre con el estándar de referencia publicado por el Grupo de Estudio de la Organización Europea para la Investigación y el Tratamiento del Cáncer/Micosis (European Organisation for Research and Treatment of Cancer/Mycoses Study Group, EORTC/MSG); ii) informaron datos por separado sobre los resultados falsos positivos, verdaderos positivos, falsos negativos y verdaderos negativos de las pruebas diagnósticas que se estaban investigando; y iii) evaluaron la prueba prospectivamente en cohortes de pacientes de una población clínica relevante, definida como un grupo de individuos con alto riesgo de aspergilosis invasora. Se excluyeron del análisis los estudios de casos y controles y los estudios retrospectivos.

Obtención y análisis de los datos

Los autores evaluaron de forma independiente la calidad y extrajeron los datos. En las pruebas de la RCP, se evaluó la necesidad de que una o dos muestras consecutivas fuesen positivas para la exactitud diagnóstica. La heterogeneidad se investigó mediante análisis de subgrupos. Se graficaron los cálculos de la sensibilidad y la especificidad a partir de cada estudio en el espacio de las características operativas del receptor (ROC, por sus siglas en inglés) y se elaboraron diagramas de bosque para la revisión visual de la variación en la exactitud de la prueba. Los metanálisis se realizaron mediante el modelo bivariado para producir estimaciones resumidas de la sensibilidad y la especificidad.

Resultados principales

Se incluyeron 29 estudios primarios (18 de la revisión original y 11 de esta actualización), correspondientes a 34 conjuntos de datos, publicados entre 2000 y 2018 en los metanálisis, con una prevalencia media de AI probada o probable de 16,3 (prevalencia media 11,1%, rango 2,5% a 57,1%). La mayoría de los pacientes habían recibido quimioterapia por malignidad hematológica o se habían sometido a un trasplante de células madre hematopoyéticas. Se utilizaron varias técnicas de RCP entre los estudios incluidos. La sensibilidad y la especificidad de la RCP para el diagnóstico de la AI variaron según los criterios interpretativos utilizados para definir un análisis como positivo. Las estimaciones resumidas de sensibilidad y especificidad fueron del 79,2% (intervalo de confianza [IC] del 95%: 71,0 a 85,5) y del 79,6% (IC del 95%: 69,9 a 86,6) para un único resultado positivo del análisis, y del 59,6% (IC del 95%: 40,7 a 76,0) y del 95,1% (IC del 95%: 87,0 a 98,2) para dos resultados positivos consecutivos.

Conclusiones de los autores

La RCP muestra una exactitud diagnóstica moderada cuando se utiliza como prueba de detección para la AI en grupos de pacientes con alto riesgo. Es importante destacar que la sensibilidad de la prueba confiere un valor predictivo negativo (VPN) alto, de manera que una prueba negativa permite excluir el diagnóstico. Los positivos consecutivos muestran buena especificidad en el diagnóstico de la AI y se podrían utilizar para decidir investigaciones radiológicas y otras investigaciones o para el tratamiento preventivo en ausencia de signos radiológicos específicos cuando la sospecha clínica de la infección es alta. Cuando un único análisis de RCP positivo se utiliza como criterio de diagnóstico para la AI en una población de 100 personas con una prevalencia de la enfermedad del 16,3% (prevalencia media general), se pasarían por alto tres pacientes con AI (sensibilidad 79,2%, falsos negativos 20,8%), y 17 personas serían tratadas innecesariamente o derivadas para realizarles análisis adicionales (especificidad 79,6%, falsos negativos 21,4%). Si utilizamos el requisito de dos análisis positivas en una población con la misma prevalencia de la enfermedad, significaría que nueve personas con AI se perderían (sensibilidad 59.6%, 40.4% falsos negativos) y cuatro personas serían innecesariamente tratadas o referidas para análisis adicionales (especificidad de 95.1%, 4.9% falsos positivos). Al igual que el galactomanano, la RCP tiene un buen VAN para excluir la enfermedad, pero la baja prevalencia de la enfermedad limita la capacidad para dictaminar un diagnóstico. Como estos biomarcadores detectan diferentes marcadores de enfermedad, es probable que su combinación resulte más útil.

Resumen en términos sencillos

Un nuevo análisis de sangre de diagnóstico no invasivo (reacción en cadena de la polimerasa) para los pacientes con riesgo de infección por micosis invasiva (aspergilosis)

Pregunta de la revisión
Se revisó la evidencia sobre la exactitud de los análisis de la reacción en cadena de la polimerasa (RCP) para el diagnóstico de la aspergilosis invasiva (AI) en personas con sistemas inmunitarios defectuosos a partir de un tratamiento médico como la quimioterapia o después de un trasplante de órganos o médula ósea.

Antecedentes
La AI es una enfermedad micótica causada un hongo muy diseminado Aspergillus , siendo la especie más común la Aspergillus fumigatus. La mayoría de las personas inhalan esporas de Aspergillus todos los días sin contraer la enfermedad. Sin embargo, las personas con sistemas inmunitarios debilitados o enfermedades pulmonares tienen un mayor riesgo de desarrollar problemas respiratorios de los pulmones y los senos paranasales debido al Aspergillus, que van desde complicaciones alérgicas hasta AI, que es la infección micótica invasiva y potencialmente mortal más común de las personas cuyo sistema inmunitario está comprometido. Sin tratamiento antimicótico, la mayoría de las personas con AI morirán como resultado directo de la AI, por lo que el diagnóstico temprano y la administración oportuna del tratamiento antimicótico apropiado son críticos para la supervivencia de estas personas. El espécimen ideal para el diagnóstico de AI sería el tejido pulmonar, pero su obtención conlleva un riesgo significativo para el paciente, por lo que existe una clara necesidad de nuevos métodos no invasivos como la RCP para demostrar la presencia del hongo en la sangre mediante la detección de sus ácidos nucleicos.

Características de los estudios
Se realizó la búsqueda más reciente de estudios en marzo de 2018 y se combinó con una búsqueda anterior en 29 estudios clínicos seleccionados que informaron la evaluación de las pruebas de RCP de forma prospectiva en cohortes de personas con alto riesgo de AI.

Estudio de las fuentes de financiación
Ninguna de las empresas involucradas en el diagnóstico de enfermedades micóticas invasivas financió ninguno de los estudios incluidos en la revisión.

Calidad de la evidencia
La mayoría de los estudios tuvo un riesgo bajo de sesgo y hubo pocas inquietudes con respecto a la aplicabilidad. Sin embargo, las diferencias en el estándar de referencia pueden haber contribuido a las diferencias encontradas en la distribución de los casos en cuanto a la clasificación como AI o no.

Resultados clave
En los estudios se utilizaron varias técnicas de RCP. El agrupamiento de los datos de los estudios mostró que la sensibilidad y la especificidad de la RCP para el diagnóstico de la AI variaban (del 59% al 79,2% y del 79% al 95,2%, respectivamente) dependiendo de los criterios interpretativos utilizados para definir una prueba como positiva. Cuando se utiliza como criterio de diagnóstico para la AI en una población de 100 personas con una prevalencia de la enfermedad del 16,3% (prevalencia media global), un único análisis positivo de RCP habría pasado por alto a tres pacientes con la enfermedad, y habría clasificado equivocadamente a 17 personas como que presentaban la enfermedad, que serían tratadas de forma innecesaria o derivadas para realizarles análisis adicionales Un requisito de dos pruebas positivas como criterio de diagnóstico en una población con la misma prevalencia de la enfermedad echaría de menos a nueve personas con la enfermedad y clasificaría falsamente a cuatro personas como portadoras de la enfermedad. Estas cifras se deben interpretar con cuidado debido a que el estándar de referencia se basa en el grado de certeza del diagnóstico y rara vez se demuestra, por lo que no puede proporcionar una evaluación coherente de los casos como AI o no AI.

En general, la RCP muestra una exactitud diagnóstica moderada cuando se utiliza como una prueba de detección para la AI en grupos de pacientes con alto riesgo. Es importante destacar que cuando la tasa de sensibilidad es baja, la sensibilidad de las pruebas significa que un resultado negativo permite excluir el diagnóstico con confianza, excepto cuando el paciente está recibiendo ciertos fármacos antimicóticos. Con la baja prevalencia de la enfermedad, un valor predictivo negativo alto, de tal manera que una prueba negativa permite excluir el diagnóstico.

Authors' conclusions

Implications for practice

The findings indicate that PCR screening tests show moderately good diagnostic accuracy when used as screening tests for IA in high‐risk patient groups. For a screening strategy, however, with the low prevalence of IA in the observed population and a low pre‐test probability of disease, the moderate sensitivity of the PCR is sufficient to ensure a good negative predictive value, such that disease can be confidently excluded and the need for empiric therapy avoided. As such, screening strategies could replace empirical antifungal therapy in selected high‐risk patients. Consecutive positive test results show excellent specificity in the diagnosis of IA and could be used to trigger radiological and other investigations or for pre‐emptive therapy in the absence of specific radiological signs when the clinical suspicion of infection is high. The subgroup analyses suggest that antifungal prophylaxis could impair performance and these conclusions may not be applicable to people on concurrent antifungal therapy. With the observed prevalence of disease (16.3%), repetition of the PCR test increase considerably the positive predictive values, with a modest decline of the negative predictive values. Therefore we recommend the repetition of the PCR assay in order to increase the diagnostic accuracy.

Implications for research

It is clear that PCR holds a lot of promise as a useful test for detecting Aspergillus infection although the diagnostic accuracy might be improved further by combining the test with other biomarkers such as GM, and this should be explored in future studies. Further validation is also needed to determine whether using PCR for screening high‐risk patients, not on anti‐mould prophylaxis, could become the standard of care. Future studies that validate PCR for aspergillosis clearly need to distinguish between use of the test to screen for the presence or absence of IA in high‐risk patients if there are no signs of illness, and its use to confirm or exclude the disease when it becomes manifest. IA can be ruled out during the risk period for as long as any single PCR test is negative and there are no clinical signs of disease. Conversely when prevalence of aspergillosis is around 10%, two or more PCR positive results can be used for mycological confirmation to allow a case of possible IA to be upgraded to probable.

The tests need to be incorporated into patient care pathways that compare prophylactic, empirical, pre‐emptive and targeted antifungal drug use looking at impacts on patient management.

It was not possible to investigate the diagnostic utility of combinations of biomarkers (e.g. PCR and GM) because the GM is incorporated into the EORTC/MSG definitions and would introduce incorporation bias. Hence, cases would have to be classified by omitting GM. Further studies are needed to assess clinical utility and cost effectiveness.

