Power Considerations in Designing and Interpreting Adaptive Clinical Trials.

Adaptive clinical trials allow researchers to make preplanned modifications based on accumulating data from an ongoing trial while preserving the trial's integrity and validity. These modifications may include early termination in cases of successes or lack of efficacy, refining the sample size, altering treatments or doses, or focusing recruitment efforts on individuals most likely to benefit. In this issue of NEJM Evidence, Geisler et al.1 report results from the Apixaban for Treatment of Embolic Stroke of Undetermined Source (ATTICUS) trial, a multicenter randomized trial of apixaban compared with aspirin in patients with cardioembolism risk factors.

Pathophysiological Sex Differences in Heart Failure Progression After Acute Coronary Syndrome: Insights From the EXAMINE Trial.

BACKGROUND: Therapies can reduce the risk of heart failure (HF) development and progression in type 2 diabetes; nevertheless, the risk of these outcomes is greater in females than in males. METHODS AND RESULTS: To investigate sex differences in HF development and progression, we compared baseline circulating proteins (Olink Cardiovascular II panel) in males and females with type 2 diabetes and recent acute coronary syndrome for the outcome of HF hospitalization. Data were from the placebo-controlled Examination of Cardiovascular Outcomes with Alogliptin vs Standard of Care (EXAMINE) trial. Pathophysiological sex-differences were interpreted with network and pathway over-representation analyses. The EXAMINE trial enrolled 5380 participants (32.1% females) with biomarker data available for 95.4% of individuals. Analyses revealed 43 biomarkers were differentially expressed in HF hospitalization, of which 18 were sex specific. Among these 43 biomarkers, interleukin-6 was identified as a central node for the pathogenesis of HF hospitalization in both females and in males. Additional pathway over-representation analyses demonstrated that biomarkers associated with inflammatory pathways related to endothelial dysfunction and cardiac fibrosis were more up-regulated in females than males with HF hospitalization. Differential expression of 3 biomarkers (pentraxin-related protein 3, hydroxyacid oxidase 1, and carbonic anhydrase 5A) was independently associated with an increased risk of HF hospitalization in females but not in males (interaction P < .05). CONCLUSIONS: In males and females with type 2 diabetes and acute coronary syndrome, interleukin-6 seems to be central in the pathogenesis of HF. Females exhibit higher levels of circulating proteins related to immunological pathways, reflecting sex-specific differences underlying HF development and progression.

External validation and extension of the TIMI risk score for heart failure in diabetes for patients with recent acute coronary syndrome: An analysis of the EXAMINE trial.

AIMS: The Thrombolysis in Myocardial Infarction Risk Score for Heart Failure (HF) in Diabetes (TRS-HFDM ) prognosticates HF hospitalization in people with type 2 diabetes (T2D). This study aimed to externally validate and extend its use for those with recent acute coronary syndrome (ACS). MATERIALS AND METHODS: The TRS-HFDM was externally validated in the Examination of Cardiovascular Outcomes with Alogliptin versus Standard of Care (EXAMINE) trial (n = 5380) and extended with natriuretic biomarkers. Missing data were multiply imputed. Initial TRS-HFDM variables were previous HF (2 points), atrial fibrillation (1 point), coronary artery disease (1 point), estimated glomerular filtration rate <60 ml/min/1.73 m2 (1 point), and urine albumin-to-creatinine ratio 30-300 mg/g (1 point) and >300 mg/g (2 points). RESULTS: In total, HF hospitalization occurred in 193 (3.6%) patients. Based on the TRS-HFDM , 25% of patients were classified as intermediate risk (1 point), 30% were classified as high risk (2 points), 19% were classified as very-high risk (3 points) and 26% were classified as severe risk (≥4 points). Before model extension, discrimination (C-index 0.76, 95%·CI 0.73-0.80) and calibration (calibration slope 0.82, 95%·CI 0.65-1.0; calibration-in-the-large -0.15, 95%·CI -0.37-0.64) were moderate-to-good in individuals with T2D and recent ACS. The extension of TRS-HFDM with the addition of N-terminal pro-B-type natriuretic peptide (NT-ProBNP) improved discrimination (C-index 0.82, 95%·CI 0.79-0.85) and calibration (calibration slope 0.84, 95%·CI 0.66-1.02; calibration-in-the-large -0.12, 95%·CI -0.33-0.081) for this higher-risk population. CONCLUSION: The TRS-HFDM with the extension of NT-ProBNP improves risk stratification and generalizes the use of the risk score for patients with T2D and ACS. Future validation studies in ACS populations may be warranted.

