Research encouraging off-label use of quetiapine: A systematic meta-epidemiological analysis.

BACKGROUND: Researchers often conduct small studies on testing a drug's efficacy in off-label indications. If positive results from these exploratory studies are not followed up by larger, randomized, double-blinded trials, physicians cannot be sure of a drug's clinical value. This may lead to off-label prescriptions of ineffective treatments. We aim to describe the way clinical studies fostered off-label prescription of the antipsychotic drug quetiapine (Seroquel). METHODS: In this systematic meta-epidemiological analysis, we searched EMBASE, MEDLINE, Cochrane CENTRAL and PsycINFO databases and included clinical studies testing quetiapine for unapproved indications between May 1995 and May 2022. We then assessed the frequency with which publications providing low-level evidence suggesting efficacy of quetiapine for off-label indications was not followed up by large, randomized and double-blinded trials within 5 years. RESULTS: In total, 176 published studies were identified that reported potential efficacy of quetiapine in at least 26 indications. Between 2000 and 2007, publication of exploratory studies suggesting promise for off-label indications rapidly outpaced publication of confirmatory trials. In the 24 indications with a minimum of 5 years of follow-up from the first positive exploratory study, 19 (79%) were not followed up with large confirmatory trials within 5 years. At least nine clinical practice guidelines recommend the use of quetiapine for seven off-label indications in which published confirmatory evidence is lacking. CONCLUSION: Many small, post-approval studies suggested the promise of quetiapine for numerous off-label indications. These findings generally went unconfirmed in large, blinded, randomized trials years after first being published. The imbalance of exploratory and confirmatory studies likely encourages ineffective off-label treatment.

Probability of Regulatory Approval Over Time: A Cohort Study of Cancer Therapies.

PURPOSE: New cancer therapies are frequently evaluated in multiple disease indications. We evaluated whether the probability of achieving US Food and Drug Administration (FDA) approval for a new cancer therapy changes with time. METHODS: We identified a cohort of anticancer drugs with a first registered efficacy trial from 2007 to 2011 on ClinicalTrials.gov. We downloaded all clinical trials for each included drug from the initiation of efficacy testing to January 11, 2021. Each trial was categorized by cancer indication and assigned to investigational trajectories on the basis of unique drug-indication pairings. We performed a univariate Cox's proportional hazards regression to assess the probability of a trajectory leading to regulatory approval over time since initiation of the first efficacy trial for a given drug. RESULTS: We included 213 drugs in our cohort, of which 37 (17.4%) received FDA approval in at least one oncology indication. In our primary analysis, we found a 15% decrease in the probability of approval for every year since initiation of the first efficacy trial (hazard ratio [HR], 0.85 [95% CI, 0.73 to 0.99]; P = .032). We found a 45% increase in the probability of approval for the first trajectory launched for a given drug in comparison with all others (HR, 0.55 [95% CI, 0.33 to 0.91]; P = .021). CONCLUSION: Drug-indication pairings pursued years after initial testing for efficacy have lowered probability of affecting care. Clinical trial investigators, sponsors, and regulatory bodies may benefit from awareness of this trend when considering both early and late trajectory trials in a drug's development.

The impact of feedback training on prediction of cancer clinical trial results.

