Using short-term endpoints to improve interim decision making and trial duration in two-stage phase II trials with nested binary endpoints.

In oncology, phase II clinical trials are often planned as single-arm two-stage designs with a binary endpoint, for example, progression-free survival after 12 months, and the option to stop for futility after the first stage. Simon's two-stage design is a very popular approach but depending on the follow-up time required to measure the patients' outcomes the trial may have to be paused undesirably long. To shorten this forced interruption, it was proposed to use a short-term endpoint for the interim decision, such as progression-free survival after 3 months. We show that if the assumptions for the short-term endpoint are misspecified, the decision-making in the interim can be misleading, resulting in a great loss of statistical power. For the setting of a binary endpoint with nested measurements, such as progression-free survival, we propose two approaches that utilize all available short-term and long-term assessments of the endpoint to guide the interim decision. One approach is based on conditional power and the other is based on Bayesian posterior predictive probability of success. In extensive simulations, we show that both methods perform similarly, when appropriately calibrated, and can greatly improve power compared to the existing approach in settings with slow patient recruitment. Software code to implement the methods is made publicly available.

Calculating power for the Finkelstein and Schoenfeld test statistic for a composite endpoint with two components.

The Finkelstein and Schoenfeld (FS) test is a popular generalized pairwise comparison approach to analyze prioritized composite endpoints (eg, components are assessed in order of clinical importance). Power and sample size estimation for the FS test, however, are generally done via simulation studies. This simulation approach can be extremely computationally burdensome, compounded by increasing number of composite endpoints and with increasing sample size. Here we propose an analytical solution to calculate power and sample size for commonly encountered two-component hierarchical composite endpoints. The power formulas are derived assuming underlying distributions in each of the component outcomes on the population level, which provide a computationally efficient and practical alternative to the standard simulation approach. Monte Carlo simulation results demonstrate that performance of the proposed power formulas are consistent with that of the simulation approach, and have generally desirable objective properties including robustness to mis-specified distributional assumptions. We demonstrate the application of the proposed formulas by calculating power and sample size for the Transthyretin Amyloidosis Cardiomyopathy Clinical Trial.

Sample size estimation using a latent variable model for mixed outcome co-primary, multiple primary and composite endpoints.

Mixed outcome endpoints that combine multiple continuous and discrete components are often employed as primary outcome measures in clinical trials. These may be in the form of co-primary endpoints, which conclude effectiveness overall if an effect occurs in all of the components, or multiple primary endpoints, which require an effect in at least one of the components. Alternatively, they may be combined to form composite endpoints, which reduce the outcomes to a one-dimensional endpoint. There are many advantages to joint modeling the individual outcomes, however in order to do this in practice we require techniques for sample size estimation. In this article we show how the latent variable model can be used to estimate the joint endpoints and propose hypotheses, power calculations and sample size estimation methods for each. We illustrate the techniques using a numerical example based on a four-dimensional endpoint and find that the sample size required for the co-primary endpoint is larger than that required for the individual endpoint with the smallest effect size. Conversely, the sample size required in the multiple primary case is similar to that needed for the outcome with the largest effect size. We show that the empirical power is achieved for each endpoint and that the FWER can be sufficiently controlled using a Bonferroni correction if the correlations between endpoints are less than 0.5. Otherwise, less conservative adjustments may be needed. We further illustrate empirically the efficiency gains that may be achieved in the composite endpoint setting.

Confirmatory adaptive group sequential designs for single-arm phase II studies with multiple time-to-event endpoints.

Existing methods concerning the assessment of long-term survival outcomes in one-armed trials are commonly restricted to one primary endpoint. Corresponding adaptive designs suffer from limitations regarding the use of information from other endpoints in interim design changes. Here we provide adaptive group sequential one-sample tests for testing hypotheses on the multivariate survival distribution derived from multi-state models, while making provision for data-dependent design modifications based on all involved time-to-event endpoints. We explicitly elaborate application of the methodology to one-sample tests for the joint distribution of (i) progression-free survival (PFS) and overall survival (OS) in the context of an illness-death model, and (ii) time to toxicity and time to progression while accounting for death as a competing event. Large sample distributions are derived using a counting process approach. Small sample properties are studied by simulation. An already established multi-state model for non-small cell lung cancer is used to illustrate the adaptive procedure.

