Prespecification of subgroup analyses and examination of treatment-subgroup interactions in cancer individual participant data meta-analyses are suboptimal

Description of subgroup reporting in clinical trials of chronic diseases: a meta-epidemiological study

INTRODUCTION

In trials, subgroup analyses are used to examine whether treatment effects differ by important patient characteristics. However, which subgroups are most commonly reported has not been comprehensively described.

DESIGN AND SETTINGS

Using a set of trials identified from the US clinical trials register (ClinicalTrials.gov), we describe every reported subgroup for a range of conditions and drug classes.

METHODS

We obtained trial characteristics from ClinicalTrials.gov via the Aggregate Analysis of ClinicalTrials.gov database. We subsequently obtained all corresponding PubMed-indexed papers and screened these for subgroup reporting. Tables and text for reported subgroups were extracted and standardised using Medical Subject Headings and WHO Anatomical Therapeutic Chemical codes. Via logistic and Poisson regression models we identified independent predictors of result reporting (any vs none) and subgroup reporting (any vs none and counts). We then summarised subgroup reporting by index condition and presented all subgroups for all trials via a web-based interactive heatmap (https://ihwph-hehta.shinyapps.io/subgroup_reporting_app/).

RESULTS

Among 2235 eligible trials, 23% (524 trials) reported subgroups. Follow-up time (OR, 95%CI: 1.13, 1.04-1.24), enrolment (per 10-fold increment, 3.48, 2.25-5.47), trial starting year (1.07, 1.03-1.11) and specific index conditions (eg, hypercholesterolaemia, hypertension, taking asthma as the reference, OR ranged from 0.15 to 10.44), predicted reporting, sponsoring source and number of arms did not. Results were similar on modelling any result reporting (except number of arms, 1.42, 1.15-1.74) and the total number of subgroups. Age (51%), gender (45%), racial group (28%) were the most frequently reported subgroups. Characteristics related to the index condition (severity/duration/types etc) were frequently reported (eg, 69% of myocardial infarction trials reported on its severity/duration/types). However, reporting on comorbidity/frailty (five trials) and mental health (four trials) was rare.

CONCLUSION

Other than age, sex, race ethnicity or geographic location and characteristics related to the index condition, information on variation in treatment effects is sparse.

PROSPERO REGISTRATION NUMBER

CRD42018048202.

Nonlinear effects and effect modification at the participant-level in IPD meta-analysis part 2: methodological guidance is available

OBJECTIVES

To review methodological guidance for nonlinear covariate-outcome associations (NL), and linear effect modification and nonlinear effect modification (LEM and NLEM) at the participant level in individual participant data meta-analyses (IPDMAs) and their power requirements.

STUDY DESIGN AND SETTING

We searched Medline, Embase, Web of Science, Scopus, PsycINFO and the Cochrane Library to identify methodology publications on IPDMA of LEM, NL or NLEM (PROSPERO CRD42019126768).

RESULTS

Through screening 6,466 records we identified 54 potential articles of which 23 full texts were relevant. Nine further relevant publications were published before or after the literature search and were added. Of these 32 references, 21 articles considered LEM, 6 articles NL or NLEM and 6 articles described sample size calculations. A book described all four. Sample size may be calculated through simulation or closed form. Assessments of LEM or NLEM at the participant level need to be based on within-trial information alone. Nonlinearity (NL or NLEM) can be modeled using polynomials or splines to avoid categorization.

CONCLUSION

Detailed methodological guidance on IPDMA of effect modification at participant-level is available. However, methodology papers for sample size and nonlinearity are rarer and may not cover all scenarios. On these aspects, further guidance is needed.

Reporting quality and risk of bias of Cochrane individual participant data meta-analyses: A cross-sectional study

OBJECTIVES

This study aimed to assess the reporting quality and risk of bias of Cochrane individual participant data meta-analyses (IPD-MAs).

METHODS

We searched the Cochrane Library and identified the Cochrane IPD-MAs. We used the Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data (PRISMA-IPD) assessed the reporting quality of included Cochrane IPD- MAs, and the Risk Of Bias In Systematic reviews (ROBIS) tool was used to assess the risk of bias. We performed stratified and correlation analyses to explore factors affecting the quality.

RESULTS

Forty-six Cochrane IPD-MAs were included in our study. Twenty-six Cochrane IPD-MAs (56.5%) had statistical or epidemiological authors involved, and 31 (67.4%) contained only IPD data. Thirty-five studies (76.1%) did not report whether they used 1-stage or 2-stage methods, and forty (87.0%) did not report the statistical techniques used for missing participant data. We found that the entire compliance reported PRISMA-IPD items of Cochrane IPD-MAs published after 2015 (n = 18; Mean ± SD: 26.61 ± 2.75) was higher than those studies published in 2015 and before (n = 28; Mean ± SD: 22.61 ± 4.73), the difference was statistically significant (p = 0.002). A strong positive correlation was found between the fully reported PRISMA-IPD items and fully accordance ROBIS items (Spearman's: ρ = 0.653, p < 0.001).

CONCLUSIONS

The quality of Cochrane IPD-MAs is not high, especially in the reporting of statistical methods. There was room for further improvement in IPD retrieval, IPD integrity and statistical analyses.

Progress and challenges of network meta-analysis

In the past years, network meta-analysis (NMA) has been widely used among clinicians, guideline makers, and health technology assessment agencies and has played an important role in clinical decision-making and guideline development. To inform further development of NMAs, we conducted a bibliometric analysis to assess the current status of published NMA methodological studies, summarized the methodological progress of seven types of NMAs, and discussed the current challenges of NMAs.