Summary of findings

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Summary of findings Summary of findings table. PCR for the diagnosis of invasive aspergillosis.

Review question: what is the diagnostic accuracy of aspergillus PCR blood test for detection of invasive aspergillosis (IA)?

Patients/population: patients at risk of IA, including neutropenic cancer patients and HSCT or solid organ transplant recipients

Index test: PCR on blood specimens (whole blood or serum). We considered different DNA extraction methods and PCR methods (e.g. nested, ELISA, qPCR)

Reference standard: EORTC/MSG criteria for invasive aspergillosis

Studies: cohort studies

Index Test: interpretative criteria to define a test as positive

Effect (95% CI)

No. of studies

Mean prevalence (range)

What do these results mean?

1 Single PCR specimen

sensitivity: 79.2% (71.0% to 85.5%)

specificity: 79.6% (69.9% to 86.6%)

27 studies

16.3% (2.5% to 57.1%)

With a prevalence of 16%, 16 out of 100 patients will develop IA. Of these, 3 will be missed by a single PCR test (20.8% of 16); of the 84 patients without IA, 17 will have a false positive result of the PCR test; repeating the test will reduced significantly rates of false positive results.

≥ 2 PCR specimens

sensitivity: 59.6% (40.7% to 76.0%)

specificity: 95.1% (87.0% to 98.2%)

9 studies

16.3% (2.5% to 57.1%)

With a prevalence of 16%, 16 out of 100 patients will develop IA. Of these, 9 will be missed using the 2 positive PCR test (40.4% of 16); of the 84 patients without IA, 4 will have a false positive result of the PCR test.

The PCR methods varied notably across studies. Several covariates (in particular, the adoption of antifungal prophylaxis and blinding to the reference test or index test) were found to substantively affect the measures of diagnostic accuracy under evaluation, mainly sensitivity and specificity.
CI: confidence interval
IA: invasive aspergillosis
PCR: polymerase chain reaction

Background

Target condition being diagnosed

Invasive aspergillosis (IA) is a disease resulting from opportunistic fungal infection and mainly affects immunocompromised hosts, particularly neutropenic patients such as those undergoing cancer treatment and hematopoietic stem cell transplantation (HCT) and solid organ transplant recipients (Flückiger 2006; Marr 2002). The highest incidence (10% to 20%) and mortality rates (60% to 90%) of IA have been reported following allogeneic HCT and heart, lung or heart/lung transplantation. The principal reason for such people developing IA is that the underlying disease and its subsequent treatment with chemotherapy induces bone marrow failure resulting in profound leucopenia and impaired innate and cell‐mediated immunity. The leucopenia is marked by a lack of functioning polymorphonuclear leucocytes, resulting in the patient lacking the phagocytic white blood cells needed to fight infections, including aspergillosis. Innate immunity is further impaired by iatrogenic damage to the local defences of the oral cavity, gastrointestinal tract and respiratory tract. Damage to the respiratory tract is poorly understood but hampers effective clearance of fungal spores, especially those of Aspergillus fumigatus which are ubiquitous in the environment, readily airborne and small enough to lodge in the alveolar spaces. The lack of local and systemic immune defences means that any spores that germinate can infect lung tissue and progress to a full‐blown infection. The disease that follows is characterised by invasion of the capillaries (angioinvasion) which can lead to further dissemination to other parts of the lung and indeed other organs, particularly the brain.

Early diagnosis of IA and prompt administration of appropriate antifungal treatment have been recognised as crucial to the survival of people with IA (Marr 2002; Walsh 2008). Antifungal drugs can be given for prevention of infection (prophylaxis), treatment of unexplained fever (empirical therapy), treatment of non‐specific clinical features or mycological evidence (pre‐emptive therapy) and treatment of possible, probable and proven invasive fungal disease (IFD) (directed therapy). Clearly, the earlier that treatment is started the better the outcome. Consequently there is an urgent need for new diagnostic tools to detect infection before disease becomes manifest, thereby allowing effective treatment strategies to be developed. The polymerase chain reaction (PCR) is becoming increasingly popular (Arvanitis 2014; Donnelly 2006; Hope 2005; Mengoli 2009; Tuon 2007; White 2015). However it was not considered robust enough to be included in the international consensus definitions of the European Organisation for Research and Treatment of Cancer/Mycoses Study Group (EORTC/MSG); (Ascioglou 2002; De Pauw 2008).

The prevalence of IA varies from 1 in 100 to about 1 in 6 depending upon the level of compromised immunity, the environmental exposure and preventative measures taken, which can include protected isolation with filtered air and antifungal prophylaxis. The outcome depends upon the extent of infection, whether diagnosis is made and treatment with an effective drug is initiated early; and, importantly, whether or not an individual's immune system begins to recover (Marr 2002; Walsh 2008).

Demonstration of fungi in diseased tissue is still required for a proven diagnosis of IFD. Unlike other infectious diseases, direct demonstration of Aspergillus infection is rarely possible by culture of sterile body fluids, and obtaining tissue from a live patient is seldom feasible because of the risks posed to the patient.by biopsy.

Recently, advances have been made on several fronts. The EORTC/MSG's published definitions of invasive fungal disease (IFD) allow for degrees of certainty of diagnosis: possible, probable and proven (Ascioglou 2002; De Pauw 2008). Definitions of invasive fungal infection were devised in 2002 and revised in 2008 to focus on fungal disease (Table 1). These are based on host factors, radiological features and mycological evidence. Probable and possible cases have to satisfy the same host and radiological criteria and they are only distinguished by the presence or absence of mycological evidence. Biomarkers have potential to detect infection before development of overt disease, allowing treatment to be initiated at an earlier stage. These definitions were only made possible by other contemporaneous developments in the field. Computer‐assisted tomography (CT scan) became more widely available, allowing lesions consistent with pulmonary IA to be detected at an early stage of disease. This offered the possibility of performing bronchoscopy to obtain bronchoalveolar fluid in which the fungus could be detected by microscopy and culture as well as galactomannan (GM). However the technique is not without risk and cannot always be performed when required. By contrast, blood is readily available which opens up the possibility of looking for fungi in an indirect fashion by detecting fungal cell components including the galactomannan of the cell wall of Aspergillus species (Leeflang 2008).

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Table 1. European Organisation for Research and Treatment of Cancer/Mycoses Study Group definitions of invasive aspergillosis

Original definitions ofAscioglou 2002

Revised definitions ofDe Pauw 2008

PROVEN IA

Specimen obtained by needle aspiration or biopsy from a normally sterile and clinically or radiologically abnormal site consistent with an infectious disease processand

either histopathological, cytopathological, or direct microscopic examination of the specimen in which hyphae are seen accompanied by evidence of associated tissue damage

or

recovery of Aspergillus species by culture from the specimen obtained by a sterile procedure excluding bronchoalveolar lavage, cranial sinus cavity, and urine

PROBABLE IA

At least 1 host factor criterion plus 1 major (or 2 minor) clinical criteria from abnormal site consistent with infectionplus 1 microbiological criterion

At least 1 host factor plus 1 clinical feature plus 1 microbiological criterion

POSSIBLE IA

At least 1 host factor criterion plus

either 1 major (or 2 minor) clinical criterion from abnormal site consistent with infection or 1 microbiological criterion

At least 1 host factor plus 1 clinical feature

Host factor criteria will include the temporal relationship between the onset of fungal disease and the receipt of an allogeneic stem cell transplant.

Clinical features include for example neutropenia, persistent fever, predisposing conditions, prolonged use of corticosteroids; in the case of lower respiratory tract infection, the presence of 1 of the following signs on CT: dense well circumscribed lesions(s) with or without a halo sign or an air crescent sign, cavity.

Microbiological criteria consist of a positive culture including the presence of fungal elements indicating a mould on microscopy or recovery by culture of Aspergillus species from sputum, bronchoalveolar lavage (BAL) fluid, bronchial brush or sinus aspirate samples; positive result for Aspergillus detection of galactomannan antigen in specimens of plasma, serum, BAL, cerebrospinal fluid or 2 or more blood samples. Major clinical criteria are, for example, new infiltrates on computerized tomography imaging (e.g. halo sign) or suggestive radiological findings.

Minor clinical criteria are suggestive symptoms and signs.

The exact definitions of the European Organisation for Research and Treatment of Cancer/Mycoses Study Group criteria and their host factor, microbiological or clinical criteria can be found in Ascioglou 2002 and De Pauw 2008.

The EORTC/MSG definitions help integrate all the clinical and laboratory information available. Combining of host factor (such as neutropenia) with clinical features (such as pulmonary nodules) and mycological evidence (such as detection of GM) allows a high level of certainty of diagnosis to be assigned. These definitions have been adopted widely by regulatory agencies, such as the European Medicines Agency and the US Food and Drug Administration, for evaluating antifungal drug products and diagnostic tests, as well as by the scientific and medical community at large for investigating epidemiology and auditing antifungal stewardship.

Whilst the range of potential drugs currently available allows prophylaxis, pre‐emptive therapy, as well as directed therapy for possible, probable and proven IFD, the ability to identify 'who needs treatment, when, and with what' is sufficiently unreliable that many physicians continue to treat empirically. Not only does this lead to unnecessary costs but it is also not clear how many people are helped or harmed by this approach. There are circumstances when a host factor is present (for instance receipt of an allogeneic hematopoietic stem cell transplant (HSCT)) and mycological evidence exists (such as Aspergillus being recovered from pulmonary secretions) without evidence of active disease. This may represent infection before disease becomes manifest and provides the opportunity for therapy to pre‐empt disease. Consequently there is an urgent need for new diagnostic tools and an assessment of their utility in the clinic. Biomarkers have the potential to detect infection before development of overt disease, allowing treatment to be initiated at an earlier stage.

Index test(s)

There are few direct diagnostic tests and those that are available are limited by the difficulties in obtaining tissue specimens to allow culture, microscopy and histology (Chamilos 2006). Blood in its various forms — whole blood, plasma and serum — is readily available, but only tests for antigens such as GM and beta‐D‐glucan have been deemed acceptable to support a diagnosis (Leeflang 2008; Pfeiffer 2006; Senn 2008). In neutropenic patients, pulmonary abnormalities consistent with invasive aspergillosis, such as nodules, often surrounded by a 'halo sign', can be detected using high‐resolution computed tomography (Greene 2007). However, the 'halo sign' is transient and only detectable during early invasive aspergillosis, after which radiological signs become non‐specific or appear too late to be therapeutically useful (Caillot 2001). Radiological signs also herald established disease so the opportunity to intervene early has been lost.

