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Cochrane Database of Systematic Reviews Protocol - Intervention

Anti‐sclerostin antibodies for the treatment of osteoporosis

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Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the benefits and harms of anti‐sclerostin antibodies for the treatment of osteoporosis.

Background

Description of the condition

Osteoporosis is defined as a systemic disorder characterized by low bone mass and deterioration of the bone tissue microarchitecture, which leads to increased bone fragility and fracture susceptibility (Bouillon 1991). The burden of osteoporosis is well defined and is considered to be a rapidly growing and global public health problem. Osteoporosis affects more than 75 million people in the USA, Europe, and Japan (WHO study group report 1994); and it results in approximately 9.0 million fractures worldwide each year (Johnell 2006). By the year 2020 it is estimated that the prevalence of osteoporosis in the USA will rise from 10 million to approximately 14 million (NOF 2002). One study estimated that in 2005 approximately two million incident fractures accounted for USD 17 billion in health care costs and with a growing aged population in the USA these estimates are likely to result in a 50% increase by 2025 (Burge 2007). Similarly high costs of osteoporosis treatment and management were estimated in Europe at EUR 37 billion in 2010 (Hernlund 2013); and in Canada at over CAD 2.3 billion (Tarride 2012). It is evident that osteoporosis can lead to significant morbidity and mortality; and management of this condition can have a major public health impact.

Description of the intervention

There are several pharmacological agents that are used to manage osteoporosis (Allen 2016; Homik 2010); these are targeted at improving bone mineral density (BMD) and reducing fragility fractures. These agents can be broadly classified into two types: antiresorptive agents; and bone stimulatory or anabolic agents (Tella 2014). Most agents act by inhibiting bone resorption: in particular calcium and vitamin D have been shown to prevent bone loss of the lumbar spine and femoral neck in steroid‐induced osteoporosis (Homik 2010); and similarly bisphosphonates have been shown to prevent vertebral fractures in steroid‐induced osteoporosis (Allen 2016). In recent times, studies have been conducted to evaluate the effectiveness of newer biological agents with bone stimulatory effects such as teriparatide (Eriksen 2004), Dickkopf‐related protein 1 (DKK1) antibodies (Glantschnig 2010), and anti‐sclerostin antibodies (Chapurlat 2016).

Sclerostin is a protein produced by osteocytes (bone cells) that inhibits bone formation (Lewiecki 2011; Van Bezooijen 2004). In the last decade romosozumab and blosozumab, two monoclonal antibodies to sclerostin that are structurally diverse, have been developed for use in humans. Romosozumab and blosozumab have been tested in phase I trials (McColm 2014; Padhi 2011), and phase II trials (McClung 2014; Recker 2015): they have been shown to be well tolerated, with significant increases in bone mass observed. This increase in bone mass was seen at all skeletal locations assessed, namely lumbar spine, total hip and femoral neck. Phase III romosozumab clinical trials are currently ongoing (NCT02016716; NCT02791516; NCT01631214; NCT02186171; NCT01796301; NCT01575834); and neither romosozumab or blosozumab are FDA approved (FDA 2017).

How the intervention might work

The process of bone remodeling allows the renewal of bone and maintenance of bone health by replacing old bone with new bone. Osteoclasts are responsible for bone resorption; and bone formation is reliant on the effects of osteoblasts. Balance between osteoclastic and osteoblastic activity maintains bone homeostasis which is mainly controlled by signaling pathways (Iñiguez‐Ariza 2015). Recently Wnt signaling pathways are being evaluated for their effects on bone (Tella 2014).

Sclerostin, which is produced by osteocytes, is transported to the surface of the bone by the canalicular network of osteocytes within bone, where it inhibits osteoblast function (Van Bezooijen 2004; Winkler 2003). It also upregulates the receptor activator of nuclear factor kappa‐B ligand (RANKL) synthesis in osteocytes, resulting in the stimulation of osteoclastogenesis (Wijenayaka 2011). Sclerostin ultimately inhibits the Wnt signaling pathway in osteoblasts resulting in lesser osteoblast proliferation and differentiation (Iñiguez‐Ariza 2015; Li 2005; Semenov 2005). Understanding of this pathway led to studies in animals: for example, in a rat model of postmenopausal osteoporosis, anti‐sclerostin antibodies stimulated bone formation and increased bone mineral density and strength (Li 2009). These observations resulted in the development of anti‐sclerostin antibodies for use in humans. Results of the animal studies and phase I and phase II trials in humans have shown that anti‐sclerostin antibodies can stimulate the Wnt and β‐catenin pathways and result in increased bone formation.

