Long-term prognosis of fatty-acid oxidation disorders in adults: Optimism despite the limited effective therapies available

International audienceIntroduction: Fatty-acid oxidation disorders (FAODs) are recessive genetic diseases. Materials and methods: We report here clinical and paraclinical data from a retrospective study of 44 adults with muscular FAODs from six French reference centers for neuromuscular or metabolic diseases. Results: The study cohort consisted of 44 adult patients: 14 with carnitine palmitoyl transferase 2 deficiency (32%), nine with multiple acyl-CoA deficiency (20%), 13 with very long-chain acyl-CoA dehydrogenase deficiency (30%), three with long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (7%), and five with short-chain acyl-CoA dehydrogenase deficiency (11%). Disease onset occurred during childhood in the majority of patients (59%), with a mean age at onset of 15 years (range = 0.5–35) and a mean of 12.6 years (range = 0–58) from disease onset to diagnosis. The principal symptoms were acute muscle manifestations (rhabdomyolysis, exercise intolerance, myalgia), sometimes associated with permanent muscle weakness. Episodes of rhabdomyolysis were frequent (84%), with a mean creatinine kinase level of 68,958 U/L (range = 660–300,000). General metabolic complications were observed in 58% of patients, respiratory manifestations in 18% of cases, and cardiological manifestations in 9% of cases. Fasting acylcarnitine profile was used to orient genetic explorations in 65% of cases. After a mean follow-up of 10 years, 33% of patients were asymptomatic and 56% continued to display symptoms after exercise. The frequency of rhabdomyolysis decreased after diagnosis in 64% of cases. Conclusion: A standardized register would complete this cohort description of muscular forms of FAODs with exhaustive data, making it possible to assess the efficacy of therapeutic protocols in real-life conditions and during the long-term follow-up of patients

Convergence of patient- and physician-reported outcomes in the French National Registry of Facioscapulohumeral Dystrophy

International audienceFacioscapulohumeral muscular dystrophy (FSHD) is among the most prevalent muscular dystrophies and currently has no treatment. Clinical and genetic heterogeneity are the main challenges to a full comprehension of the physiopathological mechanism. Improving our knowledge of FSHD is crucial to the development of future therapeutic trials and standards of care. National FSHD registries have been set up to this end. The French National Registry of FSHD combines a clinical evaluation form (CEF) and a self-report questionnaire (SRQ), filled out by a physician with expertise in neuromuscular dystrophies and by the patient, respectively. Aside from favoring recruitment, our strategy was devised to improve data quality. Indeed, the pairwise comparison of data from 281 patients for 39 items allowed for evaluating data accuracy. Kappa or intra-class coefficient (ICC) values were calculated to determine the correlation between answers provided in both the CEF and SRQ. Results Patients and physicians agreed on a majority of questions common to the SRQ and CEF (24 out of 39). Demographic, diagnosis- and care-related questions were generally answered consistently by the patient and the medical practitioner (kappa or ICC values of most items in these groups were greater than 0.8). Muscle function-related items, i.e. FSHD-specific signs, showed an overall medium to poor correlation between data provided in the two forms; the distribution of agreements in this section was markedly spread out and ranged from poor to good. In particular, there was very little agreement regarding the assessment of facial motricity and the presence of a winged scapula. However, patients and physicians agreed very well on the Vignos and Brooke scores. The report of symptoms not specific to FSHD showed general poor consistency. Conclusions Patient and physician answers are largely concordant when addressing quantitative and objective items. Consequently, we updated collection forms by relying more on patient-reported data where appropriate. We hope the revised forms will reduce data collection time while ensuring the same quality standard. With the advent of artificial intelligence and automated decision-making, high-quality and reliable data are critical to develop top-performing algorithms to improve diagnosis, care, and evaluate the efficiency of upcoming treatments