Matching-Adjusted Indirect Comparisons: A New Tool for Timely Comparative Effectiveness Research

ObjectiveIn the absence of head-to-head randomized trials, indirect comparisons of treatments across separate trials can be performed. However, these analyses may be biased by cross-trial differences in patient populations, sensitivity to modeling assumptions, and differences in the definitions of outcome measures. The objective of this study was to demonstrate how incorporating individual patient data (IPD) from trials of one treatment into indirect comparisons can address several limitations that arise in analyses based only on aggregate data.MethodsMatching-adjusted indirect comparisons (MAICs) use IPD from trials of one treatment to match baseline summary statistics reported from trials of another treatment. After matching, by using an approach similar to propensity score weighting, treatment outcomes are compared across balanced trial populations. This method is illustrated by reviewing published MAICs in different therapeutic areas. A novel analysis in attention deficit/hyperactivity disorder further demonstrates the applicability of the method. The strengths and limitations of MAICs are discussed in comparison to those of indirect comparisons that use only published aggregate data.ResultsExample applications were selected to illustrate how indirect comparisons based only on aggregate data can be limited by cross-trial differences in patient populations, differences in the definitions of outcome measures, and sensitivity to modeling assumptions. The use of IPD and MAIC is shown to address these limitations in the selected examples by reducing or removing the observed cross-trial differences. An important assumption of MAIC, as in any comparison of nonrandomized treatment groups, is that there are no unobserved cross-trial differences that could confound the comparison of outcomes.ConclusionsIndirect treatment comparisons can be limited by cross-trial differences. By combining IPD with published aggregate data, MAIC can reduce observed cross-trial differences and provide decision makers with timely comparative evidence.     

How Assessment-Schedule Matching Limits Bias When Comparing Progression-Free Survival in Single-Arm Studies: An Application in Second-Line Urothelial Carcinoma Treatments

ObjectivesPopulation-adjusted comparisons of progression-free survival (PFS) from single-arm trials of cancer treatments can be derived using matching-adjusted indirect comparisons (MAICs); however, results are still susceptible to bias, particularly if the trials had different tumor assessment schedules. This study aims to assess the effects of assessment-schedule matching (ASM) on the relative effectiveness on the PFS of avelumab versus approved comparator immunotherapies or chemotherapy after population matching in the second-line (2L) setting for metastatic urothelial carcinoma.MethodsThe MAIC used patient-level data for avelumab from the JAVELIN Solid Tumor trial (NCT01772004). PFS was compared with published curves for other treatments to obtain population-adjusted hazard ratios (HRs). The MAIC was repeated after conducting ASM for differences in tumor assessment scheduled first at 6 weeks for avelumab and durvalumab and at 8 or 9 weeks for other treatments.ResultsMAIC adjustment alone altered the HR estimates up to 23%, whereas MAIC plus ASM resulted in up to 32.7% reductions from naive comparisons. Even in cases in which MAIC had little effect, ASM brought an additional change of 11.1% to 15.4%. Overall, the HR range of avelumab versus other treatments changed from 0.83 to 1.25 for naive comparisons to 0.76 to 0.99 after ASM plus MAIC, numerically favoring avelumab.ConclusionsSmall variations in assessment schedules can introduce bias in unanchored indirect treatment comparisons of interval-censored time-to-event outcomes. In this study, adjusted PFS was comparable across second-line urothelial carcinoma treatment options, numerically favoring avelumab versus immunotherapies and chemotherapy agents. Correcting this bias is especially important when HRs are applied in cost-effectiveness models to transition patients between states.     

