Evaluation of two family-based intervention programs for children affected by rare disease and their families – research network (CARE-FAM-NET): study protocol for a rater-blinded, randomized, controlled, multicenter trial in a 2x2 factorial design

Background: Families of children with rare diseases (i.e., not more than 5 out of 10,000 people are affected) are often highly burdened with fears, insecurities and concerns regarding the affected child and its siblings. Although families caring for children with rare diseases are known to be at risk for mental disorders, the evaluation of special programs under high methodological standards has not been conducted so far. Moreover, the implementation of interventions for this group into regular care has not yet been accomplished in Germany. The efficacy and cost-effectiveness of a family-based intervention will be assessed. Methods/design: The study is a 2x2 factorial randomized controlled multicenter trial conducted at 17 study centers throughout Germany. Participants are families with children and adolescents affected by a rare disease aged 0 to 21 years. Families in the face-to-face intervention CARE-FAM, online intervention WEP-CARE or the combination of both will be treated over a period of roughly 6 months. Topics discussed in the interventions include coping, family relations, and social support. Families in the control condition will receive treatment as usual. The primary efficacy outcome is parental mental health, measured by the Structured Clinical Interview for DSM-IV (SCID-I) by blinded external raters. Further outcomes will be assessed from the parents’ as well as the children’s perspective. Participants are investigated at baseline, 6, 12 and 18 months after randomization. In addition to the assessment of various psychosocial outcomes, a comprehensive health-economic evaluation will be performed. Discussion: This paper describes the implementation and evaluation of two family-based intervention programs for Children Affected by Rare Disease and their Family’s Network (CARE-FAM-NET) in German standard care. A methodologically challenging study design is used to reflect the complexity of the actual medical care situation. This trial could be an important contribution to the improvement of care for this highly burdened group. Trial registration: German Clinical Trials Register: DRKS00015859 (registered 18 December 2018) and ClinicalTrials.gov: NCT04339465 (registered 8 April 2020). Protocol Version: 15 August 2020 (Version 6.1). Trial status: Recruitment started on 1 January 2019 and will be completed on 31 March 2021. © 2020, The Author(s)

Sample size recalculation based on the prevalence in a randomized test-treatment study

BACKGROUND: Randomized test-treatment studies aim to evaluate the clinical utility of diagnostic tests by providing evidence on their impact on patient health. However, the sample size calculation is affected by several factors involved in the test-treatment pathway, including the prevalence of the disease. Sample size planning is exposed to strong uncertainties in terms of the necessary assumptions, which have to be compensated for accordingly by adjusting prospectively determined study parameters during the course of the study. METHOD: An adaptive design with a blinded sample size recalculation in a randomized test-treatment study based on the prevalence is proposed and evaluated by a simulation study. The results of the adaptive design are compared to those of the fixed design. RESULTS: The adaptive design achieves the desired theoretical power, under the assumption that all other nuisance parameters have been specified correctly, while wrong assumptions regarding the prevalence may lead to an over- or underpowered study in the fixed design. The empirical type I error rate is sufficiently controlled in the adaptive design as well as in the fixed design. CONCLUSION: The consideration of a blinded recalculation of the sample size already during the planning of the study may be advisable in order to increase the possibility of success as well as an enhanced process of the study. However, the application of the method is subject to a number of limitations associated with the study design in terms of feasibility, sample sizes needed to be achieved, and fulfillment of necessary prerequisites

Randomized test-treatment studies with an outlook on adaptive designs

Diagnostic accuracy studies aim to examine the diagnostic accuracy of a new experimental test, but do not address the actual merit of the resulting diagnostic information to a patient in clinical practice. In order to assess the impact of diagnostic information on subsequent treatment strategies regarding patient-relevant outcomes, randomized test-treatment studies were introduced. Various designs for randomized test-treatment studies, including an evaluation of biomarkers as part of randomized biomarker-guided treatment studies, are suggested in the literature, but the nomenclature is not consistent. The aim was to provide a clear description of the different study designs within a pre-specified framework, considering their underlying assumptions, advantages as well as limitations and derivation of effect sizes required for sample size calculations. Furthermore, an outlook on adaptive designs within randomized test-treatment studies is given. The need to integrate adaptive design procedures in randomized test-treatment studies is apparent. The derivation of effect sizes induces that sample size calculation will always be based on rather vague assumptions resulting in over- or underpowered study results. Therefore, it might be advantageous to conduct a sample size re-estimation based on a nuisance parameter during the ongoing trial. Due to their increased complexity, compared to common treatment trials, the implementation of randomized test-treatment studies poses practical challenges including a huge uncertainty regarding study parameters like the expected outcome in specific subgroups or disease prevalence which might affect the sample size calculation. Since research on adaptive designs within randomized test-treatment studies is limited so far, further research is recommended

Effectiveness of a complex regional advance care planning intervention to improve care consistency with care preferences: study protocol for a multi-center, cluster-randomized controlled trial focusing on nursing home residents (BEVOR trial)

According to recent legislation, facilitated advance care planning (ACP) for nursing home (NH) residents is covered by German sickness funds. However, the effects of ACP on patient-relevant outcomes have not been studied in Germany yet. This study investigates whether implementing a complex regional ACP intervention improves care consistency with care preferences in NH residents.7702