Why it is important to do this review

Anti‐sclerostin antibodies are new biological agents that have shown promise in the treatment of osteoporosis in several pre‐clinical and clinical studies. No systematic reviews have been conducted to this date to comprehensively evaluate the effects of anti‐sclerostin antibodies in the treatment of osteoporosis. Osteoporosis can be a debilitating disease and cause significant morbidity and mortality. Antiresorptive medications inhibit bone resorption and have been well evaluated, but evidence on the benefits and harms of bone stimulatory agents like anti‐sclerostin antibodies is lacking. This review will be conducted according to the guidelines recommended by the Cochrane Musculoskeletal Group Editorial Board (Ghogomu 2014).

Objectives

To assess the benefits and harms of anti‐sclerostin antibodies for the treatment of osteoporosis.

Methods

Criteria for considering studies for this review

Types of studies

We will include randomized controlled trials (RCTs) or controlled clinical trials (CCTs). We will include studies reported as full text, those published as abstract only, and unpublished data. There will be no language restriction. We will include trials irrespective of whether measured outcome data are reported in a ‘usable’ way.

Types of participants

We will include adults over the age of 18 years with a diagnosis of osteoporosis, as defined by the World Health Organization (WHO) as a T‐score of less than −2.5 (Kanis 1994; WHO study group report 1994). We will also include participants from studies using osteoporosis definitions other than that of the WHO. We will exclude participants with the following co‐morbidities/characteristics: untreated hyperthyroidism or hypothyroidism; hypercalcemia or hypocalcemia; substantially impaired renal function or bone marrow transplantation. We will exclude participants who received therapeutic doses of systemic corticosteroids, fluoride, strontium or parathyroid hormone, systemic oral or transdermal estrogen, selective estrogen receptor modulators, bisphosphonates, denosumab, or with a known allergy to monoclonal antibody. Participants from both primary and secondary fracture prevention studies will be included.

Types of interventions

We will include trials in which the treatment arm includes anti‐sclerostin antibodies (romosozumab 210 mg or blosozumab 270 mg) versus placebo. We will pool trials in which the treatment arm includes anti‐sclerostin antibodies and the control arm includes placebo. All other comparisons (e.g. anti‐sclerostin antibodies versus bisphosphonates or any other active comparison) will be considered secondary and will be part of the appendices.

Types of outcome measures

Major Outcomes

  1. Clinical vertebral fractures.

  2. Non‐vertebral fractures.

  3. Hip fractures.

  4. Quality of life, assessed with the use of validated measures such as Short Form (SF)‐36 (Ware 1993), Health Assessment Questionnaire (HAQ) (Bruce 2005), Osteoporosis Functional Disability Questionnaire (OFDQ) (Helmes 1995), QoL Questionnaire for osteoporosis (OPTOQLQ) (Lydick 1997), Osteoporosis Assessment Questionnaire (OPAQ) (Silverman 1993; Silverman 1997) or QoL Questionnaire of European Foundation for Osteoporosis (QUALEFFO) (Lips 1996).

  5. Tolerability of treatment (withdrawals due to adverse events).

  6. Serious adverse events. The number of participants experiencing at least one serious adverse event (i.e. hospitalizations, disability or death).

  7. Total adverse events. The number of participants experiencing at least one adverse event.

Minor Outcomes

  1. Radiographic vertebral fracture.

  2. Wrist fractures.

  3. BMD measured by dual x‐ray absorptiometry or quantitative computed tomography at the total hip, femoral neck, lumbar spine and distal radius.