Molecular methods, such as the PCR, have been investigated in order to improve the diagnosis of IA (Donnelly 2006; Mengoli 2009; White 2010; White 2015). PCR can amplify a single or a few copies of target DNA allowing target detection with great sensitivity and specificity. Moreover it can be quantitative, using the procedural variant called real‐time PCR (qPCR). The sensitivity is based on the enormous potential for exponential amplification of the DNA target (the 'amplicon') due to repeated cycles of the polymerase reaction, where every cycle doubles the quantity of amplicon. Real‐time PCR continuously monitors the amplification of target DNA at every cycle. The threshold cycle number (preferred term Cq) is when the amplicon becomes detectable above the background level, as an exponentially increasing signal, and is proportional to the amount of starting DNA in the reaction. A high initial DNA concentration will require fewer cycles to reach the threshold and has an earlier Cq value. The specificity of PCR resides in the DNA oligonucleotides used as primers, allowing the terminally stable variant of the enzyme DNA polymerase to initiate sequence duplication. These primers join to the DNA target ('annealing') in a very stringent way, allowing only minimal misfit possibility. Moreover, in quantitative real time PCR (q‐RT‐PCR), the use of reporter probes, hydrolysis probes or molecular beacons that bind to the central part of the target sequence increase the assay’s specificity.

PCR has an enormous potential for diagnosing infectious diseases, particularly where traditional culture methods are less effective. The fungal genus Aspergillus is a good example of this kind of approach. The recovery of Aspergillus from blood cultures is rarely achieved even in overwhelming infection. PCR‐based tests on blood specimens have gained popularity as the platforms become more automated and extraction methods and targets become commercially available (White 2010). However, its exclusion from the EORTC/MSG definitions led to the establishment of the European Aspergillus PCR Initiative (EAPCRI), which is a working group of the International Society of Human and Animal Mycology (ISHAM). The EAPCRI has published various studies describing the critical stages in DNA isolation from blood samples (White 2010), and on the critical characteristics of a standardized Aspergillus PCR assay. These studies, allied to the standardization of qPCR assays described in the MIQE (minimum information for publication of quantitative real‐time PCR experiments) guidelines, have helped pave the way for reliable and robust PCR assays for the diagnosis of IA in the clinical setting (Bustin 2009). Progress in the standardization of methodology enabled the development of commercially available Aspergillus PCR assays in the last few years (Rath 2018).

Clinical pathway

As stated above, many physicians still opt for starting antifungal treatment empirically because of diagnostic uncertainty. This approach can lead to unnecessary treatment, which incurs extra costs, and may be harmful to some people. Diagnostic tests can be used to establish (i.e. rule in or rule out) disease. This is particularly useful for people at risk of IA where a highly sensitive test can deliver a high negative predictive value for disease, allowing empirical therapy to be safely withheld even on the basis of a single test result. Conversely, a high positive predictive value is required to rule in the diagnosis. The use of PCR as a screening tool differs fundamentally from its use as confirmation of the diagnosis. Therefore, if prevalence is low (i.e. < 10%), IA can be ruled out during the risk period for as long as any single PCR test result is negative, and there are no clinical signs of disease. Conversely, two or more PCR positive test results could be used for mycological confirmation of clinically suspected disease, also allowing a case of possible IA to be upgraded to probable IA.

Clinical pathways of managing patients can vary according to the risk of IA. Patients at high risk can be screened using GM, PCR (or both), with positive test results being used to trigger an intensive diagnostic workup with CT scanning and bronchoalveolar lavage (BAL) to determine disease (diagnostic driven) or to initiate antifungal treatment to prevent development of disease (pre‐emptive). Screening may occur throughout the period of risk or only when people develop fever. Alternatively, patients may be tested in the presence of symptoms suggestive of disease to confirm diagnosis.

Rationale

There is no single assay that has been validated for the early diagnosis of IA. Non‐culture‐based methods such as serial GM ELISA screening hold most promise in establishing early diagnosis and may result in improved outcomes, but clinical utility has not been fully established. Moreover, newer methods such as PCR are being investigated (Donnelly 2006; White 2015). As with any diagnostic test, the utility of PCR as either a screening tool or a confirmatory test will depend on the prevalence of disease in the population in which it is used. The use of prophylactic or empirical antifungal agents, availability of protective environments and other diagnostic tests will all influence how the test is used in clinical practice. It is not the aim of this present analysis to establish clinical outcomes but rather to evaluate diagnostic accuracy so that rational use of PCR testing can be applied to different populations.

Objectives

To provide an overall summary of the diagnostic accuracy of PCR‐based tests on blood specimens for the diagnosis of IA in immunocompromised people.

Secondary objectives

When studies included in the analysis also compared the diagnostic performance of PCR techniques and the GM ELISA assay, we comparatively evaluated the diagnostic performance of PCR‐based tests and GM ELISA assays. However, since the objective of this review is not to identify all studies dealing with GM ELISA assays and IA, only those within the study comparison were included in the review.

Methods

Criteria for considering studies for this review

Types of studies

We included studies using PCR techniques on blood specimens for analysis if they:

  • compared the results of PCR tests with the diagnosis made following the published case definition criteria for invasive fungal disease proposed by the EORTC/MSG; or, for studies published before the publication of these criteria in 2002, used comparable criteria as a reference standard (Ascioglou 2002; De Pauw 2008);

  • reported data on false‐positive, true‐positive, false‐negative and true‐negative results of the diagnostic tests under investigation separately; and

  • evaluated the tests prospectively in a cohort of people from a relevant clinical population, defined as a group of individuals at high risk of IA.

We classified studies, on the basis of the sampling method, as being consecutive or non‐consecutive. We regarded studies evaluating specimens from a group of people known to have aspergillosis, and from a separate group of subjects without evidence of disease, as case‐control studies (Lijmer 1999). We included these studies in the systematic review but excluded them from the quantitative analysis.

Aspergillus contamination and false positive PCR results with bronchoalveolar lavage (BAL) and sputum samples can follow inhalation of airborne spores or colonization of the lung (Lewis 2006). Moreover, BAL is an invasive procedure performed only to confirm the aetiology in a subset of cases that already meet the clinical definitions of IA. Thus, to avoid bias related to the patient selection and specimen type, we analysed only studies evaluating PCR on blood (whole blood, serum, and plasma), with exclusion of studies that analyse the accuracy of PCR tests on BAL only.

Participants

Patients at risk of IA, including neutropenic cancer patients and hematopoietic stem cell transplant (HSCT) or solid organ transplant recipients.

Index tests

PCR methods on blood specimens (whole blood or serum). We considered different DNA extraction methods and PCR methods (e.g. nested, ELISA, qPCR).

Target conditions

The target condition of this review is IA (systemic aspergillosis).

Reference standards

Definitions for invasive fungal disease were first published in 2002 by the EORTC/MSG (Ascioglou 2002); they were revised in 2008 (De Pauw 2008; Table 1). These were used as a reference standard and comparable criteria were used for studies published before the publication of the definitions in 2002. The EORTC/MSG definitions divide the patient population into four categories: people with proven IA, people with probable IA, people with possible IA, and people without IA. In accordance with the previous Aspergillus review on Aspergillus GM detection (Leeflang 2008), sensitivity and specificity were assessed in each study considering the proven and probable cases of IA as having the disease, and the cases of possible IA and no IA as not having the disease.

Search methods for identification of studies

The search strategies for MEDLINE, Embase and CENTRAL are listed in Appendix 1.

Electronic searches

We updated searches on the following electronic databases to identify reports of relevant studies for the review update.

  • Cochrane Central Register of Controlled Trials (CENTRAL; 2018, Issue 3), in the Cochrane Library;

  • MEDLINE via Ovid (June 2015 to March week 2 2018);

  • Embase via Ovid (June 2015 to 2018, week 12);

  • LILACS (June 2015 to September 2018);

  • Database of Abstracts of Reviews of Effects (DARE) to October 2018;

  • Health Technology Assessment database to October 2018;

  • Web of Science to October 2018.

Searching other resources

We also searched for unpublished material on Scopus (www.scopus.com). We checked the reference lists of all the studies identified by the above methods and contacted other authors and trialists in the field.

Data collection and analysis

Selection of studies

Two review authors (PD, RB) independently assessed the abstract (if available) of each reference identified by the search against the inclusion criteria. We resolved any disagreements that arose through discussion and consensus with a third author (MC). For the update review, we screened the search results using Covidence 2014. We retrieved those references that potentially met the inclusion criteria (based on their abstract or title) in full for further independent assessment.

Data extraction and management

We extracted the following data from each included study.

  • Study design

  • Study population

  • Reference standard and performance of the reference standard

  • Performance of the index test

  • Technical details of the PCR methods used, including genetic target of PCR and nucleotide probe sequence, and any PCR testing methods; we classified the diagnostic modalities using PCR assays according to the sampling methods and how these relate to the definition of a positive result, namely either positive PCR in at least two consecutive blood samples drawn from the same patient, or a single sample yielding a PCR positive result. When we compared PCR‐based tests to GM, we assessed whether authors explicitly mention the exclusion of the GM ELISA test from the reference test definition (EORTC/MSG criteria). In this case, we performed a direct comparison of the index test and the comparator evaluated in the same study population towards the reference standard.

  • QUADAS‐2 items

  • Data for two‐by‐two table (false‐positive, true‐positive, false‐negative and true‐negative results of the diagnostic tests under investigation and reference standard).

Pairs of authors extracted the data; they resolved disagreements by discussion.

Assessment of methodological quality

Assessment of the quality of diagnostic accuracy studies, as recommended in STARD (Standards for Reporting of Diagnostic Accuracy), is of absolute relevance in systematic reviews (Bossuyt 2003; Reitsma 2009; Whiting 2004). For this purpose, we used the Quality Assessment tool for Diagnostic Accuracy Studies (QUADAS‐2) tool , the current version of QUADAS that has been adopted for use by Cochrane and is recommended for use in all Cochrane diagnostic test accuracy reviews to evaluate the risk of bias and applicability of primary diagnostic accuracy studies. Pairs of authors independently assessed the methodological quality of the studies included, and disagreements were resolved by consensus with all of the authors.

QUADAS‐2 consists of the following four key domains.

  • Patient selection

  • Index test

  • Reference standard

  • Flow and timing

Each is assessed in terms of risk of bias and the first three in terms of concerns regarding applicability. Signalling questions are included to assist in judgements about risk of bias. Risk of bias is judged as 'low', 'high', or 'unclear'. If all signalling questions for a domain are answered 'yes' then risk of bias can be judged 'low'. If any signalling question is answered 'no' this flags the potential for bias. The 'unclear' category is used only when insufficient data are reported to permit a judgment.

