Using Medicare claims to identify second primary cancers and recurrences in order to supplement a cancer registry.
OBJECTIVE
The purpose of this study was to use Medicare claims to develop models to assist cancer registries in identifying cancer patients with second primaries or recurrences (an "event").


METHODS
Medicare inpatient and Part B data were merged with a cancer registry for patients first diagnosed in 1993-1994. Logistic regression was used to model the occurrence of an event at least 1 year after initial diagnosis, and to identify factors that could discriminate between recurrences and second primaries.


RESULTS
Predictors of an event included an inpatient cancer diagnosis, cancer diagnosis different from the initial diagnosis from any source, and radiation or surgery claims in Part B. The ROC curve area was 0.90 with all Medicare data; 0.84 when restricted to inpatient data. A cancer diagnosis different from the initial diagnosis or having surgery predicted a second primary; regional or distant stage disease, diagnosis of secondary malignancy, or an inpatient diagnosis of primary cancer in a position other than principal predicted recurrence.


CONCLUSIONS
Although Medicare claims have not been evaluated as a stand-alone system to identify second primaries and recurrences, Medicare claims may be useful tools for Cancer Registries in case ascertainment and follow-up.
McClish
Donna
D
Department of Biostatistics, Virginia Commonwealth University, 1101 East Marshall Street, Richmond, VA 23298-0032, USA. mcclish@hsc.vcu.edu
Penberthy
Lynne
L
Pugh
Amy
A
D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D007345:Insurance Claim Review; D016015:Logistic Models; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data*; D009364:Neoplasm Recurrence, Local / Q000175:diagnosis / Q000453:epidemiology*; D016609:Neoplasms, Second Primary / Q000175:diagnosis / Q000453:epidemiology*; D012372:ROC Curve; D012042:Registries; D013997:Time Factors