  4. Bone turnover markers. Markers of bone formation (intact N‐terminal propeptide of type I collagen, bone‐specific alkaline phosphatase, and C‐terminal propeptide of type I collagen) and bone resorption (C‐telopeptide of type I collagen, N‐telopeptide of type I collagen, deoxypyridinoline crosslinks and tartrate‐resistant acid phosphatase 5b).

  5. Acceptability of treatment. The proportion of patients who leave the study early for any reason.

  6. Skeletal pain report. The number of participants who experience improvement in skeletal pain sensation (e.g. back pain).

We will restrict the primary analysis of our reviews for self‐reported outcomes (e.g. outcomes such as improvement in skeletal pain report, health‐related quality of life) to trials at low risk of detection and selection bias.

Time points

Both major and minor outcomes will be assessed at 6 and 12 months.

Search methods for identification of studies

Electronic searches

We will search the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE, Embase, Web of Science, and PubMed. We will also conduct a search of ClinicalTrials.gov (www.ClinicalTrials.gov) and the WHO trials portal (www.who.int/ictrp/en/). We will search all databases from their inception to the present, and we will impose no restriction on language of publication.

For assessments on adverse effects, we will search the web sites of the regulatory agencies.

See Appendix 1 for the MEDLINE search strategy

Searching other resources

We will check reference lists of all primary studies and review articles for additional references. We will search relevant manufacturers' web sites for trial information. We will search for errata or retractions from included studies published in full text on PubMed (www.ncbi.nlm.nih.gov/pubmed), and report the date this was done within the review.

Data collection and analysis

Selection of studies

Two review authors (XP and HL) will independently screen titles and abstracts for inclusion of all the potential studies we identify as a result of the search and code them as 'retrieve' (eligible or potentially eligible/unclear) or 'do not retrieve'. We will retrieve the full‐text study reports/publication and two review authors (XP and HL) will independently screen the full text and identify studies for inclusion, and identify and record reasons for exclusion of the ineligible studies. We will resolve any disagreement through discussion or, if required, we will consult a third person (MSA). We will identify and exclude duplicates and collate multiple reports of the same study so that each study, rather than each report, is the unit of interest in the review. We will record the selection process in sufficient detail to complete a PRISMA flow diagram and 'Characteristics of excluded studies' table.

Data extraction and management

We will use a data collection form, which will be piloted on at least one study in the review, for study characteristics and outcome data. Two review authors (XP and HL) will independently extract study characteristics and data from included studies. We will resolve disagreements by consensus or by involving a third reviewer (MSA). We will extract the following study characteristics.

  1. Methods: study design, total duration of study, details of any run‐in period, number of study centers and location, study setting, withdrawals, and date of study.

  2. Participants: N, mean age, age range, sex, disease duration, severity of condition, diagnostic criteria, important osteoporosisspecific baseline data (e.g. BMD, body mass index etc.); inclusion criteria, and exclusion criteria.

  3. Interventions: intervention, comparison, and concomitant medications. Data on dosage and treatment schedules of anti‐sclerostin antibodies and the comparative medications.

  4. Outcomes: primary and secondary outcomes specified and collected, and time points reported. Number of events and number of participants per treatment group for dichotomous outcomes, and means and standard deviations and number of participants per treatment group for continuous outcomes. We will extract the number of events and number of participants per treatment group for dichotomous outcomes, and means and standard deviations and number of participants per treatment group for continuous outcomes. If both unadjusted and adjusted values for the same outcome are reported, we will report on the unadjusted values. We will note in the 'Characteristics of included studies' table if outcome data were not reported in a usable way and when data were transformed or estimated from a graph.

  5. Characteristics of the design of the trial as outlined below in the 'Assessment of risk of bias in included studies' section.

  6. Notes: funding for trial, and notable declarations of interest of trial authors.

Two review authors (XP, MLO) will transfer data into the Review Manager 5 (RevMan 5) file (Review Manager 2014). We will double‐check that data is entered correctly by comparing the data presented in the systematic review with the study reports.

  • If both final values and 'change from baseline' values are reported for the same outcome, the final value will be used.

  • If data are analyzed based on an intention‐to‐treat (ITT) sample and another sample (e.g. 'per protocol', 'as treated'), only the ITT will be used.

