BACKGROUND: Real-world data are required to fully assess the value of treatments in clinical practice. Given the importance of having all available data to make this assessment, while ensuring efficiencies in preventing duplication of data collection, the absence of a central repository of longitudinal data sources on cancer patients in Europe remains a challenge. OBJECTIVES: i)Identify and characterize existing traditional and non-traditional data sources on lung cancer and renal cell carcinoma (RCC) patients in Europe; ii)Determine the utility of each identified data source for real-world research. METHODS: A systematic literature search was conducted using MEDLINE and Embase(01/01/06-20/12/13). MeSH and Emtree terms included the following concepts: lung cancer (small-cell and non-small-cell), RCC, real-world data (registry, cohort, etc), and European countries. Clinical trials, case reports, case series, literature reviews were excluded. Identified abstracts were screened and reviewed based on relevance to key concepts. For each data source, utility was assessed using the following variables: country, setting, type (e.g. registry, EMR, etc.), clinical and baseline characteristics, tumor, biomarkers, test results, treatments, clinical and patient reported outcomes, resource utilization. RESULTS: The search yielded 2,478 abstracts for lung cancer and 698 for RCC. Following screening, 192(7.7%) and 102 (14.6%) were retained respectively. Data sources for lung cancer were equally distributed between general cancer and tumor specific registries. Most originated from the UK (33.3%) or France (13.8%). RCC data sources were primarily tumor specific and local with population size ranging from 56-1800. Data sources originated from Italy (22.5%), France, UK, and Germany (each 16.7%). Gap analyses with respect to the availability of specific data elements and utility for outcomes research will be presented. CONCLUSIONS: Data sources on cancer are highly fragmented in Europe, especially for RCC, emphasizing the need for database mapping. Completeness and consistency of the data elements needed to support technology assessments are variable.