Initiation of symptomatic medication in Alzheimer's disease clinical trials: Hypothetical versus treatment policy approach

Natural cubic splines for the analysis of Alzheimer's clinical trials

Mixed model repeated measures (MMRM) is the most common analysis approach used in clinical trials for Alzheimer's disease and other progressive diseases measured with continuous outcomes over time. The model treats time as a categorical variable, which allows an unconstrained estimate of the mean for each study visit in each randomized group. Categorizing time in this way can be problematic when assessments occur off-schedule, as including off-schedule visits can induce bias, and excluding them ignores valuable information and violates the intention to treat principle. This problem has been exacerbated by clinical trial visits which have been delayed due to the COVID19 pandemic. As an alternative to MMRM, we propose a constrained longitudinal data analysis with natural cubic splines that treats time as continuous and uses test version effects to model the mean over time. Compared to categorical-time models like MMRM and models that assume a proportional treatment effect, the spline model is shown to be more parsimonious and precise in real clinical trial datasets, and has better power and Type I error in a variety of simulation scenarios.

Real-world effects of anti-dementia treatment on mortality in patients with Alzheimer´s dementia

To examine the real-world effects of the cholinesterase inhibitors (AChEI) on all-cause mortality. A nationwide, retrospective cohort study. Participants were diagnosed with incident AD in Denmark from January 1, 2000 to December 31, 2011 with follow-up until December 31, 2012. A total of 36,513 participants were included in the current study with 22,063 deaths during 132,426 person-years of follow-up. At baseline, patients not treated with AChEI (n = 28,755 [9961 males (35%)]) had a mean age ± standard deviation (SD) of 80.33 ± 7.98 years (78.97 ± 8.26 for males and 81.04 ± 7.98 for females), as compared to 79.95 ± 7.67 (78.87 ± 7.61 for males and 80.61 ± 7.63 for females) in the group exposed at baseline. Patients treated with AChEI had a beneficial hazard ratio (HR) of 0.69, 95% confidence interval (CI) (0.67-0.71) for all-cause mortality as compared to patients not treated, with donepezil (HR 0.80, 95% CI [0.77-0.82]) and galantamine (HR 0.93,95% CI [0.89-0.97]) having beneficial effects on mortality rate as compared to non-treatment, whereas rivastigmine (HR 0.99, 95% CI [0.95-1.03]) was associated with a mortality rate comparable to non-treatment with AChEI. Patients were primarily exposed to donepezil (65.8%) with rivastigmine (19.8%) and galantamine (14.4%) being used less often. These findings underscore the effect of AChEI on not only reducing speed of cognitive decline but also directly prolonging life, which could result in changes in treatment recommendation for when to stop treatment.

Estimands-a Basic Element for Clinical Trials. Part 29 of a Series on Evaluation of Scientific Publications

BACKGROUND

Clinical trials are of central importance for the evaluation and comparison of treatments. The transparency and intelligibility of the treatment effect under investigation is an essential matter for physicians, patients, and health-care authorities. The estimand framework has been introduced because many trials are deficient in this respect.

METHODS

Introduction, definition, and application of the estimand framework on the basis of an example and a selective review of the literature.

RESULTS

The estimand framework provides a systematic approach to the definition of the treatment effect under investigation in a clinical trial. An estimand consists of five attributes: treatment, population, variable, population-level summary, and handling of intercurrent events. Each of these attributes is defined in an interdisciplinary discussion during the trial planning phase, based on the clinical question being asked. Special attention is given to the handling of intercurrent events (ICEs): these are events-e.g., discontinuation or modification of treatment or the use of emergency medication-that can occur once the treatment has begun and might affect the possibility of observing the endpoints or their interpretability. There are various strategies for the handling of ICEs; these can, for example, also reflect the existing intentionto- treat (ITT) principle. Per-protocol analyses, in contrast, are prone to bias and cannot be represented in a sensible manner by an estimand, although they may be performed as a supplementary analysis. The discussion of potential intercurrent events and how they should appropriately be handled in view of the aim of the trial must already take place in the planning phase.

CONCLUSION

Use of the estimand framework should make it easier for both physicians and patients to understand what trials reveal about the efficacy of treatment, and to compare the results of different trials.