A Comparison of Alternative Network Meta-Analysis Methods in the Presence of Nonproportional Hazards: A Case Study in First-Line Advanced or Metastatic Renal Cell Carcinoma

ObjectivesNetwork meta-analysis (NMA) of time-to-event outcomes based on constant hazard ratios can result in biased findings when the proportional hazards (PHs) assumption does not hold in a subset of trials. We aimed to summarize the published non-PH NMA methods for time-to-event outcomes, demonstrate their application, and compare their results.MethodsThe following non-PH NMA methods were compared through an illustrative case study in oncology of 4 randomized controlled trials in terms of progression-free survival and overall survival: (1) 1-step or (2) 2-step multivariate NMAs based on traditional survival distributions or fractional polynomials, (3) NMAs with restricted cubic splines for baseline hazard, and (4) restricted mean survival NMA.ResultsFor progression-free survival, the PH assumption did not hold across trials and non-PH NMA methods better reflected the relative treatment effects over time. The most flexible models (fractional polynomials and restricted cubic splines) fit better to the data than the other approaches. Estimated hazard ratios obtained with different non-PH NMA methods were similar at 5 years of follow-up but differed thereafter in the extrapolations. Although there was no strong evidence of PH violation for overall survival, non-PH NMA methods captured this uncertainty in the relative treatment effects over time.ConclusionsWhen the PH assumption is questionable in a subset of the randomized controlled trials, we recommend assessing alternative non-PH NMA methods to estimate relative treatment effects for time-to-event outcomes. We propose a transparent and explicit stepwise model selection process considering model fit, external constraints, and clinical validity. Given inherent uncertainty, sensitivity analyses are suggested.     

Critical Appraisal of Network Meta-Analyses Evaluating the Efficacy and Safety of New Oral Anticoagulants in Atrial Fibrillation Stroke Prevention Trials

ObjectivesTo critically appraise published network meta-analyses (NMAs) evaluating the efficacy or safety of the new oral anticogulants (NOACs) dabigatran, rivaroxaban, and apixaban for the prevention of stroke in patients with nonvalvular atrial fibrillation (AF).MethodsA systematic literature review was performed to identify the relevant NMAs using MEDLINE, EMBASE, Cochrane Library, Database of Abstracts of Reviews of Effects, and Health Technology Assessment. The synthesis studies were evaluated using the “Questionnaire to assess the relevance and credibility of the NMA.”ResultsEleven NMAs evaluating NOACs among adults with nonvalvular AF were identified. Most NMAs included three large phase III randomized controlled trials, comparing NOACs to adjusted-dose warfarin (Randomized Evaluation of Long-Term Anticoagulation Therapy [RE-LY], Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared With Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation [ROCKET-AF], and Apixaban for Reduction of Stroke and Other Thromboembolic Events in Atrial Fibrillation [ARISTOTLE]). The main differences identified related to potential treatment effect modifiers regarding the mean time spent in therapeutic range (TTR) in the warfarin arm, the risk of stroke or systemic embolism across the trials (mean CHADS₂ score: C = congestive heart failure, H = hypertension, A = older than age 75 years, D = diabetes mellitus, S2 = prior stroke or history of transient ischemic attack) or primary versus secondary prevention, and type of populations used in the analysis. Kansal et al. [Kansal AR, Sharma M, Bradley-Kennedy C, et al. Dabigatran versus rivaroxaban for the prevention of stroke and systemic embolism in atrial fibrillation in Canada: comparative efficacy and cost-effectiveness. Thromb Haemost 2012;108:672–82] appropriately adjusted the ROCKET-AF TTR to match the RE-LY population on the basis of individual patient data. Meta-regressions are not expected to minimize confounding bias given limited data, whereas subgroup analyses had some impact on the point estimates for the treatment comparisons.ConclusionsResults of the synthesis studies were generally comparable and suggested that the NOACs had similar efficacy, although some differences were identified depending on the outcome. The extent to which differences in the distribution of TTR, CHADS₂ score, or primary versus secondary prevention biased the results remains unclear.     

