An evaluation of confidence intervals for a cumulative proportion to enable decisions at interim reviews of single-arm trials

BACKGROUND

Clinical trials often include interim analyses of the proportion of participants experiencing an event by a fixed time-point. A pre-specified proportion excluded from a corresponding confidence interval (CI) may lead an independent monitoring committee to recommend stopping the trial. Frequently this cumulative proportion is estimated by the Kaplan-Meier estimator with a Wald approximate CI, which may have coverage issues with small samples.

METHODS

We reviewed four alternative CI methods for cumulative proportions (Beta Product Confidence Procedure (BPCP), BPCP Mid P, Rothman-Wilson, Thomas-Grunkemeier) and two CI methods for simple proportions (Clopper-Pearson, Wilson). We conducted a simulation study comparing CI methods across true event proportions for 12 scenarios differentiated by sample sizes and censoring patterns. We re-analyzed interim data from A5340, a HIV cure trial considering the proportion of participants experiencing virologic failure.

RESULTS

Our simulation study highlights the lower and upper tail error probabilities for each CI method. Across scenarios, we found differences in the performance of lower versus upper bounds. No single method is always preferred. The upper bound of a Wald approximate CI performed reasonably with some error inflation, whereas the lower bound of the BPCP Mid P method performed well. For a trial design similar to A5340, we recommend BPCP Mid P.

CONCLUSIONS

The design of future single-arm interim analyses of event proportions should consider the most appropriate CI method based on the relevant bound, anticipated sample size and event proportion. Our paper summarizes available methods, demonstrates performance in a simulation study, and includes code for implementation.

Data monitoring committees in pediatric randomized controlled trials registered in ClinicalTrials.gov

BACKGROUND

Data monitoring committees advise on clinical trial conduct through appraisal of emerging data to ensure participant safety and scientific integrity. While consideration of their use is recommended for trials performed with vulnerable populations, previous research has shown that data monitoring committees are reported infrequently in publications of pediatric randomized controlled trials. We aimed to assess the frequency of reported data monitoring committee adoption in ClinicalTrials.gov registry records and to examine the influence of key trial characteristics.

METHODS

We conducted a cross-sectional data analysis of all randomized controlled trials performed exclusively in a pediatric population and registered in ClinicalTrials.gov between 2008 and 2021. We used the Access to Aggregate Content of ClinicalTrials.gov database to retrieve publicly available information on trial characteristics and data on safety results. Abstracted data included reported trial design and conduct parameters, population and intervention characteristics, reasons for prematurely halting, serious adverse events, and mortality outcomes. We performed descriptive analyses on the collected data and explored the influence of clinical, methodological, and operational trial characteristics on the reported adoption of data monitoring committees.

RESULTS

We identified 13,928 pediatric randomized controlled trial records, of which 39.7% reported adopting a data monitoring committee, 49.0% reported not adopting a data monitoring committee, and 11.3% did not answer on this item. While the number of registered pediatric trials has been increasing since 2008, we found no clear time trend in the reported adoption of data monitoring committees. Data monitoring committees were more common in multicenter trials (50.6% vs 36.9% for single-center), multinational trials (60.2% vs 38.7% for single-country), National Institutes of Health-funded (60.3% vs 40.1% for industry-funded or 37.5% for other funders), and placebo-controlled (47.6% vs 37.5% for other types of control groups). Data monitoring committees were also more common among trials enrolling younger participants, trials employing blinding techniques, and larger trials. Data monitoring committees were more common in trials with at least one serious adverse event (52.6% vs 38.4% for those without) as well as for trials with reported deaths (70.3% vs 38.9% for trials without reported deaths). In all, 4.9% were listed as halted prematurely, most often due to low accrual rates. Trials with a data monitoring committee were more often halted for reasons related to scientific data than trials without a data monitoring committee (15.7% vs 7.3%).

CONCLUSION

According to registry records, the use of data monitoring committees in pediatric randomized controlled trials was more frequent than previously reported in reviews of published trial reports. The use of data monitoring committees varied across key clinical and trial characteristics based on which their use is recommended. Data monitoring committees may still be underutilized in pediatric trials, and reporting of this item could be improved.

Exemptions and Limited Institutional Review Board Review: A Practical Look at the 2018 Common Rule Requirements for Exempt Research

Background: The revised Common Rule sought to modernize an outdated regulatory framework, provide clarity to the research community about the application of regulations, and reduce regulatory burden. From the advance notice of proposed rulemaking in 2011 to the implementation of the Final Rule, a significant amount of commentary and opinion was generated about the rules that govern most federally funded human subjects research.

Methods: This article provides insight into the changes to the regulatory framework for low-risk research, clarifies when exemptions can be applied, and explains the use of limited institutional review board (IRB) review.

Results: In attempting to fulfill the objectives of reducing regulatory burden, freeing IRB administrative resources, and protecting human subjects, the new regulations acknowledge low-risk research and privacy concerns, as well as the increased use of biospecimens. In the Final Rule, the Office for Human Research Protections updated the definition of human subject and expanded the exemption framework. The definition of human subject in the Final Rule includes biospecimens, and the new exemption framework includes expanded definitions, modifications to existing exemption categories, the creation of new categories, and the creation of a new concept called limited IRB review. The expanded exemption framework was designed to help alleviate the regulatory burdens of low-risk research.

Conclusion: Whether the revised regulations will meet the needs of the research community and human subject participants is unknown. While the revised Common Rule includes some welcome modifications and additions, the changes have also introduced new concepts that are not fully elucidated and have therefore introduced new ambiguities.