INTRODUCTION: Funders must make difficult decisions about which squared treatments to prioritize for randomized trials. Earlier research suggests that experts have no ability to predict which treatments will vindicate their promise. We tested whether a brief training module could improve experts' trial predictions. METHODS: We randomized a sample of breast cancer and hematology-oncology experts to the presence or absence of a feedback training module where experts predicted outcomes for five recently completed randomized controlled trials and received feedback on accuracy. Experts then predicted primary outcome attainment for a sample of ongoing randomized controlled trials. Prediction skill was assessed by Brier scores, which measure the average deviation between their predictions and actual outcomes. Secondary outcomes were discrimination (ability to distinguish between positive and non-positive trials) and calibration (higher predictions reflecting higher probability of trials being positive). RESULTS: A total of 148 experts (46 for breast cancer, 54 for leukemia, and 48 for lymphoma) were randomized between May and December 2017 and included in the analysis (1217 forecasts for 25 trials). Feedback did not improve prediction skill (mean Brier score for control: 0.22, 95% confidence interval = 0.20-0.24 vs feedback arm: 0.21, 95% confidence interval = 0.20-0.23; p = 0.51). Control and feedback arms showed similar discrimination (area under the curve = 0.70 vs 0.73, p = 0.24) and calibration (calibration index = 0.01 vs 0.01, p = 0.81). However, experts in both arms offered predictions that were significantly more accurate than uninformative forecasts of 50% (Brier score = 0.25). DISCUSSION: A short training module did not improve predictions for cancer trial results. However, expert communities showed unexpected ability to anticipate positive trials.Pre-registration record: https://aspredicted.org/4ka6r.pdf.

Large numbers of patients are needed to obtain additional approvals for new cancer drugs: A retrospective cohort study.

Patients endure risk and uncertainty when they participate in clinical trials. We previously estimated that 12,217 patient-participants are required to bring a new cancer drug to market. However, many development efforts are aimed at extending the label of already approved drugs. Herein, we estimate the number of patients required to extend the indication of an FDA approved cancer drug. We identified all anti-cancer drugs approved by the FDA 2012 to 2015. We searched clinicaltrials.gov to identify all drug development trajectories (i.e., a series of one or more clinical trials testing a unique drug-indication pairing) launched after FDA approval for each drug. We identified which trajectories produced the following milestones: secondary FDA approvals, secondary FDA approvals achieving substantial clinical benefit in ESMO-MCBS, and recommendations in NCCN clinical practice guidelines. Using the total enrollment, we estimated the number of patients needed to reach each milestone. Forty-two drugs were approved by the FDA between 2012 and 2015, leading to 451 post-approval trajectories enrolling 129,548 patients. Fourteen secondary FDA approvals were identified, of which 4 met the ESMO-MCBS definition of substantial clinical benefit. Fourteen NCCN off-label recommendations were obtained. A total of 9253, 32,387 and 4627 patients were needed to attain an FDA approval, an approval with substantial clinical benefit on ESMO-MCBS, and an NCCN guideline recommendation, respectively. The number of patients needed to obtain a first secondary FDA approval was 16,596. Large numbers of patients are needed to extend the label of prior FDA approved drugs. Label extension after approval entails lower marginal costs for developers. However, extra knowledge available to researchers about a drug's safety and pharmacology after FDA approval does not appear to translate into reduced patient numbers required for developing new cancer applications.

Timing for First-in-Minor Clinical Trials of New Cancer Drugs.

OBJECTIVES: To describe the delay for first-in-minor cancer clinical trials and its relationship with the Food and Drug Administration (FDA) approval. STUDY DESIGN: We used ClinicalTrials.gov to create a sample of pediatric-relevant cancer drugs starting efficacy testing in adults from 2006 through 2011. We characterized the delay between first-in-adult efficacy trials and first-in-minor trials. We also assessed the proportion of drugs evaluated in minors that failed to gain approval, the proportions that were not evaluated in minors before receiving the FDA approval, and whether shorter delay was associated with larger effect sizes or greater probability of regulatory approval. RESULTS: Thirty-four percent of the 185 drugs in our cohort were evaluated in minors; the median delay to clinical trials was 4.16 years. Of all drugs, 17% received the FDA approval, 41% of which were never tested in minors before licensing. Of the 153 drugs not attaining approval, 78% were not evaluated in minors. Earlier testing did not significantly predict greater response rates (P = .13). Drugs not attaining regulatory approval were evaluated significantly earlier (3.0 for drugs not approved vs 5.4 years delayed testing for approved drugs, P = .019). CONCLUSIONS: New cancer drugs were typically evaluated in minors years after adult efficacy evaluation. This delay likely eliminated some drugs lacking desirable pharmacology before pediatric testing. However, some drugs that were eliminated may have had activity in pediatric indications. Approaches for prioritizing drugs for pediatric testing warrants further consideration.

