Jeroen P. Jansen

Interpreting Indirect Treatment Comparisons and Network Meta-Analysis for Health-Care Decision Making: Report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: Part 1

Evidence-based health-care decision making requires comparisons of all relevant competing interventions. In the absence of randomized, controlled trials involving a direct comparison of all treatments of interest, indirect treatment comparisons and network meta-analysis provide useful evidence for judiciously selecting the best choice(s) of treatment. Mixed treatment comparisons, a special case of network meta-analysis, combine direct and indirect evidence for particular pairwise comparisons, thereby synthesizing a greater share of the available evidence than a traditional meta-analysis. This report from the ISPOR Indirect Treatment Comparisons Good Research Practices Task Force provides guidance on the interpretation of indirect treatment comparisons and network meta-analysis to assist policymakers and health-care professionals in using its findings for decision making. We start with an overview of how networks of randomized, controlled trials allow multiple treatment comparisons of competing interventions. Next, an introduction to the synthesis of the available evidence with a focus on terminology, assumptions, validity, and statistical methods is provided, followed by advice on critically reviewing and interpreting an indirect treatment comparison or network meta-analysis to inform decision making. We finish with a discussion of what to do if there are no direct or indirect treatment comparisons of randomized, controlled trials possible and a health-care decision still needs to be made.

Conducting indirect-treatment-comparison and network-meta-analysis studies: Report of the ISPOR task force on indirect treatment comparisons good research practices: Part 2

Evidence-based health care decision making requires comparison of all relevant competing interventions. In the absence of randomized controlled trials involving a direct comparison of all treatments of interest, indirect treatment comparisons and network meta-analysis provide useful evidence for judiciously selecting the best treatment(s). Mixed treatment comparisons, a special case of network meta-analysis, combine direct evidence and indirect evidence for particular pairwise comparisons, thereby synthesizing a greater share of the available evidence than traditional meta-analysis. This report from the International Society for Pharmacoeconomics and Outcomes Research Indirect Treatment Comparisons Good Research Practices Task Force provides guidance on technical aspects of conducting network meta-analyses (our use of this term includes most methods that involve meta-analysis in the context of a network of evidence). We start with a discussion of strategies for developing networks of evidence. Next we briefly review assumptions of network meta-analysis. Then we focus on the statistical analysis of the data: objectives, models (fixed-effects and random-effects), frequentist versus Bayesian approaches, and model validation. A checklist highlights key components of network meta-analysis, and substantial examples illustrate indirect treatment comparisons (both frequentist and Bayesian approaches) and network meta-analysis. A further section discusses eight key areas for future research.

Bayesian Meta-Analysis of Multiple Treatment Comparisons: An Introduction to Mixed Treatment Comparisons

Recently, mixed treatment comparisons (MTC) have been presented as an extension of traditional meta-analysis by including multiple different pairwise comparisons across a range of different interventions. MTC allow for indirect comparisons and can therefore provide very useful information for clinical and reimbursement decision-making in the absence of head-to-head data. In this article, we provide an introductory overview of MTC illustrated with example analyses of different drug treatments in rheumatoid arthritis using a continuous patient-reported end point. As a background, we start with an overview of the traditional meta-analyses for pairwise trials, and the difference between a traditional approach and a Bayesian approach. Next, the Bayesian MTC for continuous outcomes are presented. We finish with a discussion of how MTC can best be presented in order to maximize acceptance by target audiences, i.e., clinicians and market access decision-makers.