  • If multiple time points are present, information on all time points will be extracted.

Assessment of risk of bias in included studies

Two review authors (XP and HL) will independently assess risk of bias for each study using the criteria outlined in theCochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). We will resolve any disagreements by discussion or by involving another author (MSA). We will assess the risk of bias according to the following domains.

  1. Random sequence generation.

  2. Allocation concealment.

  3. Blinding of participants and personnel.

  4. Blinding of outcome assessment.

  5. Incomplete outcome data.

  6. Selective outcome reporting.

  7. Other bias (baseline imbalance, selective subgroup reporting, supplementation for dropouts by providing additional recruits, recruitment of additional participants from a subgroup showing more or less benefit and deviation from the study protocol in a way that does not reflect clinical practice, and other sources of bias not covered in other domains of bias).

We will grade each potential source of bias as high, low or unclear and provide a quote from the study report together with a justification for our judgment in the 'Risk of bias' table. We will summarize the risk of bias judgments across different studies for each of the domains listed. We will consider blinding separately for different key patient‐reported subjective outcomes including improvement in skeletal pain (back pain), quality of life, and tolerability of treatment. In addition, we will consider the impact of missing data by key outcomes. Where information on risk of bias relates to unpublished data or correspondence with a trialist, we will note this in the 'Risk of bias' table. When considering treatment effects, we will take into account the risk of bias for the studies that contribute to that outcome. We will present the figures generated by the 'Risk of bias' tool to provide summary assessments of the risk of bias. The primary analysis for our reviews for self‐reported outcomes (e.g. outcomes such as skeletal pain, health‐related quality of life), will be restricted to trials with low risk of detection and selection bias.

Assessment of bias in conducting the systematic review

We will conduct the review according to this published protocol and report any deviations from it in the 'Differences between protocol and review' section of the systematic review.

Measures of treatment effect

We will analyse dichotomous data as risk ratios (RRs) or Peto odds ratio when the outcome is a rare event (approximately less than 10%), and use 95% confidence intervals (CIs). Continuous data will be analyzed as mean difference (MD) or standardized mean difference (SMD), depending on whether the same scale is used to measure an outcome, with 95% CIs. We will enter data presented as a scale with a consistent direction of effect across studies.

When different scales are used to measure the same conceptual outcome (e.g. quality of life), SMDs will be calculated instead, with corresponding 95% CIs. SMDs will be back‐translated to a typical scale (e.g. 0 to 10 for skeletal pain) by multiplying the SMDs by a typical among‐person standard deviation (e.g. the standard deviation of the control group at baseline from the most representative trial) (Schünemann 2011b).

We will provide the absolute per cent difference, the relative per cent change from baseline, and the number needed to treat for an additional beneficial outcome (NNTB); (the NNTB will be provided only when the outcome shows a statistically significant difference).

For dichotomous outcomes, such as serious adverse events, we will calculate the NNTB from the control group event rate and the relative risk using the Visual Rx NNT calculator (Cates 2008). We will calculate the NNTB for continuous measures using the Wells calculator (available at the CMSG Editorial office, musculoskeletal.cochrane.org/).

For dichotomous outcomes, we will calculate the absolute risk difference using the risk difference statistic in RevMan 5 software and express the result as a percentage (Review Manager 2014). For continuous outcomes, we will calculate the absolute benefit as the improvement in the intervention group minus the improvement in the control group, in the original units, and express as a percentage.

We will calculate the relative per cent change for dichotomous data as (RR − 1) and express as a percentage. For continuous outcomes, we will calculate the relative difference in the change from baseline as the absolute benefit divided by the baseline mean of the control group, and express as a percentage.

Unit of analysis issues

The participants will be the unit of analysis. Where multiple trial arms are reported in a single trial, we will include our main comparison: anti‐sclerostin antibodies versus placebo. Other comparisons will be analysed and reported separately in the appendices. If two comparisons (e.g. drug A versus placebo and drug B versus placebo) are combined in the same meta‐analysis, we will halve the control group to avoid double‐counting (Higgins 2011b). We will prioritize comparison of anti‐sclerostin antibodies in combination with calcium and vitamin D versus placebo in combination with calcium and vitamin D. We will make it clear in the 'Characteristics of included studies' table that more than two intervention groups were present in the study, where applicable.