Economic Evaluation of Cost and Time Required for a Platform Trial vs Conventional Trials.

Importance: Platform trial design allows the introduction of new interventions after the trial is initiated and offers efficiencies to clinical research. However, limited guidance exists on the economic resources required to establish and maintain platform trials. Objective: To compare cost (US dollars) and time requirements of conducting a platform trial vs a series of conventional (nonplatform) trials using a real-life example. Design, Setting, and Participants: For this economic evaluation, an online survey was administered to a group of international experts (146 participants) with publication records of platform trials to elicit their opinions on cost and time to set up and conduct platform, multigroup, and 2-group trials. Using the reported entry dates of 10 interventions into Systemic Therapy in Advancing Metastatic Prostate Cancer: Evaluation of Drug Efficacy, the longest ongoing platform trial, 3 scenarios were designed involving a single platform trial (scenario 1), 1 multigroup followed by 5 2-group trials (scenario 2), and a series of 10 2-group trials (scenario 3). All scenarios started with 5 interventions, then 5 more interventions were either added to the platform or evaluated independently. Simulations with the survey results as inputs were used to compare the platform vs conventional trial designs. Data were analyzed from July to September 2021. Exposure: Platform trial design. Main Outcomes and Measures: Total trial setup and conduct cost and cumulative duration. Results: Although setup time and cost requirements of a single trial were highest for the platform trial, cumulative requirements of setting up a series of multiple trials in scenarios 2 and 3 were larger. Compared with the platform trial, there was a median (IQR) increase of 216.7% (202.2%-242.5%) in cumulative setup costs for scenario 2 and 391.1% (365.3%-437.9%) for scenario 3. In terms of total cost, there was a median (IQR) increase of 17.4% (12.1%-22.5%) for scenario 2 and 57.5% (43.1%-69.9%) for scenario 3. There was a median (IQR) increase in cumulative trial duration of 171.1% (158.3%-184.3%) for scenario 2 and 311.9% (282.0%-349.1%) for scenario 3. Cost and time reductions in the platform trial were observed in both the initial and subsequently evaluated interventions. Conclusions and Relevance: Although setting up platform trials can take longer and be costly, the findings of this study suggest that having a single infrastructure can improve efficiencies with respect to costs and efforts.

Optimal adaptive promising zone designs.

We develop optimal decision rules for sample size re-estimation in two-stage adaptive group sequential clinical trials. It is usual for the initial sample size specification of such trials to be adequate to detect a realistic treatment effect δa with good power, but not sufficient to detect the smallest clinically meaningful treatment effect δmin . Moreover it is difficult for the sponsors of such trials to make the up-front commitment needed to adequately power a study to detect δmin . It is easier to justify increasing the sample size if the interim data enter a so-called "promising zone" that ensures with high probability that the trial will succeed. We have considered promising zone designs that optimize unconditional power and promising zone designs that optimize conditional power and have discussed the tension that exists between these two objectives. Where there is reluctance to base the sample size re-estimation rule on the parameter δmin we propose a Bayesian option whereby a prior distribution is assigned to the unknown treatment effect δ , which is then integrated out of the objective function with respect to its posterior distribution at the interim analysis.

A simulation-based comparison of estimation methods for adaptive and classical group sequential clinical trials.

