Certain sociodemographic groups are routinely underrepresented in clinical trials, limiting generalisability. Here, we describe the extent to which enriched enrolment approaches yielded a diverse trial population enriched for older age in a randomised controlled trial of a blood-based multi-cancer early detection test (NCT05611632).

People with disability have higher rates of cancer, excluding skin cancer, compared with people without disability. Food and Drug Administration draft guidelines from 2024 address use of performance status criteria to determine eligibility for clinical trials, advocating for less restrictive thresholds. We examined the exclusion of people with disability from clinical trials based on performance status and other criteria.

Rare disease drug development faces unique challenges, such as genotypic and phenotypic heterogeneity within small patient populations and a lack of established outcome measures for conditions without previously successful drug development programs. These challenges complicate the process of selecting the appropriate trial endpoints and conducting clinical trials in rare diseases. In this descriptive study, we examined novel drug approvals for non-oncologic rare diseases by the U.S. Food and Drug Administration's Center for Drug Evaluation and Research over the past decade and characterized key regulatory and trial design elements with a focus on the primary efficacy endpoint utilized as the basis of approval.

Low-intervention clinical trials have been established under the European Union Clinical Trials Regulation (EU 536/2014) which aims to simplify the conduct of clinical trials with authorized medicinal products. There is limited experience with conducting low-intervention trials. Therefore, this study aims to report on experiences and perceived (dis)advantages of low-intervention trials.

The sequential parallel comparison design has emerged as a valuable tool in clinical trials with high placebo response rates. To further enhance its efficiency and effectiveness, adaptive strategies, such as sample size adjustment and allocation ratio modification can be employed.

N-of-1 trials compare two or more treatment options for a single participant. These trials have been used to study options for chronic conditions such as arthritis and attention deficit hyperactivity disorder. In addition, they have been suggested as a means to study interventions in rare populations that may not be tractable to include in standard clinical trials, such as treatment options for HIV-positive patients in need of organ transplant. Sequential monitoring of accruing data has been well-studied in traditional clinical trials, but these methods have not yet been implemented in N-of-1 trials. However, the option to validly stop an N-of-1 trial early could deliver faster decisions that could directly improve the patient's health.

When conducting a randomised controlled trial in surgery, it is important to consider surgical learning, where surgeons' familiarity with one, or both, of the interventions increases during the trial. If present, learning may compromise trial validity. We demonstrate a statistical investigation into surgical learning within a trial of cleft palate repair.

In randomized clinical trials, multiple-testing procedures, composite endpoints, and prioritized outcome approaches are increasingly used to analyze multiple binary outcomes. Previous studies have shown that correlations between outcomes influence their sample size requirements. Although sample size is an important factor affecting the choice of statistical methods, the power and required sample sizes of methods for analyzing multiple binary outcomes have yet to be compared under the influence of outcome correlations.

Implementation and hybrid effectiveness-implementation trials aspire to speed the translation of science into practice by generating crucial evidence for improving the uptake of effective health interventions. By design, they pose unique recruitment and retention challenges due to their aims, units of analysis, and sampling plans, which typically require many clinical sites (i.e. often 20 or more) and participation by individuals who are related across multiple levels (e.g. linked organizational leaders, clinicians, and patients). In this article, we present a new multilevel, theory-informed, and relationship-centered framework for conceptualizing recruitment and retention in implementation and hybrid effectiveness-implementation trials which integrates and builds on prior work on recruitment and retention strategies in patient-focused trials. We describe the framework's application in the Working to Implement and Sustain Digital Outcome Measures hybrid type III trial, which occurred in part during the COVID-19 pandemic.

Randomized clinical trials often use stratification to ensure balance between arms. Analysis of primary endpoints of these trials typically uses a "stratified analysis," in which analyses are performed separately in each subgroup defined by the stratification factors, and those separate analyses are weighted and combined. In the phase 3 setting, stratified analyses based on a small number of stratification factors can provide a small increase in power. The impact on power and type-1 error of stratification in the setting of smaller sample sizes as in randomized phase 2 trials has not been well characterized.

Clinical trials of drugs, procedures, and other therapies play a crucial role in advancing medical science by evaluating the safety, efficacy, and optimal use of medical interventions. The design and implementation of these trials have evolved significantly over time, reflecting advancements in medicine, ethics, and methodology. Early historical examples, such as King Nebuchadnezzar II's and his captives' dietary experiment and Ambroise Paré's treatment of gunshot wounds, laid some foundational principles of trial design. The momentum of clinical trial development increased notably with James Lind's 1747 trial for scurvy and continued to progress during World War I with innovations in blood transfusion techniques. World War II (WWII) marked a pivotal moment with breakthroughs in oncology, including the development of the first modern chemotherapeutic agents derived from mustard gas and the introduction of the randomized controlled trial, credited to British epidemiologist Austin Bradford Hill, which revolutionized trial design. More recent conflicts, such as those in Vietnam, Iraq, and Afghanistan, have driven advancements in trauma care, heroin addiction treatment, and hemorrhage management. In response to historical abuses committed by the Nazis during WWII, the evolution of clinical trials has increasingly emphasized ethical standards, particularly informed consent, starting with the Doctors' Trial and the Nuremberg Code. This article discusses how military needs and wartime innovations have shaped modern clinical research, highlighting the interplay between military imperatives and medical progress. Ultimately, clinical trials play an essential role in advancing medical science and improving patient outcomes.

Clinical trials handle a huge amount of data which can be used during the trial to improve the ongoing study conduct. It is suggested by regulators to implement the remote approach to evaluate clinical trials by analysing collected data. Central statistical monitoring helps to achieve that by employing quantitative methods, the results of which are a basis for decision-making on quality issues.