Tabular and graphical displays are used to summarise QUADAS‐2 assessments. We did not calculate a summary score estimating the overall quality of an article, since their interpretation is problematic and potentially misleading (Whiting 2005).

The items of the QUADAS‐2 tool and their interpretation are reported in appendix (Appendix 2).

Statistical analysis and data synthesis

The values of sensitivity and specificity are automatically computed in Review Manager 2014. We obtained summary positive (LR+) and negative (LR−) likelihood ratios from the bivariate analysis (see below). We evaluated different interpretive criteria for a PCR‐positive result in the two‐by‐two table, namely a single positive PCR result and two positive PCR results. We have presented individual study results graphically by plotting the estimates of sensitivity and specificity (and their 95% confidence intervals (CIs)) in both forest plots and receiver operating characteristics (ROC) space.

We assessed the operating point sensitivity and specificity of the diagnostic test under scrutiny by a bivariate random‐effects approach (Reitsma 2005). The original method was modified by using a random‐effects bivariate logistic model (Chu 2006). The same procedure permits generation of a hierarchical summary receiver operating characteristic (HSROC) model (Rutter 2001). The bivariate approach examines the influence of covariates on sensitivity and specificity (or both), whilst the HSROC model is focused on threshold and accuracy (Guo 2015; Harbord 2007). In most conditions bivariate and HSROC are equivalent, particularly in the absence of covariates. When there is a considerable degree of between‐study heterogeneity, as is common in meta‐analysis of diagnostic accuracy studies, a prediction region may be preferable to a confidence region(Harbord 2007); this is assured by the bivariate approach. The results of the bivariate model can be used to calculate likelihood ratios. To calculate (negative) predictive values, an estimate of prevalence in addition to values of sensitivity and specificity is required. One can then apply a Bayesian approach to obtain predictive values from these three parameters. We performed bivariate analysis using STATA 11 software. We compared the diagnostic measures of diagnostic accuracy and related 95% CIs by adding binary covariates to the bivariate model.

Investigations of heterogeneity

We assessed heterogeneity by visual inspection of forest plots of sensitivity and specificity, and through visual examination of ROC plot of the raw data. We further investigated heterogeneity by exploring the effects of several study‐level covariates. For this, we performed a multilevel mixed‐effects logistic model using the probability of test positivity as a dependent variable; the group variable was the study, and the disease status was the first explanatory variable. This basic model admitted in turn several additional covariates. When available, we examined the following covariates.

  • Distinctive groups of patients

  • Study size (< or ≥ 100 patients)

  • Children versus adults

  • Use of antifungal prophylaxis active against Aspergillus species

  • Variation in PCR techniques (RT‐PCR versus other PCR methods)

We included the interaction between the disease status and the additional covariate into the model as well.

We have analysed the potential influence of risk of bias (e.g. blinding of the index test, blinding of the reference test) by sensitivity analysis.

Results

Results of the search

Of the 2474 references identified, we selected 215 potentially relevant citations (Figure 1). After screening titles and abstracts, we selected 91 articles for full‐text review. Of these, we excluded 62 studies for various reasons (Characteristics of excluded studies): patients were selected retrospectively in 11 studies; 20 studies did not provide sensitivity and/or specificity data for two‐by‐two tables; 13 were case‐control studies; four studies included BAL only or tissue PCR; 3 studies included a subset of previous trials; the index test was inappropriate in 6 studies and the reference standard was inappropriate in 7 studies; 2 studies were in Chinese; 3 studies were duplicates of previously published papers; and, finally, 2 for other reasons. Therefore, 29 studies published between 2000 and 2018 met the inclusion criteria and were included in the meta‐analysis (Aslan 2015; Badiee 2010; Badiee 2017; Barnes 2009; Barnes 2013; Bellanger 2015; Boch 2016; Boluk 2016; Cuenca‐Estrella 2009; da Silva 2010; El Mahallawy 2006; Ferns 2002; Florent 2006; Halliday 2006; Hebart 2000a; Hummel 2009; Imbert 2016; Landlinger 2010; Loeffler 2017; Pini 2015; Ramírez 2009; Rogers 2013; Schwarzinger 2013; Springer 2011; Springer 2016; Suarez 2008; Sugawara 2013; von Lilienfeld‐Toal 2009; White 2006). Three studies reported the diagnostic performance of PCR performed with different methodologies (Aslan 2015; Rogers 2013; Suarez 2008), and one in a different patient setting (Rogers 2013). Therefore data were analysed from 34 data sets.


Study flow diagram.

Study flow diagram.

The main characteristics of the studies are summarized in the Characteristics of included studies tables. More than 28,000 clinical blood specimens from 4718 patients at risk of IA were included. Most had received chemotherapy for a haematological malignancy or had been given a hematopoietic stem cell transplant (HSCT). The PCR techniques used are summarized in Table 2. Twenty‐eight of the selected studies (corresponding to 33 data sets) reported the results of a single PCR result, and nine studies (13 data sets) reported using two PCR results. In three studies it was possible to extract the two‐by‐two data in subsets of patients receiving or not receiving anti‐mould prophylaxis (Imbert 2016; Rogers 2013; Springer 2016). Sixteen of the studies included in the analysis also reported results of GM assay (Barnes 2009; Bellanger 2015; Cuenca‐Estrella 2009; da Silva 2010; El Mahallawy 2006; Ferns 2002; Florent 2006; Hummel 2009; Imbert 2016; Loeffler 2017; Rogers 2013; Schwarzinger 2013; Springer 2011; Springer 2016; Suarez 2008; Sugawara 2013). The study by Rogers 2013 presented two cohorts of patients (one from the University Clinic of Wurzburg, and one from Saint James's Hospital, Dublin) according to the PCR test used: Internal Transcribed Spacer (ITS) qPCR and the 28S nested PCR; the study by Suarez 2008 presented data according to the protocols for serum processing (large and small volume); and the study by Aslan 2015 according to two PCR tests used (in‐house and commercially available test).

Open in table viewer
Table 2. Technical details of the PCR methods used in the studies analysed in this review

Study

Sample type

Sample volume

DNA extraction methodsA

PCR methodC

Target gene

Appropriate controls

Requirements for positive by PCR

Methods used (refs)

Cell wall disruptionB

DNA isolation kit/protocol

NegativeD

PositiveE

PCR inhibition

Ex

PCR

Ex

PCR

Hebart 2000a

Whole blood

5 ml

Zymolase and NaOH lysis buffer

Protein precipitation and DNA precipitation

PCR‐slot blot

18S

Yes

Yes

Yes

Single positive

Einsele 1997

Ferns 2002

Whole blood

2 ml

Lyticase

QIAamp

Nested PCR

mtDNA

Yes

Yes

Yes

Yes

Positive on 2 occasions

Bretagne 1998

Tang 1993

Florent 2006

Serum

200 μl

QIAamp

PCR‐ELISA

mtDNA

Yes

Yes

Yes

2 consecutive positives

Bretagne 1998

Halliday 2006

Whole blood

500 μl

Lyticase

GenElute

Nested PCR

18S

Yes

Yes

Yes

Yes

2 consecutive positives

Skladny 1999

El Mahallawy 2006

Serum

Lyticase

QIAamp

Standard PCR

18S

Yes

Yes

Single positive

Williamson 2000

White 2006

Whole blood

2 ml

Glass beads

MagNA Pure

Nested qPCR

28S

Yes

Yes

Yes

Yes

Yes

Serial positives in single episode

Loeffler 2002; Williamson 2000

Suarez 2008

Serum

1 ml or 200 μl

MagNA Pure

qPCR

28S

Yes

Yes

Single positive

Challier 2004

Hummel 2009

Blood

5 ml

Lyticase

Phenol‐chloroform

Nested PCR

18S

Yes

Yes

Single positive

Skladny 1999

Ramírez 2009

Whole blood

5 ml

Lyticase and glass beads

QIAamp

qPCR

18S

Yes

Yes

Single positive

Loeffler 2000

Barnes 2009

Whole blood

2 ml

Glass beads

MagNA Pure

Nested qPCR

28S

Yes

Yes

Yes

Yes

Yes

Confirmed positiveF

White 2006

Cuenca‐Estrella 2009

Whole blood and serum

QIAamp

qPCR

ITS1

Yes

Yes

Yes

2 consecutive positives

Yoo 2008

von Lilienfeld‐Toal 2009

Whole blood

10 ml

Ceramic beads

Septifast

qPCR

18S

Yes

Yes

Yes

Lehmann 2008

Landlinger 2010

Whole blood

3 ml

Lyticase

MagNA Pure

qPCR

28S

Yes

Yes

Yes

Single positive

Baskova 2007; Watzinger 2004

Badiee 2010

Whole blood

3 to 5 ml

Lyticase

QIAamp

qPCR

18S

Yes

Yes

Yes

Single positive

Van Burik 1998; Kami 2001;

da Silva 2010

Serum

5 ml Blood

Lyticase

Protein precipitation and DNA precipitation

Standard PCR

18S

Yes

Yes

2 consecutive positives

Ribeiro 2006; Van Burik 1998

Springer 2011G

Whole blood

3 ml

Glass beads

High Pure PCR Template Preparation Kit (Roche)

qPCR

ITS

Yes

Yes

Single positiveH

FastPrep‐24 MP (Biomedicals)

Whole blood

5 ml

Glass beads

Standard PCR

Yes

Yes

Yes

Yes

Sachse 2009

Rogers 2013G

Whole blood

3 ml

Glass beads

High Pure PCR Template Preparation Kit (Roche)

Nested qPCR

28S

Yes

Yes

Yes

Yes

Yes

Single positiveI

White 2006

Springer 2011

qPCR

ITS1

Yes

Yes

Single positiveI

Sugawara 2013

Whole blood

1 ml

Beads and lysis buffer

Phenol‐chloroform

Nested PCR and sequencing

18S

Yes

Yes

Single positive

Nakamura 2010

Barnes 2013

Whole blood

3ml

Glass beads

Various automated extractors – Roche MagNA Pure LC Total NA, BioMerieux EasyMag, Qiagen EZ1 Advance XL tissue kit.

qPCR and nested qPCR

28S

Yes

Yes

Yes

Yes

Yes

Single and multiple positive thresholds used

White 2006

Schwarzinger 2013

Serum

1 ml

Not required

Roche MagNA Pure LC DNA

qPCR

Mitochonrial

Yes

Yes

Yes

Single positive

Botterel 2008

Aslan 2015

Serum

0.2 ml

Not required

Qiamp DNA Mini Kit

qPCR

18S and 28S

Yes

Yes

Yes

Yes

Yes

Single positive

Mycassay Aspergillus and in‐house PCR

Bellanger 2015

Serum

1 ml

Large Volume MagNa Pure Nucleic acid isolation kit

qPCR

18S

Mitochondrial (L37095)

