Background Metachromatic Leukodystrophy (MLD) is a rare autosomal-recessive lysosomal storage disorder caused by mutations in the ARSA gene. While interventional trials often use untreated siblings as controls, the genotype-phenotype correlation is only partly understood, and the variability of the clinical course between siblings is unclear with some evidence for a discrepant clinical course in juvenile patients. The aim of this study was to systematically investigate the phenotypic variation in MLD siblings in comparison to the variability in a larger MLD cohort and to case reports published in literature. Results Detailed clinical information was available from 12 sibling-pairs (3 late-infantile, 9 juvenile) and 61 single patients (29 late-infantile, 32 juvenile). Variability of age at onset was similar between the siblings and randomly chosen pairs of the remaining cohort (no statistically different Euclidean distances). However, in children with juvenile MLD both the type of first symptoms and the dynamic of the disease were less variable between siblings compared to the general cohort. In late-infantile patients, type of first symptoms and dynamic of disease were similarly homogeneous between siblings and the whole MLD cohort. Thirteen published case reports of families with affected siblings with MLD are presented with similar findings. Conclusions In a systematic analysis of phenotypic variation in families with MLD, siblings with the late-infantile form showed a similar variability as unrelated pairs of children with late-infantile MLD, whereas siblings with juvenile MLD showed a more homogeneous phenotype regarding type of first symptoms and disease evolution in comparison to unrelated children with juvenile MLD, but not regarding their age at onset. These results are highly relevant with respect to the evaluation of treatment effects and for counseling of families with affected siblings.

Background Choosing an antipsychotic medication is an important medical decision in the treatment of schizophrenia. This decision requires risk-benefit assessments of antipsychotics, and thus, shared-decision making between physician and patients is strongly encouraged. Although the efficacy and side-effect profiles of antipsychotics are well-established, there is no clear framework for the communication of the evidence between physicians and patients. For this reason, we developed an evidence-based shared-decision making assistant (SDM-assistant) that presents high-quality evidence from network meta-analysis on the efficacy and side-effect profile of antipsychotics and can be used as a basis for shared-decision making between physicians and patients when selecting antipsychotic medications. Methods The planned matched-pair cluster-randomised trial will be conducted in acute psychiatric wards (n = 14 wards planned) and will include adult inpatients with schizophrenia or schizophrenia-like disorders (N = 252 participants planned). On the intervention wards, patients and their treating physicians will use the SDM-assistant, whenever a decision on choosing an antipsychotic is warranted. On the control wards, antipsychotics will be chosen according to treatment-as-usual. The primary outcome will be patients’ perceived involvement in the decision-making during the inpatient stay as measured with the SDM-Q-9. We will also assess therapeutic alliance, symptom severity, side-effects, treatment satisfaction, adherence, quality of life, functioning and rehospitalizations as secondary outcomes. Outcomes could be analysed at discharge and at follow-up after three months from discharge. The analysis will be conducted per-protocol using mixed-effects linear regression models for continuous outcomes and logistic regression models using generalised estimating equations for dichotomous outcomes. Barriers and facilitators in the implementation of the intervention will also be examined using a qualitative content analysis. Discussion This is the first trial to examine a decision assistant specifically designed to facilitate shared-decision making for choosing antipsychotic medications, i.e., SDM-assistant, in acutely ill inpatients with schizophrenia. If the intervention can be successfully implemented, SDM-assistant could advance evidence-based medicine in schizophrenia by putting medical evidence on antipsychotics into the context of patient preferences and values. This could subsequently lead to a higher involvement of the patients in decision-making and better therapy decisions. Trial registration German Clinical Trials Register (ID: DRKS00027316, registration date 26.01.2022).

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