Design of a clinical trial using generalized pairwise comparisons to test a less intensive treatment regimen.

BACKGROUND/AIMS: Showing "similar efficacy" of a less intensive treatment typically requires a non-inferiority trial. Yet such trials may be challenging to design and conduct. In acute promyelocytic leukemia, great progress has been achieved with the introduction of targeted therapies, but toxicity remains a major clinical issue. There is a pressing need to show the favorable benefit/risk of less intensive treatment regimens. METHODS: We designed a clinical trial that uses generalized pairwise comparisons of five prioritized outcomes (alive and event-free at 2 years, grade 3/4 documented infections, differentiation syndrome, hepatotoxicity, and neuropathy) to confirm a favorable benefit/risk of a less intensive treatment regimen. We conducted simulations based on historical data and assumptions about the differences expected between the standard of care and the less intensive treatment regimen to calculate the sample size required to have high power to show a positive Net Treatment Benefit in favor of the less intensive treatment regimen. RESULTS: Across 10,000 simulations, average sample sizes of 260 to 300 patients are required for a trial using generalized pairwise comparisons to detect typical Net Treatment Benefits of 0.19 (interquartile range 0.14-0.23 for a sample size of 280). The Net Treatment Benefit is interpreted as a difference between the probability of doing better on the less intensive treatment regimen than on the standard of care, minus the probability of the opposite situation. A Net Treatment Benefit of 0.19 translates to a number needed to treat of about 5.3 patients (1/0.19 ≃ 5.3). CONCLUSION: Generalized pairwise comparisons allow for simultaneous assessment of efficacy and safety, with priority given to the former. The sample size required would be of the order of 300 patients, as compared with more than 700 patients for a non-inferiority trial using a margin of 4% against the less intensive treatment regimen for the absolute difference in event-free survival at 2 years, as considered here.

Minimization in randomized clinical trials.

In randomized trials, comparability of the treatment groups is ensured through allocation of treatments using a mechanism that involves some random element, thus controlling for confounding of the treatment effect. Completely random allocation ensures comparability between the treatment groups for all known and unknown prognostic factors. For a specific trial, however, imbalances in prognostic factors among the treatment groups may occur. Although accidental bias can be avoided in the presence of such imbalances by stratifying the analysis, most trialists, regulatory agencies, and other stakeholders prefer a balanced distribution of prognostic factors across the treatment groups. Some procedures attempt to achieve balance in baseline covariates, by stratifying the allocation for these covariates, or by dynamically adapting the allocation using covariate information during the trial (covariate-adaptive procedures). In this Tutorial, the performance of minimization, a popular covariate-adaptive procedure, is compared with two other commonly used procedures, completely random allocation and stratified blocked designs. Using individual patient data of 2 clinical trials (in advanced ovarian cancer and age-related macular degeneration), the procedures are compared in terms of operating characteristics (using asymptotic and randomization tests), predictability of treatment allocation, and achieved balance. Fifty actual trials of various sizes that applied minimization for treatment allocation are used to investigate the achieved balance. Implementation issues of minimization are described. Minimization procedures are useful in all trials but especially when (1) many major prognostic factors are known, (2) many centers of different sizes accrue patients, or (3) the trial sample size is moderate.

Surrogacy Beyond Prognosis: The Importance of "Trial-Level" Surrogacy.

Many candidate surrogate endpoints are currently assessed using a 2-level statistical approach, which consists in checking whether (1) the potential surrogate is associated with the final endpoint in individual patients and (2) the effect of treatment on the surrogate can be used to reliably predict the effect of treatment on the final endpoint. In some situations, condition (1) is fulfilled but condition (2) is not. We use concepts of causal inference to explain this apparently paradoxical situation, illustrating this review with 2 contrasting examples in operable breast cancer: the example of pathological complete response (pCR) and that of disease-free survival (DFS). In a previous meta-analysis, pCR has been shown to be a strong and independent prognostic factor for event-free survival (EFS) and overall survival (OS) after neoadjuvant treatment of operable breast cancer. Yet, in randomized trials, the effects of experimental treatments on pCR have not translated into predictable effects on EFS or OS, making pCR an "individual-level" surrogate, but not a "trial-level" surrogate. In contrast, DFS has been shown to be an acceptable surrogate for OS at both the individual and trial levels in early, HER2-positive breast cancer. The distinction between the prognostic and predictive roles of a tentative surrogate, not always made in the literature, avoids unnecessary confusion and allows better understanding of what it takes to validate a surrogate endpoint that is truly able to replace a final endpoint.