(no info on controls)

Single positive

Millon 2011,

Costa 2001

Pini 2015

Serum

0.5 ml

Not required

High Pure template (Roche)

qPCR

18S

Yes

Yes

Yes

Single Positive

Mycassay Aspergillus

Boch 2016

Whole blood

3 to 5 ml

Lyticase

Phenol‐chloroform

Nested PCR

18S

Yes

Yes

Single positive

Skladny 1999

Boluk 2016

Serum

ZR Fungal/Bacterial DNA

MiniPrep Kit

qPCR

Kit (Way2 Gene Fungi)

Yes

Yes

Single Positive

No ref to methods for Asp PCR

Imbert 2016

Serum

1 ml

MagNA Pure Compact large volume

kit on a MagNA Pure device (Roche)

qPCR

28S

Yes

Yes

Yes

Single Positive

Suarez 2008, Challier 2004

Springer 2016

Serum

1 ml

Qiaamp UltrasensVirus Kit

qPCR

ITS1‐5.8S

Yes

Yes

Yes, but Bacillus‐DNA was used

Yes

Yes

Single and multiple positive thresholds used

Skladny 1999,Springer 2012

Badiee 2017

Serum

0.2 ml

QiaAmp Mini

qPCR

18S

Skladny 1999; Shin 1999

Loeffler 2017

Cell‐free blood fraction, mostly serum

1 ml

Qiaamp UltrasensVirus Kit

qPCR

ITS1‐5.8S

Yes

Yes

Yes, but Bacillus‐DNA was used

Yes

Yes

Single positive

Skladny 1999; Springer 2016

‐: not reported; MagNA Pure: an automated DNA isolation system manufactured by Roche; mtDNA: mitochondrial DNA; PCR: polymerase chain reaction; QIAamp: QIAamp DNA isolation kit manufactured by Qiagen; Ex: extraction; ITS: Internal Trascribed Spacer; RCLB: red cell lysis buffer.

A DNA isolation protocols may include steps to remove red and white blood cells, fungal cell wall disruption and DNA purification kits.

B Lyticase/Zymolase enzymatically digest fungal cells walls; ceramic or glass beads cause mechanical disruption of the cell wall.

C PCR methods used vary between standard PCR where products are resolved on agarose gels to detect positive or negative reactions or quantitative PCR (qPCR) which allows real time monitoring of the reaction. Nested qPCR involves first round standard PCR and second round qPCR.

D Negative DNA extraction controls feature a sample blank, e.g. blood or sterile solution, that allows detection of any contamination in the DNA isolation protocol.

E Positive DNA extraction controls are a sample blank that is spiked with fungal or specific bacterial spores to ensure that the DNA isolation protocol is working optimally.

F The confirmed positive requires that any single positive sample is confirmed with an additional sample from the same patient. Barnes 2009 also used multiple analyses to determine the effectiveness of single versus multiple positives to yield diagnostic accuracy.

G Studies assessed the effectiveness of more than 1 assay.

H The study analysed the effect of both single and multiple positives.

I The effects of both single and multiple positives were analysed as well as analyses of combined PCR and galactomannan tests.

Methodological quality of included studies

We summarize the quality of studies as assessed by the QUADAS‐2 tool in tables and graphs. Figure 2 shows the overall risk of bias and applicability concerns for the 29 selected studies. Figure 3 presents the quality assessment results for the individual studies. For all QUADAS‐2 domains, most studies were at low risk of bias and low concern regarding applicability. In the patient selection domain, all the studies enrolled a homogenous and representative population of patients at risk of IA; 75% of studies were at low risk of bias because they enrolled participants consecutively and avoided inappropriate exclusions. We graded six studies as being at unclear risk of bias because the manner of patient selection was not stated; and we graded one study at high risk of bias because it included retrospectively a heterogeneous population with various underlying diseases, mostly haematologic and neutropenic, but also patients with a non‐invasive form of aspergillosis.


Risk of bias and applicability concerns graph: review authors' judgements about each domain presented as percentages across included studies

Risk of bias and applicability concerns graph: review authors' judgements about each domain presented as percentages across included studies


Risk of bias and applicability concerns summary: review authors' judgements about each domain for each included study

Risk of bias and applicability concerns summary: review authors' judgements about each domain for each included study

In the index test domain, we considered 50% of studies to be at low risk of bias and 70% of studies to be at low concern regarding applicability. We judged the remaining studies to be at unclear risk of bias because it was unclear if the index test was performed knowing the results of the reference standard. In the reference standard domain, we judged around 70% of studies to be at low risk of bias because it was stated that the reference standard results were interpreted without knowledge of the results of the index test, while in the remaining studies it was not specified. Applicability was of low concern for almost all studies in the reference standard domain. In the flow and timing domain, we judged 70% of studies to be at low risk of bias because all patients were accounted for in the analysis, the appropriate reference standard was used, and information about uninterpretable results was provided. We had nearly complete information for all studies.

Findings

Results of the meta‐analysis

Based on 29 included studies, the median number of patients per study was 99 (range 17 to 549), and the mean prevalence of proven or probable IA was 16.3% (median 11.1, range 2.5% to 57.1%). The sensitivity and specificity of PCR for the diagnosis of IA varied according to the interpretative criteria used to define a test as positive. For PCR assays, we evaluated the requirement for either one or two consecutive samples to be positive for diagnostic accuracy. With the one positive requirement, the sensitivity reported in the studies ranged from 22% to 100%, and specificity from 2% to 100%. With the two positive requirements the sensitivity reported in the included studies ranged from 0% to 92%, and specificity from 75% to 100%. The summary estimates of sensitivity and specificity were 79.2% (95% CI 71.0% to 85.5%) and 79.6% (95% CI 69.9% to 86.6%) for a single positive result requirement, and 59.6% (95% CI 40.7% to 76.0%) and 95.1% (95% CI 87.0% to 98.2%) for two positive results requirement. LR+/LR− were 3.8 (95% CI 2.6 to 5.7)/0.26 (95% CI 0.18 to 0.36) for a single positive result, and 12.2 (95% CI 4.2 to 35.3)/0.42 (95% CI 0.26 to 0.67) for two positive results. When used in isolation, a single PCR positive test as diagnostic criterion for IA in a population of 100 people with a disease prevalence of 16.3% (overall mean prevalence), three people who have IA would be missed (sensitivity 79.2%, 20.8% false negatives), and 17 people would be unnecessarily treated or referred for further tests (specificity of 79.6%, 21.4% false positive). If we use the 'two positive tests' requirement in a population with the same disease prevalence, it would mean that nine IA people would be missed (sensitivity 59.6%, 40.4% false negatives) and four people would be unnecessarily treated or referred for further tests (specificity of 95.1%, 4.9% false positive).

Heterogeneity

The appearance of the forest plots for PCR show a wide range of diagnostic indices at study level; this was more apparent for specificity using the 'single positive' requirement, and for sensitivity using the 'two positive' requirement. (Figure 4; Figure 5). Visual inspection of the prediction ellipses in the bivariate analysis show a large area occupying most of the full probabilistic space; the degree of eccentricity was more pronounced in the specificity direction for a 'single positive' requirement, and in the sensitivity direction for 'two positives' requirement (Figure 6; Figure 7).


Forest plot of PCR: one (single) positive requirement.

Forest plot of PCR: one (single) positive requirement.


Forest plot of PCR: two positive requirement.

Forest plot of PCR: two positive requirement.


Summary ROC Plot. Bivariate analysis of the sensitivity and specificity of the PCR as a diagnostic tool for Aspergillus invasive infection. One single positive PCR result is required to define the test as positive

Summary ROC Plot. Bivariate analysis of the sensitivity and specificity of the PCR as a diagnostic tool for Aspergillus invasive infection. One single positive PCR result is required to define the test as positive


Summary ROC Plot. Bivariate analysis of the sensitivity and specificity of the PCR as a diagnostic tool for Aspergillus invasive infection. Two or more consecutive positive PCR result are required to define the test as positive.

Summary ROC Plot. Bivariate analysis of the sensitivity and specificity of the PCR as a diagnostic tool for Aspergillus invasive infection. Two or more consecutive positive PCR result are required to define the test as positive.

We investigate heterogeneity by subgroups analyses.

Bivariate analysis

Graphs (ellipses) of bivariate models for the two different criteria for PCR positivity are shown in Figure 6 and Figure 7. We excluded unpaired studies for the evaluation of the differential effect of the single positive/two positive criterion. We reduced the number of studies included in the paired analysis to eight, corresponding to 12 comparisons of PCR test (each paired for 'single positive' and 'two positive' criteria; Badiee 2010; Barnes 2013; Cuenca‐Estrella 2009; Florent 2006; Halliday 2006; Rogers 2013; Springer 2011; Suarez 2008). When sensitivity and specificity data from the bivariate model were compared, changing the 'positive results' requirement from one to two increased specificity significantly from 79.5% to 95.1% ( P value < 0.0001). By contrast, the sensitivity decreased significantly from 79.2% to 59.6% (P value < 0.0001). The joint effect on sensitivity and specificity was also significant (P value < 0.0001) (Table 3).

Open in table viewer
Table 3. Subgroup analyses

Covariate

Subgroup

Index

mean

95% CI

Subgroup Difference: P

Anti‐mould prophylaxis

yes

sensitivity

0.8206

0.7536; 0.8725

not significant

no

sensitivity

0.7577

0.6440; 0.8439

yes

specificity

0.6470

0.5638; 0.7222

0.0387

no

specificity

0.7901

0.6769; 0.8712

EORTC criteria 2008 vs 2002

2008

sensitivity

0.7311

0.6324; 0.8112

not significant

2002

sensitivity

0.7878

0.7061; 0.8516

2008

specificity

0.7339

0.6098; 0.8296

not significant

2002

specificity

0.8226

0.6559; 0.9186

Blind reference

yes

sensitivity

0.7384

0.6124; 0.8345

not significant

no

sensitivity

0.7676

0.6652; 0.8460

yes

specificity

0.6284

0.5429; 0.7065

0.0009

no

specificity

0.8553

0.7555; 0.9187

Blind index

yes

sensitivity

0.7209

0.6402; 0.7895

not significant

no

sensitivity

0.7584

0.6476; 0.8428

yes

specificity

0.6646

0.5532; 0.7603

0.0161

no

specificity

0.8295

0.7354; 0.8950

In‐house vs commercial kit

In‐house

sensitivity

0.7489

0.6038; 0.8537

not significant

kit

sensitivity

0.6576

0.3274; 0.8835

In‐house

specificity

0.8428

0.7263; 0.9155

not significant

kit

specificity

0.7674

0.4165; 0.9384

Whole blood vs serum

WB

sensitivity

0.8114

0.7304; 0.8724

not significant

serum

sensitivity

0.7130

0.5956; 0.8073

WB

specificity

0.7243

0.6382; 0.7965

not significant

serum

specificity

0.8139

0.6661; 0.9056

Effects of 6 binary covariates on the sensitivity and specificity of the Aspergillus PCR. Meta‐analytical pooling for proportions (method of logits, DerSimonian‐Laird estimator for tau², inverse variance method), subgroup analysis. Mean values and 95% confidence intervals are reported. “Subgroup Difference: P” reports the comparison between 2 subgroups as difference within the same index for each covariate, as P value. Significant results were found for specificity under prophylaxis (as decrease under prophylaxis), specificity under blind reference (as decrease under blind reference), specificity under blind index (as decrease under blind index). Analysis performed with R version 3.5.3.