Statistical methods for controlling the type-I error of hypothesis tests in adaptive group sequential clinical trials are well established and well understood. However, methods for obtaining statistically valid point estimates and confidence intervals for adaptive designs are not as well established or as well understood. At the end of an adaptive trial, one may calculate the repeated confidence interval (RCI), which provides conservative coverage of δ , or the backward image confidence interval (BWCI), which provides exact coverage of δ and is an extension of the stagewise adjusted confidence interval (SWCI, used in classical group sequential designs). The BWCI can also provide a median unbiased estimate (MUE) of δ . There is a need to better understand the coverage and possible biases associated with these methods. We conducted a simulation study exploring parameter estimation following sample size reestimation based on testing methods with strong control of type-I error. Generally, the BWCI provided exact coverage, the naïve CI provided inconsistent coverage, and the RCI provided conservative coverage. Additionally, we note considerable asymmetry in the coverage from above/from below for the RCI, although we did not see any instance where the 95% RCI excluded the true parameter more than 2.5% on either side. At the end of an adaptive group sequential trial, we strongly recommend the use of the BWCI (and associated MUE), with the RCI computed during interim looks; the naïve CI should be avoided. These results and conclusions also hold true for classical group sequential designs.

Robust group sequential designs for trials with survival endpoints and delayed response.

Randomized clinical trials in oncology typically utilize time-to-event endpoints such as progression-free survival or overall survival as their primary efficacy endpoints, and the most commonly used statistical test to analyze these endpoints is the log-rank test. The power of the log-rank test depends on the behavior of the hazard ratio of the treatment arm to the control arm. Under the assumption of proportional hazards, the log-rank test is asymptotically fully efficient. However, this proportionality assumption does not hold true if there is a delayed treatment effect. Cancer immunology has evolved over time and several cancer vaccines are available in the market for treating existing cancers. This includes sipuleucel-T for metastatic hormone-refractory prostate cancer, nivolumab for metastatic melanoma, and pembrolizumab for advanced nonsmall-cell lung cancer. As cancer vaccines require some time to elicit an immune response, a delayed treatment effect is observed, resulting in a violation of the proportional hazards assumption. Thus, the traditional log-rank test may not be optimal for testing immuno-oncology drugs in randomized clinical trials. Moreover, the new immuno-oncology compounds have been shown to be very effective in prolonging overall survival. Therefore, it is desirable to implement a group sequential design with the possibility of early stopping for overwhelming efficacy. In this paper, we investigate the max-combo test, which utilizes the maximum of two weighted log-rank statistics, as a robust alternative to the log-rank test. The new test is implemented for two-stage designs with possible early stopping at the interim analysis time point. Two classes of weights are investigated for the max-combo test: the Fleming and Harrington (1981) Gρ,γ$G^{\rho , \gamma }$ weights and the Magirr and Burman (2019) modest (τ∗)$ (\tau ^{*})$  weights.

Blood and Urine Biomarkers Predicting Worsening Kidney Function in Patients with Type 2 Diabetes Post-Acute Coronary Syndrome: An Analysis from the EXAMINE Trial.

INTRODUCTION: Worsening kidney function (WKF) is frequent among patients with type 2 diabetes (T2D) and a recent acute coronary syndrome (ACS) and is associated with a poor prognosis. An accurate prediction of WKF is clinically important. AIMS: Using data from the Cardiovascular Outcomes Study of Alogliptin in Patients with Type 2 Diabetes and Acute Coronary Syndrome trial including patients with T2D and a recent ACS, and a large biomarker panel incorporating proteins measured both in blood and urine, we aim to determine those with best performance for WKF prediction. METHODS: WKF was defined as a ≥40% estimated glomerular filtration rate (eGFR) drop from baseline, eGFR <15 mL/min, or dialysis. Mixed-effects and time-updated Cox models were used. RESULTS: 5,131 patients were included from whom 222 (4.3%) developed at least one WKF episode over a median follow-up of 18 months. Patients who developed WKF were more frequently women, had longer diabetes duration, a more frequent heart failure history, higher anemia prevalence, and impaired kidney function. In multivariable models including all variables (clinical and biomarkers) independently associated with WKF with a p value ≤0.0001, blood kidney injury molecule 1 (KIM-1) was (by far) the variable with strongest WKF association, followed by anemia. KIM-1 alone provided good discrimination for WKF prediction (area under the curve = 0.73). Patients in the high KIM-1-derived risk tertile had a 6.7-fold higher risk of any WKF than patients classified as low risk. In time-updated Cox models, the occurrence of WKF was independently associated with a higher risk of death: adjusted hazard ratio = 4.93 (3.06-7.96), p value <0.0001. CONCLUSION: Blood KIM-1 was the biomarker with the strongest association with WKF. The occurrence of WKF was independently associated with a higher risk of subsequent cardiovascular events and mortality.

