Improving Collection and Analysis of Overall Survival Data.

Advances in anticancer therapies have provided crucial benefits for millions of patients who are living long and fulfilling lives. Although these successes should be celebrated, there is certainly room to continue improving cancer care. Increased long-term survival presents additional challenges for determining whether new therapies further extend patients' lives through clinical trials, commonly known as the gold standard endpoint of overall survival (OS).

Treatment effect measures under nonproportional hazards.

In a clinical trial with a time-to-event endpoint the treatment effect can be measured in various ways. Under proportional hazards all reasonable measures (such as the hazard ratio and the difference in restricted mean survival time) are consistent in the following sense: Take any control group survival distribution such that the hazard rate remains above zero; if there is no benefit by any measure there is no benefit by all measures, and as the magnitude of treatment benefit increases by any measure it increases by all measures. Under nonproportional hazards, however, survival curves can cross, and the direction of the effect for any pair of measures can be inconsistent.

A shrinkage estimator for subgroup analysis without the exchangeability assumption.

Shrinkage estimators for exploratory subgroup analyses are intuitively appealing and can greatly improve estimation over standard analysis approaches; however, adoption of these estimators has been limited by reliance on the exchangeability assumption. This paper describes a new shrinkage estimator that does not rely on this assumption. Rather than assuming that treatment effect sizes within subgroups are randomly distributed around an overall mean, this new estimator assumes that the difference between the effect sizes in any given pair of subgroups is randomly distributed around zero.

Content Validity of HIT-6 as a Measure of Headache Impact in People With Migraine: A Narrative Review.

Background: The short-form Headache Impact Test (HIT-6) is a widely used patient-reported outcome measure that assesses the negative effects of headaches on normal activity. It was developed using the general headache population and prior to the establishment of the now well-accepted FDA patient-reported guidance.

Objective: The objective of this narrative review was to examine existing qualitative research in patients with migraine and headache, providing insight into the relevance and meaningfulness of HIT-6 items to the lives of migraine patients.

Some remaining challenges regarding multiple endpoints in clinical trials.

Despite recent advance in methods for handling multiple endpoints in clinical trials, some challenges remain. This paper discusses some of these challenges, including confusion surrounding the terminology used to describe the multiple endpoints, the justification for simultaneously testing for non-inferiority and superiority in a non-inferiority trial, lack of agreement on the situations under which multiple objectives do or do not lead to the need for a multiplicity correction, and choice of the most appropriate multiple comparisons procedure. In addition, this paper will discuss the position of the recent FDA draft guidance, Multiple Endpoints in Clinical Trials, on these issues.

Responsibilities of Data Monitoring Committees: Consensus Recommendations.

Background: A data monitoring committee (DMC) has special responsibilities for protecting the safety of clinical trial participants. Few guidance documents are available that address the operations and mechanics of establishing, serving on, or reporting to a DMC. This article provides a practical guide to sponsors, institutions, and individuals responsible for, or serving on, a DMC.

Statistical Considerations on the Evaluation of Imbalances of Adverse Events in Randomized Clinical Trials.

Adverse events (AEs) data compose the main body of safety data in clinical trials. Medically important imbalances of AEs in large double-blind randomized controlled trials (RCTs) are signals of potential adverse drug reactions. They will be further evaluated for causality and shape the initial label that gives users necessary information on the safe use of the drug.

Choosing Appropriate Metrics to Evaluate Adverse Events in Safety Evaluation.

Safety assessment and monitoring are critical throughout the life cycle of drug development. The evaluation of safety information, specifically adverse events, from clinical trials has always been challenging for a number of reasons, such as the unexpectedness and rarity of some important adverse events, the fact that some events can recur, and the events' variability in duration and severity. To accurately characterize and communicate the risk profile of a drug, the choice of metrics is critical.

Remaining Challenges in Assessing Non-Inferiority.

Despite decades of experience with non-inferiority trials, they remain a source of great controversy and involve fundamental areas of disagreement. Indeed, there can be little more fundamental than the definition of the hypothesis to be tested, and yet it can be argued that the null hypothesis commonly used in these trials, which involves specification of a non-inferiority margin, is the wrong one. Non-inferiority trials involve an indirect comparison between the experimental treatment under evaluation and placebo, but the null hypothesis based on a non-inferiority margin does not address this aspect of the trial's objective.

Pure and hybrid causal effects on variables associated with an incident event.

This article is concerned with the assessment of the causal effect of a treatment on a variable that is defined only in the subset of patients who experience a specific event. In this case, the treatment can affect the variable directly, as well as indirectly through its effect on the occurrence and severity of the event. In this article we describe the pure (direct) and hybrid (direct and indirect) causal effects and methods typically used to assess them.

The issue of multiplicity in noninferiority studies.

Background: In a clinical study to evaluate noninferiority (NI) of an experimental drug relative to an established therapy, it is common to further test superiority of the experimental drug after NI is established. It has been shown that no multiplicity issue exists between NI and superiority tests of the primary endpoint. However, when there is an additional, or secondary, endpoint that will be tested for superiority in a hierarchical fashion to the NI testing of the primary endpoint, it is not clear whether the overall type I error rate is strictly controlled among all the tests.

