Estimating the rate and reasons of clinical trial failure in urologic oncology.

OBJECTIVES: Clinical trials are pillars of modern clinical evidence generation. However, the clinical trial enterprise can be inefficient, and trials often fail before their planned endpoint is reached. We sought to estimate how often urologic oncology trials fail, why trials fail, and associations with trial failure. METHODS: We queried phase 2/3 urologic clinical trial data from ClinicalTrials.gov registered between 2007 and 2019, with status marked as active, completed, or terminated. We extracted relevant trial data, including anticipated and actual accrual, from trial records and ClinicalTrials.gov archives. We manually coded reasons given in the "why stopped" free text field for trial failure into categories (poor accrual, interim results, toxicity/adverse events, study agent unavailable, canceled by the sponsor, inadequate budget, logistics, trial no longer needed, principal investigator left, no reason given, or other). We considered trials terminated for safety or efficacy to be completed trials. Trials marked as terminated for other reasons were considered failed trials. We then estimated the rate of trial failure using competing risks methods. Finally, we assessed associations with trial failure using a Cox proportional hazards model. RESULTS: A total of 1,869 urologic oncology trials were included. Of these, 225 (12.0%) failed, and 51 (2.7%) were terminated for "good" reasons (e.g., toxicity, efficacy). Of the 225 failed trials, 122 (54%) failed due to poor accrual. Failed trials had a lower anticipated accrual than successfully completed trials (55 vs. 63 patients, P<0.001). A total of 6,832 patients were actually accrued to failed trials. The 10-year estimated risk of trial failure was 17% (95% CI 15%-22%). Single center trials, phase 3 trials, drug trials, and trials with exclusively USA sites were more likely to fail. CONCLUSION: We estimate that 17%, or roughly 1 in 6, of urologic oncology trials fail, most frequently for poor accrual. Further investigations are needed into systemic, trial, and site-specific factors that may impact accrual and successful trial completion.

Termination rates and histological reclassification of active surveillance patients with low- and early intermediate-risk prostate cancer: results of the PREFERE trial.

PURPOSE: Active surveillance (AS) strategies for patients with low- and early intermediate-risk prostate cancer are still not consistently defined. Within a controlled randomized trial, active surveillance was compared to other treatment options for patients with prostate cancer. Aim of this analysis was to report on termination rates of patients treated with AS including different grade groups. METHODS: A randomized trial comparing radical prostatectomy, active surveillance, external beam radiotherapy and brachytherapy was performed from 2013 to 2016 and included 345 patients with low- and early intermediate-risk prostate cancer (ISUP grade groups 1 and 2). The trial was prematurely stopped due to slow accrual. A total of 130 patients were treated with active surveillance. Among them, 42 patients were diagnosed with intermediate-risk PCA. Reference pathology and AS quality control were performed throughout. RESULTS: After a median follow-up time of 18.8 months, 73 out of the 130 patients (56%) terminated active surveillance. Of these, 56 (77%) patients were histologically reclassified at the time of rebiopsy, including 35% and 60% of the grade group 1 and 2 patients, respectively. No patients who underwent radical prostatectomy at the time of reclassification had radical prostatectomy specimens ≥ grade group 3. CONCLUSION: In this prospectively analyzed subcohort of patients with AS and conventional staging within a randomized trial, the 2-year histological reclassification rates were higher than those previously reported. Active surveillance may not be based on conventional staging alone, and patients with grade group 2 cancers may be recommended for active surveillance in carefully controlled trials only.

Clinical trials in urological oncology: COVID-19 and the potential need for a new perspective.

The COVID-19 pandemic has led to the suspension, termination or alteration of thousands of clinical trials as the health emergency escalated globally. Whilst the rapid suspension of certain clinical trials was necessary to ensure the safety of high-risk or vulnerable trial participants as well as healthcare workers, the long-term ramifications that this delay will have on the field of urologic oncology is unknown. The COVID-19 pandemic has highlighted the need to plan for and implement new strategies to advance our understanding of unmet areas of need in urologic oncology. The COVID-19 pandemic has led to the suspension, termination or alteration of thousands of clinical trials as the health emergency escalated globally. Whilst the rapid suspension of certain clinical trials was necessary to ensure the safety of high-risk or vulnerable trial participants as well as healthcare workers, the long-term ramifications that this delay will have on the field of urologic oncology is unknown. The COVID-19 pandemic has highlighted the need to plan for and implement new strategies to advance our understanding of unmet areas of need in urologic oncology.

A Bayesian basket trial design accounting for uncertainties of homogeneity and heterogeneity of treatment effect among subpopulations.