Network Meta-Analysis: Development of a Three-Level Hierarchical Modeling Approach Incorporating Dose-Related Constraints

BackgroundNetwork meta-analysis (NMA) is commonly used in evidence synthesis; however, in situations in which there are a large number of treatment options, which may be subdivided into classes, and relatively few trials, NMAs produce considerable uncertainty in the estimated treatment effects, and consequently, identification of the most beneficial intervention remains inconclusive.ObjectiveTo develop and demonstrate the use of evidence synthesis methods to evaluate extensive treatment networks with a limited number of trials, making use of classes.MethodsUsing Bayesian Markov chain Monte Carlo methods, we build on the existing work of a random effects NMA to develop a three-level hierarchical NMA model that accounts for the exchangeability between treatments within the same class as well as for the residual between-study heterogeneity. We demonstrate the application of these methods to a continuous and binary outcome, using a motivating example of overactive bladder. We illustrate methods for incorporating ordering constraints in increasing doses, model selection, and assessing inconsistency between the direct and indirect evidence.ResultsThe methods were applied to a data set obtained from a systematic literature review of trials for overactive bladder, evaluating the mean reduction in incontinence episodes from baseline and the number of patients reporting one or more adverse events. The data set involved 72 trials comparing 34 interventions that were categorized into nine classes of interventions, including placebo.ConclusionsBayesian three-level hierarchical NMAs have the potential to increase the precision in the effect estimates while maintaining the interpretability of the individual interventions for decision making.     

The Effects of Model Misspecification in Unanchored Matching-Adjusted Indirect Comparison: Results of a Simulation Study

ObjectivesTo assess the performance of unanchored matching-adjusted indirect comparison (MAIC) by matching on first moments or higher moments in a cross-study comparisons under a variety of conditions. A secondary objective was to gauge the performance of the method relative to propensity score weighting (PSW).MethodsA simulation study was designed based on an oncology example, where MAIC was used to account for differences between a contemporary trial in which patients had more favorable characteristics and a historical control. A variety of scenarios were then tested varying the setup of the simulation study, including violating the implicit or explicit assumptions of MAIC.ResultsUnder ideal conditions and under a variety of scenarios, MAIC performed well (shown by a low mean absolute error [MAE]) and was unbiased (shown by a mean error [ME] of about zero). The performance of the method deteriorated where the matched characteristics had low explanatory power or there was poor overlap between studies. Only when important characteristics are not included in the matching did the method become biased (nonzero ME). Where the method showed poor performance, this was exaggerated if matching was also performed on the variance (ie, higher moments). Relative to PSW, MAIC provided similar results in most circumstances, although it exhibited slightly higher MAE and a higher chance of exaggerating bias.ConclusionsMAIC appears well suited to adjust for cross-trial comparisons provided the assumptions underpinning the model are met, with relatively little efficiency loss compared with PSW.     

Investigating Trends in the Quality of Reporting of Patient-Reported Outcomes in Oncology Over Time: Analysis of 631 Randomized Controlled Trials Published Between 2004 and 2019

ObjectivesIncomplete reporting of key information on patient-reported outcomes (PROs) in randomized controlled trials (RCTs) in oncology has been highlighted repeatedly as a major barrier to the use of study findings in clinical practice. We investigated whether the quality of reporting of PRO data in cancer RCTs has improved over the last 15 years.MethodsWe identified all cancer RCTs with PRO endpoints conducted across the most prevalent solid tumor types worldwide published between 2004 and 2019. The quality of PRO reporting was assessed using the International Society for Quality of Life Research recommended standards, which include important aspects related to assessment methodology, statistical analyses, and interpretation of data.ResultsWe assessed a total of 631 cancer RCTs in breast (n = 187), lung (n = 131), prostate (n = 120), colorectal (n = 107), and gynecological (n = 86) cancer. We observed a higher adherence to the International Society for Quality of Life Research reporting criteria in the more recently published studies. In a multivariable linear regression analysis, we observed a statistically significant improvement in the quality of PRO reporting over time (P<.001), and this relationship was independent of other measured confounding factors, such as sample size and study sponsorship. Overall, the quality of PRO reporting was higher for studies published after the publication of the Consolidated Standards of Reporting Trials-PRO Extension.ConclusionsThe quality of PRO reporting in cancer RCTs published in the last 15 years has improved significantly. Our findings are encouraging because better reporting of PRO results may translate into a greater impact of study findings on real-world practice.     