Dealing with missing data

We will contact investigators or study sponsors in order to verify key study characteristics and obtain missing numerical outcome data where possible (e.g. when a study is identified as abstract only or when data are not available for all participants). Where this is not possible, and the missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results by a sensitivity analysis. We will describe any assumptions and imputations to handle missing data clearly; and explore the effect of imputation using sensitivity analyses.

For dichotomous outcomes, the withdrawal rate will be calculated using the number of patients randomized in the group as the denominator. For continuous outcomes (e.g. mean change in pain score), we will calculate the MD or SMD based on the number of patients analyzed at that time point. If the number of patients analyzed is not presented for each time point, the number of randomized patients in each group at baseline will be used.

Where possible, missing standard deviations (SDs)will be computed from other statistics such as standard errors, CIs or P values, according to the methods recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011c). Where SD is not presented for follow‐up, or cannot be calculated from other statistics, we will use the baseline SD instead if available (Fu 2015). When the mean is not presented, we will use the median if reported. We will use the interquartile range (IQR) to calculate the SD as recommended in the Cochrane Handbook for Systematic Reviews of interventions (SD = IQR/1.35), when necessary (Higgins 2011b). If standard deviations cannot be calculated, they will be imputed (e.g. from other studies in the meta‐analysis).

Assessment of heterogeneity

We will examine data from the data extraction tables to assess clinical and methodological diversity in terms of participants, interventions, outcomes and study characteristics for the included studies; and from these we will determine whether a meta‐analysis is appropriate. We will assess statistical heterogeneity by visual inspection of the forest plot to assess for obvious differences in result between the studies, and by using the I² and Chi² statistical tests.

As recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2011), the interpretation of an I² value of 0% to 40% 'might not be important'; 30% to 60% may represent 'moderate' heterogeneity; 50% to 90% may represent 'substantial' heterogeneity; and 75% to 100% represents 'considerable' heterogeneity. As noted in the Cochrane Handbook for Systematic Reviews of Interventions, we will keep in mind that the importance of I² depends on (i) magnitude and direction of effects and (ii) strength of evidence for heterogeneity.

The Chi² test will be interpreted where a P value less than or equal to 0.10 will indicate evidence of statistical heterogeneity. If we detect significant heterogeneity (I² > 40%), we will examine the included studies for sources of heterogeneity, including differences in participant characteristics and other potential reasons for differences in effect sizes.

Assessment of reporting biases

If there are at least 10 trials, we will create and examine a funnel plot to explore possible publication biases. In interpreting funnel plots, we will examine the different possible reasons for funnel plot asymmetry as outlined in section 10.4 of the Cochrane Handbook for Systematic Reviews of interventions and relate this to the results of the review. If we are able to pool more than 10 trials, we will undertake formal statistical tests to investigate funnel plot asymmetry, and will follow the recommendations in section 10.4 of the Cochrane Handbook for Systematic Reviews of interventions (Sterne 2011).

To assess outcome reporting bias, we will check trial protocols against published reports. For studies published after 1 July 2005, we will screen the Clinical Trial Register at the International Clinical Trials Registry Platform of the World Health Organization (www.who.int/ictrp/en/) for the a priori trial protocol. We will evaluate whether selective reporting of outcomes is present.

Data synthesis

We will undertake meta‐analyses only where this is meaningful, i.e. if the treatments, participants and the underlying clinical question are similar enough for pooling to make sense. We will use a random‐effects model for analysis. We will perform a sensitivity analysis by performing analyses using the fixed‐effect model as an alternate approach. We will combine the data from included trials in a meta‐analysis if two or more studies report on the same outcomes (anti‐sclerostin antibodies in combination with calcium; and vitamin D versus placebo in combination with calcium and vitamin D).

