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.

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.

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.

Bayesian optimal phase II clinical trial design with time-to-event endpoint.

We propose a Bayesian optimal phase II (BOP2) design for clinical trials with a time-to-event endpoint (eg, progression-free survival [PFS]) or co-primary endpoints consisted of a time-to-event endpoint and a categorical endpoint (eg, PFS and toxicity). We use an exponential-inverse gamma model to model the time to event. At each interim, the go/no-go decision is made by comparing the posterior probabilities of the event of interest with an adaptive probability cutoff. The BOP2 design is flexible in the number of interim looks and applicable to both single-arm and two-arm trials. The design maximizes the power for detecting effective treatments, with a well-controlled type I error, thereby bridging the gap between Bayesian designs and frequentist designs. The BOP2 design is easy to implement. Its stopping boundary can be enumerated and included in study protocol before the onset of the trial for single-arm studies. Simulation studies show that the BOP2 design has favorable operating characteristics, with higher power and lower risk of incorrectly terminating the trial than some Bayesian phase II designs. The software to implement the BOP2 design will be freely available at www.trialdesign.org.

Reasons for Premature Conclusion of Late Phase Clinical Trials: An Analysis of ClinicalTrials.gov Registered Phase III Trials.

BACKGROUND: Confirmatory phase III trials aim to provide decisive evidence about a medical product's safety and efficacy. Although these trials are planned and conducted based on accumulated knowledge, they are not without risk or uncertainty. A trial prematurely concluding contributes to great loss in both financial and human research resources. METHODS: We categorized and evaluated trials concluded prematurely after recruitment had begun, as registered in Clinical Trials.gov between January 2013 and August 2017. RESULTS: We found 9828 registered interventional phase III trials; of those, 320 were concluded prematurely. Many clinical trials were concluded prematurely for reasons related to reducing participant risk, such as interim stopping for safety, efficacy, or futility. Yet, 70% trials were halted for other reasons, such as insufficient recruitment (the most often cited reason) or unspecified business decisions. Of all prematurely concluded trials, 102 trials evaluated 72 different novel therapeutics; in 66.7% of these trials, the clinical development program was stopped entirely. Most of the prematurely concluded trials (78%) had not provided results to ClinicalTrials.gov at the time of this analysis. CONCLUSIONS: Evaluation of the factors that influence premature conclusion could inform solutions for improving research participation and help ensure trial completion. Registering and reporting results acknowledges the voluntary contribution and consent expectations of research participants.

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.

Evaluating futility of a binary clinical endpoint using early read-outs.

Interim analyses are routinely used to monitor accumulating data in clinical trials. When the objective of the interim analysis is to stop the trial if the trial is deemed futile, it must ideally be conducted as early as possible. In trials where the clinical endpoint of interest is only observed after a long follow-up, many enrolled patients may therefore have no information on the primary endpoint available at the time of the interim analysis. To facilitate earlier decision-making, one may incorporate early response data that are predictive for the primary endpoint (eg, an assessment of the primary endpoint at an earlier time) in the interim analysis. Most attention so far has been given to the development of interim test statistics that include such short-term endpoints, but not to decision procedures. Existing tests moreover perform poorly when the information is scarce, eg, due to rare events, when the cohort of patients with observed primary endpoint data is small, or when the short-term endpoint is a strong but imperfect predictor. In view of this, we develop an interim decision procedure based on the conditional power approach that utilizes the short-term and long-term binary endpoints in a framework that is expected to provide reliable inferences, even when the primary endpoint is only available for a few patients, and has the added advantage that it allows the use of historical information. The operational characteristics of the proposed procedure are evaluated for the phase III clinical trial that motivated this approach, using simulation studies.

Performance and predictors of recruitment success in National Heart, Lung, and Blood Institute's cardiovascular clinical trials.