Matching-Adjusted Indirect Comparisons of Lorlatinib Versus Chemotherapy for Patients With Second-Line or Later Anaplastic Lymphoma Kinase–Positive Non–Small Cell Lung Cancer

ObjectivesThis study aimed to compare the relative efficacy of lorlatinib, an anaplastic lymphoma kinase–tyrosine kinase inhibitor, with chemotherapy, for patients with second-line or later advanced anaplastic lymphoma kinase–positive non–small cell lung cancer. The endpoints of interest were overall survival (OS) and progression-free survival (PFS).MethodsEvidence for lorlatinib was informed by the single-arm phase I/II trial B7461001. A systematic literature review (SLR) was performed to identify OS and PFS data for chemotherapy. Unanchored matching-adjusted indirect comparisons (MAICs) between lorlatinib and chemotherapy (pemetrexed/docetaxel, platinum-based, or systemic therapy) were performed.ResultsThe SLR identified 3 relevant studies reporting PFS. Lorlatinib was associated with a significant decrease in the hazard of progression versus the 2 types of chemotherapy assessed. For PFS, the MAIC of lorlatinib versus the combined treatment arm of docetaxel or pemetrexed resulted in an adjusted hazard ratio (HR) of 0.22 (95% confidence interval [CI] 0.15-0.31). When lorlatinib was compared with platinum-based chemotherapy through an MAIC, the adjusted HR for PFS was 0.40 (95% CI 0.29-0.55). An exploratory comparison was performed for OS with evidence for systemic therapy (assumed equivalent to chemotherapy) not identified in the SLR. Lorlatinib provided a significant decrease in hazard of death (OS) versus systemic therapy, with HRs ranging from 0.12 (95% CI 0.05-0.27) to 0.43 (95% CI 0.27-0.60).ConclusionsLorlatinib demonstrated a significant improvement in PFS compared with chemotherapy, although limitations in the analyses were identified. The evidence informing OS comparisons was highly limited but suggested benefit of lorlatinib compared with systemic therapy.     

Observational studies using propensity score analysis underestimated the effect sizes in critical care medicine

Background and ObjectivePropensity score (PS) analysis has been increasingly used in critical care medicine; however, its validation has not been systematically investigated. The present study aimed to compare effect sizes in PS-based observational studies vs. randomized controlled trials (RCTs) (or meta-analysis of RCTs).MethodsCritical care observational studies using PS were systematically searched in PubMed from inception to April 2013. Identified PS-based studies were matched to one or more RCTs in terms of population, intervention, comparison, and outcome. The effect sizes of experimental treatments were compared for PS-based studies vs. RCTs (or meta-analysis of RCTs) with sign test. Furthermore, ratio of odds ratio (ROR) was calculated from the interaction term of treatment × study type in a logistic regression model. A ROR < 1 indicates greater benefit for experimental treatment in RCTs compared with PS-based studies. RORs of each comparison were pooled by using meta-analytic approach with random-effects model.ResultsA total of 20 PS-based studies were identified and matched to RCTs. Twelve of the 20 comparisons showed greater beneficial effect for experimental treatment in RCTs than that in PS-based studies (sign test P = 0.503). The difference was statistically significant in four comparisons. ROR can be calculated from 13 comparisons, of which four showed significantly greater beneficial effect for experimental treatment in RCTs. The pooled ROR was 0.71 (95% CI: 0.63, 0.79; P = 0.002), suggesting that RCTs (or meta-analysis of RCTs) were more likely to report beneficial effect for the experimental treatment than PS-based studies. The result remained unchanged in sensitivity analysis and meta-regression.ConclusionIn critical care literature, PS-based observational study is likely to report less beneficial effect of experimental treatment compared with RCTs (or meta-analysis of RCTs).     

