A Multimodal Lifestyle Psychosocial Survivorship Program in Young Cancer Survivors: The CARE for CAYA Program-A Randomized Clinical Trial Embedded in a Longitudinal Cohort Study.

Importance: There is a lack of trials examining the effect of counseling interventions for child, adolescent, and younger adult (CAYA) cancer survivors. Objective: To assess lifestyle habits and the psychosocial situation of CAYAs to determine the efficacy of needs-based interventions in the CARE for CAYA program (CFC-P). Design, Setting, and Participants: The CFC-P was conducted as a multicenter program in 14 German outpatient clinics, mainly university cancer centers. Recruitment began January 1, 2018; a randomized clinical trial was conducted until July 15, 2019; and intervention was continued as a longitudinal cohort study until March 31, 2021. Data preparation was conducted from April 1, 2021, and analysis was conducted from August 14, 2021, to May 31, 2022. Herein, predefined confirmatory analyses pertain to the RCT and descriptive results relate to the overall longitudinal study. Data analysis was based on the full analysis set, which is as close as possible to the intention-to-treat principle. Intervention: A comprehensive assessment determined needs in physical activity, nutrition and psychooncology. Those with high needs participated in 1 to 3 modules. In the RCT, the IG received 5 counseling sessions plus newsletters, while the control group CG received 1 counseling session. Main Outcomes and Measures: The primary outcome was the change in the rate of CAYAs with high needs at 52 weeks. Secondary outcomes were feasibility, modular-specific end points, satisfaction, quality of life, and fatigue. Results: Of 1502 approached CAYAs aged 15 to 39 years, 692 declined participation. Another 22 CAYAs were excluded, resulting in 788 participants. In the randomized clinical trial, 359 CAYAs were randomized (intervention group [IG], n = 183; control group [CG], n = 176), and 274 were followed up. In the RCT, the median age was 25.0 (IQR, 19.9-32.2) years; 226 were female (63.0%) and 133 male (37.0%). After 52 weeks, 120 CAYAs (87.0%) in the IG and 115 (86.5%) in the CG still had a high need in at least 1 module (odds ratio, 1.04; 95% CI, 0.51-2.11; P = .91). Both groups reported reduced needs, improved quality of life, reduced fatigue, and high satisfaction with the CFC-P. Conclusions and Relevance: In this randomized clinical trial, the implementation of a lifestyle program in this cohort was deemed necessary, despite not meeting the primary outcome. The interventions did not alter the rate of high needs. The results may provide guidance for the development of multimodal interventions in the follow-up care of CAYAs. Trial Registration: German Clinical Trial Register: DRKS00012504.

Implementation of a clinical long-term follow-up database for adult childhood cancer survivors in Germany: a feasibility study at two specialised late effects clinics.

PURPOSE: Childhood cancer survivors (CCS) are at risk for increased morbidity and reduced quality of life associated with treatment-related late effects. In Germany, however, only a few of the more than 40,000 CCS registered in the German Childhood Cancer Registry (GCCR) currently benefit from adequate clinical long-term follow-up (LTFU) structures. To establish a comprehensive knowledge base on CCS' long-term health in Germany, a database was developed in cooperation with the GCCR. Following a first evaluation phase at two German university centres, this database will be implemented more widely within Germany allowing longitudinal documentation of clinical LTFU data. METHODS: The feasibility study cohort comprised 208 CCS aged 18 or older whose medical, mental and psychosocial health data were collected during routine LTFU or first clinic visits in adult care. CCS were enrolled from 04/2021 to 12/2022, and data entry was completed by 03/2023. Descriptive data analysis was conducted. All CCS were stratified into three risk groups (RG) based on their individual risk for developing late effects resulting from their respective diagnoses and treatments. RESULTS: Chronic health conditions of various organ systems associated with late and long-term effects of cancer therapy affected CCS in all RG supporting the clinical relevance of risk-adapted LTFU. Enrolment into the database was feasible and broadly accepted amongst CCS. CONCLUSION: Implementation of a clinical follow-up care infrastructure and database in Germany will pave the way to collect clinically evaluated and regularly updated health data of potentially over 40,000 German CCS and facilitate future national and international cooperation.

openEHR Mapper - A Tool to Fuse Clinical and Genomic Data Using the openEHR Standard.

Precision medicine is an emerging and important field for health care. Molecular tumor boards use a combination of clinical and molecular data, such as somatic tumor mutations to decide on personalized therapies for patients who have run out of standard treatment options. Personalized treatment decisions require clinical data from the hospital information system and mutation data to be accessible in a structured way. Here we introduce an open data platform to meet these requirements. We use the openEHR standard to create an expert-curated data model that is stored in a vendor-neutral format. Clinical and molecular patient data is integrated into cBioPortal, a warehousing solution for cancer genomic studies that is extended for use in clinical routine for molecular tumor boards. For data integration, we developed openEHR Mapper, a tool that allows to (i) process input data, (ii) communicate with the openEHR repository, and (iii) export the data to cBioPortal. We benchmarked the mapper performance using XML and JSON as serialization format and added caching capabilities as well as multi-threading to the openEHR Mapper.

Using Graph Tools on Metadata Repositories.

To exchange data across several sites or to interpret it at a later point in time, it is necessary to create a general understanding of the data. As a standard practice, this understanding is achieved through metadata. These metadata are usually stored in relational databases, so-called metadata repositories (MDR). Typical functions of such an MDR include pure storage, administration and other specific metadata functionalities such as finding relations among data elements. This results in a multitude of connections between the data elements, which can be described as highly interconnected graphs. To use alternative databases such as graph databases for modelling and visualisation it has already been proven to be beneficial in previous studies. The objective of this work is to evaluate how on-board techniques rely on matching and mapping using a graph database. Different datasets relating to cancer were entered, and algorithms for metadata management were applied.