Long-term health consequences of cancer and its therapy affect most CCS, resulting in a reduced health-related quality of life and life expectancy in this growing cohort (Byrne et al. 2022; van Erp et al. 2021). Comprehensive risk-based care facilitates timely diagnosis and treatment of late effects and is recommended in numerous guidelines (Frobisher et al. 2017; Kremer et al. 2013). These recommendations are based on regularly updated, extensive analyses of CCS’ health status during LTFU. For some late effects specific surveillance strategies are lacking as reliable data on occurrence and complications of some chronic health conditions are not available yet (Bowers et al. 2021). Recommendations in favor of or against surveillance modalities, however, require careful balancing of potential benefits and harms (Clement et al. 2018; Heinzel et al. 2022). Prospectively documented and evaluated late effects in nationwide CCS cohorts can fill these knowledge gaps (Yeh et al. 2022) and serve as a basis for future joint projects. In several countries national cohorts of CCS, who are regularly followed up by questionnaire surveys or clinically in specialised LTFU clinics, have been established (Winther et al. 2015). To provide comprehensive information on CCS’ health status in Germany, which goes beyond the current regular follow-up on subsequent neoplasms and relapses conducted by the GCCR, a database was created to support standardised prospective and longitudinal clinical data collection from routine LTFU assessments. Generally, acceptance of the database was successful in both participating clinics with almost all eligible CCS participating in this feasibility study.
Nationwide implementation of this database over the following years will provide clinically evaluated and regularly updated health data of potentially over 40,000 German CCS. These prospectively collected data can contribute to larger international analyses of CCS data, thus creating the basis for better tailored and individualised, risk-adapted LTFU recommendations.
According to the risk stratification approach (Frobisher et al. 2017) which was applied to our cohort, a considerable larger proportion of CCS allocated to RG3 (high risk for late effects) suffered from chronic health conditions than CCS of RG1 (low risk) and RG2 (intermediate risk). This difference is most pronounced for occurrence of endocrinological and cardiovascular disorders, as well as ear-nose-throat disorders, degree of disability and occurrence of subsequent neoplasms thus supporting the clinical relevance of the proposed risk stratification. Yet, it also needs to be considered that CCS in RG3 were generally older, so time since treatment was longest in this group. This limitation in this first data analysis will potentially be diminished once the cohort documented in the database exceeds a higher number of CCS. Number of health conditions with time increased in our cohort as has also been previously described (Suh et al. 2020), emphasising the necessity of LTFU, potentially life-long. However, our findings also demonstrate an already high number of chronic health conditions in a cohort of young adult CCS, illustrated e. g. by a high occurrence of endocrinological disorders, which is in line with previous work and underlines the need for regular, life-long surveillance from the beginning of survivorship on (Bhakta et al. 2017; Brignardello et al. 2013).
LTFU aims at holistic health assessment. The database correspondingly includes data on physical and mental health conditions, assessment of general health information such as vaccination record, medical history and substance use as well as psychosocial and socioeconomic parameters. Analyses of this data provide an overview of the CCS’ characteristics as well as overall and in-depth assessment of their health status, e.g. alongside the documentation of organ systems affected by health conditions, also their type and extent are documented. Specific information on health care provision derived from data analyses can be directly transferred back into LTFU care and support its improvement by adapting to CCS’ needs.
To optimise data quality for future projects, careful consideration of possible imprecisions and errors in data assessment and documentation was conducted. In this context, some limitations were detected, e.g. some variables generating high numbers of missing data due to a missing “no” option. Interpretation of such missings as negation might distort results. For this first analysis within the feasibility study, we regard our approach as justifiable, seeing as findings in the affected variables would have likely been entered into the database had they been clear and available. For example, we argue that a relapse, had it occurred, would have been documented. For future use and implementation a “no” option was added to these variables; for “infertility” the variable “no clinical and laboratory evidence of infertility” will be added to the assessment. In addition, occurrence of hypogonadism could not be evaluated in women taking contraceptives if no further medical history was available. That is why our numbers might differ from expected prevalences from former studies (Mostoufi-Moab et al. 2016). Careful documentation of medical history and medications is essential to generate plausible data. A checklist will be forwarded to all participating LTFU centres to ensure complete data acquisition and to minimise missing data (Online Resource 1). Furthermore, to prevent systematic errors in data entry, a database manual containing background information on respective variables was provided and will be adapted for all future study centres. All identified limitations will be addressed in a database update to optimise future analyses.