The case against censoring of progression-free survival in cancer clinical trials - A pandemic shutdown as an illustration.

BACKGROUND: Missing data may lead to loss of statistical power and introduce bias in clinical trials. The Covid-19 pandemic has had a profound impact on patient health care and on the conduct of cancer clinical trials. Although several endpoints may be affected, progression-free survival (PFS) is of major concern, given its frequent use as primary endpoint in advanced cancer and the fact that missed radiographic assessments are to be expected. The recent introduction of the estimand framework creates an opportunity to define more precisely the target of estimation and ensure alignment between the scientific question and the statistical analysis. METHODS: We used simulations to investigate the impact of two basic approaches for handling missing tumor scans due to the pandemic: a "treatment policy" strategy, which consisted in ascribing events to the time they are observed, and a "hypothetical" approach of censoring patients with events during the shutdown period at the last assessment prior to that period. We computed the power of the logrank test, estimated hazard ratios (HR) using Cox models, and estimated median PFS times without and with a hypothetical 6-month shutdown period with no patient enrollment or tumor scans being performed, varying the shutdown starting times. RESULTS: Compared with the results in the absence of shutdown, the "treatment policy" strategy slightly overestimated median PFS proportionally to the timing of the shutdown period, but power was not affected. Except for one specific scenario, there was no impact on the estimated HR. In general, the pandemic had a greater impact on the analyses using the "hypothetical" strategy, which led to decreased power and overestimated median PFS times to a greater extent than the "treatment policy" strategy. CONCLUSION: As a rule, we suggest that the treatment policy approach, which conforms with the intent-to-treat principle, should be the primary analysis to avoid unnecessary loss of power and minimize bias in median PFS estimates.

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.

Central statistical monitoring of investigator-led clinical trials in oncology.

Investigator-led clinical trials are pragmatic trials that aim to investigate the benefits and harms of treatments in routine clinical practice. These much-needed trials represent the majority of all trials currently conducted. They are however threatened by the rising costs of clinical research, which are in part due to extensive trial monitoring processes that focus on unimportant details. Risk-based quality management focuses, instead, on "things that really matter". We discuss the role of central statistical monitoring as part of risk-based quality management. We describe the principles of central statistical monitoring, provide examples of its use, and argue that it could help drive down the cost of randomized clinical trials, especially investigator-led trials, whilst improving their quality.

Disease-free survival as a surrogate for overall survival in patients with HER2-positive, early breast cancer in trials of adjuvant trastuzumab for up to 1 year: a systematic review and meta-analysis.

BACKGROUND: Although frequently used as a primary endpoint, disease-free survival has not been validated as a surrogate for overall survival in early breast cancer. We investigated this surrogacy in the adjuvant setting of treatment with anti-HER2 antibodies. METHODS: In a systematic review and meta-analysis, we identified published and non-published randomised controlled trials with completed accrual and available disease-free survival and overall survival results for the intention-to-treat population as of September 2016. Bibliographic databases (MEDLINE, Embase, and Cochrane Central Register of Controlled Trials), clinical trial registries (Clinicaltrials.gov, EU Clinical Trials Register, WHO International Clinical Trials Registry Platform, and PharmNet.Bund), and trial registries from relevant pharmaceutical companies were searched. Eligibility for treatment of HER2-positive early breast cancer required at least one group to have an anti-HER antibody treatment (ie, trastuzumab, pertuzumab, or trastuzumab emtansine) planned for 12 months, and at least one control arm with chemotherapy without the antibody, a lower total dose or duration of the antibody, or observation alone. Units of analysis were contrasts: two-group trials gave rise to one contrast, whereas trials with more than two groups gave rise to more than one contrast. We excluded trials enrolling patients with recurrent, metastatic, or non-invasive disease, and those testing neoadjuvant therapy exclusively. Our primary objective was to estimate patient-level and trial-level correlations between disease-free survival and overall survival. We measured the association between disease-free survival and overall survival using Spearman's correlation coefficient (rs), and the association between hazard ratios (HRs) for disease-free survival and overall survival using R2. We computed the surrogate threshold effect, the maximum HR for disease-free survival that statistically predicts an HR for overall survival less than 1·00 in a future trial. FINDINGS: Eight trials (n=21 480 patients) gave rise to a full set (12 contrasts). Patient-level associations between disease-free and overall survival were strong (rs=0·90 [95% CI 0·89-0·90]). Trial-level associations gave rise to values of R2 of 0·75 (95% CI 0·50-1·00) for the full set. Subgroups defined by nodal status and hormone receptor status yielded qualitatively similar results. Depending on the expected number of deaths in a future trial, the surrogate threshold effects ranged from 0·56 to 0·81, based on the full set. INTERPRETATION: These findings suggest that it is appropriate to continue to use disease-free survival as a surrogate for overall survival in trials in HER-2-positive, early breast cancer. The key limitation of this study is the dependence of its results on the trials included and on the existence of an outlying trial. FUNDING: Roche Pharma AG.