Body weight changes in patients with type 2 diabetes and a recent acute coronary syndrome: an analysis from the EXAMINE trial.

BACKGROUND: Patients with type 2 diabetes (T2D) may experience frequent body weight changes over time. The prognostic impact of these weight changes (gains or losses) requires further study. AIMS: To study the associations between changes in body weight (intentional or unintentional) with subsequent outcomes. METHODS: The EXAMINE trial included 5380 patients with T2D and a recent acute coronary syndrome, who were randomized to alogliptin or placebo. Time-updated Cox models and mixed effects models were used to test the associations between changes in body weight and subsequent outcomes over a median follow-up of 1.6 (1.0-2.1) years. RESULTS: During the post-randomization follow-up period, 1044 patients (19.4%) experienced a weight loss ≥ 5% of baseline weight, 2677 (49.8%) had a stable weight, and 1659 (30.8%) had a ≥ 5 % weight gain. Patients with weight loss were more frequently women and had more co-morbid conditions. In contrast, patients who gained ≥ 5% weight were more frequently men with less co-morbid conditions. A weight loss ≥ 5% was independently associated with a higher risk of subsequent adverse outcomes, including all-cause mortality: adjusted HR (95% CI) = 1.79 (1.33-2.42), P < 0.001. Similar associations were found for cardiovascular mortality, the composite of cardiovascular mortality or heart failure hospitalization, and the primary outcome. A weight gain ≥ 5% was independently associated with an increase in the risk of subsequent cardiovascular mortality or heart failure hospitalization only: adjusted HR (95% CI) = 1.34 (1.02-1.76), P = 0.033. CONCLUSIONS: In patients with T2D who had a recent ACS/MI, a ≥ 5% loss of body weight was associated with a higher risk of subsequent cardiovascular events and mortality.

Gaining Efficiency in Clinical Trials With Cardiac Biomarkers: JACC Review Topic of the Week.

The momentum of cardiovascular drug development has slowed dramatically. Use of validated cardiac biomarkers in clinical trials could accelerate development of much-needed therapies, but biomarkers have been used less for cardiovascular drug development than in therapeutic areas such as oncology. Moreover, there are inconsistences in biomarker use in clinical trials, such as sample type, collection times, analytical methods, and storage for future research. With these needs in mind, participants in a Cardiac Safety Research Consortium Think Tank proposed the development of international guidance in this area, together with improved quality assurance and analytical methods, to determine what biomarkers can reliably show. Participants recommended the development of systematic methods for sample collection, and the archiving of samples in all cardiovascular clinical trials (including creation of a biobank or repository). The academic and regulatory communities also agreed to work together to ensure that published information is fully and clearly expressed.

Influence of sex, age and race on coronary and heart failure events in patients with diabetes and post-acute coronary syndrome.

