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Data Monitoring Committees (DMCs) have the important task to protect the safety of current and future patients during the conduct of a clinical study. Unfortunately, their work is often made difficult by voluminous DMC reports that are poorly structured and difficult to digest. In this article, we suggest improved solutions. Starting from a principled approach and building upon previous proposals, we offer concrete and easily understood displays, including related computer code. While leveraging modern tools, the most important is that these displays support the DMC’s workflow in answering the relevant questions of interest. We hope that the adoption of these proposals can ease the task of DMCs, and importantly, lead to better decision-making for the benefit of patients.

Emeritus Editor-in-Chief, Richard Shader, published 2 editorials in 2014 to state that Clinical Therapeutics’ would no longer consider simple innovator vs generic bioequivalence studies for publication and would require a rationale for the choice of agents when submitting drug–drug interaction studies for consideration. The intervening decade of developments in this field provides an opportunity to comment on these trends. Lewis Scheiner anchors the subsequent discussion in a “Learn and Confirm” super-structure of thinking about the goals of early development of pharmaceutical agents. Subsequent experience with newer agents that are focused on immunological targets has led to a shift from the simple No Observable Effect Level (NOEL) model to the Minimal Anticipated Biological Effect Level (MABEL) model for biologically focused effects to assess pre-clinical data in guiding the selection of a starting dose for First-in-Human studies. The primary tasks of Phase I activities are to describe the pharmacokinetics (determination of absorption, distribution, metabolism, and excretion) and essential pharmacodynamics (the dose correlation with the physiological responses, plus any untoward effects, including idiosyncratic responses) keeping in mind reporting requirements. Other Phase I activities usually conducted later in the development cycle include evaluation of drug interactions with food and other pharmaceutical agents and thorough QT studies. Phase I studies have been evolving in response to the unrelenting pressures to improve access and efficiencies in time, cost, and effort. Changes have been occurring in the characteristics of the participating populations, the starting dose, and shifts in the enrollment schedule to a more flexible, data-driven, adaptive design. Additional issues have gained attention in the recent past, including Phase 0/microdosing, use of Phase I studies explicitly for treatment in the case of oncological products, involvement of Data Safety Monitoring Committees especially for first-in-class molecules, and improved means of optimizing selection of candidate agents for advancement to subsequent stages of development. Of final importance is the need for greater transparency of the presently inaccessible, early development study data maintained in commercial corporate legacy databases. Taken together, these developments and innovations by a broad range of stakeholders point to continuing opportunities for clinical investigators to explore the potential of Phase I studies to contribute to their own specialties.

Objective Most pragmatic trials follow the PRagmatic Explanatory Continuum Indicator Summary (PRECIS-2) criteria. The criteria specify unobtrusive measurement of participants’ protocol adherence and practitioners’ intervention fidelity but suggest no special monitoring strategies to assure trial integrity. We present experience with adherence/fidelity monitoring in the Pain Management Collaboratory (PMC) and provide recommendations for their monitoring in pragmatic trials to preserve inferences of treatment comparisons. Methods In November 2021, we surveyed 10 of 11 originally funded PMC pragmatic trials to determine the extent to which adherence and fidelity data were being monitored. Results Of the 10 PMC trials, 8 track adherence/fidelity. The electronic health record is the most frequent source for monitoring adherence (7/10) and fidelity (5/10). Most adherence data are used to monitor participant engagement with the trial intervention (4/10) and are reviewed by study teams (8/10) and often with a data and safety monitoring board (DSMB) (5/10). Half of the trials (5/10) reported using fidelity data for feedback/training; such data are not shared with a DSMB (0/10). Only 2 of 10 trials reported having prespecified guidance or rules around adherence/fidelity (eg, stopping rules or thresholds for corrective action, such as retraining). Conclusions As a best practice for pragmatic trials, we recommend early and regular adherence/fidelity monitoring to determine whether intervention delivery is as intended. We propose a 2-stage process with thresholds for intervening and triggers for conducting a formal futility analysis if adherence and fidelity are not maintained. The level of monitoring should be unobtrusive for both participants and those delivering the intervention; resulting data should be reviewed by an independent DSMB.