Meta-Research on Oncology Trials: A Toolkit for Researchers with Limited Resources.

"Meta-research" is a discipline that investigates research practices. Meta-research on clinical trials is an attempt to summarize descriptive and methodological features of published or ongoing clinical trials, including aspects of their implementation, design, analysis, reporting, and interpretation. In this type of investigation, the unit of analysis is a primary source of information about a clinical trial (e.g., published reports, study protocols, or abstracts), with meta-research being a second layer of information that summarizes what is known from various primary sources. After the formulation of the primary research question, the methodology of meta-research resembles that of other research projects, with predefined eligibility criteria, exposure variables, primary and secondary outcomes of interest, and an analysis plan. This type of study usually provides a high-level picture of the literature on a specific topic, always accompanied by a critical evaluation of the methodology and/or the quality of reporting of the studies included. Because relatively few resources are consumed to produce meta-research, these studies offer a great opportunity for clinical scientists working in settings with limited resources. In this article, we present the principles of designing and conducting meta-research and use our experience to suggest recommendations on how to perform and how to report this type of potentially very creative study. IMPLICATIONS FOR PRACTICE: The term meta-research pertains to a type of study in which the unit of analysis is, in most cases, the publication of a clinical trial. This type of study usually provides a high-level picture of the literature on a specific topic, always accompanied by a critical evaluation of the methodology, design, and/or the quality of reporting of the studies included. Because relatively few resources are consumed to produce meta-research, these studies offer a great opportunity for clinical scientists who work in low-income countries. This article presents the principles of designing and conducting meta-research and proposes practical recommendations on how to perform and report this type of potentially very creative study.

Time to Review the Role of Surrogate End Points in Health Policy: State of the Art and the Way Forward.

The efficacy of medicines, medical devices, and other health technologies should be proved in trials that assess final patient-relevant outcomes such as survival or morbidity. Market access and coverage decisions are, however, often based on surrogate end points, biomarkers, or intermediate end points, which aim to substitute and predict patient-relevant outcomes that are unavailable because of methodological, financial, or practical constraints. We provide a summary of the present use of surrogate end points in health care policy, discussing the case for and against their adoption and reviewing validation methods. We introduce a three-step framework for policymakers to handle surrogates, which involves establishing the level of evidence, assessing the strength of the association, and quantifying relations between surrogates and final outcomes. Although the use of surrogates can be problematic, they can, when selected and validated appropriately, offer important opportunities for more efficient clinical trials and faster access to new health technologies that benefit patients and health care systems.

The impact of data errors on the outcome of randomized clinical trials.

Background/aims Considerable human and financial resources are typically spent to ensure that data collected for clinical trials are free from errors. We investigated the impact of random and systematic errors on the outcome of randomized clinical trials. Methods We used individual patient data relating to response endpoints of interest in two published randomized clinical trials, one in ophthalmology and one in oncology. These randomized clinical trials enrolled 1186 patients with age-related macular degeneration and 736 patients with metastatic colorectal cancer. The ophthalmology trial tested the benefit of pegaptanib for the treatment of age-related macular degeneration and identified a statistically significant treatment benefit, whereas the oncology trial assessed the benefit of adding cetuximab to a regimen of capecitabine, oxaliplatin, and bevacizumab for the treatment of metastatic colorectal cancer and failed to identify a statistically significant treatment difference. We simulated trial results by adding errors that were independent of the treatment group (random errors) and errors that favored one of the treatment groups (systematic errors). We added such errors to the data for the response endpoint of interest for increasing proportions of randomly selected patients. Results Random errors added to up to 50% of the cases produced only slightly inflated variance in the estimated treatment effect of both trials, with no qualitative change in the p-value. In contrast, systematic errors produced bias even for very small proportions of patients with added errors. Conclusion A substantial amount of random errors is required before appreciable effects on the outcome of randomized clinical trials are noted. In contrast, even a small amount of systematic errors can severely bias the estimated treatment effects. Therefore, resources devoted to randomized clinical trials should be spent primarily on minimizing sources of systematic errors which can bias the analyses, rather than on random errors which result only in a small loss in power.