Comparison of Weight Loss Among Named Diet Programs in Overweight and Obese Adults: A Meta-analysis

IMPORTANCE Many claims have been made regarding the superiority of one diet or another for inducing weight loss. Which diet is best remains unclear. OBJECTIVE To determine weight loss outcomes for popular diets based on diet class (macronutrient composition) and named diet. DATA SOURCES Search of 6 electronic databases: AMED, CDSR, CENTRAL, CINAHL, EMBASE, and MEDLINE from inception of each database to April 2014. STUDY SELECTION Overweight or obese adults (body mass index ≥25) randomized to a popular self-administered named diet and reporting weight or body mass index data at 3-month follow-up or longer. DATA EXTRACTION AND SYNTHESIS Two reviewers independently extracted data on populations, interventions, outcomes, risk of bias, and quality of evidence. A Bayesian framework was used to perform a series of random-effects network meta-analyses with meta-regression to estimate the relative effectiveness of diet classes and programs for change in weight and body mass index from baseline. Our analyses adjusted for behavioral support and exercise. MAIN OUTCOMES AND MEASURES Weight loss and body mass index at 6- and 12-month follow-up (±3 months for both periods). RESULTS Among 59 eligible articles reporting 48 unique randomized trials (including 7286 individuals) and compared with no diet, the largest weight loss was associated with low-carbohydrate diets (8.73 kg [95% credible interval {CI}, 7.27 to 10.20 kg] at 6-month follow-up and 7.25 kg [95% CI, 5.33 to 9.25 kg] at 12-month follow-up) and low-fat diets (7.99 kg [95% CI, 6.01 to 9.92 kg] at 6-month follow-up and 7.27 kg [95% CI, 5.26 to 9.34 kg] at 12-month follow-up). Weight loss differences between individual diets were minimal. For example, the Atkins diet resulted in a 1.71 kg greater weight loss than the Zone diet at 6-month follow-up. Between 6- and 12-month follow-up, the influence of behavioral support (3.23 kg [95% CI, 2.23 to 4.23 kg] at 6-month follow-up vs 1.08 kg [95% CI, -1.82 to 3.96 kg] at 12-month follow-up) and exercise (0.64 kg [95% CI, -0.35 to 1.66 kg] vs 2.13 kg [95% CI, 0.43 to 3.85 kg], respectively) on weight loss differed. CONCLUSIONS AND RELEVANCE Significant weight loss was observed with any low-carbohydrate or low-fat diet. Weight loss differences between individual named diets were small. This supports the practice of recommending any diet that a patient will adhere to in order to lose weight.

Is network meta-analysis as valid as standard pairwise meta-analysis? It all depends on the distribution of effect modifiers

BackgroundIn the last decade, network meta-analysis of randomized controlled trials has been introduced as an extension of pairwise meta-analysis. The advantage of network meta-analysis over standard pairwise meta-analysis is that it facilitates indirect comparisons of multiple interventions that have not been studied in a head-to-head fashion. Although assumptions underlying pairwise meta-analyses are well understood, those concerning network meta-analyses are perceived to be more complex and prone to misinterpretation.DiscussionIn this paper, we aim to provide a basic explanation when network meta-analysis is as valid as pairwise meta-analysis. We focus on the primary role of effect modifiers, which are study and patient characteristics associated with treatment effects. Because network meta-analysis includes different trials comparing different interventions, the distribution of effect modifiers cannot only vary across studies for a particular comparison (as with standard pairwise meta-analysis, causing heterogeneity), but also between comparisons (causing inconsistency). If there is an imbalance in the distribution of effect modifiers between different types of direct comparisons, the related indirect comparisons will be biased. If it can be assumed that this is not the case, network meta-analysis is as valid as pairwise meta-analysis.SummaryThe validity of network meta-analysis is based on the underlying assumption that there is no imbalance in the distribution of effect modifiers across the different types of direct treatment comparisons, regardless of the structure of the evidence network.