Introduction: Interferon γ is a potent proinflammatory cytokine implicated in the inflammation of Crohn’s disease (CD). We evaluated the safety and efficacy of fontolizumab, a humanised anti-interferon γ antibody, in patients with moderate to severe CD. Methods: A total of 133 patients with Crohn’s disease activity index (CDAI) scores between 250 and 450, inclusive, were randomised to receive placebo or fontolizumab 4 or 10 mg/kg. Forty two patients received one dose and 91 patients received two doses on days 0 and 28. Investigators and patients were unaware of assignment. Study end points were safety, clinical response (decrease in CDAI of 100 points or more), and remission (CDAI ⩽150). Results: There was no statistically significant difference in the primary end point of the study (clinical response) between the fontolizumab and placebo groups after a single dose at day 28. However, patients receiving two doses of fontolizumab demonstrated doubling in response rate at day 56 compared with placebo: 32% (9/28) versus 69% (22/32, p = 0.02) and 67% (21/31, p = 0.03) for the placebo, and 4 and 10 mg/kg fontolizumab groups, respectively. Stratification according to elevated baseline C reactive protein levels resulted in a decreased placebo response and pronounced differences in clinical benefit. Two grade 3 adverse events were reported and were considered to be related to CD. One death (during sleep) and one serious adverse event (an elective hospitalisation) occurred, both considered unrelated. Conclusion: Treating active CD with fontolizumab was well tolerated and resulted in increased rates of clinical response and remission compared with placebo.

Background Sharing interim result measures by the Data Safety Monitoring Board (DSMB) with non-DSMB members is an important issue that can affect trial integrity. Currently, it is unclear if there are demographic factors associated with sharing such information. This study’s objective is to primarily explore the demographic factors associated with the DSMB sharing certain interim result measures and secondarily, explore demographic factors associated with the perceived usefulness in sharing certain interim result measures, with non-DSMB members. Methods We conducted an online survey of members of the Society of Clinical Trials (SCT) and International Society of Clinical Biostatistics (ISCB) in 2015 asking their professional views on the DSMB sharing interim trial results, specifically the interim control event rate (IControlER), interim combined even rate (ICombinedER), adaptive conditional power (ACP) and unconditional conditional power (UCP) with non-DSMB members. Binary logistic and multiple linear regressions were used to explore if demographic factors were associated with sharing a certain interim result measure and the perceived usefulness of sharing that interim result measure, respectively. Multiple imputation (MI) was used to evaluate the impact of missing data as a sensitivity analysis. Results Approximately 3136 (936 from SCT + ~ 2200 from ISCB) members were invited (response rate of 12%; [371/3136]. Two main findings: (1) involvement in more than 15 private industry-sponsored trials was associated with not endorsing the sharing of the IControlER (odds ratio [OR] = 2.92; 95% confidence interval [CI]: 1.31, 6.52]; p  = 0.012), and (2) involvement in more than 15 private industry-sponsored trials was associated positively with an increase in the perceived usefulness in sharing the ACP by 2.35 points (beta coefficient estimate = 2.35 [95% CI: 0.45, 4.05], p  = 0.017. The findings were similar after sensitivity analyses. Conclusions An individual involved with more than 15 trials that had some form of private industry sponsorship is a demographic factor associated with NOT sharing the IControlER by the DSMB and an increased perceived usefulness in sharing the ACP at interim. Further studies are needed to evaluate for these demographic factors given the limitations of this study related to missing data. Due to some key limitations, regarding high non-response and missing data, we caution interpreting the results as definitive, but rather look at them as a first exploratory step to find potential associations for further evaluation.

To examine whether primary reports of randomized clinical trials (RCTs) in six high-impact, general medical journals reported (1) whether or not a Data Monitoring Committee/Data and Safety Monitoring Board (DMC/DSMB) was used and (2) the composition of the responsibilities of the reported DSMB/DMCs. Systematic review of RCTs published in 2014 in Annals of Internal Medicine, BMJ, NEJM, JAMA, JAMA Internal Medicine, and Lancet. Of the 294 articles identified, 174 (59%) mentioned using a DMC/DSMB. Of these 174, 126 (72%) indicated at least one responsibility of the DMC/DSMB, 26% listed the names of the DMC/DSMB members, and another 14% listed both their names and affiliations. Only one article stated that a DSMB was not used. The remaining 119 articles did not report whether or not a DMC/DSMB was used, although 59 had previously stated in a clinical trials registry entry or a published protocol that a DMC/DSMB was to be used. Considering the major role that DMC/DSMBs play in protecting participant safety, data quality, and interim analyses in RCTs, we recommend that authors of publications of RCTs report whether a DMC/DSMB was used and the responsibilities and members of DMC/DSMBs to increase transparency regarding study conduct.