Risk Factors for Mortality and Outcomes in Pediatric Acute Lung Injury/Acute Respiratory Distress Syndrome.

OBJECTIVES: Children admitted to PICUs often present with or develop respiratory failure that requires mechanical ventilation. We prospectively identified children admitted to three general PICUs, with the goal of identifying risk factors for mortality. DESIGN: Prospective multicenter observational study. SETTING: Three general PICUs, two in São Paulo and one in Curitiba, Brazil. PATIENTS: Children aged between 1 month and 15 years, consecutively admitted between August 2008 and July 2010, with acute lung injury or acute respiratory distress syndrome that developed at least 12 hours after invasive or noninvasive mechanical ventilation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used logistic regression models to explore the relationship between death and independent variables. Of 3,046 patients admitted to the three PICUs, 1,658 patients underwent mechanical ventilation, and 84 fulfilled the acute lung injury/acute respiratory distress syndrome inclusion criteria and were analyzed. Nearly 60% were boys, and the median age was 31 months. Pressure control/assist control was the initial mode of mechanical ventilation in 86% of cases, and the median durations of mechanical ventilation and PICU stay were 12 and 15 days, respectively. None of the eight patients with acute lung injury died, whereas 33 of 76 of the remaining patients with acute respiratory distress syndrome died, for an overall mortality rate of 39.3% (95% CI, 28.8-50.6%). In different multivariate logistic regression model, the number of organ dysfunctions at admission, peak inspiratory pressure, airway pressure gradient on day 1, and the mean airway pressure gradient over the first 7 days of mechanical ventilation were significantly associated with mortality. CONCLUSION: Mortality is high in pediatric acute lung injury/acute respiratory distress syndrome. Mechanical ventilation-associated risk factors for death among such patients are potential targets for intervention.

Validation of surrogate endpoints in advanced solid tumors: systematic review of statistical methods, results, and implications for policy makers.

OBJECTIVES: Licensing of, and coverage decisions on, new therapies should rely on evidence from patient-relevant endpoints such as overall survival (OS). Nevertheless, evidence from surrogate endpoints may also be useful, as it may not only expedite the regulatory approval of new therapies but also inform coverage decisions. It is, therefore, essential that candidate surrogate endpoints be properly validated. However, there is no consensus on statistical methods for such validation and on how the evidence thus derived should be applied by policy makers. METHODS: We review current statistical approaches to surrogate-endpoint validation based on meta-analysis in various advanced-tumor settings. We assessed the suitability of two surrogates (progression-free survival [PFS] and time-to-progression [TTP]) using three current validation frameworks: Elston and Taylor's framework, the German Institute of Quality and Efficiency in Health Care's (IQWiG) framework and the Biomarker-Surrogacy Evaluation Schema (BSES3). RESULTS: A wide variety of statistical methods have been used to assess surrogacy. The strength of the association between the two surrogates and OS was generally low. The level of evidence (observation-level versus treatment-level) available varied considerably by cancer type, by evaluation tools and was not always consistent even within one specific cancer type. CONCLUSIONS: Not in all solid tumors the treatment-level association between PFS or TTP and OS has been investigated. According to IQWiG's framework, only PFS achieved acceptable evidence of surrogacy in metastatic colorectal and ovarian cancer treated with cytotoxic agents. Our study emphasizes the challenges of surrogate-endpoint validation and the importance of building consensus on the development of evaluation frameworks.

Brazilian abstracts presented at the American Urological Association annual meetings: contribution, publication rates, and comparison with oncology abstracts.

