Exploring the potential of German claims data to identify incident lung cancer patients.

Abstract

Background: Real-world healthcare databases offer great potential for cancer research, but the valid identification of cancer patients is crucial for the suitability of a database in this regard. We aimed to assess the plausibility of an algorithm to identify incident lung cancer (LC) patients in German claims data.

Methods: Using the German Pharmacoepidemiological Research Database (GePaRD; claims data from ∼ 20% of the German population) we applied a previously developed algorithm which identifies incident LC patients and classifies them into advanced and non-advanced. We calculated age-standardized incidence rates (ASIRs) per 100,000 for the years 2013-2018. Further, we assessed the ASIRs stratified by the deprivation index of the district of residence and determined age-standardized five-year absolute and relative survival. We stratified all analyses by sex.

Results: Overall, we identified ∼ 9,500 - 10,500 incident LC patients per year. In 2018, (N = 10,625, mean age: 69.2 years in men) the proportion classified as advanced at diagnosis was 71.4%; the ASIRs of LC were 45 per 100,000 in men (9% lower than in 2013) and 27 per 100,000 persons in women (similar to 2013). ASIRs were lowest in persons living in areas with a low deprivation index. Age-standardized five-year absolute and relative survival rates, respectively, were 31% and 34% in women and 27% and 31% in men.

Conclusions: The algorithm we applied to identify incident LC patients in German claims data yielded plausible results, supporting its validity.

Trial registration: Not applicable.