Subgroups analysis and bivariate analysis with covariates

We carried out a subgroup analysis of adult and paediatric studies (Boch 2016; El Mahallawy 2006; Halliday 2006; Hummel 2009; Landlinger 2010). The diagnostic yield did not differ significantly between adult and paediatric studies. However, the limited number of paediatric studies does not allow a firm conclusion to be drawn regarding the diagnostic performance of PCR in paediatric patients. We also performed a subgroup analysis according to study size. Studies were defined as small size (15 studies) or large size (14 studies) according to the number of enrolled people (< or ≥ 100). Likewise study size did not have a significant impact on performance of PCR test.

We also performed a subgroup analysis of studies endorsing 2002 EORTC criteria (10 studies: El Mahallawy 2006; Ferns 2002; Florent 2006; Halliday 2006; Hebart 2000a; Hummel 2009; Ramírez 2009; Suarez 2008; von Lilienfeld‐Toal 2009; White 2006) or 2008 criteria (seven studies: Badiee 2010; Barnes 2009; Cuenca‐Estrella 2009; da Silva 2010; Rogers 2013; Springer 2011; Sugawara 2013), using the bivariate method and considering the results of PCR test with the 'single positive' criterion. One study stated the use of EORTC criteria but did not mention which criteria were employed (Landlinger 2010). Lower sensitivity and specificity values were found for studies using 2008 criteria compared to those using 2002 criteria (73.1% (95% CI 63.2 to 81.1) and 73.3% (95% CI 60.9 to 82.9) versus 78.7% (95% CI 70.6 to 85.1) and 82.2% (95% CI 65.5 to 91.8), respectively), but these differences were not statistically significant and probably driven by the low estimates of diagnostic accuracy found in some of the 2008 studies (Rogers 2013; Springer 2011) (Table 3).

Twelve studies used anti‐mould prophylaxis (itraconazole, voriconazole, amphotericins or caspofungin) in the entire population or in a subset of patients under investigation ( Barnes 2009; Barnes 2013; Cuenca‐Estrella 2009; Ferns 2002; Florent 2006; Hummel 2009; Imbert 2016; Loeffler 2017; Rogers 2013; Springer 2016; Sugawara 2013; White 2006) ; ). Thirteen studies did not use antimould prophylaxis at all (Badiee 2010;Badiee 2017; Boch 2016; Boluk 2016; da Silva 2010; El Mahallawy 2006; Halliday 2006Hebart 2000a; Landlinger 2010; Rogers 2013; Schwarzinger 2013; von Lilienfeld‐Toal 2009); or only in a subset of patients (Imbert 2016; Springer 2016). Fluconazole was used as prophylaxis in four studies (Badiee 2010; Halliday 2006; Hebart 2000a; Springer 2011). When examining data under the criterion 'single positive', the anti‐mould prophylaxis produced a significant reduction of specificity (from 0.79 (95% CI 0.67 to 0.87) to 0.64 (95% CI 0.56 to 0.72), coupled with no significant increase of sensitivity (from 0.75 (95% CI 0.64 to 0.84) to 0.82 (95% CI 0.75 to 0.87) (Data table 4).

The PCR methods varied notably. Some studies were based on gel electrophoretic visualization after proper staining of the amplicons, whereas others were based on automated procedures, such as real‐time PCR, with substantial differences regarding the threshold of detection. We relied on the reported qualitative (positive/negative) test results only, and did not take the possible cut‐point/threshold variation across studies into consideration. Comparison of the three studies — Aslan 2015, Boluk 2016 and Pini 2015 — analyzed in this review that used kit‐based assays to 15 studies (Badiee 2010; Badiee 2017; Bellanger 2015; Cuenca‐Estrella 2009; Imbert 2016; Landlinger 2010; Loeffler 2017; Ramírez 2009; Rogers 2013; Schwarzinger 2013; Springer 2011; Springer 2016; Suarez 2008; von Lilienfeld‐Toal 2009) that used in‐house qPCR assays (excluding end‐point or nested PCR) did not reveal any statistically significant differences between kit and in‐house assays. There was a trend for greater sensitivity and specificity for the in‐house assays compared to commercially available kits (0.74 vs 0.65; 0.84 vs 0.76, respectively), although these differences did not reach statistical significance. Whole blood PCR test had higher sensitivity and lower specificity compared to serum PCR test, but these differences were not statistically significant (Table 3).

Quality items that did have an effect on sensitivity or specificity were blinding of the index test (4% decrease in sensitivity and 17% decrease in specificity) and blinding of the reference standard (5% decrease in sensitivity and 14% decrease in specificity). In other words, failure of blinding produced a spurious increase in overall accuracy.

Predictive values

Positive and negative predictive value (PPV and NPV, respectively) of Aspergillus PCR detection are shown in Figure 8 (Figure 8). The predictive values were calculated by applying the Bayes rule. The use of the two positive criteria produces a significant increase in the PPVs, and only a slight decrease of NPVs. With a mean prevalence of invasive aspergillosis of 16%, the PPV is 42.8% with a 'single positive test' criterion, and 70.3% with 'two positive tests' criterion; for NPV these figures are 95.1% and 92.4%, respectively.


Predictive values. Positive and negative predictive value (PPV and NPV, respectively) of the Aspergillus PCR detection test (y‐axis) as a function of the prevalence of the disease, invasive aspergillosis (x‐axis). The curves are related to the diagnostic criterion (a single positive result or two consecutive positive PCR results). The PVs were calculated by applying the Bayes rule. The mean prevalence of invasive aspergillosis (16.3%) is indicated by the vertical dashed line. It corresponds to PPV1 = 42%, NPV1 = 95%, PPV2 = 70%, NPV2 = 92%.

Predictive values. Positive and negative predictive value (PPV and NPV, respectively) of the Aspergillus PCR detection test (y‐axis) as a function of the prevalence of the disease, invasive aspergillosis (x‐axis). The curves are related to the diagnostic criterion (a single positive result or two consecutive positive PCR results). The PVs were calculated by applying the Bayes rule. The mean prevalence of invasive aspergillosis (16.3%) is indicated by the vertical dashed line. It corresponds to PPV1 = 42%, NPV1 = 95%, PPV2 = 70%, NPV2 = 92%.

Comparison between PCR techniques and GM assay

Sixteen studies also evaluated GM assay (Barnes 2009; Bellanger 2015; Cuenca‐Estrella 2009; da Silva 2010; El Mahallawy 2006; Ferns 2002; Florent 2006; Hummel 2009; Imbert 2016; Loeffler 2017; Rogers 2013; Schwarzinger 2013; Springer 2011; Springer 2016; Suarez 2008; Sugawara 2013), but in all studies but one GM was part of the reference standard (Suarez 2008). Thus to avoid incorporation bias, we did not compare data of GM assay to PCR, and did not include them in the current review.

In the study by Suarez 2008, sensitivity and specificity were 100% and 96.7% for qPCR using large sample volume (LSV), and 88.2% and 95.8% for GM. Thus the overall performance of qPCR using LSV was consistently higher than that of GM.

Discussion

Summary of main results

We included 29 primary studies, corresponding to 34 data sets, in the meta‐analyses: 18 RCTs were included in the original review, and we identified 11 additional trials for this update. The mean prevalence of IA (proven or probable) in the included studies was 16.3%. The majority of patients had received chemotherapy for a haematological malignancy or had been given a hematopoietic stem cell transplant (HSCT). Several PCR techniques were used among the included studies. The sensitivity and specificity of PCR for the diagnosis of IA varied according to the interpretative criteria used to define a test as positive. For PCR assays, we evaluated for diagnostic accuracy the requirement for either one or two consecutive samples to be positive. The summary estimate of sensitivity and specificity were 79.2% (95% CI 71.0% to 85.5%) and 79.6% (69.9% to 86.6%) for a single positive test result, and 59.6% (40.7% to 76.0%) and 95.1% (87.0% to 98.2%) for two positive test results. The findings indicate that PCR shows moderate diagnostic accuracy when used as a screening test for invasive aspergillosis in high‐risk patient groups. We found several covariates (in particular, the adoption of antifungal prophylaxis and blinding to the reference test or index test) to substantially affect the measures of diagnostic accuracy under evaluation, particularly sensitivity and specificity. The uneven distribution of these covariates may explain, at least partly, the large heterogeneity found in this analysis. The subgroup analyses suggest that antifungal prophylaxis might impair performance and these conclusions may not be applicable to patients on concurrent antifungal therapy.

Strengths and weaknesses of the review

The findings of this review are based on comprehensive searching, strict inclusion criteria, and standardized data extraction. The strength of our review is that it enables an assessment of the diagnostic accuracy of PCR for detection of IA in a homogenous population of patients at risk of IA. We used the strict inclusion criteria (cohort of consecutive patients, including neutropenic cancer patients and hematopoietic stem cell or solid organ transplant recipients) to cover the spectrum of diseases likely to be encountered in the current or future use of this diagnostic test.

We only included studies that used the EORTC/MSG criteria or a similar reference standard. Differences in the reference standard may have contributed to differences we found in the distribution of patients with probable, possible and no invasive aspergillosis, but not 'proven disease' as this relies on demonstration of the fungus in tissue. For instance, the clinical features in the revised definitions are based solely on radiological evidence of IA whereas the original 2002 definitions also included minor signs such as fever and cough as evidence of disease. Consequently, employing the revised definitions to cases classified as possible IA by the 2002 definitions would only be retained as such if there was radiological evidence. Applying the 2008 definitions would have a similar effect on probable IA for the same reasons.