BACKGROUND: Women, older patients and non-White ethnic groups experience a substantial proportion of acute coronary syndromes (ACS), although they have been historically underrepresented in ACS randomized clinical trials (RCTs). To assess the influence of sex, age and race on major adverse cardiovascular events (MACE) and on heart failure events, we studied patients with type 2 diabetes in a large post-ACS trial (EXAMINE). METHODS: Differences in baseline characteristics and the respective composite endpoint of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke (MACE) and cardiovascular death or heart failure hospitalization (HF events) were evaluated by subgroups in a cohort of post-ACS patients with diabetes, using unadjusted and adjusted Cox regression modelling. RESULTS: The EXAMINE trial enrolled 5380 patients with 35% aged > 65, 32% female and 27% non-White. The risk of MACE was higher in non-White compared to White patients after adjustment for potential confounding (HR = 1.35; 95% CI 1.04-1.75), but there were no significant differences by sex and age (HR = 1.03; 95% CI 0.87-1.22 for women; HR = 1.14; 95% CI 0.96-1.35 for patients ≥ 65 years). The risk of HF events was higher in non-White patients (HR = 1.56; 95% CI 1.13-2.14), and in patients aged > 65 (HR = 1.33; 95% CI 1.07-1.66) and nominally so in women (HR = 1.23; 95% CI 0.99-1.52). The additive risk of each demographic factor (women, older age and non-White race) was greater for HF events in comparison with MACE. Moreover, non-White elderly patients consistently had poorer prognosis regardless of sex. CONCLUSIONS: Older adults, women and non-White patients with diabetes who are post-ACS are often underrepresented in RCTs. The risk for HF events was higher in older and non-White patients, with a trend towards significance in women, whereas only non-White patients (and not women and older patients) were at higher risk for MACE. Future trials should enrich enrollment of these persons at risk.

Red cell distribution width in patients with diabetes and myocardial infarction: An analysis from the EXAMINE trial.

AIM: To determine the clinical correlates of increased red blood cell distribution width (RDW), its potential mechanistic association with multiple circulating biomarkers, and its prognostic value in patients with type 2 diabetes (T2D) who had a recent acute coronary syndrome. METHODS: We used time-updated Cox models applied to patients enrolled in the Examination of Cardiovascular Outcomes with Alogliptin versus Standard of Care (EXAMINE) trial. RESULTS: A total of 5380 patients were included, the median age was 61 years and 32% were women. Patients with higher RDW were older, more frequently women, with a longer diabetes duration and increased co-morbidities. An RDW of more than 16.1% (both baseline and time-updated) was independently associated with the study primary composite outcome of non-fatal myocardial infarction, non-fatal stroke or cardiovascular death (time-updated adjusted HR = 1.36, 95% CI = 1.16-1.61, p < .001), all-cause death (time-updated adjusted HR = 2.01, 95% CI = 1.60-2.53, p < .001), as well as mortality from non-cardiovascular causes (time-updated adjusted HR = 2.67, 95% CI = 1.72-4.15, p < .001). RDW had a weak-to-moderate correlation with haemoglobin and circulating markers that reflected inflammation, apoptosis, fibrosis and congestion. Alogliptin did not alter RDW values. CONCLUSIONS: RDW is a marker of disease severity associated with a multitude of poor outcomes, including both cardiovascular and non-cardiovascular death. RDW correlated modestly with inflammatory, pro-apoptotic, pro-fibrotic and congestion markers, and its levels were not affected by alogliptin during the course of the trial.

Multi-proteomic approach to predict specific cardiovascular events in patients with diabetes and myocardial infarction: findings from the EXAMINE trial.