Measuring,Analyzing, and Presenting Work Productivity Loss in Randomized Controlled Trials: A Scoping Review

ObjectivesThis study aimed to conduct a scoping review of randomized controlled trials (RCTs) and investigate which work productivity loss outcomes were measured in these RCTs, how each outcome was measured and analyzed, and how the results for each outcome were presented.MethodsA systematic search was conducted from January 2010 to April 2020 from 2 databases: PubMed and Cochrane Central Register of Controlled Trials. Data on country, study population, disease focus, sample size, work productivity loss outcomes measured (absenteeism, presenteeism, employment status changes), and methods used to measure, report, and analyze each work productivity loss outcome were extracted and analyzed.ResultsWe found 435 studies measuring absenteeism or presenteeism, of which 155 studies (35.6%) measured both absenteeism and presenteeism and were included in our final review. Only 9 studies also measured employment status changes. The most used questionnaire was the Work Productivity and Activity Impairment Questionnaire. The analysis of absenteeism and presenteeism data was mostly done using regression models (n = 98, n = 98, respectively) for which a normal distribution was assumed (n = 77, n = 89, respectively). Absenteeism results were most often presented in time whereas presenteeism was commonly presented using a percent scale or score.ConclusionsThere is a lack of consensus on how to measure, analyze, and present work productivity loss outcomes in RCTs published in the past 10 years. The diversity of measurement, analysis, and presentation methods used in RCTs may make comparability challenging. There is a need for guidelines providing recommendations to standardize the comprehensiveness and the appropriateness of methods used to measure, analyze, and report work productivity loss in RCTs.     

Network geometry shows evidence sequestration for medical vs. surgical practices: treatments for basal cell carcinoma

ObjectivesBasal cell carcinoma (BCC) is the most common cancer with 2 million treatments per year with little evidence-based guidelines for treatment. There are three classes of interventions (surgical, destructive, and topical) for BCC, and this study aimed to determine whether there are preferences or avoidances in comparisons of different types of treatments for BCC in randomized controlled trials (RCTs).Study Design and SettingPubMed, Cochrane Central Registry of Clinical Trials, and ClinicalTrials.Gov were used to identify eligible published and registered ongoing RCTs.ResultsFifty-five trials (42 published and 13 registered trials) were identified. Only one unpublished registered trial compared a topical vs. a surgical intervention, and only one trial compared a topical vs. a destructive intervention. Conversely, 44 of the 55 trials compared interventions within the same treatment class and 9 of 55 trials compared surgical vs. destructive interventions. In most trials, selection of same-class comparators was not necessitated by the type of BCC lesions (nonaggressive superficial or nodular vs. aggressive, infiltrative, morpheic BCCs, P = 0.155) or their location (face vs. nonfacial, P = 0.137).ConclusionThis is the first time that an evaluation of network geometry is applied to address issues of comparisons between different families of interventions that belong to different specialties and practices (medical vs. surgical). Previous evaluations of homophily have addressed different families of interventions, in which all interventions are medical (drugs) and performed in the same health-care settings. The noncommunicating bodies of evidence between medical and surgical interventions that we document highlight a problem of unnecessary sequestration of the evidence and the corresponding health-care practices.     

Influenza vaccination for HIV-positive people: Systematic review and network meta-analysis

BackgroundPeople with Human Immunodeficiency Virus (HIV) are highly susceptible to influenza-related morbidity and mortality. In order to assess comparative efficacy of influenza vaccine strategies among HIV-positive people, we performed a systematic review and Bayesian network meta-analysis (NMA).MethodsIn this systematic review, we searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and CINAHL between 1946 and July 2015 for randomized controlled trials (RCTs) on influenza vaccines for HIV-positive adults reporting seroconversion or seroprotection outcomes. The NMAs were conducted within a Bayesian framework and logistic models were used for comparing the effect of the vaccine strategies on the two outcomes.ResultsA total of 1957 publications were identified, 143 were selected for full review, and 13 RCTs were included in our final analysis. Fourteen separate NMAs were conducted by outcomes, vaccine strain, and different outcome measurement timepoints. For example, compared with the 15 μg single vaccine strategy, the odds ratio was the highest for the adjuvant 7.5 μg booster strategy (2.99 [95% credible interval 1.18–7.66]) when comparing seroconversion for H1N1 at 14–41 days after the last dose of vaccination and for the 60 μg single strategy (2.33 [1.31–4.18]) when comparing seroconversion for strain B.ConclusionsThe adjuvant 7.5 μg booster and 60 μg single vaccine strategies provided better seroconversion and seroprotection outcomes. These findings have important implications for national and international guidelines for influenza vaccination for HIV-positive people and future research.     

