Comparing methods to combine functional loss and mortality in clinical trials for amyotrophic lateral sclerosis

Introduction

Amyotrophic lateral sclerosis (ALS) is an incurable, rapidly progressive, neurodegenerative disease. As ALS significantly reduces the patient's life expectancy, evaluating the efficacy of experimental treatments in terms of a benefit to survival is the ultimate goal of any ALS clinical trial.¹ However, survival time may be influenced by life-extending interventions (such as gastrostomy or tracheostomy) and provides little information about the patient's functioning and disability during life.^2–7 Moreover, measuring survival time requires lengthy and large clinical trials, which may not be suitable during either early or late phases of drug development, especially when one considers the relatively low incidence of ALS.^2–6,8

In order to reduce both the sample size and the duration of ALS clinical trials, functional outcome measures, such as the revised amyotrophic lateral sclerosis functional rating scale (ALSFRS-R), are often used as a primary end point.⁹ The ALSFRS-R is a clinically relevant, easily obtained, well-validated measurement, which is highly predictive of overall survival.^2–4,6 However, results from earlier development programs, with positive Phase II results on functional measures, have until now translated poorly into Phase III survival end points.^2,4 Furthermore, it remains a matter of debate how one should manage missing data from functional scores due to death.^1,9,10

Although both the functional and survival end points have their own strengths and weaknesses, treatments for ALS may, nevertheless, affect both survival and function simultaneously. Therefore, any trial based on a single end point might only partially capture the full treatment effect and potentially falsely discard the tested agent as futile.^1,10 Several solutions have been suggested and used in past ALS clinical trials to circumvent this issue, with most notably the combined assessment of function and survival (CAFS).^11,12 The CAFS has been shown by simulation to increase statistical power when there is a treatment effect on both the functional and survival end points.^1,10 However, an important limitation of the CAFS is that it becomes underpowered when there is an exclusive survival benefit without functional gain, a scenario seen, for example, in the riluzole trials, which could potentially lead to false-negative conclusions.^1,10,13

Joint models (or shared parameter models) are another well-known method to simultaneously analyze functional decline and mortality.¹⁴ In contrast to the...