Bypassing phase 2 in cancer drug development erodes the risk/benefit balance in phase 3 trials.

OBJECTIVES: Drug developers sometimes launch phase 3 (P3) trials without supporting evidence from phase 2 (P2) trials. We call this practice "P2 bypass." The aims of this study were to estimate the prevalence of P2 bypass and to compare the safety and efficacy results for P3 trials that bypassed with those that did not. STUDY DESIGN AND SETTING: We created a sample of P3 solid tumor trials registered on ClinicalTrials.gov with primary completion dates between 2013 and 2019. We then attempted to match each with a supporting P2 trial using strict and broad criteria. P3 outcomes were meta-analyzed using a random effects model with subgroup contrast between trials that bypassed and those that did not. RESULTS: 129 P3 trial arms met eligibility and nearly half involved P2 bypass. P3 trials involving P2 bypass produced significantly and nonsignificantly worse pooled efficacy estimates using broad and strict matching criteria, respectively. We did not observe significant differences in safety outcomes between P3 trials that bypassed P2 and those that did not. CONCLUSION: The risk/benefit balance of P3 trials that bypassed P2 is less favourable than for trials supported by P2.

Predicting Clinical Trial Results: A Synthesis of Five Empirical Studies and Their Implications.

Expectations about future events underlie practically every decision we make, including those in medical research. This paper reviews five studies undertaken to assess how well medical experts could predict the outcomes of clinical trials. It explains why expert trial forecasting was the focus of study and argues that forecasting skill affords insights into the quality of expert judgment and might be harnessed to improve decision-making in care, policy, and research. The paper also addresses potential criticisms of the research agenda and summarizes key findings from the five studies of trial forecasting. Together, the studies suggest that trials frequently deliver surprising results to expert communities and that individual experts are often uninformative when it comes to forecasting trial outcome and recruitment. However, the findings also suggest that expert forecasts often contain a "signal" about whether a trial will be positive, especially when forecasts are aggregated. The paper concludes with needs for further research and tentative policy recommendations.

Varieties of Community Uncertainty and Clinical Equipoise.

The judgments of conscientious and informed experts play a central role in two elements of clinical equipoise. The first, and most widely discussed, element involves ensuring that no participant in a randomized trial is allocated to a level of treatment that everyone agrees is substandard. The second, and less often discussed, element involves ensuring that trials are likely to generate social value by producing the information necessary to resolve a clinically meaningful uncertainty or disagreement about the relative merits of a set of interventions. The distribution of judgments in expert communities can take many forms, each with important implications for whether a trial satisfies one or both elements of clinical equipoise. In this article we use a graphical approach to represent three ways in which expert community uncertainty can vary: by spread, modality, and skew. Understanding these different distributions of expert judgment has three important implications: it helps to make operational the requirement of social value, it shows that some conditions for initiating studies to promote social value diverge from common assumptions about clinical equipoise, and it has important implications for how trials should be designed and monitored, and what patients should be told during informed consent.

Competition for recruitment in SARS-CoV-2 Trials in the United States: a longitudinal cohort analysis.

OBJECTIVE: Competition among trials for patient enrollment can impede recruitment. We hypothesized that this occurred early in the COVID-19 pandemic, when an unprecedented number of clinical trials were launched. We performed a simple and multivariable regression analysis evaluating the relationship between the proportion of SARS-CoV-2 investigational trial sites within each USA state with unsuccessful patient-participant recruitment and: (i) the proportion of cases required to reach state recruitment goals; (ii) state population based on data from the US Census; and, (iii) number of trial sites per state. RESULTS: Our study included 151 clinical trials. The proportion of trials with successful recruitment was 72.19% (109 of 151 trials). We did not find a significant relationship between unsuccessful patient-participant recruitment, state recruitment goals, state population or the number of trial sites per state in both our simple and multivariable regression analyses. Our results do not suggest that early in the COVID-19 pandemic, competition for patient-participants impeded successful recruitment in SARS-CoV-2 trials. This may reflect the unique circumstances of the first few months of the pandemic in the United States, in which the number and location of SARS-CoV-2 cases was sufficient to meet trial recruitment requirements, despite the large number of trials launched.