Predicting analysis time in event-driven clinical trials with event-reporting lag.

For a clinical trial with a time-to-event primary endpoint, the rate of accrual of the event of interest determines the timing of the analysis, upon which significant resources and strategic planning depend. It is important to be able to predict the analysis time early and accurately. Currently available methods use either parametric or nonparametric models to predict the analysis time based on accumulating information about enrollment, event, and study withdrawal rates and implicitly assume that the available data are completely reported at the time of performing the prediction.

Indirect comparisons in the comparative efficacy and non-inferiority settings.

International Conference on Harmonization E10 concerns non-inferiority trials and the assessment of comparative efficacy, both of which often involve indirect comparisons. In the non-inferiority setting, there are clinical trial results directly comparing an experimental treatment with an active control, and clinical trial results directly comparing the active control with placebo, and there is an interest in the indirect comparison of the experimental treatment with placebo. In the comparative efficacy setting, there may be separate clinical trial results comparing each of two treatments with placebo, and there is interest in an indirect comparison of the treatments.

On the clinical meaningfulness of a treatment's effect on a time-to-event variable.

The standard analysis of a time-to-event variable often involves the calculation of a hazard ratio based on a survival model such as Cox regression; however, many people consider such relative measures of effect to be poor expressions of clinical meaningfulness. Two absolute measures of effect are often used to assess clinical meaningfulness: (1) many disease areas frequently use the absolute difference in event rates (or its inverse, the number-needed-to-treat) and (2) oncology frequently uses the difference between the median survival times in the two groups. While both of these measures appear reasonable, they directly contradict each other.

Statins for secondary prevention of cardiovascular disease: the right dose.

Since the publication of the 4S trial in 1994, there has emerged a consensus that statins save lives and decrease myocardial infarctions and strokes in coronary artery disease (CAD) patients irrespective of baseline serum cholesterol. However, there is controversy over the correct dose and the utility of the treatment-to-goal (cholesterol, low-density lipoprotein) approach. To answer remaining questions about the optimal statin dose in CAD patients, we have performed simple and meta-analyses of 3 large long-term (approx.

Predictors of cardiovascular events in patients with hypertension and left ventricular hypertrophy: the Losartan Intervention for Endpoint reduction in hypertension study.

Objective: We assessed readily available patient characteristics, including albuminuria (not included in traditional cardiovascular risk scores), as predictors of cardiovascular events in hypertension with left ventricular hypertrophy (LVH) and developed risk algorithms/scores for outcomes.

Methods: The Losartan Intervention For Endpoint reduction in hypertension (LIFE) study compared effects of losartan-based versus atenolol-based therapy on cardiovascular events in 9193 patients with hypertension and LVH. Univariate and multivariate analyses identified baseline variables with significant impact on development of the primary composite endpoint (cardiovascular death, stroke and myocardial infarction) and its components.

Moderate alcohol consumption is associated with reduced long-term cardiovascular risk in patients following a complicated acute myocardial infarction.

Background: The impact on prognosis of alcohol use in patients with coronary artery disease remains uncertain. We related alcohol use to all-cause mortality, cardiovascular (CV)-mortality and hospitalization in patients following a complicated myocardial infarction (MI).

Methods: In the OPTIMAAL trial, 5477 patients from 7 Western European countries with heart failure and/or evidence of left ventricular dysfunction following MI were recruited.

Responder analyses and the assessment of a clinically relevant treatment effect.

Ideally, a clinical trial should be able to demonstrate not only a statistically significant improvement in the primary efficacy endpoint, but also that the magnitude of the effect is clinically relevant. One proposed approach to address this question is a responder analysis, in which a continuous primary efficacy measure is dichotomized into "responders" and "non-responders." In this paper we discuss various weaknesses with this approach, including a potentially large cost in statistical efficiency, as well as its failure to achieve its main goal.

Controlling the type 1 error rate in non-inferiority trials.

Two different approaches have been proposed for establishing the efficacy of an experimental therapy through a non-inferiority trial: The fixed-margin approach involves first defining a non-inferiority margin and then demonstrating that the experimental therapy is not worse than the control by more than this amount, and the synthesis approach involves combining the data from the non-inferiority trial with the data from historical trials evaluating the effect of the control. In this paper, we introduce a unified approach that has both these approaches as special cases and show how the parameters of this approach can be selected to control the unconditional type 1 error rate in the presence of departures from the assumptions of assay sensitivity and constancy. It is shown that the fixed-margin approach can be extremely inefficient and that it is always possible to achieve equivalent control of the unconditional type 1 error rate, with higher power, by using an appropriately chosen synthesis method.

Preservation of effect and the regulatory approval of new treatments on the basis of non-inferiority trials.

The criteria for approval of an experimental treatment on the basis of active-controlled non-inferiority trials often include demonstration of 'preservation of effect' relative to the active control. While this appears on its surface to be a reasonable criterion, on closer inspection it can be shown to lead to serious logical inconsistencies. In particular, an experimental treatment may have clinical trial results that are superior to those for the standard treatment and yet fail to meet this criterion for approval.