BACKGROUND: Patients with diabetes who had a recent myocardial infarction (MI) are at high risk of cardiovascular events. Therefore, risk assessment is important for treatment and shared decisions. We used data from EXAMINE trial to investigate whether a multi-proteomic approach would provide specific proteomic signatures and also improve the prognostic capacity for determining the risk of cardiovascular death, MI, stroke, heart failure [HF], all-cause death, and combinations of these outcomes. METHODS: 93 circulating proteins (92 from the Olink® CVDII plus troponin) were assessed in 5131 patients. Cox, competing risks, and reclassification measures were applied. RESULTS: The clinical model showed good discrimination and calibration for all outcomes. On top of the clinical model that included age, sex, smoking, diabetes duration, history of MI (prior to the index MI of inclusion), history of HF hospitalization, history of stroke, atrial fibrillation, hypertension, systolic blood pressure, statin therapy, estimated glomerular filtration rate, and study treatment (alogliptin or placebo), troponin and BNP added prognostic information to the composite of cardiovascular death, MI, or stroke (∆C-index + 5%) and cardiovascular death alone (∆C-index + 7%). Troponin, BNP, and TRAILR2 added prognostic information on all-cause death and the composite of cardiovascular death or HF hospitalization. HF hospitalization alone was improved by adding BNP and Gal-9. For MI, troponin, FGF23, and AMBP added prognostic value; whereas for stroke, only troponin added prognostic value (multi-proteomics improved C-index > 3% [p < 0.001] for all the studied outcomes). The addition of the final biomarker selection to the clinical model improved event reclassification (cNRI from + 23% to + 64%). Specifically, the addition of the biomarkers allowed a better classification of patients at low risk (as having "true" low risk) and patients and high risk (as having "true" high risk). These results were consistent for all the studied outcomes with even more marked differences in the fatal events. CONCLUSIONS: The addition of multi-proteomic biomarkers to a clinical model in this population with diabetes and a recent MI allowed a better risk prediction and event reclassification, potentially helping for better risk assessment and targeted treatment decisions. T2D type 2 diabetes, MI myocardial infarction, CV cardiovascular, HFH heart failure hospitalization, Δ delta, cNRI continuous net reclassification index, BNP brain natriuretic peptide, TRAILR2 trail receptor 2 (or death receptor 5), Gal-9 galectin-9, FGF23 fibroblast growth factor 23.

Timing of randomization after an acute coronary syndrome in patients with type 2 diabetes mellitus.

BACKGROUND: The timing of enrolment following an acute coronary syndrome (ACS) may influence cardiovascular (CV) outcomes and potentially treatment effect in clinical trials. Understanding the timing and type of clinical events after an ACS will allow for clinicians to better tailor evidence-based treatments to optimize therapeutic effect. Using a large contemporary trial in patients with type 2 diabetes mellitus (T2DM) post-ACS, we examined the impact of timing of enrolment on subsequent CV outcomes. METHODS: EXAMINE was a randomized trial of alogliptin versus placebo in 5,380 patients with T2DM and a recent ACS from October 2009 to March 2013. The primary outcome was a composite of CV death, nonfatal myocardial infarction (MI), or nonfatal stroke. The median follow-up was 18 months. In this post hoc analysis, we examined the occurrence of subsequent CV events by timing of enrollment divided by tertiles of time from ACS to randomization: 8-34, 35-56, and 57-141 days. RESULTS: Patients randomized early (compared to the latest times) had less comorbidities at baseline including a history of heart failure (HF; 24.7% vs 33.0%), prior coronary artery bypass graft (9.6% vs 15.9%), or atrial fibrillation (5.9% vs 9.4%). Despite the reduced comorbidity burden, the risk of the primary outcome was highest in patients randomized early compared to the latest time (adjusted hazard ratio 1.47; 95% CI 1.21-1.74). Similarly, patients randomized early had an increased risk of recurrent MI (adjusted hazard ratio 1.51; 95% CI 1.17-1.96) and HF hospitalization (1.49; 95% CI 1.05-2.10). CONCLUSIONS: In a contemporary cohort of T2DM with a recent ACS, the risk for recurrent CV events including MI and HF hospitalization is elevated early after an ACS. Given the emergence of antihyperglycemic therapies that reduce the risk of MI and HF among patients with T2DM at high CV risk, future studies evaluating the initiation of these therapies in the early period following an ACS are warranted given the large burden of potentially modifiable CV events.

Alogliptin after acute coronary syndrome in patients with type 2 diabetes: a renal function stratified analysis of the EXAMINE trial.