Clarifying the Ethics and Oversight of Chimeric Research.

This article is the lead piece in a special report that presents the results of a bioethical investigation into chimeric research, which involves the insertion of human cells into nonhuman animals and nonhuman animal embryos, including into their brains. Rapid scientific developments in this field may advance knowledge and could lead to new therapies for humans. They also reveal the conceptual, ethical, and procedural limitations of existing ethics guidance for human-nonhuman chimeric research. Led by bioethics researchers working closely with an interdisciplinary work group, the investigation focused on generating conceptual clarity and identifying improvements to governance approaches, with the goal of helping scholars, funders, scientists, institutional leaders, and oversight bodies (embryonic stem cell research oversight [ESCRO] committees and institutional animal care and use committees [IACUCs]) deliver principled and trustworthy oversight of this area of science. The article, which focuses on human-nonhuman animal chimeric research that is stem cell based, identifies key ethical issues in and offers ten recommendations regarding the ethics and oversight of this research. Turning from bioethics' previous focus on human-centered questions about the ethics of "humanization" and this research's potential impact on concepts like human dignity, this article emphasizes the importance of nonhuman animal welfare concerns in chimeric research and argues for less-siloed governance and oversight and more-comprehensive public communication.

Participant Recruitment From Low- and Middle-Income Countries for Pivotal Trials of Drugs Approved by the U.S. Food and Drug Administration : A Cross-Sectional Analysis.

BACKGROUND: Many participants in clinical trials supporting U.S. Food and Drug Administration (FDA) drug approvals are recruited from outside the United States, including from low- and middle-income countries (LMICs). Where participants are recruited for pivotal trials has implications for ethical research conduct and generalizability. OBJECTIVE: To describe LMIC recruitment for pivotal trials of newly approved drugs for cancer, neurologic disease, and cardiovascular disease. DESIGN: Cross-sectional analysis. SETTING: Pivotal trials of new cancer, cardiovascular, and neurologic drugs approved from 2012 to 2019 matched to ClinicalTrials.gov, FDA records, and publications. MEASUREMENTS: Host countries and available per country enrollments were extracted. The primary end point was the proportion of pivotal trials enrolling participants in LMICs. The secondary end point was the proportion of pivotal trial participants contributed by LMICs for each indication area. RESULTS: Data were obtained from 66 new drugs and 144 pivotal clinical trials. All cardiovascular approvals (12 drugs, 29 trials) and neurologic approvals (26 drugs, 54 trials) were analyzed, as well as a random sample of cancer approvals (28 of 85 drugs [33%]) matched to their pivotal trials (61 of 210 trials [29%]). Among the trials, 56% in cancer, 79% in cardiovascular disease, and 56% in neurology recruited from an LMIC. For multicountry trials, country-level enrollment figures were not available for 71 trials (55%). For those reporting per country enrollment, the percentage of participants recruited from LMICs was 8% for cancer trials, 36% for cardiovascular trials, and 17% for neurology trials. LIMITATIONS: The study was limited to FDA-approved drugs in 3 areas, including a sample of cancer drugs. Pivotal trials of nonapproved drugs or drugs for other indications were not captured. CONCLUSION: Most pivotal trials for FDA-approved drugs recruit from LMICs. Publications and FDA documents generally do not provide country-level data on recruitment. PRIMARY FUNDING SOURCE: None.

Diminishing clinical impact for post-approval cancer clinical trials: A retrospective cohort study.