Basket trials are a recent and innovative approach in oncological clinical trial design. A basket trial is a type of clinical trial for which eligibility is based on the presence of a specific genomic alteration, irrespective of cancer type. Additionally, basket trials are often used to evaluate the response rate of an investigational therapy across several types of cancer. Recently developed statistical methods for evaluating the response rate in basket trials can be generally categorized into two groups: (a) those that account for the degrees of homogeneity/heterogeneity of response rates among subpopulations, and (b) those using borrowed response rate information across subpopulations to improve the statistical efficiency using Bayesian hierarchical models. In this study, we developed a new basket trial design that accounts for the uncertainties of homogeneity and heterogeneity of response rates among subpopulations using the Bayesian model averaging approach. We demonstrated the utility of the proposed method by comparing our approach against other methods for the two methodological groups using simulated and actual data. On an average, the proposed methods offered an intermediate performance between the BHM-weak and BHM-strong methods. The proposed method would be useful for "signal-finding" basket trials without prior information on the treatment effect of an investigational drug, in part because the proposed method does not require specifications regarding prior distributions of homogeneity response rates among subpopulations.

Comparing Bayesian early stopping boundaries for phase II clinical trials.

When designing phase II clinical trials, it is important to construct interim monitoring rules that achieve a balance between reliable early stopping for futility or safety and maintaining a high true positive probability (TPP), which is the probability of not stopping if the new treatment is truly safe and effective. We define and compare several methods for specifying early stopping boundaries as functions of interim sample size, rather than as fixed cut-offs, using Bayesian posterior probabilities as decision criteria. We consider boundaries with constant, linear, or exponential shapes. For design optimization criteria, we use the TPP and mean number of patients enrolled in the trial. Simulations to evaluate and compare the designs' operating characteristics under a range of scenarios show that, while there is no uniformly optimal boundary, an appropriately calibrated exponential shape maintains high TPP while limiting the number of patients assigned to a treatment with an inferior response rate or an excessive toxicity rate.

Optimal adaptive single-arm phase II trials under quantified uncertainty.

Single-arm trials with binary endpoint are firmly established in e.g., early clinical oncology. Here, two-stage designs are often employed to allow early termination of the trial in the case of an unexpectedly large or small response rate to the new treatment. Various designs have been proposed over the last few years which usually require strong assumptions about the true response rate during planning. Often, these designs are not robust to deviations from the planning assumptions. In this paper, we define a Bayesian framework for scoring two-stage designs under uncertainty and investigate the characteristics of designs optimizing a commonly employed performance score of Liu et al. The resulting optimal designs are compared with an alternative, utility-based approach incorporating expected power and sample size. We provide insights in the underlying implicit assumptions of using expected power for scoring adaptive designs and relate the global score function to the practice of sample size recalculation based on conditional power. An in-depth comparison of the features of the different performance scores and their respective optimizing designs provides the guidance for practitioners who face the problem of choosing between the various options. A software implementation of the proposed methods is publicly available online.

Rates of Discontinuation and Nonpublication of Head and Neck Cancer Randomized Clinical Trials.

Importance: Randomized clinical trials (RCTs) play an important role in clinical decision-making, and discontinuation or nonpublication of these trials are causes of great concern. The extent of discontinued or unpublished RCTs about head and neck cancer remains unclear. Objective: To assess the rate of discontinuation or nonpublication of RCTs involving patients with head and neck cancer. This objective was measured by observing 3 domains: discontinuation of trial, nonpublication of trial data, and feasibility of contacting trial investigators of aforementioned trials. Evidence Review: For this study, the sample was derived using the ClinicalTrials.gov advanced search feature on March 18, 2019, to locate completed and discontinued RCTs pertaining to head and neck cancer registered before this date. Trials were analyzed to identify reasons for trial discontinuation and publication status of each trial. If publication status or reason for trial discontinuation was not allocated through the systematic search of ClinicalTrials.gov, the corresponding author was emailed to determine publication status. Findings: After exclusions, 130 RCTs were included. Of these trials, 92 (70.8%) were completed and 38 (29.2%) were discontinued for various reasons. The most common reason for discontinuation of trials was committee recommendations. Of the 130 analyzed trials, 67 (51.5%) were published in a peer-reviewed journal and 63 (48.5%) were unpublished trials. Of the 92 completed trials, 55 (59.8%) were published and 37 (40.2%) remained unpublished 3 or more years after trial completion. Trials funded by other sources (private, nonprofit, or the National Institutes of Health) were more likely to reach publication than industry-funded RCTs (unadjusted odds ratio, 4.3 [95% CI, 1.3-14.0]; adjusted odds ratio, 4.1 [95% CI, 1.2-14.3]). Conclusions and Relevance: Of RCTs in head and neck cancer, 29.2% were discontinued and 40.2% completed trials never reached publication. The findings suggest that needs exist for RCT guidance of head and neck cancer. The reporting of reasons for trial discontinuation appears to be lacking, and trial publication rates were low. This study is relevant to many physicians and researchers because it identifies potential sources of decreased research productivity and ethics.