Scoping Review of Randomized Trials With Discontinuation of Medicines in Older Adults

ObjectivesTo map the randomized trial evidence describing the feasibility of discontinuing active medications with potential adverse effects in older patients.DesignScoping review with systematic search of PubMed, Embase, and Cochrane Library.Setting and ParticipantsRandomized trials investigating discontinuation of a single medicine or medicine class in patients with mean age ≥65 years.MethodsWe extracted trial characteristics including study design and assessed bias. As proxies for the “feasibility of discontinuation,” we extracted the “dropout rate” and “disease recurrence rate.”ResultsWe identified 40 trials investigating discontinuation of symptomatic (n = 26), preventive (n = 6), or both preventive and symptomatic medicines (n = 8) against psychiatric (n = 10), neurologic (n = 9), musculoskeletal (n = 8), cardiovascular (n = 5), respiratory (n = 4), and urologic diseases (n = 4). Five discontinuation designs were used, 75% (30/40) of trials were placebo-controlled, and 48% (19/40) of trials had bias disfavoring discontinuation. The dropout rate was similar between the discontinuation group and the continuation group in 79% of the trials (30/38), whereas disease recurrence was similar in 72% (23/32) of the trials. In 42% (13/31) of trials reporting both dropout rate and disease recurrence rate, the differences between groups were statistically insignificant and less than 10%; these trials investigated discontinuation of cholinesterase inhibitors for Alzheimer's disease in various settings (n = 3), alendronate for osteoporosis (n = 3), glucosamine for osteoarthritis, lithium as adjunct for unipolar depression, statins for cardiovascular disease in patients with limited life expectancy, droxidopa for neurogenic orthostatic hypotension, tamsulosin for lower urinary tract symptoms, sertraline for major depressive episode, and fentanyl patch for low back or osteoarthritis pain.Conclusions and ImplicationsWe identified 40 randomized trials using a variety of designs investigating discontinuation of both symptomatic and preventive medicines in older patients. Discontinuation of medicines seems feasible for most of the investigated medicines. This scoping review can guide clinical practice and future trials on deprescribing.     

Searching for Indirect Evidence and Extending the Network of Studies for Network Meta-Analysis: Case Study in Venous Thromboembolic Events Prevention Following Elective Total Knee Replacement Surgery

ObjectiveTo evaluate the effect of study identification methods and network size on the relative effectiveness and cost-effectiveness of recommended pharmacological venous thromboembolic events (VTEs) prophylaxis for adult patients undergoing elective total knee replacement surgery in the United Kingdom.MethodsA stepwise literature search specifically designed to identify indirect evidence was conducted to extend the original clinical review from the latest National Institute for Health and Care Excellence (NICE) VTE technology appraisal. Different network sizes or network orders, based on the successive searches, informed three network meta-analyses (NMAs), which were compared with a replicated base case. The resulting comparative estimates were inputted in an economic model to investigate the effect of network size on cost-effectiveness probabilities.ResultsSearches increased the number of indirect comparisons between VTE interventions, progressively widening the relevant network of studies for NMA. Precision around mean relative treatment effects was increased as the network was extended from the base case to first-order NMA, but further extensions had limited effect. Cost-effectiveness analysis results were largely insensitive to variation in clinical inputs from the different NMA orders.ConclusionsNo standard methodology is currently recommended by NICE to identify the most relevant network of studies for NMA. Our study showed that optimizing the identification of studies for NMA can extend the evidence base for analysis and reduce the uncertainty in relative effectiveness estimates. Although in our example network extensions did not affect the acceptability of available treatments in VTE prevention based on cost-effectiveness results, it may in other applications.     

Variation in results from randomized,controlled trials: stochastic or systematic?