BACKGROUND: Once a drug gets FDA approved, researchers often attempt to discover new applications in different indications. The clinical impact of such post-approval activities is uncertain. We aimed to compare the clinical impact of research efforts started after approval with those started before for cancer drugs. METHODS: We used Drugs@FDA to perform a retrospective cohort study of secondary approvals for cancer drugs that were initially FDA approved between 2005 and 2017. Clinicaltrials.gov was used to identify the beginning of each research trajectory that resulted in a secondary FDA approval. Each trajectory was classified as pre- or post-approval depending on if it was initiated before or after initial drug licensure. Clinical impact was assessed by comparing secondary approvals and NCCN off-label recommendations deriving from pre- vs. post-approval trajectories, pooled effect sizes, incidence, and level of evidence. RESULTS: We identified 77 broad secondary approvals, 60 of which had at least 6 years follow-up. Of these, 9 (15%) resulted from post-approval trajectories, a proportion that is significantly lower than would be expected if the timing of research didn't impact approval (McNemar's test p = 0.001). Compared to pre-approval trajectories, approvals resulting from post-approval trajectories were for cancers with lower mean incidence (6.11 vs 14.83, p = 0.006) and were based on pivotal trials with smaller pooled effect sizes (0.69 vs 0.57, p = 0.02) that were less likely to be randomized (38.5% vs 64.1%, p = 0.145). We identified 69 NCCN off-label recommendations. The proportion stemming from post-approval trajectories was similar to that for pre-approval (56.5% vs. 43.5%). However, recommendations from post-approval trajectories were significantly more likely to involve rare diseases (76.7% vs 51.4%, p = 0.019) and nonsignificantly less likely to be based on level 1 evidence (11.6% vs 22.9%, p = 0.309). CONCLUSION: Secondary FDA approvals are less likely to result from post-approval trajectories and tend to be less impactful compared to approvals originating from research started before first FDA licensure. However, post-approval trajectories may be as likely to lead to NCCN recommendations for off-label use. Limitations of this work include our use of indirect measures of impact and limited follow-up time for trajectories. Our study protocol was pre-registered (https://osf.io/5g3jw/).

The proportion of randomized controlled trials that inform clinical practice.

Prior studies suggest that clinical trials are often hampered by problems in design, conduct, and reporting that limit their uptake in clinical practice. We have described 'informativeness' as the ability of a trial to guide clinical, policy, or research decisions. Little is known about the proportion of initiated trials that inform clinical practice. We created a cohort of randomized interventional clinical trials in three disease areas (ischemic heart disease, diabetes mellitus, and lung cancer) that were initiated between January 1, 2009 and December 31, 2010 using ClinicalTrials.gov. We restricted inclusion to trials aimed at answering a clinical question related to the treatment or prevention of disease. Our primary outcome was the proportion of clinical trials fulfilling four conditions of informativeness: importance of the clinical question, trial design, feasibility, and reporting of results. Our study included 125 clinical trials. The proportion meeting four conditions for informativeness was 26.4% (95% CI 18.9-35.0). Sixty-seven percent of participants were enrolled in informative trials. The proportion of informative trials did not differ significantly between our three disease areas. Our results suggest that the majority of randomized interventional trials designed to guide clinical practice possess features that may compromise their ability to do so. This highlights opportunities to improve the scientific vetting of clinical research.

Success rates for US and Canadian anticancer drug development efforts in pediatric oncology.