Unlocking the power of personalised medicine in oncology hinges on the integration of clinical trial data with translational data (i.e. biospecimen-derived molecular information). This combined analysis allows researchers to tailor treatments to a patient's unique biological makeup. However, current practices within UK Clinical Trials Units present challenges. While clinical data are held in standardised formats, translational data are complex, diverse, and requires specialised storage. This disparity in format creates significant hurdles for researchers aiming to curate, integrate and analyse these datasets effectively. This article proposes a novel solution: an open-source SQL database schema designed specifically for the needs of academic trial units. Inspired by Cancer Research UK's commitment to open data sharing and exemplified by the Southampton Clinical Trials Unit's CONFIRM trial (with over 150,000 clinical data points), this schema offers a cost-effective and practical 'middle ground' between raw data and expensive Secure Data Environments/Trusted Research Environments. By acting as a central hub for both clinical and translational data, the schema facilitates seamless data sharing and analysis. Researchers gain a holistic view of trials, enabling exploration of connections between clinical observations and the molecular underpinnings of treatment response. Detailed instructions for setting up the database are provided. The open-source nature and straightforward design ensure ease of implementation and affordability, while robust security measures safeguard sensitive data. We further showcase how researchers can leverage popular statistical software like R to directly query the database. This approach fosters collaboration within the academic discovery community, ultimately accelerating progress towards personalised cancer therapies.

Enoximone, a phosphodiesterase III inhibitor, was approved in Germany in 1989 and initially proposed for heart failure and perioperative cardiac conditions. The research of Joachim Boldt and his supervisor Gunter Hempelmann came under scrutiny after investigations revealed systematic scientific misconduct leading to numerous retractions. Therefore, early enoximone studies by Boldt and Hempelmann from 1988 to 1991 were reviewed.

There is increasing recognition that the interpretation of active-controlled HIV prevention trials should consider the counterfactual placebo HIV incidence rate, that is, the rate that would have been observed if the trial had included a placebo control arm. The PrEPVacc HIV vaccine and pre-exposure prophylaxis trial (NCT04066881) incorporated a pre-trial registration cohort partly for this purpose. In this article, we describe our attempts to model the counterfactual placebo HIV incidence rate from the registration cohort.

Monitoring the conduct of phase III randomized controlled trials is driven by ethical reasons to protect the study integrity and the safety of trial participants. We propose a group sequential, pragmatic approach for monitoring the accumulating efficacy information in randomized controlled trials. The "Population Health Research Institute boundary" is simple to implement and sensible, as it considers the reduction in uncertainty with increasing information as the study progresses. It is also pragmatic, since it takes into consideration the typical monitoring behavior of monitoring committees of large multicenter trials and is relatively easily implemented. It not only controls the overall Lan-DeMets type I error probability (alpha) spent, but performs better than other group sequential boundaries for the total nominal study alpha. We illustrate the use of our monitoring approach in the early termination of two past completed trials.

Clinical trials provide an opportunity to identify new treatments and can offer patients access to treatments otherwise unavailable. However, approximately 10% of paediatric clinical trials discontinue before the trial has completed. If this premature termination is because the trial treatment(s) being investigated are identified to be ineffective or unsafe, it results in the abrupt discontinuation of the investigational medicinal product for participants. For some participants, there may not be other treatment options to pursue at the trial-end. Trials prematurely terminating can be a distressing experience for all involved and currently there is little published evidence about the guidance provided to healthcare professionals in the event of premature trial termination. The study protocol is the source of guidance for healthcare professionals delivering clinical research, detailing how to conduct all aspects of the trial. The aim was to quantify the proportion of clinical trial protocols that included premature trial termination and subsequently those that provided instructions related to participant management and care. In addition, to analyse the context in which premature termination was included and the detail of any instructions for participant management and care.

A growing literature has explored the ethical obligations and current practices related to sharing aggregate results with research participants. However, no prior work has examined these issues in the context of pragmatic clinical trials. Several characteristics of pragmatic clinical trials may complicate both the ethics and the logistics of sharing aggregate results. Among these characteristics include that pragmatic clinical trials may affect the rights, welfare, and interests of not only patient-subjects but also clinicians, meaning that results may be owed to a broader range of groups than typically considered in other research contexts. In addition, some pragmatic clinical trials are conducted under a waiver of informed consent, meaning sharing results may alert participants that they were enrolled without their consent. This article explores the ethical dimensions that can inform decision-making about sharing aggregate results from pragmatic clinical trials, and provides recommendations for that sharing. A central insight is that healthcare institutions-as key partners for the conduct of pragmatic clinical trials-must also be key partners in decision-making about sharing aggregate pragmatic clinical trial results. We conclude with insights for future research.

Over the course of a clinical trial, irregularities may arise in the data. Trialists implement human-intensive, expensive central statistical monitoring procedures to identify and correct these irregularities before the results of the trial are analyzed and disseminated. Machine learning algorithms have shown promise for identifying center-level irregularities in multi-center clinical trials with minimal human intervention. We aimed to characterize the form-level data irregularities in several historical clinical trials and evaluate the ability of a machine learning-based outlier detection algorithm to identify them.

Amid growing emphasis from pharmaceutical companies, advocacy groups, and regulatory bodies for sharing of individual participant data, recent audits reveal limited sharing, particularly for high-revenue medicines. Therefore, this study aimed to assess the individual participant data-sharing eligibility of clinical trials supporting the Food and Drug Administration approval of the top 30 highest-revenue medicines for 2021.

The Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) was developed to capture symptomatic adverse events from the patient perspective. We aim to describe statistical properties of PRO-CTCAE items and summary scores and to provide evidence for recommendations regarding PRO-CTCAE administration and reporting.