Indirect Treatment Comparison/Network Meta-Analysis Study Questionnaire to Assess Relevance and Credibility to Inform Health Care Decision Making: An ISPOR-AMCP-NPC Good Practice Task Force Report

Despite the great realized or potential value of network meta-analysis of randomized controlled trial evidence to inform health care decision making, many decision makers might not be familiar with these techniques. The Task Force developed a consensus-based 26-item questionnaire to help decision makers assess the relevance and credibility of indirect treatment comparisons and network meta-analysis to help inform health care decision making. The relevance domain of the questionnaire (4 questions) calls for assessments about the applicability of network meta-analysis results to the setting of interest to the decision maker. The remaining 22 questions belong to an overall credibility domain and pertain to assessments about whether the network meta-analysis results provide a valid answer to the question they are designed to answer by examining 1) the used evidence base, 2) analysis methods, 3) reporting quality and transparency, 4) interpretation of findings, and 5) conflicts of interest. The questionnaire aims to help readers of network meta-analysis opine about their confidence in the credibility and applicability of the results of a network meta-analysis, and help make decision makers aware of the subtleties involved in the analysis of networks of randomized trial evidence. It is anticipated that user feedback will permit periodic evaluation and modification of the questionnaire.

Self-monitoring of glucose in type 2 diabetes mellitus:a Bayesian meta-analysis of direct and indirect comparisons

ABSTRACT Objective: To evaluate the relative effectiveness of interventions with self-monitoring blood glucose and self-monitoring of urine glucose, versus interventions without self-monitoring, in terms of HbA1c reductions in type 2 diabetes mellitus. Methods: Thirteen published full reports on randomised controlled trials investigating the effects of self-monitoring glucose were identified by a systematic search of Medline, Embase, the Cochrane Library (1966–Nov 2005) and previous reviews. Three types of studies were included: self-monitoring of blood glucose versus no self-monitoring, self-monitoring of blood glucose versus self-monitoring of urine glucose and self-monitoring of blood glucose with regular feedback versus monitoring without feedback. The internal validity of studies was assessed systematically by two reviewers, using 13 criteria of a validated list. Results from the three types of studies were analysed simultaneously with a Bayesian meta-analysis of direct and indirect comparisons. Results: Adjusted for baseline HbA1c level and internal validity, interventions with self-monitoring of blood glucose showed a reduction in HbA1c of 0.40 percentage-points (%) (95% credible interval [CrI] 0.07 to 0.70%) in comparison to interventions without self-monitoring. Regular feedback more than doubled the HbA1c reduction. Self-monitoring of urine glucose showed comparable results to interventions without self-monitoring (0.02% decrease in HbA1c; 95% CrI –0.62 to 0.70%). There is a 88% probability that interventions with self-monitoring blood glucose are more effective than interventions with urine glucose monitoring (relative reduction in HbA1c is 0.38%, 95% CrI –0.30 to 1.00%). Conclusion: The randomized clinical trials performed to date provided positive results on the effectiveness of interventions with self-monitoring of blood glucose in type 2 diabetes mellitus. Regular medical feedback of the monitored HbA1c levels is important. Furthermore, self-monitoring of blood glucose is likely to be more effective than self-monitoring of urine glucose.

Dose-response relations between occupational exposures to physical and psychosocial factors and the risk of low back pain

Aims: To assess dose-response relations between occupational exposures to physical and psychosocial factors and the risk of low back pain. Methods: A cohort of 523 subjects, working in nursing homes and homes for the elderly, was followed prospectively for one year. Physical load for different occupations was assessed by quantitative observations at the workplace. Information on low back pain and other factors was gathered with questionnaires administered at baseline and at one year. Two outcome measures of low back pain incidence were used: any new episode of pain lasting for at least a few hours during follow up (LBP); and any new episode of disabling pain that interfered with daily activities during follow up (LBP/D). Hierarchical regression analysis with a spline function was used to estimate dose-response relations. Results: The risk of LBP was not associated with physical factors, controlling for confounders; but this outcome was inversely associated with age and weakly, though imprecisely, associated with two psychosocial factors—low decision authority and high work demands. In contrast, the risk of LBP/D was positively associated with age and not associated with the psychosocial factors. Trunk flexion over 45 degrees was monotonically associated with the risk of LBP/D; the estimated relative risk was 3.18 (95% CI 1.13 to 9.00) for 1 hour and 45 minutes of bending per week (90th centile), relative to 30 minutes per week. The hierarchical estimates of effect were more stable than were the maximum likelihood estimates. Conclusion: Occupational exposure to trunk flexion over 45 degrees appears to be a risk factor for low back pain with disability among persons employed in nursing homes and homes for the elderly in the Netherlands.

