Dataset Information

Departures from community equipoise may lead to incorrect inference in randomized trials.

ABSTRACT:

Objective

To assess the impact of selective enrollment on the results of randomized controlled trials (RCTs).

Study design and setting

We simulated an RCT of arthroscopic partial meniscectomy vs. nonoperative therapy in patients with meniscal tear and osteoarthritis (OA). We estimated efficacy with the risk ratio (RR) comparing the likelihood of clinically important improvement after surgery with that after nonoperative therapy. We assumed that efficacy differs by extent of OA. We simulated four scenarios: (1) nonselective enrollment; (2) higher likelihood of enrolling subjects with mild OA; (3) higher likelihood of enrolling subjects with severe OA; (4) much higher likelihood of enrolling subjects with severe OA. For each scenario, we simulated 100 trials with sample size 340.

Results

With nonselective enrollment, reflecting community equipoise, the results in 100 trials were consistent with those in the underlying population (mean RR: 1.87; 95% confidence interval [95% CI]: 1.57, 2.14). Selective enrollment of subjects with much higher likelihood of severe OA resulted in 28% lower efficacy of surgery (mean RR: 1.34; 95% CI: 0.93, 2.15), with 95% CI containing the true efficacy in just 25% of trials and empirical power of 44%.

Conclusion

Selective enrollment with respect to factors associated with efficacy may affect trial results and lead to inaccurate conclusions.

SUBMITTER: Katz JN

PROVIDER: S-EPMC2958234 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

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Publications

Departures from community equipoise may lead to incorrect inference in randomized trials.

Katz Jeffrey N JN Wright John J Levy Bruce A BA Baron John A JA Losina Elena E

Journal of clinical epidemiology 20100717 3

<h4>Objective</h4>To assess the impact of selective enrollment on the results of randomized controlled trials (RCTs).<h4>Study design and setting</h4>We simulated an RCT of arthroscopic partial meniscectomy vs. nonoperative therapy in patients with meniscal tear and osteoarthritis (OA). We estimated efficacy with the risk ratio (RR) comparing the likelihood of clinically important improvement after surgery with that after nonoperative therapy. We assumed that efficacy differs by extent of OA. We ...[more]

PMID: 20638236

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Project description:Understanding the evolutionary impacts of harvest on fish populations is important for informing fisheries management and conservation and has become a growing research topic over the last decade. However, the dynamics of fish populations are highly complex, and phenotypes can be influenced by many biotic and abiotic factors. Therefore, it is vital to collect robust data and explore multiple alternative hypotheses before concluding that fish populations are influenced by harvest. In their recently published manuscript, Bowles et al, Evolutionary Applications, 13(6):1128 conducted age/growth and genomic analysis of walleye (Sander vitreus) populations sampled 13-15 years (1-2.5 generations) apart and hypothesized that observed phenotypic and genomic changes in this time period were likely due to harvest. Specifically, Bowles et al. (2020) documented differential declines in size-at-age in three exploited walleye populations compared to a separate, but presumably less-exploited, reference population. Additionally, they documented population genetic differentiation in one population pair, homogenization in another, and outlier loci putatively under selection across time points. Based on their phenotypic and genetic results, they hypothesized that selective harvest had led to fisheries-induced evolution (referred to as nascent changes) in the exploited populations in as little as 1-2.5 generations. We re-analyzed their data and found that (a) sizes declined across both exploited and reference populations during the time period studied and (b) observed genomic differentiation in their study was the result of inadequate data filtering, including retaining individuals with high amounts of missing data and retaining potentially undersplit and oversplit loci that created false signals of differentiation between time points. This re-analysis did not provide evidence for phenotypic or genetic changes attributable to harvest in any of the study populations, contrasting the hypotheses presented by Bowles et al. (2020). Our comment highlights the potential pitfalls associated with conducting age/growth analyses with low sample sizes and inadequately filtering genomic datasets.

Dataset Information

Departures from community equipoise may lead to incorrect inference in randomized trials.

Objective

Study design and setting

Results

Conclusion

Publications

Departures from community equipoise may lead to incorrect inference in randomized trials.

Similar Datasets

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