Background Sharing interim results by the Data Safety Monitoring Board (DSMB) with non-DSMB members is an issue that can affect trial integrity. It is unclear what should be shared. This study assesses the views of professionals to understand what interim information should be shared at interim, with whom and why. Methods Conducted an online survey of members of the Society of Clinical Trials (SCT) and International Society of Clinical Biostatistics (ISCB) in 2015 asking their professional views on sharing interim results. Email was used to advertise the survey and a link in the email was provided to the online survey. Results Approximately 3136 (936 SCT members + 2200 ISCB members) members were invited. The response rate was 12% (371/3136). The majority reported the Interim Control Event Rate (IControlER) (149/237; 62.9% [95% CI, 56.7–69.0%]), Adaptive Conditional Power (ACP) (144/224; 64.3% [95% CI, 58.0%–70.6%]) and the Unconditional Conditional Power (UCP) (126/208; 60.6% [95% CI, 53.9–67.2%]) should not be shared with non-DSMB members. The majority reported that the Interim Combined Event Rate (ICombinedER) (168/262; 64.1% [95% CI, 58.0–69.9%]) should be shared with non-DSMB members particularly the steering committee (SC) because it does not unmask interim results and helps with monitoring trial progress, safety, and design assumptions. Conclusion The IControlER and ACP are unmasking of interim results and should not be shared. The UCP is a technical measure that is potentially misleading and also should not be shared. The ICombinedER is usually known by the SC and sponsor making it easy to determine group rates if the IControlER is known. Though most respondents thought the ICombinedER should be shared with the SC as it does not unmask relative effects between groups, we do not recommend sharing the ICombinedER as it is flawed measure that can have multiple interpretations possibly suggesting that one group is performing better, worse or the same as a comparator group, leading to guesses about how groups are doing relative to one another.

Raynaud’s phenomenon (RP) is relevant to the rheumatologist because it may signify an underlying connective tissue disease and also because it can be very challenging to treat, especially when it has progressed to digital ulceration or critical ischaemia. This review article discusses diagnosis (does this patient have an underlying connective tissue disease?), including the role for nailfold capillaroscopy, and treatment. Management of ‘uncomplicated’ RP is first described and then treatment of RP complicated by progression to digital ulceration or critical ischaemia, highlighting recent advances (including phosphodiesterase type 5 inhibition, and endothelin 1 receptor antagonism) and the evidence base underpinning these. Possible future therapies are briefly discussed.

Monitoring patient safety during clinical trials is a critical component throughout the drug development life-cycle. Pharmaceutical sponsors must work proactively and collaboratively with all stakeholders to ensure a systematic approach to safety monitoring. The regulatory landscape has evolved with increased requirements for risk management plans, risk evaluation and minimization strategies. As the industry transitions from passive to active safety surveillance activities, there will be greater demand for more comprehensive and innovative approaches that apply quantitative methods to accumulating data from all sources, ranging from the discovery and preclinical through clinical and post-approval stages. Statistical methods, especially those based on the Bayesian framework, are important tools to help provide objectivity and rigor to the safety monitoring process.

Background Sharing interim data, results or result extrapolations is an important issue that can affect trial integrity. The different ways in which Data Safety Monitoring Boards (DSMBs) share interim results with non-DSMB members and the acceptability of such practices are poorly understood. Our objective was to undertake a narrative review specifically on what kind of interim results, if any, should be shared by the DSMB with non-DSMB members and why. Methods We conducted a narrative review using a systematic search strategy of several databases and major health research stakeholders. Literature was included if there was some discussion within the full text about sharing interim trial results with non-DSMB members. Results About 79.6% (129/162) of included citations were based on author’s views, 16.7% (27/162) on research guidelines and 3.7% (6/162) on surveys. The largest group of citations, 73/162 (45%), expresses the opinion or argument against sharing interim results with exceptions. Trailing closely, 71/162 (43.8%) of the included citations support the opinion or argument that interim results should not be shared and should remain confidential with the DSMB. Half of the six surveys support sharing in some capacity, while the other three do not. Eleven circumstances were found that potentially warrant interim result sharing by the DSMB; they relate to (1) usual practices by DSMBs, (2) trial completion threatened, (3) patient safety, (4) regulatory approval and (5) other circumstances. Dominant risks for sharing under these conditions are associated with introducing trial bias. Discussion/conclusion There was no majority view in the literature. However, the largest group of citations included express the idea that interim results should remain confidential with the DSMB but also acknowledge circumstances when they could be shared with non-DSMB members. Limitations of this review are that (1) the included literature predominately provides personal perspectives, not evidence, and (2) surveys found globally focus on trial monitoring practices lacking detailed information on what specifically to share, with whom and why. More research is needed with the use of a detailed survey of the clinical trial community focused on DSMB sharing interim results, to better understand and guide DSMB interim result sharing practices.