Keratin-associated epidermolysis bullosa simplex: phenotypes and challenges in clinical trials - a narrative review and systematic update.

Introduction: Clinical research on innovative therapies for the rare genodermatosis epidermolysis bullosa (EB) faces significant challenges, including small sample sizes, disease heterogeneity with intra- and inter-individual variability, limited understanding of pathogenic mechanisms and natural disease course, as well as the lack of patient-centred core outcomes. Moreover, existing tools and techniques to assess disease activity and dynamics are heterogeneous, inconsistent, and may fail to consider or inaccurately emphasize particularities of individual patients and distinct EB subtypes.

Methods: In order to exemplify the differences between keratin-associated subtypes of EB simplex (k-EBS), we summarized respective clinical characteristics in a narrative way.

Reflection on clinical and methodological issues in rare disease clinical trials.

Rare diseases present critical challenges to healthcare systems, patients, and caregivers due to their low prevalence and unique characteristics. Designing clinical trials and developing statistical methodologies for evaluating interventions in rare diseases face several challenges. The "EBStatMax" project, part of the European Joint Programme on Rare Diseases' Demonstration Projects, aimed to address one of these challenges, namely: designing and analyzing longitudinal cross-over data in rare diseases, like Epidermolysis bullosa simplex (EBS).

Milestone events in recessive dystrophic epidermolysis bullosa: findings of the PEBLES study.

Background: In recessive dystrophic epidermolysis bullosa (RDEB), complications like oesophageal strictures, hand contractures, cardiomyopathy and cutaneous squamous cell carcinoma (SCC) may develop. These complications necessitate procedures such as oesophageal dilatation (OD), gastrostomy tube placement and hand surgery.

Objectives: To determine the prevalence and age of onset of milestone events by RDEB subtype, specifically dysphagia, first OD, first gastrostomy tube, first hand surgery, cardiomyopathy, first SCC and death.

Impact of anastomotic leak vs pneumonia on failure to rescue after transthoracic esophagectomy for cancer.

Background: Data about failure to rescue (FTR) after esophagectomy for cancer and its association with patient and procedure-related risk factors are limited. This study aimed to analyze such aspects, particularly focusing on the effect of pneumonia and anastomotic leak on FTR.

Methods: Patients who underwent an Ivor Lewis esophagectomy for cancer between 2008 and 2022 in 2 tertiary European centers were prospectively identified.

Statistical recommendations for count, binary, and ordinal data in rare disease cross-over trials.

Background: Recommendations for statistical methods in rare disease trials are scarce, especially for cross-over designs. As a result various state-of-the-art methodologies were compared as neutrally as possible using an illustrative data set from epidermolysis bullosa research to build recommendations for count, binary, and ordinal outcome variables. For this purpose, parametric (model averaging), semiparametric (generalized estimating equations type [GEE-like]) and nonparametric (generalized pairwise comparisons [GPC] and a marginal model implemented in the R package nparLD) methods were chosen by an international consortium of statisticians.

How to analyze continuous and discrete repeated measures in small-sample cross-over trials?

To optimize the use of data from a small number of subjects in rare disease trials, an at first sight advantageous design is the repeated measures cross-over design. However, it is unclear how these within-treatment period and within-subject clustered data are best analyzed in small-sample trials. In a real-data simulation study based upon a recent epidermolysis bullosa simplex trial using this design, we compare non-parametric marginal models, generalized pairwise comparison models, GEE-type models and parametric model averaging for both repeated binary and count data.

A neutral comparison of statistical methods for analyzing longitudinally measured ordinal outcomes in rare diseases.

Ordinal data in a repeated measures design of a crossover study for rare diseases usually do not allow for the use of standard parametric methods, and hence, nonparametric methods should be considered instead. However, only limited simulation studies in settings with small sample sizes exist. Therefore, starting from an Epidermolysis Bullosa simplex trial with the above-mentioned design, a rank-based approach using the R package nparLD and different generalized pairwise comparisons (GPC) methods were compared impartially in a simulation study.