Discontinuation of surgical versus nonsurgical clinical trials: an analysis of 88,498 trials.

BACKGROUND: It has been previously reported that over 20% of surgical trials will be discontinued prematurely raising ethical and financial concerns. Previous studies have been limited in scope owing to the need for manual review of selected trials. To date, there has been no broad analysis comparing surgical and nonsurgical registered clinical trials. MATERIALS AND METHODS: ClinicalTrials.gov was queried October 7, 2017 for all US trials from 2005 to 2017. Trials were assigned to surgical or nonsurgical groups by automated sorting. The sorting algorithm was validated by comparison with manual assignments made by blinded investigators. Comparisons were made between trial status, funding sources, and trial design. The reasons for discontinuation were examined and tabulated. RESULTS: The database search yielded 82,719 nonsurgical and 5779 surgical trials after automatic assignment. The algorithm for assignments had an overall accuracy of 87.99% and a positive likelihood ratio of 6.09 and negative likelihood ratio of 0.093. Significant differences existed in trial status (nonsurgical versus surgical: completed: 55.51% versus 39.49%, P < 0.001 and discontinued: 11.07% versus 15.97%, P < 0.001). Discontinuation due to poor recruitment was more commonly cited by surgical trials (44.65% versus 34.74% P < 0.001). Industry funding predicted discontinuation for all trials (odds ratio 1.63 P < 0.001) and surgical trials independently (OR 1.25 P = 0.041). Patient enrollment, reporting results, and NIH funding were all protective against discontinuation. CONCLUSIONS: Surgical trials are more likely to prematurely discontinue than nonsurgical trials. Industry funding independently predicts trial discontinuation. Poor recruitment is a major cause of early trial discontinuation for all trials and is more pronounced in surgical trials.

Statistical controversies in clinical research: futility analyses in oncology-lessons on potential pitfalls from a randomized controlled trial.

BACKGROUND: Pre-planned futility analyses are commonly used in oncology studies. The LUME-Lung 2 study (NCT00806819; 1199.14) was stopped early based on a pre-planned, non-binding futility analysis of investigator-assessed progression-free survival (PFS), although subsequent analysis showed that the primary endpoint of improvement in centrally reviewed PFS was met. Retrospective analyses were conducted to understand the discrepancy between interim futility and final analyses. MATERIALS AND METHODS: LUME-Lung 2 investigated nintedanib in combination with pemetrexed versus placebo‒pemetrexed for the treatment of patients with advanced or recurrent non-squamous non-small cell lung cancer who had relapsed or failed one prior line of chemotherapy. Pre-planned futility analysis was carried out by the Data Monitoring Committee (DMC) after 50% of the events for the primary PFS analysis (713 events) had occurred; the threshold for futility was a conditional power of < 20%. Conditional/predictive powers and hazard ratios were calculated retrospectively after varying percentages of events had occurred for both investigator- and centrally reviewed PFS. RESULTS: At the time of the pre-planned futility analysis, the conditional power was 10.3% and the predictive power was 18.5%; no safety issues were identified. Retrospective analysis showed that the conditional and predictive powers fluctuated considerably over time for both investigator- and centrally reviewed PFS and that the power only dropped by a notable amount, and below the futility threshold, at the time of the futility analysis. CONCLUSIONS: Retrospective investigations suggest that, had the DMC analysis been carried out at another time point, or had centrally reviewed PFS data been used, the futility outcome may have been different and the trial may have been continued. The design of futility analyses requires careful consideration and confirming negative futility outcomes by second analysis may be appropriate. TRIAL NUMBER: NCT00806819.

Early Termination of Randomized Clinical Trials in Orthopaedics.

Randomized controlled clinical trials (RCTs) in orthopaedics, similar to all medical fields, provide the highest level of clinical data and constitute the cornerstone for evidence-based therapeutic advances. Orthopaedic clinical trials face the same challenges as in other medical fields, such as insufficient recruitment, unforeseen adverse events, and futility. In this article, we highlight the reasons for early termination of clinical trials and provide examples of each type.