Anti‐mould prophylaxis reduces the proportion of proven/probable cases of IA (according to EORTC/MSG criteria) which is associated with a lower specificity of the Aspergillus PCR testing of blood. It is likely that PCR can detect infection before overt disease is radiologically detectable. Consequently, people with positive results who did not meet the criteria for proven or probable disease could have had early infection that resolved either with empirical or pre‐emptive antifungal treatment or as a result of resolution of the underlying immunosuppression.

The antifungal administration could mask a proportion of invasive infections, thus lowering the diagnostic recognition of a proportion of them. A raw calculation indicates a prevalence of 17.4% without prophylaxis, 10.4% with prophylaxis. Meanwhile, the PCR could maintain its ability to detect the Aspergillus DNA in the blood of the patients. Alternatively, the prophylaxis could maintain the fungal growth in a pre‐invasive stage, though not impeding the shedding of genomic material into the circulation, possibly enhancing its release through damage to the fungal cell wall or membrane.

The lack of direct comparisons with other biomarkers including GM and beta‐D‐glucan could be a further shortcoming. Looking at our findings and at those of other reviews, the performance of the PCR test is comparable to that reported for GM and superior to beta‐D‐glucan. It is likely that combinations of different biomarkers will provide the optimal diagnostic performance. Also it was difficult to distinguish between using PCR for screening purposes and for confirming the diagnosis as these are associated with low and high a priori likelihood respectively. Furthermore, screening requires testing at regular intervals during the period of risk (typically every 3 to 4 days) whereas tests for confirming the diagnosis of IFD will only be done once.

The molecular basis for azole resistance has been described, and the ability to detect Aspergillus DNA also raises the possibility of rapid detection of antifungal resistance using the same specimen. This could optimise patient management further and should be explored in future studies.

Applicability of findings to the review question

We noted that most studies performed PCR in high‐level reference laboratories, but it is not clear whether intermediate/peripheral laboratories might be settings that match the review question. An important step towards the standardisation and widespread uptake of PCR‐based diagnosis for aspergillosis will be the adoption of effective kit‐based assays. Much has been done by the EAPCRI to establish a standard for PCR that should help laboratories offering the test (www.eapcri.eu). However incorporating PCR into routine practice also requires an explicit protocol indicating who should be tested, when and how frequently, as well as what action should be taken in the event of a given result (Barnes 2018). Moreover the process needs to be completed within a frame so that the results can be used to best advantage by the clinician. This requires an explicit care plan or pathway, a multidisciplinary approach and a clear understanding between the clinic and laboratory to ensure a smooth turnaround.

Study flow diagram.
Figuras y tablas -
Figure 1

Study flow diagram.

Risk of bias and applicability concerns graph: review authors' judgements about each domain presented as percentages across included studies
Figuras y tablas -
Figure 2

Risk of bias and applicability concerns graph: review authors' judgements about each domain presented as percentages across included studies

Risk of bias and applicability concerns summary: review authors' judgements about each domain for each included study
Figuras y tablas -
Figure 3

Risk of bias and applicability concerns summary: review authors' judgements about each domain for each included study

Forest plot of PCR: one (single) positive requirement.
Figuras y tablas -
Figure 4

Forest plot of PCR: one (single) positive requirement.

Forest plot of PCR: two positive requirement.
Figuras y tablas -
Figure 5

Forest plot of PCR: two positive requirement.

Summary ROC Plot. Bivariate analysis of the sensitivity and specificity of the PCR as a diagnostic tool for Aspergillus invasive infection. One single positive PCR result is required to define the test as positive
Figuras y tablas -
Figure 6

Summary ROC Plot. Bivariate analysis of the sensitivity and specificity of the PCR as a diagnostic tool for Aspergillus invasive infection. One single positive PCR result is required to define the test as positive

Summary ROC Plot. Bivariate analysis of the sensitivity and specificity of the PCR as a diagnostic tool for Aspergillus invasive infection. Two or more consecutive positive PCR result are required to define the test as positive.
Figuras y tablas -
Figure 7

Summary ROC Plot. Bivariate analysis of the sensitivity and specificity of the PCR as a diagnostic tool for Aspergillus invasive infection. Two or more consecutive positive PCR result are required to define the test as positive.

Predictive values. Positive and negative predictive value (PPV and NPV, respectively) of the Aspergillus PCR detection test (y‐axis) as a function of the prevalence of the disease, invasive aspergillosis (x‐axis). The curves are related to the diagnostic criterion (a single positive result or two consecutive positive PCR results). The PVs were calculated by applying the Bayes rule. The mean prevalence of invasive aspergillosis (16.3%) is indicated by the vertical dashed line. It corresponds to PPV1 = 42%, NPV1 = 95%, PPV2 = 70%, NPV2 = 92%.
Figuras y tablas -
Figure 8

Predictive values. Positive and negative predictive value (PPV and NPV, respectively) of the Aspergillus PCR detection test (y‐axis) as a function of the prevalence of the disease, invasive aspergillosis (x‐axis). The curves are related to the diagnostic criterion (a single positive result or two consecutive positive PCR results). The PVs were calculated by applying the Bayes rule. The mean prevalence of invasive aspergillosis (16.3%) is indicated by the vertical dashed line. It corresponds to PPV1 = 42%, NPV1 = 95%, PPV2 = 70%, NPV2 = 92%.

PCR: single positive requirement.
Figuras y tablas -
Test 1

PCR: single positive requirement.

PCR: two positive requirement.
Figuras y tablas -
Test 2

PCR: two positive requirement.

no anti‐mould prophylaxis.
Figuras y tablas -
Test 3

no anti‐mould prophylaxis.

antimould prophylaxis.
Figuras y tablas -
Test 4

antimould prophylaxis.

in‐house qPCR.
Figuras y tablas -
Test 5

in‐house qPCR.

qPCR kit.
Figuras y tablas -
Test 6

qPCR kit.

PCR on whole blood.
Figuras y tablas -
Test 7

PCR on whole blood.

PCR on serum.
Figuras y tablas -
Test 8

PCR on serum.

Summary of findings Summary of findings table. PCR for the diagnosis of invasive aspergillosis.

Review question: what is the diagnostic accuracy of aspergillus PCR blood test for detection of invasive aspergillosis (IA)?

Patients/population: patients at risk of IA, including neutropenic cancer patients and HSCT or solid organ transplant recipients

Index test: PCR on blood specimens (whole blood or serum). We considered different DNA extraction methods and PCR methods (e.g. nested, ELISA, qPCR)

Reference standard: EORTC/MSG criteria for invasive aspergillosis

Studies: cohort studies

Index Test: interpretative criteria to define a test as positive

Effect (95% CI)

No. of studies

Mean prevalence (range)

What do these results mean?

1 Single PCR specimen

sensitivity: 79.2% (71.0% to 85.5%)

specificity: 79.6% (69.9% to 86.6%)

27 studies

16.3% (2.5% to 57.1%)

With a prevalence of 16%, 16 out of 100 patients will develop IA. Of these, 3 will be missed by a single PCR test (20.8% of 16); of the 84 patients without IA, 17 will have a false positive result of the PCR test; repeating the test will reduced significantly rates of false positive results.

≥ 2 PCR specimens

sensitivity: 59.6% (40.7% to 76.0%)

specificity: 95.1% (87.0% to 98.2%)

9 studies

16.3% (2.5% to 57.1%)

With a prevalence of 16%, 16 out of 100 patients will develop IA. Of these, 9 will be missed using the 2 positive PCR test (40.4% of 16); of the 84 patients without IA, 4 will have a false positive result of the PCR test.

The PCR methods varied notably across studies. Several covariates (in particular, the adoption of antifungal prophylaxis and blinding to the reference test or index test) were found to substantively affect the measures of diagnostic accuracy under evaluation, mainly sensitivity and specificity.
CI: confidence interval
IA: invasive aspergillosis
PCR: polymerase chain reaction

Figuras y tablas -
Summary of findings Summary of findings table. PCR for the diagnosis of invasive aspergillosis.
Table 1. European Organisation for Research and Treatment of Cancer/Mycoses Study Group definitions of invasive aspergillosis

Original definitions ofAscioglou 2002

Revised definitions ofDe Pauw 2008

PROVEN IA

Specimen obtained by needle aspiration or biopsy from a normally sterile and clinically or radiologically abnormal site consistent with an infectious disease processand

either histopathological, cytopathological, or direct microscopic examination of the specimen in which hyphae are seen accompanied by evidence of associated tissue damage

or

recovery of Aspergillus species by culture from the specimen obtained by a sterile procedure excluding bronchoalveolar lavage, cranial sinus cavity, and urine

PROBABLE IA

At least 1 host factor criterion plus 1 major (or 2 minor) clinical criteria from abnormal site consistent with infectionplus 1 microbiological criterion

At least 1 host factor plus 1 clinical feature plus 1 microbiological criterion

POSSIBLE IA

At least 1 host factor criterion plus

either 1 major (or 2 minor) clinical criterion from abnormal site consistent with infection or 1 microbiological criterion

At least 1 host factor plus 1 clinical feature

Host factor criteria will include the temporal relationship between the onset of fungal disease and the receipt of an allogeneic stem cell transplant.

Clinical features include for example neutropenia, persistent fever, predisposing conditions, prolonged use of corticosteroids; in the case of lower respiratory tract infection, the presence of 1 of the following signs on CT: dense well circumscribed lesions(s) with or without a halo sign or an air crescent sign, cavity.

Microbiological criteria consist of a positive culture including the presence of fungal elements indicating a mould on microscopy or recovery by culture of Aspergillus species from sputum, bronchoalveolar lavage (BAL) fluid, bronchial brush or sinus aspirate samples; positive result for Aspergillus detection of galactomannan antigen in specimens of plasma, serum, BAL, cerebrospinal fluid or 2 or more blood samples. Major clinical criteria are, for example, new infiltrates on computerized tomography imaging (e.g. halo sign) or suggestive radiological findings.

Minor clinical criteria are suggestive symptoms and signs.

The exact definitions of the European Organisation for Research and Treatment of Cancer/Mycoses Study Group criteria and their host factor, microbiological or clinical criteria can be found in Ascioglou 2002 and De Pauw 2008.