Background/Aims Identifying predictors of recruitment success in clinical trials, particularly prior to study launch, could contribute to higher study completion rates and improved scientific return on investment. This article evaluates the performance of clinical trials funded by the National Heart, Lung, and Blood Institute that began recruitment before and after implementation of National Heart, Lung, and Blood Institute's 2009 Accrual Policy and identifies study-related factors that predict recruitment success. Methods A retrospective analysis of National Heart, Lung, and Blood Institute's cardiovascular clinical trials with initial funding from 1996 to 2012 was performed to assess recruitment success. Success was defined as ≥100% enrollment of the proposed sample size within the duration initially proposed by investigators. Trials were assigned to categories (pre-policy vs post-policy) based on whether the first patient was enrolled before or after the 2009 Accrual Policy implementation. Potential determinants of successful recruitment were evaluated using multivariable logistic regression. Results Of 167 trials analyzed, 26.3% met the definition of success. Twenty-four trials (14.4%) were terminated early and 15 (62.5%) for insufficient recruitment. Trials failed due to <100% enrollment (22.8%), longer duration (19.8%), or both (31.1%). Trials testing behavioral interventions, those conducted within a National Heart, Lung, and Blood Institute-funded network, and those with normal controls were predictive of success. The proportion of successful clinical trials increased from 23% in the pre-policy era to 30% post-policy, although the difference was not statistically significant ( p = 0.29). Conclusion Enrollment success rates for National Heart, Lung, and Blood Institute's clinical trials are concerning. The 2009 National Heart, Lung, and Blood Institute Accrual Policy did not significantly improve trial success. Clinical trials testing behavioral interventions, those conducted within networks, and those with normal controls were predictive of recruitment success. Components of networks may provide model practices to help other trials attain success, including close attention to oversight activities such as recruitment plans, real-time enrollment monitoring, corrective action plans to address shortfalls, and close sponsor-investigator collaborations.

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.

Randomized controlled trials in pediatric patients had higher completion rates than adult trials: a cross-sectional study.

OBJECTIVE: Conduct of clinical trials is perceived to be more challenging in children than in adults. This study aimed to evaluate the impact of the age of participants on completion rates of randomized controlled trials (RCTs). STUDY DESIGN AND SETTING: A cross-sectional study on RCTs registered in the ClinicalTrials.gov database. All RCTs registered up to December 31, 2016, were extracted and were classified according to their recruitment status: active, completed, or discontinued and according to the age of participants: children (<17 years), adults (≥18 years), and mixed-age population. A logistic regression model was applied to assess the impact of participant's age category on trial completion while controlling for other relevant trial features. RESULTS: A total of 65,095 registered RCTs were identified. Among pediatric trials, 49.9% were completed and 8.5% were discontinued. Among adult and mixed age RCTs, respectively, 49.7% and 47.9% were completed whereas, 10.2% and 9.4% were discontinued. Overall, pediatric and mixed age RCTs were more likely to be registered as completed than adult RCTs (odds ratio: 1.16, 95% CI: 1.02-1.30; odds ratio: 1.15, 95% CI: 1.04-1.27, respectively). Also, funding source, type of intervention under evaluation, primary trial purpose, use of a blinding procedure, use of a placebo, and participants' assignment model were identified as independent predictors of RCT completion. CONCLUSION: Contrary to current perceptions and despite several specific challenges, recruitment of children and adolescents is not a limiting factor to completing a RCT. Other study features such as funding source, impact completeness and should be carefully considered before initiating research.

Bayesian optimal response-adaptive design for binary responses using stopping rule.

Response-adaptive designs are used in phase III clinical trials to allocate a larger number of patients to the better treatment arm. Optimal designs are explored in the recent years in the context of response-adaptive designs, in the frequentist view point only. In the present paper, we propose some response-adaptive designs for two treatments based on Bayesian prediction for phase III clinical trials. Some properties are studied and numerically compared with some existing competitors. A real data set is used to illustrate the applicability of the proposed methodology where we redesign the experiment using parameters derived from the data set.

Nonpublication and discontinuation of randomised controlled trials in newborns.