BACKGROUND: The EXAMINE trial tested the efficacy and safety of alogliptin, an inhibitor of dipeptidyl peptidase 4, compared with placebo in 5380 patients with type 2 diabetes and a recent acute coronary syndrome. Because alogliptin is cleared by the kidney, patients were stratified according to screening renal function within two independently randomized strata: (1) estimated glomerular filtration rate (eGFR) ≥ 60 ml/min/1.73m2 and (2) eGFR < 60 ml/min/1.73m2. We aim to assess the efficacy and safety of alogliptin vs. placebo according to the renal function strata. METHODS: Cox-proportional hazard models with an interaction term by renal function strata were used. The primary endpoint was a composite of cardiovascular death, nonfatal myocardial infarction (MI), or nonfatal stroke. RESULTS: Patient characteristics were balanced within each renal function strata. In total, 3946 patients were randomized within the eGFR ≥ 60 stratum, and 1434 patients within the eGFR < 60 stratum. The effect of alogliptin was modified by the renal function strata. PRIMARY OUTCOME: eGFR ≥ 60 HR = 0.81, 95%CI, 0.65-0.99, and eGFR < 60 HR = 1.20, 95%CI, 0.95-1.53; interactionp = 0.014. Cardiovascular death: eGFR ≥ 60 HR = 0.61, 95%CI, 0.42-0.88, and eGFR < 60 HR = 1.16, 95%CI, 0.82-1.65; interactionp = 0.013. Non-fatal MI: eGFR ≥ 60 HR = 0.86, 95%CI, 0.66-1.13, and eGFR < 60 HR = 1.48, 95%CI, 1.07-2.06; interactionp = 0.013. CONCLUSIONS: Alogliptin may benefit patients with eGFR ≥ 60, but may be detrimental to patients with eGFR < 60 ml/min/1.73m2. These hypothesis-generating findings require further validation to assess the potential benefit and risk of alogliptin across the renal function spectrum among patients with type 2 diabetes and a recent acute coronary syndrome. TRIAL REGISTRATION: ClinicalTrials.gov, NCT00968708.

Adaptive multiarm multistage clinical trials.

Two methods for designing adaptive multiarm multistage (MAMS) clinical trials, originating from conceptually different group sequential frameworks are presented, and their operating characteristics are compared. In both methods pairwise comparisons are made, stage-by-stage, between each treatment arm and a common control arm with the goal of identifying active treatments and dropping inactive ones. At any stage one may alter the future course of the trial through adaptive changes to the prespecified decision rules for treatment selection and sample size reestimation, and notwithstanding such changes, both methods guarantee strong control of the family-wise error rate. The stage-wise MAMS approach was historically the first to be developed and remains the standard method for designing inferentially seamless phase 2-3 clinical trials. In this approach, at each stage, the data from each treatment comparison are summarized by a single multiplicity adjusted P-value. These stage-wise P-values are combined by a prespecified combination function and the resultant test statistic is monitored with respect to the classical two-arm group sequential efficacy boundaries. The cumulative MAMS approach is a more recent development in which a separate test statistic is constructed for each treatment comparison from the cumulative data at each stage. These statistics are then monitored with respect to multiplicity adjusted group sequential efficacy boundaries. We compared the powers of the two methods for designs with two and three active treatment arms, under commonly utilized decision rules for treatment selection, sample size reestimation and early stopping. In our investigations, which were carried out over a reasonably exhaustive exploration of the parameter space, the cumulative MAMS designs were more powerful than the stage-wise MAMS designs, except for the homogeneous case of equal treatment effects, where a small power advantage was discernable for the stage-wise MAMS designs.

Optimal promising zone designs.

Clinical trials with adaptive sample size reassessment based on an unblinded analysis of interim results are perhaps the most popular class of adaptive designs (see Elsäßer et al., 2007). Such trials are typically designed by prespecifying a zone for the interim test statistic, termed the promising zone, along with a decision rule for increasing the sample size within that zone. Mehta and Pocock (2011) provided some examples of promising zone designs and discussed several procedures for controlling their type-1 error. They did not, however, address how to choose the promising zone or the corresponding sample size reassessment rule, and proposed instead that the operating characteristics of alternative promising zone designs could be compared by simulation. Jennison and Turnbull (2015) developed an approach based on maximizing expected utility whereby one could evaluate alternative promising zone designs relative to a gold-standard optimal design. In this paper, we show how, by eliciting a few preferences from the trial sponsor, one can construct promising zone designs that are both intuitive and achieve the Jennison and Turnbull (2015) gold-standard for optimality.