Failure of Investigational Drugs in Late-Stage Clinical Development and Publication of Trial Results.

IMPORTANCE: Many investigational drugs fail in late-stage clinical development. A better understanding of why investigational drugs fail can inform clinical practice, regulatory decisions, and future research. OBJECTIVE: To assess factors associated with regulatory approval or reasons for failure of investigational therapeutics in phase 3 or pivotal trials and rates of publication of trial results. DESIGN, SETTING, AND PARTICIPANTS: Using public sources and commercial databases, we identified investigational therapeutics that entered pivotal trials between 1998 and 2008, with follow-up through 2015. Agents were classified by therapeutic area, orphan designation status, fast track designation, novelty of biological pathway, company size, and as a pharmacologic or biologic product. MAIN OUTCOMES AND MEASURES: For each product, we identified reasons for failure (efficacy, safety, commercial) and assessed the rates of publication of trial results. We used multivariable logistic regression models to evaluate factors associated with regulatory approval. RESULTS: Among 640 novel therapeutics, 344 (54%) failed in clinical development, 230 (36%) were approved by the US Food and Drug Administration (FDA), and 66 (10%) were approved in other countries but not by the FDA. Most products failed due to inadequate efficacy (n = 195; 57%), while 59 (17%) failed because of safety concerns and 74 (22%) failed due to commercial reasons. The pivotal trial results were published in peer-reviewed journals for 138 of the 344 (40%) failed agents. Of 74 trials for agents that failed for commercial reasons, only 6 (8.1%) were published. In analyses adjusted for therapeutic area, agent type, firm size, orphan designation, fast-track status, trial year, and novelty of biological pathway, orphan-designated drugs were significantly more likely than nonorphan drugs to be approved (46% vs 34%; adjusted odds ratio [aOR], 2.3; 95% CI, 1.4-3.7). Cancer drugs (27% vs 39%; aOR, 0.5; 95% CI, 0.3-0.9) and agents sponsored by small and medium-size companies (28% vs 42%; aOR, 0.4; 95% CI, 0.3-0.7) were significantly less likely to be approved. CONCLUSIONS AND RELEVANCE: Roughly half of investigational drugs entering late-stage clinical development fail during or after pivotal clinical trials, primarily because of concerns about safety, efficacy, or both. Results for the majority of studies of investigational drugs that fail are not published in peer-reviewed journals.

Enrollment and Stopping Rules for Managing Toxicity Requiring Long Follow-Up in Phase II Oncology Trials.

Monitoring of toxicity is often conducted in Phase II trials in oncology to avoid an excessive number of toxicities if the wrong dose is chosen for Phase II. Existing stopping rules for toxicity use information from patients who have already completed follow-up. We describe a stopping rule that uses all available data to determine whether to stop for toxicity or not when follow-up for toxicity is long. We propose an enrollment rule that prescribes the maximum number of patients that may be enrolled at any given point in the trial.

Bayesian sequential monitoring design for two-arm randomized clinical trials with noncompliance.

In early-phase clinical trials, interim monitoring is commonly conducted based on the estimated intent-to-treat effect, which is subject to bias in the presence of noncompliance. To address this issue, we propose a Bayesian sequential monitoring trial design based on the estimation of the causal effect using a principal stratification approach. The proposed design simultaneously considers efficacy and toxicity outcomes and utilizes covariates to predict a patient's potential compliance behavior and identify the causal effects. Based on accumulating data, we continuously update the posterior estimates of the causal treatment effects and adaptively make the go/no-go decision for the trial. Numerical results show that the proposed method has desirable operating characteristics and addresses the issue of noncompliance.

Adult cancer clinical trials that fail to complete: an epidemic?

The number and diversity of cancer therapeutics in the pipeline has increased over the past decade due to an enhanced understanding of cancer biology and the identification of novel therapeutic targets. At the same time, the cost of bringing new drugs to market and the regulatory burdens associated with clinical drug development have progressively increased. The finite number of eligible patients and limited financial resources available to evaluate promising new therapeutics represent rate-limiting factors in the effort to translate preclinical discoveries into the next generation of standard therapeutic approaches. Optimal use of resources requires understanding and ultimately addressing inefficiencies in the cancer clinical trials system. Prior analyses have demonstrated that a large proportion of trials initiated by the National Cancer Institute (NCI) Cooperative Group system are never completed. While NCI Cooperative Group trials are important, they represent only a small proportion of all cancer clinical trials performed. Herein, we explore the problem of cancer clinical trials that fail to complete within the broader cancer clinical trials enterprise. Among 7776 phase II-III adult cancer clinical trials initiated between 2005-2011, we found a seven-year cumulative incidence of failure to complete of approximately 20% (95% confidence interval = 18% to 22%). Nearly 48000 patients were enrolled in trials that failed to complete. These trials likely contribute little to the scientific knowledge base, divert resources and patients from answering other critical questions, and represent a barrier to progress.