GRADE and 'Summary of findings' table

We will create a 'Summary of findings' table using the following outcomes: 1. clinical vertebral fractures; 2. non‐vertebral fractures; 3. hip fractures; 4. quality of life; 5. tolerability of treatment (withdrawals due to adverse events); 6. serious adverse events; and 7. total adverse events. Two people (XP and HL) will independently assess the quality of the evidence. We will use the five GRADE considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of a body of evidence as it relates to the studies which contribute data to the meta‐analyses for the prespecified outcomes, and report the quality of evidence as high, moderate, low, or very low. We will use methods and recommendations described in Section 8.5 and 8.7 and chapters 11 and 12 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a; Schünemann 2011a), using GRADEpro software. We will justify all decisions to down‐grade the quality of studies using footnotes and we will make comments to aid readers' understanding of the review where necessary. The main comparison for the 'Summary of findings' table will be anti‐sclerostin antibodies in combination with calcium; and vitamin D versus placebo in combination with calcium and vitamin D. If multiple time points are reported we will report primarily on 52 weeks, then on 24 weeks and then on 12 weeks.

We will provide the number needed to treat for an additional beneficial outcome (NNTB) or the number needed to treat for an additional harmful outcome (NNTH), absolute and relative per cent change, in the comments column of the 'Summary of findings' table as described in the 'Measures of treatment effect' section above.

Subgroup analysis and investigation of heterogeneity

We plan to carry out the following subgroup analyses to investigate the robustness of the treatment effect of anti‐sclerostin antibodies in combination with calcium, and vitamin D versus placebo in combination with calcium and vitamin D.

  1. Gender (men versus women). Prevalence of osteoporosis and fractures maybe different in women and men and potentially respond differently to osteoporosis treatment interventions.

  2. Menopausal status (premenopausal versus postmenopausal). Prevalence of osteoporosis and fractures may be higher in postmenopausal women in comparison to premenopausal women and potentially respond differently to osteoporosis treatment interventions.

  3. Definition of osteoporosis. The World Health Organization defines osteoporosis as a T‐score of less than −2.5 (Kanis 1994, WHO study group report 1994). However, it is possible for research studies to use other definitions such as a T‐score of less than −2.0, and others.

  4. Categorization of osteoporosis such as steroid‐induced osteoporosis versus post‐menopausal osteoporosis. The mechanisms of bone loss and osteoporosis may differ by the implicated causal variable.

  5. By dose. There may be differences in benefits and harms at different doses of the intervention and this needs to be explored.

  6. Primary versus secondary fracture prevention.

We will use the formal test for subgroup interactions in Review Manager 5 (Review Manager 2014); and we will use caution in the interpretation of subgroup analyses as advised in section 9.6 of the Cochrane Handbook for Systematic Reviews of interventions. The magnitude of the effects will be compared between the subgroups by means of assessing the overlap of the CIs of the summary estimated. Non‐overlap of the CIs indicates statistical significance. We plan to analyse the outcome of clinical vertebral fractures in the subgroup analyses, and if not reported, subgroup analysis will not be conducted.

Sensitivity analysis

We will perform sensitivity analysis by assessing 'high‐quality' studies versus 'low‐quality' studies. We will define 'high quality' as those studies with adequate concealment of allocation, proper blinding of outcome assessor for subjective outcomes including improvement in skeletal pain report (back pain), quality of life and tolerability of treatment, and a drop‐out rate of less than 15%. In addition, we will perform a sensitivity analysis on those trials receiving funding from a pharmaceutical company versus those trials that do not receive such funding. We will also do a sensitivity analysis based on the fixed‐effect model and random‐effects model of meta‐analysis, as described under 'Data collection and analysis' above. We plan to include clinical vertebral fractures and non‐vertebral fractures in the sensitivity analyses, when data are available.

Interpreting results and reaching conclusions

We will follow the guidelines in the Cochrane Handbook for Systematic Reviews of Interventions for interpreting results (Schünemann 2011b), and will be aware of distinguishing a lack of evidence of effect from a lack of effect. We will base our conclusions only on findings from the quantitative or narrative synthesis of included studies for this review. We will avoid making recommendations for practice and our implications for research will suggest priorities for future research and outline what the remaining uncertainties are in the area.