PURPOSE: Scientific research originating from Brazil appears to be rising in several medical fields. Research results are often presented at scientific meetings before publication in peer-reviewed journals. We investigated the publication rate of Brazilian studies presented in American Urological Association (AUA) meetings and compared with the rate of publication of Brazilian oncological studies presented at the American Society of Clinical Oncology (ASCO) meetings. MATERIALS AND METHODS: a hand search of 12,454 abstracts presented at aua meetings 2001-2007 was conducted. abstracts for which at least two-thirds of institutions were from brazil were considered as brazilian. final publication was searched in pubmed and lilacs databases. oncological abstracts were also hand searched in the asco meetings proceedings in the same years. RESULTS: There was no significant temporal trend in the proportion of AUA studies originating from Brazil along those 7 years. A total of 195 abstracts (1.57%) were from Brazil. One hundred (51.3%) abstracts were published in full, and the estimated 5-year publication rate was 48.2%. There was a progressive increase in publication rates for studies categorized as video, poster, and podium presentations. Considering abstracts presented in years 2001-2005, urologic publication rate was significantly higher than for abstracts presented at the ASCO meeting. CONCLUSIONS: Our results suggest that the Brazilian contribution to AUA meetings is at a plateau and that the Brazilian literature contribution is greater in urology than in oncology. Efforts must be invested towards raising this plateau and understanding qualitative aspects of the urology scientific output from Brazil.

Trial Design for Cancer Immunotherapy: A Methodological Toolkit.

Immunotherapy with checkpoint inhibitors (CPIs) and cell-based products has revolutionized the treatment of various solid tumors and hematologic malignancies. These agents have shown unprecedented response rates and long-term benefits in various settings. These clinical advances have also pointed to the need for new or adapted approaches to trial design and assessment of efficacy and safety, both in the early and late phases of drug development. Some of the conventional statistical methods and endpoints used in other areas of oncology appear to be less appropriate in immuno-oncology. Conversely, other methods and endpoints have emerged as alternatives. In this article, we discuss issues related to trial design in the early and late phases of drug development in immuno-oncology, with a focus on CPIs. For early trials, we review the most salient issues related to dose escalation, use and limitations of tumor response and progression criteria for immunotherapy, the role of duration of response as an endpoint in and of itself, and the need to conduct randomized trials as early as possible in the development of new therapies. For late phases, we discuss the choice of primary endpoints for randomized trials, review the current status of surrogate endpoints, and discuss specific statistical issues related to immunotherapy, including non-proportional hazards in the assessment of time-to-event endpoints, alternatives to the Cox model in these settings, and the method of generalized pairwise comparisons, which can provide a patient-centric assessment of clinical benefit and be used to design randomized trials.

Re-Evaluation of Pathologic Complete Response as a Surrogate for Event-Free and Overall Survival in Human Epidermal Growth Factor Receptor 2-Positive, Early Breast Cancer Treated With Neoadjuvant Therapy Including Anti-Human Epidermal Growth Factor Receptor 2 Therapy.

PURPOSE: Pathologic complete response (pCR) has prognostic importance and is frequently used as a primary end point, but doubts remain about its validity as a surrogate for event-free survival (EFS) and overall survival (OS) in human epidermal growth factor receptor 2 (HER2)-positive, early breast cancer. METHODS: We obtained individual-patient data from randomized trials of neoadjuvant anti-HER2 therapy that enrolled at least 100 patients, had data for pCR, EFS, and OS, and a median follow-up of at least 3 years. We quantified the patient-level association between pCR (defined as ypT0/Tis ypN0) and both EFS and OS using odds ratios (ORs, with ORs >1.00 indicating a benefit from achieving a pCR). We quantified the trial-level association between treatment effects on pCR and on EFS and OS using R2 (with values above 0.75 considered as indicating strong associations). RESULTS: Eleven of 15 eligible trials had data for analysis (3,980 patients, with a median follow-up of 62 months). Considering all trials, we found strong patient-level associations, with ORs of 2.64 (95% CI, 2.20 to 3.07) for EFS and 3.15 (95% CI, 2.38 to 3.91) for OS; however, trial-level associations were weak, with an unadjusted R2 of 0.23 (95% CI, 0 to 0.66) for EFS and 0.02 (95% CI, 0 to 0.17) for OS. We found qualitatively similar results when grouping trials according to different clinical questions, when analyzing only patients with hormone receptor-negative disease, and when using a more stringent definition of pCR (ypT0 ypN0). CONCLUSION: Although pCR may be useful for patient management, it cannot be considered as a surrogate for EFS or OS in neoadjuvant trials of HER2-positive, operable breast cancer.

Pathologic Complete Response and Individual Patient Prognosis After Neoadjuvant Chemotherapy Plus Anti-Human Epidermal Growth Factor Receptor 2 Therapy of Human Epidermal Growth Factor Receptor 2-Positive Early Breast Cancer.

