Duchenne muscular dystrophy (DMD) is a rare, severe, progressive muscle-wasting disease leading to disability and premature death. Patients lack the muscle membrane-stabilizing protein dystrophin. Antisense oligonucleotide (AON)-mediated exon skipping is a therapeutic approach that aims to induce production of partially functional dystrophins. Recently, an AON targeting exon 51 became the first of its class to be approved by the United States regulators [Food and Drug Administration (FDA)] for the treatment of DMD. A unique aspect of the exon-skipping approach for DMD is that, depending on the size and location of the mutation, different exons need to be skipped. This challenge raises a number of questions regarding the development and regulatory approval of those individual compounds. In this study, we present a perspective on those questions, following a European stakeholder meeting involving academics, regulators, and representatives from industry and patient organizations, and in the light of the most recent scientific and regulatory experience.

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Treatment non-compliance and missing data are common problems in clinical trials. Non-compliance is a broad term including any kind of deviation from the assigned treatment protocol, such as dose modification, treatment discontinuation or switch, often resulting in missing values. Missing values and treatment non-compliance may bias study results. Follow-up of all patients until the planned end of treatment period irrespective of their protocol adherence may provide useful information on the effectiveness of a study drug, taking the actual compliance into account. In this paper, we consider non-compliance as discontinuation of treatment and assume that the endpoint of interest is recorded for some non-complying patients after treatment discontinuation. As a result, the patient's longitudinal profile is dividable into on- and off-treatment observations. Within the framework of depression trials, which usually show a considerably high amount of dropouts, we compare different analysis strategies including both on- and off-treatment observations to gain insight into how the additional use of off-treatment data may affect the trial's outcome. We compare naïve strategies, which simply ignore off-treatment data or treat on- and off-treatment data in the same way, with more complex strategies based on piecewise linear mixed models, which assume different treatment effects for on- and off-treatment data. We show that naïve strategies may considerably overestimate treatment effects. Therefore, it is worthwhile to follow up as many patients as possible until the end of their planned treatment period irrespective of compliance, including all available data in an analysis that accounts for the different treatment conditions.

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As medical care for the majority of the elderly population is provided by general practitioners, adequate longitudinal studies are of special interest for investigating drug safety in the elderly. This aim is being pursued by the AgeCoDe study (German study on aging, cognition and dementia in primary care patients), a prospective, multicentre observational study, which is being carried out within the German competence network of degenerative dementia (Kompetenznetz Degenerative Demenzen).