Profile of the multicenter cohort of the German Cancer Consortium's Clinical Communication Platform.

Treatment concepts in oncology are becoming increasingly personalized and diverse. Successively, changes in standards of care mandate continuous monitoring of patient pathways and clinical outcomes based on large, representative real-world data. The German Cancer Consortium's (DKTK) Clinical Communication Platform (CCP) provides such opportunity. Connecting fourteen university hospital-based cancer centers, the CCP relies on a federated IT-infrastructure sourcing data from facility-based cancer registry units and biobanks. Federated analyses resulted in a cohort of 600,915 patients, out of which 232,991 were incident since 2013 and for which a comprehensive documentation is available. Next to demographic data (i.e., age at diagnosis: 2.0% 0-20 years, 8.3% 21-40 years, 30.9% 41-60 years, 50.1% 61-80 years, 8.8% 81+ years; and gender: 45.2% female, 54.7% male, 0.1% other) and diagnoses (five most frequent tumor origins: 22,523 prostate, 18,409 breast, 15,575 lung, 13,964 skin/malignant melanoma, 9005 brain), the cohort dataset contains information about therapeutic interventions and response assessments and is connected to 287,883 liquid and tissue biosamples. Focusing on diagnoses and therapy-sequences, showcase analyses of diagnosis-specific sub-cohorts (pancreas, larynx, kidney, thyroid gland) demonstrate the analytical opportunities offered by the cohort's data. Due to its data granularity and size, the cohort is a potential catalyst for translational cancer research. It provides rapid access to comprehensive patient groups and may improve the understanding of the clinical course of various (even rare) malignancies. Therefore, the cohort may serve as a decisions-making tool for clinical trial design and contributes to the evaluation of scientific findings under real-world conditions.

Liquid Biopsy in Colorectal Cancer: Quo Vadis? Implementation of Liquid Biopsies in Routine Clinical Patient Care in Two German Comprehensive Cancer Centers.

Objectives: The use of liquid biopsies (LB) in patients with solid malignancies enables comprehensive genomic profiling (CGP) of circulating tumor DNA (ctDNA) and has the potential to guide therapy stratification and support disease monitoring. To examine clinical uptake of LB in a real-world setting, LB implementation was analyzed at two German cancer centers (LMU Munich and Charité - Universitätsmedizin Berlin) between 2017 and 2021, with focus on colorectal cancer (CRC) patients. Methods: In this retrospective analysis, all patients who received a LB between January 2017 and December 2021 as part of routine clinical management were included. To provide adequate context, we collected disease characteristics and technical specifications of the LB methods applied. Additionally, we examined the concordance of RAS status in tumor tissue and LB. Finally, we discuss the potential of LB as a diagnostic tool to drive personalized treatment in CRC patients and how to implement LB in clinical routine. Results: In total, our cohort included 86 CRC patients and 161 LB conducted in these patients between 2017 and 2021. In 59 patients, comparison between tissue-based and liquid-based molecular diagnostics, revealed a divergence in 23 (39%) of the evaluable samples. Conclusion: Our real-world data analysis indicates that the possibilities of LB are not yet exploited in everyday clinical practice. Currently, the variety of methods and lack of standardization, as well as restricted reimbursement for liquid based CGP hinder the use of LB in clinical routine. To overcome these issues, prospective clinical trials are needed to provide evidence driving the implementation of LB into the management of CRC patients and to support their implementation into clinical guidelines.

Can routine register data be used to identify vulnerable lung cancer patients of suboptimal care in a German comprehensive cancer centre?

OBJECTIVES: Several patient factors have been described to influence access to optimal cancer care like socioeconomic factors or place of residence. In this study, we investigate whether data routinely collected in a clinical cancer registry can be used to identify populations of lung cancer patients with increased risk of not receiving optimal cancer care. METHODS: We analysed data of 837 lung cancer patients extracted from the clinical cancer registry of a German university hospital. We compared patient populations by two indicators of optimal care, namely implementation of tumour board meeting recommendations as well as the timeliness of care. RESULTS: There was a high rate of implementation of tumour board meeting recommendations of 94.4%. Reasons for non-implementation were mainly a patient's own wish or a worsening of the health situation. Of all patient parameters, only tumour stage was associated with the two optimal care indicators. CONCLUSION: Using routine data from a clinical cancer registry, we were not able to identify patient populations at risk of not getting optimal care and the implementation of guideline-conform care appeared to be very high in this setting. However, limitations were the ambiguity of optimal care indicators and availability of parameters predictive for patients' vulnerability.

Automated Reports for Monitoring and Improving Data Quality in a Translational Research Network.

Standardised, automated quality reports were generated at three pilot locations of the decentralized translational research network DKTK with separated local data warehouses (LDW), for assessing syntactic conformity against common data element definitions deposited in a central metadata repository (MDR). Deviations in the LDW were categorised, and locally corrected. Comparisons of reports from two time points confirm a major improvement in data quality in terms of syntactic conformity, an essential prerequisite for network-wide data integration.

Proof-of-Concept Integration of Heterogeneous Biobank IT Infrastructures into a Hybrid Biobanking Network.

Cross-institutional biobank networks hold the promise of supporting medicine by enabling the exchange of associated samples for research purposes. Various initiatives, such as BBMRI-ERIC and German Biobank Node (GBN), aim to interconnect biobanks for enabling the compilation of joint biomaterial collections. However, building software platforms to facilitate such collaboration is challenging due to the heterogeneity of existing biobank IT infrastructures and the necessary efforts for installing and maintaining additional software components. As a remedy, this paper presents the concept of a hybrid network for interconnecting already existing software components commonly found in biobanks and a proof-of-concept implementation of two prototypes involving four biobanks of the German Biobank Node. Here we demonstrate the successful bridging of two IT systems found in many German biobanks - Samply and i2b2.