BACKGROUND: Approximately 5% of adult cancer interventions put into clinical testing attain regulatory approval. Little is known about corresponding rates for pediatric cancer. METHODS: Our primary outcomes were the proportion of interventions graduating to the next trial phase, randomized trials, and/or clinical practice. We created a saturation sample of clinical trials by searching ClinicalTrials.gov for all pediatric anticancer trials in the United States or Canada. Trial characteristics were extracted automatically from ClinicalTrials.gov records, and cancer indication/drug class categorization, biomarker enrichment, and Food and Drug Administration (FDA) approval status at time of recruitment were double-extracted from each record. Regulatory approval status and labeling modifications for each intervention were determined by searching Drugs@FDA and the New Pediatric Labeling Information Database. RESULTS: Five hundred eighty-nine pediatric trials launched between 1987 and 2019 were captured. The overall probability of graduation was 17.0%; 18.9% of interventions graduated from phase 1 to phase 2 trials, and 1.6% of interventions graduated from phase 2 to phase 3 trials. The proportion of interventions advancing from phase 1 to FDA approval was 3.6%, and 1.9% of interventions tested in phase 1 advanced to a randomized phase 2 trial. Only biomarker enrichment was significantly predictive of graduation from phase 1 to phase 2 trials (p = .011). CONCLUSION: The proportion of interventions advancing from phase 1 testing to FDA approval was similar to estimates for adult oncology. Our findings highlight the challenges for current paradigms of pediatric anticancer drug development.

Quantifying Patient Investment in Novel Neurological Drug Development.

While the drug development literature provides numerous estimates of the financial costs to bring a new drug to market, the investment of patient-participants in the research process has not been described. Trial participants and their caregivers, like companies, invest time and undertake risk when they participate in prelicense trials. We determined the average number of patient-participants needed to develop a novel neurological drug. We created a cohort of 108 unapproved drugs first tested for efficacy between 2006 and 2011 and used ClinicalTrials.gov to capture enrollment in all subsequent prelicense trials of these drugs over a 9-year period. Our primary outcome was the average number of patients enrolled in prelicense neurological drug trials per drug that ultimately attained FDA approval, including patients who participated in both successful and unsuccessful development efforts. Five drugs (4.6%) were FDA approved, and 66,751 patient-participants were enrolled across successful and unsuccessful drug development efforts, resulting in an average of 13,350 patients for each drug attaining approval (95% CI 7155 to 54,954). Our estimates reveal the substantial amount patients and their caregivers contribute to private drug development.

Completeness of clinical evidence citation in trial protocols: A cross-sectional analysis.

BACKGROUND: Human protection policies require assessment of how proposed clinical trials relate to prior and ongoing studies testing similar hypotheses. We assessed the extent to which clinical trial protocols cited relevant published and ongoing clinical trials that would have been easily accessible with reference searches. METHODS: We created a random sample of trial protocols using ClinicalTrials.gov, stratifying by industry and non-industry-sponsored studies. We then conducted reference searches to determine the extent to which protocols cited clinical trials with identical intervention-indication pairings that were accessible in PubMed and ClinicalTrials.gov at the time of trial initiation. FINDINGS: Of the 101 trial protocols evaluated, 73 had at least one identified citable trial. None contained statements suggesting a systematic search for relevant clinical evidence. Of industry-sponsored trial protocols with at least one identified citable trial, 7 of 23 (30.4%) did not cite any published clinical trials and 10 of 33 (30.3%) did not cite any ongoing relevant trials. Of the non-industry-sponsored trial protocols with at least one identified citable trial, 5 of 28 (17.9%) did not cite any published clinical trials and 14 of 19 (73.7%) did not cite any ongoing trials. CONCLUSIONS: Clinical trial protocols undercite accessible, relevant trials and do not document systematic searches for relevant clinical trials. Consequently, ethics review committees often receive an incomplete picture of the research landscape if they review protocols similar to those deposited on ClinicalTrials.gov. FUNDING: This study was funded by the Canadian Institutes of Health Research and the Greenwall Foundation.

Interventions for physician prescribers of opioids for chronic non-cancer pain: protocol for an overview of systematic reviews.