Copy Number Variation and Rearrangements Assessment in Cancer: Comparison of Droplet Digital PCR with the Current Approaches.

The cytogenetic and molecular assessment of deletions, amplifications and rearrangements are key aspects in the diagnosis and therapy of cancer. Not only the initial evaluation and classification of the disease, but also the follow-up of the tumor rely on these laboratory approaches. The therapeutic choice can be guided by the results of the laboratory testing. Genetic deletions and/or amplifications directly affect the susceptibility or the resistance to specific therapies. In an era of personalized medicine, the correct and reliable molecular characterization of the disease, also during the therapeutic path, acquires a pivotal role. Molecular assays like multiplex ligation-dependent probe amplification and droplet digital PCR represent exceptional tools for a sensitive and reliable detection of genetic alterations and deserve a role in molecular oncology. In this manuscript we provide a technical comparison of these two approaches with the golden standard represented by fluorescence in situ hybridization. We also describe some relevant targets currently evaluated with these techniques in solid and hematologic tumors.

Endoscopy and central reading in inflammatory bowel disease clinical trials: achievements, challenges and future developments.

Central reading, that is, independent, off-site, blinded review or reading of imaging endpoints, has been identified as a crucial component in the conduct and analysis of inflammatory bowel disease clinical trials. Central reading is the final step in a workflow that has many parts, all of which can be improved. Furthermore, the best reading algorithm and the most intensive central reader training cannot make up for deficiencies in the acquisition stage (clinical trial endoscopy) or improve on the limitations of the underlying score (outcome instrument). In this review, academic and industry experts review scoring systems, and propose a theoretical framework for central reading that predicts when improvements in statistical power, affecting trial size and chances of success, can be expected: Multireader models can be conceptualised as statistical or non-statistical (social). Important organisational and operational factors, such as training and retraining of readers, optimal bowel preparation for colonoscopy, video quality, optimal or at least acceptable read duration times and other quality control matters, are addressed as well. The theory and practice of central reading and the conduct of endoscopy in clinical trials are interdisciplinary topics that should be of interest to many, regulators, clinical trial experts, gastroenterology societies and those in the academic community who endeavour to develop new scoring systems using traditional and machine learning approaches.

Statistical aspects in adjuvant and neoadjuvant trials for gastrointestinal cancer in 2020: focus on time-to-event endpoints.

PURPOSE OF REVIEW: Clinical-trial design, analysis, and interpretation entails the use of efficient and reliable endpoints. Statistical issues related to endpoints warrant continued attention, as they may have a substantial impact on the conduct of clinical trials and on interpretation of their results. RECENT FINDINGS: We review concepts and discuss recent developments related to the use of time-to-event endpoints in studies on adjuvant and neoadjuvant therapy for colon, pancreatic, and gastric adenocarcinomas. The definition of endpoints has varied to a considerable extent in these settings. Although these variations are relevant in interpreting results from individual trials, they probably have a small impact when considered in aggregate. In terms of surrogacy, most published reports so far have used aggregated data. A few studies based on the preferred method of a metaanalysis of individual-patient data have shown that disease-free survival (DFS) is a surrogate for overall survival in the adjuvant therapy of stage III colon cancer and in gastric cancer, whereas DFS with a landmark of six months is a surrogate for overall survival in the neoadjuvant therapy of adenocarcinoma of the esophagus, gastroesophageal junction, or stomach. SUMMARY: Testing novel agents in gastrointestinal cancer requires continued attention to statistical issues related to endpoints.

Core outcome set measurement for future clinical trials in acute myeloid leukemia: the HARMONY study protocol using a multi-stakeholder consensus-based Delphi process and a final consensus meeting.

