title: Agreement of diagnosis and its date for hematologic malignancies and solid tumors between medicare claims and cancer registry data.
abstract: OBJECTIVE
  Claims data may be a suitable source studying associations between drugs and cancer. However, linkage between cancer registry and claims data including pharmacy-dispensing information is not always available. We examined the accuracy of claims-based definitions of incident cancers and their date of diagnosis.
  
  
  METHODS
  Four claims-based definitions were developed to identify incident leukemia, lymphoma, lung, colorectal, stomach, and breast cancer. We identified a cohort of subjects aged >or=65 (1997-2000) from Pennsylvania Medicare and drug benefit program data linked with the state cancer registry. We calculated sensitivity, specificity, and positive predictive values of the claims-based definitions using registry as the gold standard. We further assessed the agreement between diagnosis dates from two data sources.
  
  
  RESULTS
  All definitions had very high specificity (>or=98%), while sensitivity varied between 40% and 90%. Test characteristics did not vary systematically by age groups. The date of first diagnosis according to Medicare data tended to be later than the date recorded in the registry data except for breast cancer. The differences in dates of first diagnosis were within 14 days for 75% to 88% of the cases. Bias due to outcome misclassification of our claims-based definition of cancer was minimal in our example of a cohort study.
  
  
  CONCLUSIONS
  Claims data can identify incident hematologic malignancies and solid tumors with very high specificity with sufficient agreement in the date of first diagnosis. The impact of bias due to outcome misclassification and thus the usefulness of claims-based cancer definitions as cancer outcome markers in etiologic studies need to be assessed for each study setting.
authors: Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. ssetoguchi@partners.org
authors: Soko
authors: S
authors: Setoguchi
authors: Daniel H
authors: DH
authors: Solomon
authors: Robert J
authors: RJ
authors: Glynn
authors: E Francis
authors: EF
authors: Cook
authors: Raisa
authors: R
authors: Levin
authors: Sebastian
authors: S
authors: Schneeweiss
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D019337:Hematologic Neoplasms / Q000175:diagnosis* / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D007344:Insurance Claim Reporting; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data; D009369:Neoplasms / Q000175:diagnosis* / Q000453:epidemiology; D010414:Pennsylvania / Q000453:epidemiology; D015995:Prevalence; D012042:Registries / Q000706:statistics & numerical data; D012680:Sensitivity and Specificity