Impact of lack-of-benefit stopping rules on treatment effect estimates of two-arm multi-stage (TAMS) trials with time to event outcome.

BACKGROUND: In 2011, Royston et al. described technical details of a two-arm, multi-stage (TAMS) design. The design enables a trial to be stopped part-way through recruitment if the accumulating data suggests a lack of benefit of the experimental arm. Such interim decisions can be made using data on an available 'intermediate' outcome. At the conclusion of the trial, the definitive outcome is analyzed. Typical intermediate and definitive outcomes in cancer might be progression-free and overall survival, respectively. In TAMS designs, the stopping rule applied at the interim stage(s) affects the sampling distribution of the treatment effect estimator, potentially inducing bias that needs addressing. METHODS: We quantified the bias in the treatment effect estimator in TAMS trials according to the size of the treatment effect and for different designs. We also retrospectively 'redesigned' completed cancer trials as TAMS trials and used the bootstrap to quantify bias. RESULTS: In trials in which the experimental treatment is better than the control and which continue to their planned end, the bias in the estimate of treatment effect is small and of no practical importance. In trials stopped for lack of benefit at an interim stage, the treatment effect estimate is biased at the time of interim assessment. This bias is markedly reduced by further patient follow-up and reanalysis at the planned 'end' of the trial. CONCLUSIONS: Provided that all patients in a TAMS trial are followed up to the planned end of the trial, the bias in the estimated treatment effect is of no practical importance. Bias correction is then unnecessary.

Adaptive Bayesian randomized trials: realizing their potential.

Bayesian adaptive designs offer the flexibility to adapt the conduct of a trial in response to accumulating evidence. This ability of the trial to adapt is especially appealing when studying an intervention that evolves rapidly. Examples of design adaptations include dropping arms from a study, sample size re-estimation, or stopping a trial early. The choice of adaptive design must match the objectives of the trial, and this paper gives examples of designs suitable for exploratory trials, explanatory trials, and trials assessing cost-effectiveness.

The dangers of stopping a trial too early.

To ensure that participants in randomized controlled trials are protected from harm, interim analyses and review of results by an independent data monitoring committee have become standard practice. If an analysis of accumulating data partway through a trial reveals an unanticipated degree of benefit or toxicity, or differences in outcomes between the intervention and control groups are so unimpressive that any prospect of a positive result with the planned sample size is extremely unlikely, investigators may stop the trial earlier than originally scheduled. The practice of stopping randomized controlled trials early is, however, problematic, especially if the trial is stopped for apparent benefit. Concerns in trials stopped early for apparent benefit include appropriate interpretation of results and ethical problems concerning trial participants, clinicians, and society as a whole. In this article, we review the epidemiology of trials stopped early and illustrate some of the problems and controversies associated with stopping randomized controlled trials early for apparent benefit. Finally, we offer guidance for clinicians, those running clinical trials, and authors of systematic reviews.

Civil society perspectives on negative biomedical HIV prevention trial results and implications for future trials.

Community engagement is crucial to ongoing development and testing of sorely needed new biomedical HIV prevention technologies. Yet, negative trial results raise significant challenges for community engagement in HIV prevention trials, including the early termination of the Cellulose Sulfate microbicide trial and two Phase IIb HIV vaccine trials (STEP and Phambili). The present study aimed to explore the perspectives and experiences of civil society organization (CSO) representatives regarding negative HIV prevention trial results and perceived implications for future trials. We conducted in-depth interviews with 14 respondents from a broad range of South African and international CSOs, and analyzed data using thematic analysis. CSO representatives reported disappointment in response to negative trial results, but acknowledged such outcomes as inherent to clinical research. Respondents indicated that in theory negative trial results seem likely to impact on willingness to participate in future trials, but that in practice people in South Africa have continued to volunteer. Negative trial results were described as having contributed to improving ethical standards, and to a re-evaluation of the scientific agenda. Such negative results were identified as potentially impacting on funding for trials and engagement activities. Our findings indicate that trial closures may be used constructively to support opportunities for reflection and renewed vigilance in strategies for stakeholder engagement, communicating trial outcomes, and building research literacy among communities; however, these strategies require sustained resources for community engagement and capacity-building.