BACKGROUND: Acute myeloid leukemia (AML) is the most common acute leukemia in adults and has an unacceptably low cure rate. In recent years, a number of new treatment strategies and compounds were developed for the treatment of AML. There were several randomized controlled clinical trials with the objective to improve patients' management and patients' outcome in AML. Unfortunately, these trials are not always directly comparable since they do not measure the same outcomes, and currently there are no core outcome sets that can be used to guide outcome selection and harmonization in this disease area. The HARMONY (Healthcare Alliance for Resourceful Medicine Offensive against Neoplasms in Hematology) Alliance is a public-private European network established in 2017 and currently includes 53 partners and 32 associated members from 22 countries. Amongst many other goals of the HARMONY Alliance, Work Package 2 focuses on defining outcomes that are relevant to each hematological malignancy. Accordingly, this pilot study will be performed to define a core outcome set in AML. METHODS: The pilot study will use a three-round Delphi survey and a final consensus meeting to define a core outcome set. Participants will be recruited from different stakeholder groups, including patients, clinicians, regulators and members of the European Federation of Pharmaceutical Industries and Associations. At the pre-Delphi stage, a literature research was conducted followed by several semi-structured interviews of clinical public and private key opinion leaders. Subsequently, the preliminary outcome list was discussed in several multi-stakeholder face-to-face meetings. The Delphi survey will reduce the preliminary outcome list to essential core outcomes. After completion of the last Delphi round, a final face-to-face meeting is planned to achieve consensus about the core outcome set in AML. DISCUSSION: As part of the HARMONY Alliance, the pilot Delphi aims to define a core outcome set in AML on the basis of a multi-stakeholder consensus. Such a core outcome set will help to allow consistent comparison of future clinical trials and real-world evidence research and ensures that appropriate outcomes valued by a range of stakeholders are measured within future trials.

Guidelines for time-to-event end-point definitions in adjuvant randomised trials for patients with localised colon cancer: Results of the DATECAN initiative.

BACKGROUND: The variability of definitions for time-to-event (TTE) end-points impacts the conclusions of randomised clinical trials (RCTs). The Definition for the Assessment of Time-to-event Endpoints in CANcer (DATECAN) initiative aims to provide consensus definitions for TTE end-points used in RCTs. Here, we formulate guidelines for adjuvant colon cancer RCTs. METHODS: We performed a literature review to identify TTE end-points and events included in their definition in RCT publications. Then, a consensus was reached among a panel of international experts, using a formal modified Delphi method, with 2 rounds of questionnaires and an in-person meeting. RESULTS: Twenty-four experts scored 72 events involved in 6 TTE end-points. Consensus was reached for 24%, 57% and 100% events after the first round, second round and in-person meeting. For RCTs not using overall survival as their primary end-point, the experts recommend using disease-free survival (DFS) rather than recurrence-free survival (RFS) or time to recurrence (TTR) as the primary end-point. The consensus definition of DFS includes all causes of death, second primary colorectal cancers (CRCs), anastomotic relapse and metastatic relapse as an event, but not second primary non-CRCs. Events included in the RFS definition are the same as for DFS with the exception of second primary CRCs. The consensus definition of TTR includes anastomotic or metastatic relapse, death with evidence of recurrence and death from CC cause. CONCLUSION: Standardised definitions of TTE end-points ensure the reproducibility of the end-points between RCTs and facilitate cross-trial comparisons. These definitions should be integrated in standard practice for the design, reporting and interpretation of adjuvant CC RCTs.

International development and implementation of a core measurement set for research and audit studies in implant-based breast reconstruction: a study protocol.

INTRODUCTION: Outcome reporting in research studies of breast reconstruction is inconsistent and lacks standardisation. The results of individual studies therefore cannot be meaningfully compared or combined limiting their value. A core outcome set (COS) has been developed to address these issues and identified 11 key outcomes to be measured and reported in all future research and audit studies in reconstructive breast surgery (RBS). A COS represents what key outcomes should be measured. The next step is to determine how and when this should be done. The aim of this study is to develop a core measurement set (CMS) for use in research and audit studies in implant-based breast reconstruction. METHODS AND ANALYSIS: The CMS will be developed in accordance with the guidance developed by the Core Outcome Measures in Effectiveness Trials initiative (COMET) and COnsensus-based Standards for the selection of health Measurement Instruments (COSMIN) group for the selection of outcome measurement instruments (OMIs) for relevant outcome domains included in the RBS COS. This will involve three phases with strategies to promote implementation as a final additional phase. The phases are (1) conceptual considerations in which the target population, procedures and settings are defined; (2) systematic reviews to identify existing clinical, patient-reported and cosmetic OMIs and, if appropriate, assess their quality using COSMIN methodology; (3) a modified Delphi process including sequential Delphi surveys involving approximately 100 healthcare professionals and a face to face consensus meeting to agree and ratify which outcome definitions and OMIs should be used and standardised time points for assessment; (4) strategies to promote dissemination and adoption of the CMS. ETHICS AND DISSEMINATION: Ethical approval has been granted by University of Bristol Faculty Research Ethics Committee FREC ID 60221. Dissemination strategies will include scientific meeting presentations and peer-reviewed journal publications. Implementation activities will include engagement with journal editors and funders to promote uptake and use of the CMS.

