Bringing data monitoring committee charters into the sunlight.

Clinical trials investigating novel or high risk interventions, or studying vulnerable participants, often use a data monitoring committee to oversee the progress of the trial. The data monitoring committee serves both an ethical and a scientific function, by protecting the interests of trial participants while ensuring the integrity of the trial results. A data monitoring committee charter, which typically describes the procedures by which data monitoring committees operate, contains details about the data monitoring committee's organizational structure, membership, meeting frequency, sequential monitoring guidelines, and the overall contents of data monitoring committee reports for interim review. These charters, however, are generally not reviewed by outside entities and are rarely publicly available. The result is that a key component of trial oversight remains in the dark. We recommend that ClinicalTrials.gov modify its system to allow uploading of data monitoring committee charters, as is already possible for other important study documents and that clinical trialists take advantage of this opportunity to voluntarily upload the data monitoring committee charter for trials that have one. The resulting cache of publicly available data monitoring committee charters should provide important insights for those interested in a particular trial, as well as for meta-researchers who wish to understand and potentially improve how this important component of trial oversight is actually being applied.

Comparison of Availability of Trial Results in ClinicalTrials.gov and PubMed by Data Source and Funder Type.

This study examines the dissemination of trial results by data source (ie, ClinicalTrials.gov and PubMed) and funder type (ie, industry and nonindustry).

ClinicalTrials.gov and Drugs@FDA: A Comparison of Results Reporting for New Drug Approval Trials.

BACKGROUND: Pharmaceutical companies and other trial sponsors must submit certain trial results to ClinicalTrials.gov. The validity of these results is unclear. PURPOSE: To validate results posted on ClinicalTrials.gov against publicly available U.S. Food and Drug Administration (FDA) reviews on Drugs@FDA. DATA SOURCES: ClinicalTrials.gov (registry and results database) and Drugs@FDA (medical and statistical reviews). STUDY SELECTION: 100 parallel-group, randomized trials for new drug approvals (January 2013 to July 2014) with results posted on ClinicalTrials.gov (15 March 2015). DATA EXTRACTION: 2 assessors extracted, and another verified, the trial design, primary and secondary outcomes, adverse events, and deaths. RESULTS: Most trials were phase 3 (90%), double-blind (92%), and placebo-controlled (73%) and involved 32 drugs from 24 companies. Of 137 primary outcomes identified from ClinicalTrials.gov, 134 (98%) had corresponding data at Drugs@FDA, 130 (95%) had concordant definitions, and 107 (78%) had concordant results. Most differences were nominal (that is, relative difference <10%). Primary outcome results in 14 trials could not be validated. Of 1927 secondary outcomes from ClinicalTrials.gov, Drugs@FDA mentioned 1061 (55%) and included results data for 367 (19%). Of 96 trials with 1 or more serious adverse events in either source, 14 could be compared and 7 had discordant numbers of persons experiencing the adverse events. Of 62 trials with 1 or more deaths in either source, 25 could be compared and 17 were discordant. LIMITATION: Unknown generalizability to uncontrolled or crossover trial results. CONCLUSION: Primary outcome definitions and results were largely concordant between ClinicalTrials.gov and Drugs@FDA. Half the secondary outcomes, as well as serious events and deaths, could not be validated because Drugs@FDA includes only "key outcomes" for regulatory decision making and frequently includes only adverse event results aggregated across multiple trials. PRIMARY FUNDING SOURCE: National Library of Medicine.

Reporting discrepancies between the ClinicalTrials.gov results database and peer-reviewed publications.

BACKGROUND: ClinicalTrials.gov requires reporting of result summaries for many drug and device trials. PURPOSE: To evaluate the consistency of reporting of trials that are registered in the ClinicalTrials.gov results database and published in the literature. DATA SOURCES: ClinicalTrials.gov results database and matched publications identified through ClinicalTrials.gov and a manual search of 2 electronic databases. STUDY SELECTION: 10% random sample of phase 3 or 4 trials with results in the ClinicalTrials.gov results database, completed before 1 January 2009, with 2 or more groups. DATA EXTRACTION: One reviewer extracted data about trial design and results from the results database and matching publications. A subsample was independently verified. DATA SYNTHESIS: Of 110 trials with results, most were industry-sponsored, parallel-design drug studies. The most common inconsistency was the number of secondary outcome measures reported (80%). Sixteen trials (15%) reported the primary outcome description inconsistently, and 22 (20%) reported the primary outcome value inconsistently. Thirty-eight trials inconsistently reported the number of individuals with a serious adverse event (SAE); of these, 33 (87%) reported more SAEs in ClinicalTrials.gov. Among the 84 trials that reported SAEs in ClinicalTrials.gov, 11 publications did not mention SAEs, 5 reported them as zero or not occurring, and 21 reported a different number of SAEs. Among 29 trials that reported deaths in ClinicalTrials.gov, 28% differed from the matched publication. LIMITATION: Small sample that included earliest results posted to the database. CONCLUSION: Reporting discrepancies between the ClinicalTrials.gov results database and matching publications are common. Which source contains the more accurate account of results is unclear, although ClinicalTrials.gov may provide a more comprehensive description of adverse events than the publication. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.