INTRODUCTION: Interventions targeting behaviours of physician prescribers of opioids for chronic non-cancer pain have been introduced to combat the opioid crisis. Systematic reviews have evaluated effects of specific interventions (eg, prescriber education, prescription drug monitoring programmes) on patient and population health outcomes and prescriber behaviour. Integration of findings across intervention types is needed to better understand the effects of prescriber-targeted interventions. METHODS AND ANALYSIS: We will conduct an overview of systematic reviews. Eligible systematic reviews will include primary studies that evaluated any intervention targeting the behaviours of physician prescribers of opioids for chronic non-cancer pain in an outpatient or mixed setting, compared with no intervention, usual practice or another active or control intervention. Eligible outcomes will pertain to the intervention effect on patient and population health or opioid prescribing behaviour. We will search MEDLINE, Embase and PsycInfo via Ovid; the Cochrane Database of Systematic Reviews and Epistemonikos from inception. We will also hand search reference lists for additional publications. Screening and data extraction will be conducted independently by two reviewers, with disagreements resolved by consensus or consultation with a third reviewer. The risk of bias of included systematic reviews will be assessed in duplicate by two reviewers using the Risk of Bias in Systematic Reviews tool. Results will be synthesised narratively by intervention type and grouped by outcome. To assist with result interpretation, outcomes will be labelled as intended or unintended according to intervention objectives, and as positive, negative, evidence of no effect or inconclusive evidence according to effect on the population (for patient and population health outcomes) or intervention objectives (for prescriber outcomes). ETHICS AND DISSEMINATION: As the proposed study will use published data, ethics approval is not required. Dissemination of results will be achieved through publication of a manuscript in a peer-reviewed journal and conference presentations. PROSPERO REGISTRATION NUMBER: CRD42020156815.

Practical steps to identifying the research risk of pragmatic trials.

BACKGROUND: Pragmatic randomized clinical trials that compare two or more purportedly "within the standard of care" interventions attempt to provide real-world evidence for policy and practice decisions. There is considerable debate regarding their research risk status, which in turn could lead to debates about appropriate consent requirements. Yet no practical guidance for identifying the research risks of pragmatic randomized clinical trials is available. METHODS: We developed a practical, four-step process for identifying and evaluating the research risk of pragmatic trials that can be applied to those pragmatic randomized clinical trials that compare two or more "standard of care" or "accepted" interventions. RESULTS: Using a variety of examples of standard of care pragmatic randomized clinical trials (ranging from trials comparing: insurance coverage conditions, patient reminders for health screens, intensive care unit procedures, post-stroke interventions, and drugs for life-threatening conditions), we illustrate in a four-step process how any pragmatic randomized clinical trial purportedly comparing standard interventions can be evaluated for their research risks. CONCLUSION: Although determining the risk status of a standard of care pragmatic randomized clinical trial is only one necessary element in the ethical oversight of such pragmatic randomized clinical trials, it is a central element. Our four-step process of pragmatic randomized clinical trial risk determination provides a practical, transparent, and systematic approach with likely low risk of bias.

Ethical Considerations for Phase I Trials in Oncology.

Phase I trials often represent the first occasion where new cancer strategies are tested in patients. Various developments in cancer biology, methodology, regulation, and medical ethics have altered the ethical landscape of such trials. We provide a narrative review of contemporary ethical challenges in design, conduct, and reporting of phase I cancer trials and outline recommendations for addressing each. We organized our review around four topics, supplementing the first three with scoping reviews: (1) benefit/risk, (2) research biopsies, (3) therapeutic misconception and misestimation, and (4) reporting. The main ethical challenges of conducting phase I trials stem from three issues. First, phase I trials often involve higher research burden and scientific uncertainty compared with other cancer trials. Second, many patients arrive at phase I trials at a transitional point in their illness trajectory where they have exhausted standard survival-extending options. Third, phase I trial results play a major role in informing downstream drug development and regulatory decisions. Together, these issues create distinct pressures for study design, ethical review, informed consent, and reporting. Developments in methodology, regulation, cancer biology, and ethical awareness have helped mitigate some of these challenges, while introducing others. We conclude our review with a series of recommendations regarding trial design, ethical review, consent, and reporting. We also outline several unresolved questions that, if addressed, would strengthen the ethical foundation of phase I cancer trials.