ObjectiveRandomized controlled trials (RCTs) are considered the highest grade of research evidence, yet properly conducted trials investigating the same association often yield conflicting results. Our objective was to assess whether variability in treatment protocols of RCTs investigating the same topic could explain distinct patterns of outcomes.Study Design and SettingA review of meta-analyses identified clinical topics involving RCTs with variable pharmacologic dosing and disparate outcomes. Topics were retained if at least two pairs of trials had results suggesting contradictory yet strong exposure–outcome associations.ResultsThe search yielded 6 clinical topics and 58 RCTs, and individual RCTs were classified into two groups, based on low and high dosages of the intervention. Aggregate odds ratios for studies in the low- and high-dose groups were often substantially discordant. For example, odds ratios were 1.76 (95% confidence interval [CI] = 1.02–3.03) for low-dose and 0.56 (95% CI = 0.31–1.03) for high-dose trials evaluating low-molecular weight heparin and pulmonary embolism. In an exploratory analysis, outcomes for low- and high-dose groups in the comparison arms of trials (including patients assigned to placebo) had statistically significant differences in four of five analyzable topics, suggesting differences in patient characteristics across trials.ConclusionConflicting results from RCTs can represent a spectrum of “real” outcomes for specific treatments. Such trials are best evaluated by considering concurrently both the validity of study design as well as the generalizability of patients and interventions involved.     

Evaluating Matching‐Adjusted Indirect Comparisons in Practice: A Case Study of Patients with Attention‐Deficit/Hyperactivity Disorder

Differences in patient characteristics across trials may bias efficacy estimates from indirect treatment comparisons. To address this issue, matching‐adjusted indirect comparison (MAIC) measures treatment efficacy after weighting individual patient data to match patient characteristics across trials. To date, however, there is no consensus on how best to implement MAIC. To address this issue, we applied MAIC to measure how two attention‐deficit/hyperactivity disorder (ADHD) treatments (guanfacine extended release and atomoxetine hydrochloride) affect patients' ADHD symptoms, as measured by the ADHD Rating Scale IV score. We tested MAIC sensitivity to: matched patient characteristics, matched statistical moments, weighting matrix, and placebo‐arm matching (i.e., matching on outcomes in the placebo arm). After applying MAIC, guanfacine and atomoxetine had similar reductions in ADHD symptoms (Δ: 0.4, p < 0.737). The results were similar for three of four sensitivity analyses. When we applied MAIC with placebo‐arm matching, however, guanfacine reduced symptoms more than atomoxetine (Δ: ?3.9, p < 0.004). We discuss the implication of this finding and advise MAIC practitioners to carefully consider the use of placebo‐arm matching, depending on the presence of residual confounding across trials. Copyright © 2016 John Wiley & Sons, Ltd.     

Management of Sarcopenia: A Network Meta-Analysis of Randomized Controlled Trials

ObjectiveThis study aimed to determine the comparative effectiveness of interventions in treatment of sarcopenia. The primary outcome was the measure of treatment effect on muscle mass, and secondary outcomes were the treatment effect on muscle strength and physical performance.DesignSystematic review and network meta-analysis (NMA).Setting and ParticipantsParticipants with sarcopenia receiving interventions targeting sarcopenia in any setting.MethodsData sources: Relevant RCTs were identified by a systematic search of several electronic databases, including CINAHL, Embase, MEDLINE, and the Cochrane Central Registry of Controlled Trials (CENTRAL) from January 1995 to July 2019. Duplicate title and abstract and full-text screening, data extraction, and risk of bias assessment were performed.Data extraction: All RCTs examining sarcopenia interventions [mixed exercise (combined aerobic and resistance exercise), aerobic exercise, resistance exercise, balance exercise, physical activity and protein or nutrition supplementation, acupuncture, whole-body vibration, protein supplement or interventions to increase protein intake, any nutritional intervention other than protein, and pharmacotherapy] were included. Comparators were standard care, placebo, or another intervention.Data synthesis: We performed Bayesian NMA; continuous outcome data were pooled using the standardized mean difference effect size. Interventions were ranked using the surface under the cumulative ranking curve (SUCRA) for each outcome.ResultsA total of 59 RCTs were included after screening of 4315 citations and 313 full-text articles. Network meta-analysis of muscle mass outcome (including 46 RCTs, 3649 participants, 11 interventions) suggested that mixed exercise were the most effective intervention (SUCRA = 93.94%) to increase muscle mass. Physical activity and protein or nutrition supplementation, and aerobic exercise were the most effective interventions to improve muscle strength and physical performance, respectively. Overall, mixed exercise is the most effective intervention in increasing muscle mass and was one of the 3 most effective interventions in increasing muscle strength and physical performance.Conclusions and ImplicationsMixed exercise and physical activity with nutritional supplementation are the most effective sarcopenia interventions. Most of the included studies have a high risk of bias. More robust RCTs are needed to increase the confidence of our NMA results and the quality of evidence.     