The ClinicalTrials.gov results database--update and key issues.

BACKGROUND: The ClinicalTrials.gov trial registry was expanded in 2008 to include a database for reporting summary results. We summarize the structure and contents of the results database, provide an update of relevant policies, and show how the data can be used to gain insight into the state of clinical research. METHODS: We analyzed ClinicalTrials.gov data that were publicly available between September 2009 and September 2010. RESULTS: As of September 27, 2010, ClinicalTrials.gov received approximately 330 new and 2000 revised registrations each week, along with 30 new and 80 revised results submissions. We characterized the 79,413 registry and 2178 results of trial records available as of September 2010. From a sample cohort of results records, 78 of 150 (52%) had associated publications within 2 years after posting. Of results records available publicly, 20% reported more than two primary outcome measures and 5% reported more than five. Of a sample of 100 registry record outcome measures, 61% lacked specificity in describing the metric used in the planned analysis. In a sample of 700 results records, the mean number of different analysis populations per study group was 2.5 (median, 1; range, 1 to 25). Of these trials, 24% reported results for 90% or less of their participants. CONCLUSIONS: ClinicalTrials.gov provides access to study results not otherwise available to the public. Although the database allows examination of various aspects of ongoing and completed clinical trials, its ultimate usefulness depends on the research community to submit accurate, informative data.

Independent data monitoring committees: preparing a path for the future.

Independent data monitoring committees (IDMCs) were introduced to monitor patient safety and study conduct in randomized clinical trials (RCTs), but certain challenges regarding the utilization of IDMCs have developed. First, the roles and responsibilities of IDMCs are expanding, perhaps due to increasing trial complexity and heterogeneity regarding medical, ethical, legal, regulatory, and financial issues. Second, no standard for IDMC operating procedures exists, and there is uncertainty about who should determine standards and whether standards should vary with trial size and design. Third, considerable variability in communication pathways exist across IDMC interfaces with regulatory agencies, academic coordinating centers, and sponsors. Finally, there has been a substantial increase in the number of RCTs using IDMCs, yet there is no set of qualifications to help guide the training and development of the next generation of IDMC members. Recently, an expert panel of representatives from government, industry, and academia assembled at the Duke Clinical Research Institute to address these challenges and to develop recommendations for the future utilization of IDMCs in RCTs.

Deprioritization of Ongoing Clinical Trials.

To be ethical, clinical trials must exhibit a favorable risk-benefit balance at the time of their initiation. However, in some cases, the expected value of a study decreases while the study is ongoing, due to developments outside of the study itself, such as findings from other studies or an otherwise shifting evidence base. While such situations are acknowledged in the research community, they have not received sufficient attention, given the high costs of uninformative studies, both in material and human capital. In addition, the Covid-19 pandemic has exposed serious shortcomings with current approaches to monitoring studies for continued relevance and value. In this article, with reference to a case study from the Covid-19 pandemic, we identify and describe the importance and challenge of ensuring that clinical trials continue to exhibit scientific relevance and value once initiated. We explore the ethical dynamics of these situations and identify unresolved issues. While more empirical work is needed to ensure that proposed solutions to the issues are evidence based, we offer some provisional considerations that amount to a framework for approaching these challenging situations.

How to limit uninformative trials: Results from a Delphi working group.

To be justifiable, clinical trials must test novel hypotheses and produce informative results. However, many trials fail on this score. A Delphi process was used to establish consensus on 35 recommendations across five domains related to the role of scientific review in preventing uninformative trials.

Characterization of key information sections in informed consent forms posted on ClinicalTrials.gov.

Introduction: Recent revisions to the US Federal Common Rule governing human studies funded or conducted by the federal government require the provision of a "concise and focused" key information (KI) section in informed consent forms (ICFs). We performed a systematic study to characterize KI sections of ICFs for federally funded trials available on ClinicalTrials.gov. Methods: We downloaded ICFs posted on ClinicalTrials.gov for treatment trials initiated on or after the revised Common Rule effective date. Trial records (n = 102) were assessed by intervention type, study phase, recruitment status, and enrollment size. The ICFs and their KI sections, if present, were characterized by page length, word count, readability, topic, and formatting elements. Results: Of the 102 trial records, 76 had identifiable KI sections that were, on average, 10% of the total length of full ICF documents. KI readability grade level was not notably different from other sections of ICFs. Most KI sections were distinguished by section headers and included lists but contained few other formatting elements. Most KI sections included a subset of topics consistent with the basic elements of informed consent specified in the Common Rule. Conclusion: Many of the KI sections in the study sample aligned with practices suggested in the preamble to the revised Common Rule. Further, our results suggest that some KI sections were tailored in study-specific ways. Nevertheless, guidelines on how to write concise and comprehensible KI sections would improve the utility and readability of KI sections.