Costs of conservative management of early-stage prostate cancer compared to radical prostatectomy–a claims data analysis. Issue 1 (December 2016) - Brandes, Alina; Koerber, Florian; Schwarzkopf, Larissa; Hunger, Matthias; Rogowski, Wolf; Waidelich, Raphaela
Abstract Background Due to widespread PSA testing incidence rates of localized prostate cancer increase but curative treatment is often not required. Overtreatment imposes a substantial economic burden on health care systems. We compared the direct medical costs of conservative management and radical therapy for the management of early-stage prostate cancer in routine care. Methods An observational study design is chosen based on claims data of a German statutory health insurance fund for the years 2008–2011. Three hundred fifty-three age-matched men diagnosed with prostate cancer and treated with conservative management and radical prostatectomy, are included. Individuals with diagnoses of metastases or treatment of advanced prostate cancer are excluded. In an excess cost approach direct medical costs are considered from an insured community perspective for in- and outpatient care, pharmaceuticals, physiotherapy, and assistive technologies. Generalized linear models adjust for comorbidity by Charlson comorbidity score and recycled predictions method calculates per capita costs per treatment strategy. Results After follow-up of 2.5 years per capita costs of conservative management are €6611 lower than costs of prostatectomy ([−9734;−3547], p < 0.0001). Complications increase costs of assistive technologies by 30% (p = 0.0182), but do not influence any other costs. Results are robust to cost outliers and incidence of prostate cancer diagnosis. The short time horizon does not allow assessing long-term consequences of conservative management. Conclusions At a time horizon of 2.5 years, conservative management is preferable to radical prostatectomy in terms of costs. Claims data analysis is limited in the selection of comparable treatment groups, as clinical information is scarce and bias due to non-randomization can only be partly mitigated by matching and confounder adjustment.