Using Health Insurance Claims Data To Assess Long-term Disease Progression In A Prostate Cancer Cohort
Background: Long-term population-based cohort studies of men diagnosed with prostate cancer are limited. However, adverse outcomes can occur many years after treatment. Herein, we aim to assess the utility of using claims data to identify prostate cancer progression 10−15 years after diagnosis. Methods: The study population was derived from the North Carolina−Louisiana Prostate Cancer Project (PCaP). PCaP-North Carolina (NC) included 1031 men diagnosed with prostate cancer from 2004 to 2009. An initial follow-up with a survey and manual medical record abstraction occurred from 2008 to 2011 (Follow-up 1). Herein, we extended this follow-up with linkage to healthcare claims data from North Carolina (2011−2017) and a second, supplementary 10-year follow-up survey (2018−2020) (Follow-up 2). Vital statistics data also were utilized. Long-term oncological progression was determined using these data sources in combination with expert clinical input. Results: Among the 1031 baseline PCaP-NC participants, 652 were linked to medical claims. Forty-two percent of the men had insurance coverage for the entire 72 months of follow-up. In addition, 275 baseline participants completed the supplementary 10-year follow-up survey. Using all sources of follow-up data, we identified a progression event in 259 of 1031 (25%) men with more than 10 years of follow-up data after diagnosis. Conclusions: Understanding long-term clinical outcomes is essential for improving the lives of prostate cancer survivors. However, access and utility of long-term clinical outcomes with claims alone remain a challenge due to individualized agreements required with each insurer for data access, lack of detailed clinical information, and gaps in insurance coverage. We were able to utilize claims data to determine long-term progression due to several unique advantages that included the availability of detailed baseline clinical characteristics and treatments, detailed manually abstracted clinical data at 5 years of follow-up, vital statistics data, and a supplementary 10-year follow-up survey.
Khan, Saira; Vohra, Sanah; Farnan, Laura; Elmore, Shekinah N.C.; Toumbou, Khadijah; Madhav, K. C.; Fontham, Elizabeth T.H.; Peters, Edward S.; Mohler, James L.; and Bensen, Jeannette T., "Using Health Insurance Claims Data To Assess Long-term Disease Progression In A Prostate Cancer Cohort" (2022). School of Medicine Faculty Publications. 543.