Justification and reporting of subgroup analyses were lacking or inadequate in randomized controlled trials

Fan, Jingchun; Bachmann, Max

doi:10.1016/j.jclinepi.2018.12.009

Cited by 25 publications

(26 citation statements)

References 32 publications

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“…Thus, our findings in the addiction clinical trial literature fitted within the broader context . In addition to our previous studies, several others suggest that selective reporting of outcomes and analyses is common in clinical trials. Beyond selective outcome reporting, our study shows that a significant proportion of RCTs in our sample were registered after patient enrollment ended or were not registered at all.…”

Section: Discussionsupporting

confidence: 77%

Evaluation of selective outcome reporting and trial registration practices among addiction clinical trials

et al. 2020

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Background and Aims Selective outcome reporting occurs when trialists pre-specify primary and secondary outcomes during trial planning but alter the definitions in the published report. Here, we investigate selective outcome reporting in published addiction randomized controlled trials (RCTs) and evaluate whether particular funding sources are associated with an increased likelihood of selective outcome reporting. Design We conducted a cross-sectional study of published addiction clinical trials. A PubMed search was performed to identify RCTs in addiction journals from 2013 to 2017. Included studies used a randomized design to address one of the following topics: (1) drug, alcohol and tobacco addiction prevention, (2) stabilization following excessive use of a substance, (3) relapse prevention or (4) recovery maintenance.Setting Single-center, medical research institution. Participants Our sample included 162 RCTs that were prospectively registered with a clearly defined primary outcome. Measurement We extracted the following items from addiction RCTs: journal, funding source, trial registry number (if included), sample size, dates of subject enrollment, whether primary and secondary outcomes were denoted, all published outcomes, P-value for all outcomes and whether authors mentioned any deviations from the trial protocol as it related to RCT outcomes. Findings In total, 47 of 162 RCTs (29.0%) had at least one major discrepancy between the trial registry and published RCT. Overall, these 47 RCTs included 54 major discrepancies. The most common major discrepancy was demotion of a primary registered outcome (19/54, 35.2%). The majority of RCTs (132/162, 81.5%) were funded from public sources. Additionally, 166 RCTs were excluded from our sample because registration could not be confirmed. Conclusions There is evidence suggestive of selective outcome reporting in addiction randomized controlled trials (RCTs). The most common major discrepancies pertained to the primary outcome.

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Section: Discussionsupporting

confidence: 77%

Evaluation of selective outcome reporting and trial registration practices among addiction clinical trials

et al. 2020

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“…while the design effect for testing treatment effect heterogeneity with respect to an individual-level covariate is implied from Equations (11) and (15),…”

Section: Basic Setting With One Covariatementioning

confidence: 99%

“…Then given the value of n, we simulate individual-level outcomes Y ij from model (3), where we choose 2 = 0.25 and 3 = 0.1. As we have explained in Section 3.1, these regression parameters are ancillary to sample size determination as they are not part of Equation (11). A total of 5000 data replicates are generated for each scenario, and the linear mixed effects model (3) is fit to each data set using the restricted maximum likelihood estimation (REML).…”

Section: Simulation Designmentioning

confidence: 99%

“…Systematic reviews of individually randomized trials suggest that HTE tends to be overlooked and inadequately reported. [9][10][11] In particular, the sample size estimates provided in the design stage are usually specific to testing the OTE in the study population, and it is unknown whether the trial has adequate power to detect the HTE. Furthermore, separate subgroup analyses are frequently conducted in an ad hoc fashion and could involve multiple comparisons that are subject to false positive results.…”

Section: Introductionmentioning

confidence: 99%

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Sample size requirements for detecting treatment effect heterogeneity in cluster randomized trials