Management of Frailty: A Systematic Review and Network Meta-analysis of Randomized Controlled Trials

ObjectiveTo analyze and determine the comparative effectiveness of interventions targeting frailty prevention or treatment on frailty as a primary outcome and quality of life, cognition, depression, and adverse events as secondary outcomes.DesignSystematic review and network meta-analysis (NMA).MethodsData sources—Relevant randomized controlled trials (RCTs) were identified by a systematic search of several electronic databases including MEDLINE, EMBASE, CINAHL, and AMED. Duplicate title and abstract and full-text screening, data extraction, and risk of bias assessment were performed. Data extraction—All RCTs examining frailty interventions aimed to decrease frailty were included. Comparators were standard care, placebo, or another intervention. Data synthesis—We performed both standard pairwise meta-analysis and Bayesian NMA. Dichotomous outcome data were pooled using the odds ratio effect size, whereas continuous outcome data were pooled using the standardized mean difference (SMD) effect size. Interventions were ranked using the surface under the cumulative ranking curve (SUCRA) for each outcome. The quality of evidence was evaluated using the GRADE approach.ResultsA total of 66 RCTs were included after screening of 7090 citations and 749 full-text articles. NMA of frailty outcome (including 21 RCTs, 5262 participants, and 8 interventions) suggested that the physical activity intervention, when compared to placebo and standard care, was associated with reductions in frailty (SMD –0.92, 95% confidence interval ?1.55, ?0.29). According to SUCRA, physical activity intervention and physical activity plus nutritional supplementation were probably the most effective intervention (100% and 71% likelihood, respectively) to reduce frailty. Physical activity was probably the most effective or the second most effective interventions for all included outcomes.Conclusion and implicationsPhysical activity is one of the most effective frailty interventions. The quality of evidence of the current review is low and very low. More robust RCTs are needed to increase the confidence of our NMA results and the quality of evidence.     

State of use of Electronic Data Capture (EDC) tools in randomized controlled trials in India

ObjectivesElectronic data capture (EDC) tools can improve data quality gathered in clinical trials and may be more cost-effective. However, limited data is available on the adoption of EDC tools in randomized controlled trials (RCT) conducted in India. The objective of the current study was to determine the EDC adoption rate in RCTs in India.MethodsWe invited investigators of registered RCTs in India to an online survey. The questionnaire included questions on the use of EDC and features available. An EDC sophistication level (range 1 - 6) was computed. Respondents were also asked about barriers to the implementation of EDC. The EDC adoption rate (EAR) was defined as the proportion of clinical trials where EDC with a sophistication level of 2 or more was used. Multivariable logistic regression was used to identify factors that predicted EDC adoption.Results321 responses were received for 400 unique trials (participation rate of 21%), with an EAR of 27.5% (95% confidence intervals : 23.4% to 32.1%, n = 110). The number of sites influenced EDC adoption (odds ratio : 1.26, 95% CI : 1.12 - 1.47, p = 0.001) on multivariable analysis. EAR did not increase over time. The key barriers identified for not using an EDC were lack of technical support (170, 63.0%) and software cost (132, 48.9%).ConclusionsThe survey shows a low EAR in randomized trials registered in India. The barriers identified in the survey would need systematic solutions to improve the EAR in the future.