Surrogate Endpoints in Localized Prostate Cancer.

Randomized clinical trials assessing novel therapies in men with localized prostate cancer frequently require large patient numbers and more than a decade of follow-up to demonstrate improvements in overall survival. As the landscape of treatment options for prostate cancer is rapidly changing, clinical trials requiring long follow-up threaten to impede treatment improvements and run the risk of results being obsolete by the time that they are reported in publication. To address these issues, there has been tremendous interest in identifying an intermediate clinical endpoint that can be assessed earlier in the disease course to serve as a robust surrogate for overall survival in men with localized prostate cancer. Herein we review the relevant data for surrogate endpoints in localized prostate cancer, highlighting the work performed by the Intermediate Clinical Endpoints in Cancer of the Prostate Working Group identifying metastasis-free survival as a valid surrogate for men treated for localized prostate cancer.

Beyond Randomized Clinical Trials: Use of External Controls.

Randomized controlled trials are the gold standard to investigate efficacy and safety of new treatments. In certain settings, however, randomizing patients to control may be difficult for ethical or feasibility reasons. Borrowing strength using relevant individual patient data on control from external trials or real-world data (RWD) sources may then allow us to reduce, or even eliminate, the concurrent control group. Naive direct use of external control data is not valid due to differences in patient characteristics and other confounding factors. Instead, we suggest the rigorous application of meta-analytic and propensity score methods to use external controls in a principled way. We illustrate these methods with two case studies: (i) a single-arm trial in a rare cancer disease, using propensity score matching to construct an external control from RWD; (ii) a randomized trial in children with multiple sclerosis, borrowing strength from past trials using a Bayesian meta-analytic approach.

Evolving primary and secondary endpoints in randomized controlled trials leading to approval of biologics and small molecules in IBD: an historical perspective.

Introduction: Therapeutic goals in inflammatory bowel diseases (IBD) have evolved, over the last decades, from clinical response to complete remission (clinical and endoscopic remission).Areas covered: Development of biologics and small molecules has been associated with the development of new endpoints in IBD trials that could not have been achieved in the pre-biologics era. Herein, we focus on evolving endpoints for approved biologics and small molecules. We searched for relevant publications using Medline/PubMed, Embase and the Cochrane Library from their inception to 1 July 2019.Expert opinion: Endpoints differ between induction (clinical and endoscopic response) and maintenance trials (clinical and endoscopic remission) because the goal is to evaluate the anti-inflammatory effect of a given drug during induction, whereas full disease control is the ultimate goal during the maintenance phase in order to change patients' life and disease course. Histological healing has recently emerged as a new co-primary endpoint in ulcerative colitis, and is now part of the definition of mucosal healing in these trials. Whether new endpoints such as transmural and radiologic healing could become an endpoint and replace endoscopy in Crohn's disease trials in the near future requires further investigation.

Are Surrogate Endpoints Unbiased Metrics in Clinical Benefit Scores of the ASCO Value Framework?