Indirect comparison of tocilizumab and other biologic agents in patients with rheumatoid arthritis and inadequate response to disease-modifying antirheumatic drugs.

OBJECTIVES To compare the patterns of American College of Rheumatology (ACR) response between tocilizumab and other biologic agents in patients with rheumatoid arthritis who have inadequate response to disease-modifying antirheumatic drugs (DMARD-IR). METHODS Systematic literature review identified similarly designed double-blind, randomized, placebo-controlled trials over an 18-year period that investigated the effectiveness of abatacept (2), rituximab (2), and TNF-alpha inhibitors etanercept, infliximab, and adalimumab (11) in DMARD-IR patients; data from 3 placebo-controlled, phase 3 trials for tocilizumab, a newly developed IL-6 inhibitor, were included. The endpoint of interest was ACR20/50/70 response criteria at 24 to 30 weeks. Results were analyzed simultaneously using Bayesian mixed-treatment comparison techniques. Nonoverlapping ACR response rates (ACR70) for each agent were compared among treatments to identify differences in ACR response pattern. Separate analyses of overlapping ACR20/50/70 responses were conducted to identify the source of any differences. Results were expressed as relative risk of ACR20/50/70 response and associated 95% credible interval (CrI). RESULTS Patterns across nonoverlapping ACR response levels varied significantly across treatments. In subsequent analyses, the effectiveness of tocilizumab appeared to be comparable to that of other biologic agents for ACR20 and ACR50 responses but greater for ACR70. Specifically, tocilizumab had greater ACR70 responses than both TNF-alpha inhibitors (relative risk = 1.8; CrI = 1.2, 2.6) and abatacept (relative risk = 2.0; CrI = 1.3, 3.1). CONCLUSIONS Among DMARD-IR patients, tocilizumab shows a pattern of response that differs from that of other biologic agents. Post-hoc analyses suggest that the difference lies in a higher likelihood of ACR70 response with tocilizumab.

Treatment of Ureteral and Renal Stones: A Systematic Review and Meta-Analysis of Randomized, Controlled Trials

PURPOSE We compared the clinical outcomes of patients with ureteral or renal stones treated with ureteroscopy, shock wave lithotripsy using HM3 (Dornier®) and nonHM3 lithotripters, and percutaneous nephrolithotomy. MATERIALS AND METHODS A systematic literature search identified 6, 4 and 3 randomized, controlled trials of treatment of distal and proximal ureteral stones, and renal stones, respectively, published between 1995 and 2010. Overall stone-free, re-treatment and complication rates were calculated by meta-analytical techniques. RESULTS Based on the randomized, controlled trials evaluated the treatment of distal ureteral stones with semirigid ureteroscopy showed a 55% greater probability (pooled RR 1.55, 95% CI 1.13-2.56) of stone-free status at the initial assessment than treatment with shock wave lithotripsy. Patients treated with semirigid ureteroscopy were also less likely to require re-treatment than those treated with shock wave lithotripsy (nonHM3) (RR 0.14, 95% CI 0.08-0.23). The risk of complications was no different between the 2 modalities. Only 2 of the 4 randomized, controlled trials identified for proximal ureteral stones evaluated flexible ureteroscopy and each focused specifically on the treatment of stones 1.5 cm or greater, limiting their clinical relevance. The degree of heterogeneity among the studies evaluating renal stones was so great that it precluded any meaningful comparison. CONCLUSIONS Semirigid ureteroscopy is more efficacious than shock wave lithotripsy for distal ureteral stones. To our knowledge there are no relevant randomized, controlled trials of flexible ureteroscopy treatment of proximal ureteral calculi of a size commonly noted in the clinical setting. Collectively the comparative effectiveness of ureteroscopy and shock wave lithotripsy for proximal ureteral and renal calculi is poorly characterized with no meaningful published studies.