Yang

Li²,

Starks

et al. 2020

Statistics in Medicine

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Cluster randomized trials (CRTs) refer to experiments with randomization carried out at the cluster or the group level. While numerous statistical methods have been developed for the design and analysis of CRTs, most of the existing methods focused on testing the overall treatment effect across the population characteristics, with few discussions on the differential treatment effect among subpopulations. In addition, the sample size and power requirements for detecting differential treatment effect in CRTs remain unclear, but are helpful for studies planned with such an objective. In this article, we develop a new sample size formula for detecting treatment effect heterogeneity in two-level CRTs for continuous outcomes, continuous or binary covariates measured at cluster or individual level. We also investigate the roles of two intraclass correlation coefficients (ICCs): the adjusted ICC for the outcome of interest and the marginal ICC for the covariate of interest. We further derive a closed-form design effect formula to facilitate the application of the proposed method, and provide extensions to accommodate multiple covariates. Extensive simulations are carried out to validate the proposed formula in finite samples. We find that the empirical power agrees well with the prediction across a range of parameter constellations, when data are analyzed by a linear mixed effects model with a treatment-by-covariate interaction. Finally, we use data from the HF-ACTION study to illustrate the proposed sample size procedure for detecting heterogeneous treatment effects.

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“…However, subgroup analyses are subject to multiple methodological challenges which can complicate their interpretation, including increased risks of type I error due to multiple testing and low statistical power [20]. Some reviews have found that subgroup analyses are often poorly justified, infrequently pre-specified, and inadequately reported [21]. While such challenges may seem to discourage their use, lack of disaggregation or descriptive detail means that judgments about the policy relevance of the evidence to people who live with social disadvantage may be difficult for decision-makers who are using the evidence to inform and implement policies, programs, or individual patient care.…”

Section: Introductionmentioning

confidence: 99%

Reporting of health equity considerations in cluster and individually randomized trials

Petkovic

Jull

Yoganathan

et al. 2020

Trials

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Background: The randomized controlled trial (RCT) is considered the gold standard study design to inform decisions about the effectiveness of interventions. However, a common limitation is inadequate reporting of the applicability of the intervention and trial results for people who are "socially disadvantaged" and this can affect policy-makers' decisions. We previously developed a framework for identifying health-equity-relevant trials, along with a reporting guideline for transparent reporting. In this study, we provide a descriptive assessment of healthequity considerations in 200 randomly sampled equity-relevant trials. Methods: We developed a search strategy to identify health-equity-relevant trials published between 2013 and 2015. We randomly sorted the 4316 records identified by the search and screened studies until 100 individually randomized (RCTs) and 100 cluster randomized controlled trials (CRTs) were identified. We developed and pilottested a data extraction form based on our initial work, to inform the development of our reporting guideline for equity-relevant randomized trials. Results: In total, 39 trials (20%) were conducted in a low-and middle-income country and 157 trials (79%) in a high-income country focused on socially disadvantaged populations (78% CRTs, 79% RCTs). Seventy-four trials (37%) reported a subgroup analysis across a population characteristic associated with disadvantage (25% CRT, 49% RCTs), with 19% of included studies reporting subgroup analyses across sex, 9% across race/ethnicity/culture, and 4% across socioeconomic status. No subgroup analyses were reported for place of residence, occupation, religion, education, or social capital. One hundred and forty-one trials (71%) discussed the applicability of their results to one or more socially disadvantaged populations (68% of CRT, 73% of RCT). Discussion: In this set of trials, selected for their relevance to health equity, data that were disaggregated for socially disadvantaged populations were rarely reported. We found that even when the data are available, opportunities to analyze health-equity considerations are frequently missed. The recently published equity extension of the Consolidated Reporting Standards for Randomized Trials (CONSORT-Equity) may help improve delineation of hypotheses related to socially disadvantaged populations, and transparency and completeness of reporting of health-equity considerations in RCTs. This study can serve as a baseline assessment of the reporting of equity considerations.

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Justification and reporting of subgroup analyses were lacking or inadequate in randomized controlled trials

Cited by 25 publications

References 32 publications

Evaluation of selective outcome reporting and trial registration practices among addiction clinical trials

Evaluation of selective outcome reporting and trial registration practices among addiction clinical trials

Sample size requirements for detecting treatment effect heterogeneity in cluster randomized trials

Reporting of health equity considerations in cluster and individually randomized trials

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