BACKGROUND: Clinical benefit scores (CBS) are key elements of the ASCO Value Framework (ASCO-VF) and are weighted based on a hierarchy of efficacy endpoints: hazard ratio for death (HR OS), median overall survival (mOS), HR for disease progression (HR PFS), median progression-free survival (mPFS), and response rate (RR). When HR OS is unavailable, the other endpoints serve as "surrogates" to calculate CBS. CBS are computed from PFS or RR in 39.6% of randomized controlled trials. This study examined whether surrogate-derived CBS offer unbiased scoring compared with HR OS-derived CBS. METHODS: Using the ASCO-VF, CBS for advanced disease settings were computed for randomized controlled trials of oncology drug approvals by the FDA, European Medicines Agency, and Health Canada in January 2006 through December 2017. Mean differences of surrogate-derived CBS minus HR OS-derived CBS assessed the tendency of surrogate-derived CBS to overestimate or underestimate clinical benefit. Spearman's correlation evaluated the association between surrogate- and HR OS-derived CBS. Mean absolute error assessed the average difference between surrogate-derived CBS relative to HR OS-derived CBS. RESULTS: CBS derived from mOS, HR PFS, mPFS, and RR overestimated HR OS-derived CBS in 58%, 68%, 77%, and 55% of pairs and overall by an average of 5.62 (n=90), 6.86 (n=110), 29.81 (n=101), and 3.58 (n=108), respectively. Correlation coefficients were 0.80 (95% CI, 0.70-0.86), 0.38 (0.20-0.53), 0.20 (0.00-0.38), and 0.01 (-0.18 to 0.19) for mOS-, HR PFS-, mPFS-, and RR-derived CBS, respectively, and mean absolute errors were 11.32, 12.34, 40.40, and 18.63, respectively. CONCLUSIONS: Based on the ASCO-VF algorithm, HR PFS-, mPFS-, and RR-derived CBS are suboptimal surrogates, because they were shown to be biased and poorly correlated to HR OS-derived CBS. Despite lower weighting than OS in the ASCO-VF algorithm, PFS still overestimated CBS. Simple rescaling of surrogate endpoints may not improve their validity within the ASCO-VF given their poor correlations with HR OS-derived CBS.

Innovative Thinking on Endpoint Selection in Clinical Trials.

In clinical trials, selection of appropriate study endpoints is critical for an accurate and reliable evaluation of safety and effectiveness of a test treatment under investigation. In practice, however, there are usually multiple endpoints available for measurement of disease status and/or therapeutic effect of the test treatment under study. For example, in cancer clinical trials, overall survival, response rate, and/or time to disease progression are usually considered as primary clinical endpoints for evaluation of safety and effectiveness of the test treatment under investigation. Once the study endpoints have been selected, sample size required for achieving a desired power is then determined. It, however, should be noted that different study endpoints may result in different sample sizes. In practice, it is usually not clear which study endpoint can best inform the disease status and measure the treatment effect. Moreover, different study endpoints may not translate one another although they may be highly correlated one another. In this article, we intend to develop an innovative endpoint namely therapeutic index based on a utility function to combine and utilize information collected from all study endpoints. Statistical properties and performances of the proposed therapeutic index are evaluated theoretically. A numerical example concerning a cancer clinical trial is given to illustrate the use of the proposed therapeutic index.

Measuring the unmeasurable: automated bone scan index as a quantitative endpoint in prostate cancer clinical trials.

BACKGROUND: Up to 90% of men with metastatic castration-resistant prostate cancer (mCRPC) will have a distribution of disease that includes bone metastases demonstrated on a Technetium-99m (99mTc-MDP) bone scan. The Prostate Cancer Working Group 2 and 3 Consensus Criteria standardized the criteria for assessing progression based on the development of new lesions. These criteria have been recognized by regulatory authorities for drug approval. The bone scan index (BSI) is a method to quantitatively measure the burden of bony disease, and can assess both disease progression and regression. The automated BSI (aBSI) is a method of computer analysis to assess BSI, and is being qualified as a clinical trials endpoint. METHODS: Manual searching was used to identify the literature on BSI and aBSI. We summarize the most relevant aspects of the retrospective and prospective studies evaluating aBSI measurements, and provide a critical discussion on the potential advantages and caveats of aBSI. RESULTS: The development of neural artificial networks (EXINI boneBSI) to automatically determine the BSI reduces the turnaround time for assessing BSI with high reproducibility and accuracy. Several studies showed that the concordance between aBSI and BSI, as well as the interobserver concordance of aBSI, was >0.95. In a phase 3 assessment of aBSI, a doubling value increased the risk of death in 20%, pre-treatment aBSI values independently correlated with overall survival (OS) and time to symptomatic progression. Retrospective studies suggest that a decrease in aBSI after treatment may correlate with higher survival when compared with increasing aBSI. CONCLUSIONS: aBSI provides a quantitative measurement that is feasible, reproducible, and in analyses to date correlates with OS and symptomatic progression. These findings support the aBSI to risk-stratify men with mCRPC for clinical trial enrollment. Future studies quantifying aBSI change over time as an intermediate endpoint for evaluating new systemic therapies are needed.