AIM: To determine the rate of nonpublication and discontinuation of randomised controlled trials (RCTs) in newborns. METHODS: This was a retrospective, cross-sectional study of RCTs registered with the Australian and New Zealand Clinical Trials Registry (ANZCTR) between 2008 and 2012. RESULTS: Fifty trials were identified, of which 23 (46%) were retrospectively registered. Thirty trials (60%) were published. After a median follow-up of 8.0 (range 4.6-17.4) years from Research Ethics Committee approval, 15 of 41 completed trials (37%) remained unpublished, representing 5422 neonatal trial participants. Nine trials (18%) were discontinued, including four that were published. The most frequent reason for discontinuation was poor recruitment (n = 4). Sample size discrepancies between registration and publication were found in 17 (65%) of the 26 completed, published trials. In nine (35%) of these trials, the calculated sample size in the method section of the published article differed from the planned sample size in the trial registry (relative difference -20% to +33%). CONCLUSION: Nonpublication and discontinuation of RCTs conducted in newborns is common. Additional efforts are needed to minimise the number of neonatal trial participants that are exposed to interventions without subsequent publication.

Early termination of cardiovascular trials as a consequence of poor accrual: analysis of ClinicalTrials.gov 2006-2015.

OBJECTIVES: To present a snapshot of experimental cardiovascular research with a focus on geographical and temporal patterns of early termination due to poor accrual. SETTING: The Aggregate Analysis of ClinicalTrials.gov (AACT) database, reflecting ClinicalTrials.gov as of 27 March 2016. DESIGN: The AACT database was searched for all cardiovascular clinical trials that started from January 2006 up to December 2015. RESULTS: Thirteen thousand and seven hundred twenty-nine cardiovascular trials were identified. Of these, 8900 (65%) were classified as closed studies. Globally, 11% of closed trials were terminated. This proportion varied from 9.6% to 14% for trials recruiting from Europe and Americas, respectively, with a slightly decreasing trend (p=0.02) over the study period. The most common reason for trials failing to complete was poor accrual (41%). Intercontinental trials exhibited lower figures of poor accrual as the reason for their early stopping, as compared with trials recruiting in a single continent (28% vs 44%, p=0.002). CONCLUSIONS: Poor accrual significantly challenges the successful completion of cardiovascular clinical trials. Findings are suggestive of a positive effect of globalisation of cardiovascular clinical research on the achievement of enrolment goals within a reasonable time frame.

Discontinuation and non-publication of clinical trials in cardiovascular medicine.

BACKGROUND: Appropriate dissemination of clinical data is crucial for minimising bias. Despite this, high rates of study discontinuation and non-publication have been reported among clinical trials. Cardiovascular medicine receives a substantial proportion of academic funding; however, predictors of non-publication among cardiovascular trials are not well-established. METHODS: The National Clinical Trials database was searched for cardiovascular trials completed between January 2010 and January 2014. Associated publications were identified in Medline or Embase. Relevant variables were extracted and subject to chi-squared and logistic regression to identify predictors of discontinuation and non-publication. RESULTS: After reviewing 2035 trials, 431 trials were included, of which 82.1% (n=354; 119,233 participants) were completed. Among completed trials, 70.3% (n=249; 99,095 participants) were published. Industry funding was associated with increased likelihood of non-publication (odds ratio [OR] 2.84; 95% confidence interval [CI] 1.47-5.51; P=0.002), while non-randomised studies were more likely to remain unpublished than randomised counterparts. Industry-funded studies were over three times more likely to be discontinued than those sponsored by academic institutions (OR 3.89; CI 1.54-9.83; P=0.004). Trials studying heart failure and atrial fibrillation were more likely to be discontinued compared to trials studying coronary artery disease (OR 2.83; CI 1.23-6.51; and OR 3.10; CI 1.21-7.96, respectively). Of the total 135,714 participants, 25,565 were recruited into unpublished studies. CONCLUSIONS: Discontinuation and non-publication of cardiovascular trials are common, resulting in data from thousands of participants remaining unpublished. Funding source and randomisation are strong predictors of non-publication, while sponsor type, phase and blinding status are key predictors of discontinuation.