Clinical Trials

Phase II cancer clinical trial designs commonly incorporate an interim analysis for lack of efficacy. To strictly and ethically implement such designs, one should suspend accrual in cases where pending patient outcomes can affect early termination decisions. This article aims to evaluate various options for accrual suspension and illustrate how the suspension strategy affects operating characteristics of the trial.

We define a strict suspension strategy for determining whether one should continue, suspend, or restart accrual at any point within the trial. The strategy is compared to a naive implementation of suspension and a strategy of no suspension. We evaluate the methods’ operating characteristics by simulation.

The suspension strategy has little effect on type I error, power, and early termination probability. Methods that involve stricter suspension policies generally lead to smaller but longer trials. Differences across strategies are substantial when the ratio of enrollment rate to outcome availability rate is high.

The suspension strategy is most relevant in trials that accrue rapidly and require lengthy observation of each subject. The choice of suspension strategy involves a tradeoff between the cost of implementing a potentially complex suspension algorithm in real time versus the cost of enrolling more patients and exposing them to a potentially toxic and ineffective treatment regimen.

Missing data are an unavoidable problem in clinical trials. Most existing missing data approaches assume the missing data are missing at random. However, the missing at random assumption is often questionable when the real causes of missing data are not well known and cannot be tested from observed data.

We propose a specific missing not at random assumption, which we call masked missing not at random, which may be more plausible than missing at random for masked clinical trials. We formulate models for categorical and continuous outcomes under this assumption. Simulations are conducted to examine the finite sample performance of our methods and compare them with other methods. R code for the proposed methods is provided in supplementary materials.

Simulation studies confirm that maximum likelihood methods assuming masked missing not at random outperform complete case analysis and maximum likelihood assuming missing at random when masked missing not at random is true. For the particular missing at random model where both of missing at random and masked missing not at random are satisfied, theory suggests that maximum likelihood assuming missing at random is at least as efficient as maximum likelihood assuming masked missing not at random. However, maximum likelihood assuming masked missing not at random is nearly as efficient as maximum likelihood assuming missing at random in our simulated settings. We also applied our methods to the TRial Of Preventing HYpertension study. The missing at random estimated treatment effect and its 95% confidence interval are robust to deviations from missing at random of the form implied by masked missing not at random.

Methods based on the masked missing not at random assumption are useful for masked clinical trials, either in their own right or to provide a form of sensitivity analysis for deviations from missing at random. Missing at random analysis might be favored on grounds of efficiency if the estimates based on masked missing not at random and missing at random are similar, but if the estimates are substantially different, the masked missing not at random estimates might be preferred because the mechanism is more plausible.

Subject-specific electrocardiographic QT interval correction for heart rate is often used in clinical trials with frequent electrocardiographic recordings. However, in these studies relatively few 10-s, 12-lead electrocardiograms may be available for calculating the individual correction. Highly automated QT and RR measurement tools have made it practical to measure electrocardiographic intervals on large volumes of continuous electrocardiogram data. The purpose of this study was to determine whether an automated method can be used in lieu of a manual method.

In 49 subjects who completed all treatments in a four-armed crossover study we compared two methods for derivation of individualized rate-correction coefficients: manual measurement on 10-s electrocardiograms and automated measurement of QT and RR during continuous 24-h electrocardiogram recordings. The four treatments, received by each subject in a latin-square randomization sequence were placebo, moxifloxacin, and two doses of an investigational drug.

Analysis of continuous electrocardiogram data yielded a lower standard deviation of QT:RR regression values than the manual method, though the differences were not statistically significant. The within-subject and within-treatment coefficients of variation between the manual and automated methods were not significantly different. Corrected QT values from the two methods had similar rates of true and false positive identification of moxifloxacin’s QT prolonging effect.

An automated method for individualized rate correction applied to continuous electrocardiogram data could be advantageous in clinical trials, as the automated method is simpler, is based upon a much larger volume of data, yields similar results, and requires no human over-reading of the measurements.

Retaining patients in prevention of mother-to-child transmission of HIV studies can be challenging in resource-limited settings, where high lost to follow-up rates have been reported. In this article, we describe the effectiveness of methods used to encourage retention in the Breastfeeding, Antiretrovirals, and Nutrition study and analyze factors associated with lost to follow-up in the study.

The Breastfeeding, Antiretrovirals, and Nutrition clinical trial was designed to evaluate the efficacy of three different mother-to-child HIV transmission prevention strategies. Lower than expected participant retention prompted enhanced efforts to reduce lost to follow-up during the conduct of the trial. Following study completion, we employed regression modeling to determine predictors of perfect attendance and variables associated with being lost to follow-up.

During the study, intensive tracing efforts were initiated after the first 1686 mother–infant pairs had been enrolled, and 327 pairs were missing. Of these pairs, 60 were located and had complete data obtained. Among the 683 participants enrolling after initiation of intensive tracing efforts, the lost to follow-up rate was 3.4%. At study’s end, 290 (12.2%) of the 2369 mother–infant pairs were lost to follow-up. Among successfully traced missing pairs, relocation was common and three were deceased. Log-binomial regression modeling revealed higher maternal hemoglobin and older maternal age to be significant predictors of perfect attendance. These factors and the presence of food insecurity were also significantly associated with lower rates of lost to follow-up.

In this large HIV prevention trial, intensive tracing efforts centered on reaching study participants at their homes succeeded in finding a substantial proportion of lost to follow-up participants and were very effective in preventing further lost to follow-up during the remainder of the trial. The association between food insecurity and lower rates of lost to follow-up is likely related to the study’s provision of nutritional support, including a family maize supplement, which may have contributed to patient retention.

Over the last decade, the United Kingdom has invested significant resources in its clinical trial infrastructure. Clinical research networks have been formed, and some general oversight functions for clinical research have been centralised. One of the initiatives is a registration programme for Clinical Trials Units involved in the coordination of clinical trials. An international review panel of experts in clinical trials has been convened for three reviews over time, reviewing applications from Clinical Trials Units in the United Kingdom. The process benefited from earlier work by the National Cancer Research Institute that developed accreditation procedures for trials units involved in cancer trials. This article describes the experience with the three reviews of UK Clinical Trials Units which submitted applications.

This article describes the evolution and impact of this registration process from the perspective of the current international review panel members, some of whom have served on all reviews, including two done by the National Cancer Research Institute.

Applications for registration were invited from all active, non-commercial Clinical Trials Units in the United Kingdom. The invitations were issued in 2007, 2009 and 2012, and applicants were asked to describe their expertise and staffing levels in specific areas. To ensure that the reviews were as objective as possible, a description of expected core competencies was developed and applicants were asked to document their compliance with meeting these. The review panel assessed each Clinical Trials Unit against the competencies. The Clinical Trials Unit registration process has evolved over time with each successive review benefiting from what was learned in earlier ones.

The review panel has seen positive changes over time, including an increase in the number of units applying, a greater awareness on the part of host institutions about the trials activity within their organisations, more widespread development of Standard Operating Procedures in key areas and improvements in information technology systems used to host clinical trials databases. Key funders are awarding funds only to registered units, and host institutions are implementing procedures and structures to ensure improved communication between all parties involved in trials within their organisation.

The registration process developed in the United Kingdom has helped to ensure that trials units in the United Kingdom are compliant with regulatory standards and can meet acceptable standards of quality in their conduct of clinical trials. There is an increased awareness among funders, host institutions and Clinical Trials Units themselves of the required competencies, and communication between all those involved in trials has increased. The registration process is an effective and financially viable way of ensuring that objective standards are met at a national level.