PURPOSE: The achievement of pathologic complete response (pCR) is strongly prognostic for event-free survival (EFS) and overall survival (OS) in patients with early breast cancer (EBC), and adapting postneoadjuvant therapy improves long-term outcomes for patients with HER2-positive disease not achieving pCR. We sought to investigate prognostic factors for EFS and OS among patients with and without pCR after neoadjuvant systemic treatment consisting of chemotherapy plus anti-HER2 therapy. MATERIALS AND METHODS: We used individual data from 3,710 patients randomly assigned in 11 neoadjuvant trials for HER2-positive EBC with ≥100 patients enrolled, available data for pCR, EFS, and OS, and follow-up ≥3 years. We assessed baseline clinical tumor size (cT) and clinical nodal status (cN) as prognostic factors using stratified (by trial and treatment) Cox models separately for hormone receptor-positive versus hormone receptor-negative disease, and for patients who had pCR (pCR+; ypT0/is, ypN0) versus patients who did not achieve a pCR (pCR-). RESULTS: The median follow-up overall was 61.2 months. In pCR+ patients, cT and cN were significant independent prognostic factors for EFS, whereas only cT was a significant predictor for OS. In pCR- patients, cT, cN, and hormone receptor status were significant independent predictors for both EFS and OS. Regardless of hormone receptor status, cT, and cN, the 5-year EFS/OS rates were higher in pCR+ patients than in pCR- patients. In most subsets with regards to hormone receptor and pCR status, cT and cN were independent prognostic factors for both EFS and OS, including pCR+ patients. CONCLUSION: These results confirm that patients achieving pCR have far better survival outcomes than patients who do not. The traditional poor prognostic features, namely tumor size and nodal status, remain important even after a pCR.

Non-inferiority trials in breast and non-small cell lung cancer: choice of non-inferiority margins and other statistical aspects.

BACKGROUND: Determining the non-inferiority margin is an essential step in the design and interpretation of non-inferiority trials, and this margin should be preferably justified on clinical and statistical grounds. METHODS: After a PubMed search for phase III trials in advanced breast cancer (BC) or non-small cell lung cancer (NSCLC) published between January 1998 and December 2009 in 11 leading journals, non-inferiority trials were selected by manual search of the full papers. RESULTS: Twenty-four of 195 trials had a primary non-inferiority hypothesis. When the two six-year study periods were compared, there were time trends within BC and NSCLC, with most non-inferiority trials in BC reported in the first six-year period, and vice-versa for NSCLC. The median sample size was larger for non-inferiority than superiority trials (p < 0.01). The choice of a non-inferiority margin was reportedly justified in only five cases. Non-inferiority trials were more likely than superiority trials to yield positive results (p < 0.001), as were trials in breast cancer (p = 0.02). CONCLUSIONS: Non-inferiority margins for cancer trials appear to be chosen mostly on historical grounds. Since nearly three-quarters of non-inferiority trials achieve their primary objective, the extent to which the choice of margins has influence on trial results remains to be determined.

Clinical Trial Endpoints in Metastatic Cancer: Using Individual Participant Data to Inform Future Trials Methodology.

Meta-analysis based on individual participant data (IPD) is a powerful methodology for synthesizing evidence by combining information drawn from multiple trials. Hitherto, its principal application has been in questions of clinical management, but an increasingly important use is in clarifying trials methodology, for instance in the selection of endpoints, as discussed in this review. In oncology, the Aide et Recherche en Cancérologie Digestive (ARCAD) Metastatic Colorectal Cancer Database is a leader in the use of IPD-based meta-analysis in methodological research. The ARCAD database contains IPD from more than 38 000 patients enrolled in 46 studies and continues to collect phase III trial data. Here, we review the principal findings of the ARCAD project in respect of endpoint selection and examine their implications for cancer trials. Analysis of the database has confirmed that progression-free survival (PFS) is no longer a valid surrogate endpoint predictive of overall survival in the first-line treatment of colorectal cancer. Nonetheless, PFS remains an endpoint of choice for most first-line trials in metastatic colorectal cancer and other solid tumors. Only substantial PFS effects are likely to translate into clinically meaningful benefits, and accordingly, we advocate an oncology research model designed to identify highly effective treatments in carefully defined patient groups. We also review the use of the ARCAD database in assessing clinical response including novel response metrics and prognostic markers. These studies demonstrate the value of IPD as a tool for methodological studies and provide a reference point for the expansion of this approach within clinical cancer research.