Figuras y tablas -
Table 1. European Organisation for Research and Treatment of Cancer/Mycoses Study Group definitions of invasive aspergillosis
Table 2. Technical details of the PCR methods used in the studies analysed in this review

Study

Sample type

Sample volume

DNA extraction methodsA

PCR methodC

Target gene

Appropriate controls

Requirements for positive by PCR

Methods used (refs)

Cell wall disruptionB

DNA isolation kit/protocol

NegativeD

PositiveE

PCR inhibition

Ex

PCR

Ex

PCR

Hebart 2000a

Whole blood

5 ml

Zymolase and NaOH lysis buffer

Protein precipitation and DNA precipitation

PCR‐slot blot

18S

Yes

Yes

Yes

Single positive

Einsele 1997

Ferns 2002

Whole blood

2 ml

Lyticase

QIAamp

Nested PCR

mtDNA

Yes

Yes

Yes

Yes

Positive on 2 occasions

Bretagne 1998

Tang 1993

Florent 2006

Serum

200 μl

QIAamp

PCR‐ELISA

mtDNA

Yes

Yes

Yes

2 consecutive positives

Bretagne 1998

Halliday 2006

Whole blood

500 μl

Lyticase

GenElute

Nested PCR

18S

Yes

Yes

Yes

Yes

2 consecutive positives

Skladny 1999

El Mahallawy 2006

Serum

Lyticase

QIAamp

Standard PCR

18S

Yes

Yes

Single positive

Williamson 2000

White 2006

Whole blood

2 ml

Glass beads

MagNA Pure

Nested qPCR

28S

Yes

Yes

Yes

Yes

Yes

Serial positives in single episode

Loeffler 2002; Williamson 2000

Suarez 2008

Serum

1 ml or 200 μl

MagNA Pure

qPCR

28S

Yes

Yes

Single positive

Challier 2004

Hummel 2009

Blood

5 ml

Lyticase

Phenol‐chloroform

Nested PCR

18S

Yes

Yes

Single positive

Skladny 1999

Ramírez 2009

Whole blood

5 ml

Lyticase and glass beads

QIAamp

qPCR

18S

Yes

Yes

Single positive

Loeffler 2000

Barnes 2009

Whole blood

2 ml

Glass beads

MagNA Pure

Nested qPCR

28S

Yes

Yes

Yes

Yes

Yes

Confirmed positiveF

White 2006

Cuenca‐Estrella 2009

Whole blood and serum

QIAamp

qPCR

ITS1

Yes

Yes

Yes

2 consecutive positives

Yoo 2008

von Lilienfeld‐Toal 2009

Whole blood

10 ml

Ceramic beads

Septifast

qPCR

18S

Yes

Yes

Yes

Lehmann 2008

Landlinger 2010

Whole blood

3 ml

Lyticase

MagNA Pure

qPCR

28S

Yes

Yes

Yes

Single positive

Baskova 2007; Watzinger 2004

Badiee 2010

Whole blood

3 to 5 ml

Lyticase

QIAamp

qPCR

18S

Yes

Yes

Yes

Single positive

Van Burik 1998; Kami 2001;

da Silva 2010

Serum

5 ml Blood

Lyticase

Protein precipitation and DNA precipitation

Standard PCR

18S

Yes

Yes

2 consecutive positives

Ribeiro 2006; Van Burik 1998

Springer 2011G

Whole blood

3 ml

Glass beads

High Pure PCR Template Preparation Kit (Roche)

qPCR

ITS

Yes

Yes

Single positiveH

FastPrep‐24 MP (Biomedicals)

Whole blood

5 ml

Glass beads

Standard PCR

Yes

Yes

Yes

Yes

Sachse 2009

Rogers 2013G

Whole blood

3 ml

Glass beads

High Pure PCR Template Preparation Kit (Roche)

Nested qPCR

28S

Yes

Yes

Yes

Yes

Yes

Single positiveI

White 2006

Springer 2011

qPCR

ITS1

Yes

Yes

Single positiveI

Sugawara 2013

Whole blood

1 ml

Beads and lysis buffer

Phenol‐chloroform

Nested PCR and sequencing

18S

Yes

Yes

Single positive

Nakamura 2010

Barnes 2013

Whole blood

3ml

Glass beads

Various automated extractors – Roche MagNA Pure LC Total NA, BioMerieux EasyMag, Qiagen EZ1 Advance XL tissue kit.

qPCR and nested qPCR

28S

Yes

Yes

Yes

Yes

Yes

Single and multiple positive thresholds used

White 2006

Schwarzinger 2013

Serum

1 ml

Not required

Roche MagNA Pure LC DNA

qPCR

Mitochonrial

Yes

Yes

Yes

Single positive

Botterel 2008

Aslan 2015

Serum

0.2 ml

Not required

Qiamp DNA Mini Kit

qPCR

18S and 28S

Yes

Yes

Yes

Yes

Yes

Single positive

Mycassay Aspergillus and in‐house PCR

Bellanger 2015

Serum

1 ml

Large Volume MagNa Pure Nucleic acid isolation kit

qPCR

18S

Mitochondrial (L37095)

(no info on controls)

Single positive

Millon 2011,

Costa 2001

Pini 2015

Serum

0.5 ml

Not required

High Pure template (Roche)

qPCR

18S

Yes

Yes

Yes

Single Positive

Mycassay Aspergillus

Boch 2016

Whole blood

3 to 5 ml

Lyticase

Phenol‐chloroform

Nested PCR

18S

Yes

Yes

Single positive

Skladny 1999

Boluk 2016

Serum

ZR Fungal/Bacterial DNA

MiniPrep Kit

qPCR

Kit (Way2 Gene Fungi)

Yes

Yes

Single Positive

No ref to methods for Asp PCR

Imbert 2016

Serum

1 ml

MagNA Pure Compact large volume

kit on a MagNA Pure device (Roche)

qPCR

28S

Yes

Yes

Yes

Single Positive

Suarez 2008, Challier 2004

Springer 2016

Serum

1 ml

Qiaamp UltrasensVirus Kit

qPCR

ITS1‐5.8S

Yes

Yes

Yes, but Bacillus‐DNA was used

Yes

Yes

Single and multiple positive thresholds used

Skladny 1999,Springer 2012

Badiee 2017

Serum

0.2 ml

QiaAmp Mini

qPCR

18S

Skladny 1999; Shin 1999

Loeffler 2017

Cell‐free blood fraction, mostly serum

1 ml

Qiaamp UltrasensVirus Kit

qPCR

ITS1‐5.8S

Yes

Yes

Yes, but Bacillus‐DNA was used

Yes

Yes

Single positive

Skladny 1999; Springer 2016

‐: not reported; MagNA Pure: an automated DNA isolation system manufactured by Roche; mtDNA: mitochondrial DNA; PCR: polymerase chain reaction; QIAamp: QIAamp DNA isolation kit manufactured by Qiagen; Ex: extraction; ITS: Internal Trascribed Spacer; RCLB: red cell lysis buffer.

A DNA isolation protocols may include steps to remove red and white blood cells, fungal cell wall disruption and DNA purification kits.

B Lyticase/Zymolase enzymatically digest fungal cells walls; ceramic or glass beads cause mechanical disruption of the cell wall.

C PCR methods used vary between standard PCR where products are resolved on agarose gels to detect positive or negative reactions or quantitative PCR (qPCR) which allows real time monitoring of the reaction. Nested qPCR involves first round standard PCR and second round qPCR.

D Negative DNA extraction controls feature a sample blank, e.g. blood or sterile solution, that allows detection of any contamination in the DNA isolation protocol.

E Positive DNA extraction controls are a sample blank that is spiked with fungal or specific bacterial spores to ensure that the DNA isolation protocol is working optimally.

F The confirmed positive requires that any single positive sample is confirmed with an additional sample from the same patient. Barnes 2009 also used multiple analyses to determine the effectiveness of single versus multiple positives to yield diagnostic accuracy.

G Studies assessed the effectiveness of more than 1 assay.

H The study analysed the effect of both single and multiple positives.

I The effects of both single and multiple positives were analysed as well as analyses of combined PCR and galactomannan tests.

Figuras y tablas -
Table 2. Technical details of the PCR methods used in the studies analysed in this review
Table 3. Subgroup analyses

Covariate

Subgroup

Index

mean

95% CI

Subgroup Difference: P

Anti‐mould prophylaxis

yes

sensitivity

0.8206

0.7536; 0.8725

not significant

no

sensitivity

0.7577

0.6440; 0.8439

yes

specificity

0.6470

0.5638; 0.7222

0.0387

no

specificity

0.7901

0.6769; 0.8712

EORTC criteria 2008 vs 2002

2008

sensitivity

0.7311

0.6324; 0.8112

not significant

2002

sensitivity

0.7878

0.7061; 0.8516

2008

specificity

0.7339

0.6098; 0.8296

not significant

2002

specificity

0.8226

0.6559; 0.9186

Blind reference

yes

sensitivity

0.7384

0.6124; 0.8345

not significant

no

sensitivity

0.7676

0.6652; 0.8460

yes

specificity

0.6284

0.5429; 0.7065

0.0009

no

specificity

0.8553

0.7555; 0.9187

Blind index

yes

sensitivity

0.7209

0.6402; 0.7895

not significant

no

sensitivity

0.7584

0.6476; 0.8428

yes

specificity

0.6646

0.5532; 0.7603

0.0161

no

specificity

0.8295

0.7354; 0.8950

In‐house vs commercial kit

In‐house

sensitivity

0.7489

0.6038; 0.8537

not significant

kit

sensitivity

0.6576

0.3274; 0.8835

In‐house

specificity

0.8428

0.7263; 0.9155

not significant

kit

specificity

0.7674

0.4165; 0.9384

Whole blood vs serum

WB

sensitivity

0.8114

0.7304; 0.8724

not significant

serum

sensitivity

0.7130

0.5956; 0.8073

WB

specificity

0.7243

0.6382; 0.7965

not significant

serum

specificity

0.8139

0.6661; 0.9056

Effects of 6 binary covariates on the sensitivity and specificity of the Aspergillus PCR. Meta‐analytical pooling for proportions (method of logits, DerSimonian‐Laird estimator for tau², inverse variance method), subgroup analysis. Mean values and 95% confidence intervals are reported. “Subgroup Difference: P” reports the comparison between 2 subgroups as difference within the same index for each covariate, as P value. Significant results were found for specificity under prophylaxis (as decrease under prophylaxis), specificity under blind reference (as decrease under blind reference), specificity under blind index (as decrease under blind index). Analysis performed with R version 3.5.3.

Figuras y tablas -
Table 3. Subgroup analyses
Table Tests. Data tables by test

Test

No. of studies

No. of participants

1 PCR: single positive requirement Show forest plot

28

4989

2 PCR: two positive requirement Show forest plot

9

2151

3 no anti‐mould prophylaxis Show forest plot

13

1464

4 antimould prophylaxis Show forest plot

12

1478

5 in‐house qPCR Show forest plot

15

2661

6 qPCR kit Show forest plot

3

302

7 PCR on whole blood Show forest plot

15

2217

8 PCR on serum Show forest plot

13

2481

Figuras y tablas -
Table Tests. Data tables by test