Fasiglifam-Induced Liver Injury in Patients With Type 2 Diabetes: Results of a Randomized Controlled Cardiovascular Outcomes Safety Trial.

OBJECTIVE: To evaluate the cardiovascular (CV) safety of fasiglifam, a first-in-man G-protein-coupled receptor 40 (GPR40) agonist, in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: A phase 3 multicenter randomized double-blind placebo-controlled two-arm trial was intended to randomize 5,000 participants with type 2 diabetes at high CV risk to fasiglifam or placebo. The primary objective of the trial was to rule out an upper noninferiority bound >1.3 for a one-sided 97.5% confidence limit of the hazard ratio (HR) for CV composite events during treatment with fasiglifam compared with placebo. The primary outcome was the time to first occurrence of any component of the major adverse CV event composite of CV death, nonfatal myocardial infarction, nonfatal stroke, and hospitalization for unstable angina. RESULTS: The study enrolled 3,207 participants but was terminated because of liver safety concerns. Increased rates of liver enzyme elevation (AST/ALT ≥3-5 × upper limit of normal [ULN]) with fasiglifam were observed. The incidence of ALT or AST ≥3 × ULN with fasiglifam compared with placebo was 2.1% vs. 0.5%, P < 0.001, and the incidence for ≥10 × ULN was 0.31% vs. 0.06%, P < 0.001. A primary CV composite outcome occurred in 40 participants, 2.5% each in the fasiglifam and placebo arms at 12 months (HR 1.05; 95% CI 0.67, 1.63). CONCLUSIONS: Development of fasiglifam was terminated due to concerns of drug-induced liver injury. Performance of a U.S. Food and Drug Administration-mandated CV outcomes trial supported the termination of the fasiglifam clinical program.

Average Clinician-Measured Blood Pressures and Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus and Ischemic Heart Disease in the EXAMINE Trial.

Background Blood pressure ( BP ) treatment goals in patients with diabetes mellitus and increased cardiovascular risk remain controversial. Our study objective was to determine cardiovascular outcomes according to achieved BP s over the average follow-up period in the EXAMINE (Examination of Cardiovascular Outcomes With Alogliptin Versus Standard of Care) trial. Methods and Results EXAMINE was a cardiovascular outcomes trial in 5380 patients with type 2 diabetes mellitus and recent acute coronary syndromes. Risks of major adverse cardiac events and cardiovascular death or heart failure were analyzed using a Cox proportional hazards model with adjustment for baseline covariates in 10-mm Hg increments of clinician-measured systolic BP from ≤100 to >160 mm Hg and diastolic BP from ≤60 to >100 mm Hg averaged during the 24 months after randomization. Based on 2015 guidelines from the American College of Cardiology, the American Heart Association and the American Society of Hypertension and 2017 American Diabetes Association guidelines, systolic BP s of 131 to 140 mm Hg and diastolic BP s of 81 to 90 mm Hg were the reference groups. A U-shaped relationship between cardiovascular outcomes and BP s was observed. Importantly, compared with the systolic BP reference group, adjusted hazard ratios for major adverse cardiac events and cardiovascular death or heart failure were significantly higher in patients with systolic BP s <130 mm Hg. Similarly, compared with the diastolic BP reference group, adjusted hazard ratios for major adverse cardiac events and for cardiovascular death or heart failure were significantly higher for diastolic BP s <80 mm Hg. Conclusions In patients with type 2 diabetes mellitus and recent acute coronary syndrome, average BP s <130/80 mm Hg were associated with worsened cardiovascular outcomes. These data suggest that intensive control of BP in patients with type 2 diabetes mellitus and ischemic heart disease should be evaluated in a prospective randomized trial. Clinical Trial Registration URL : https://www.clinicaltrials.gov . Unique identifier: NCT 00968708.