title: Validating billing/encounter codes as indicators of lung, colorectal, breast, and prostate cancer recurrence using 2 large contemporary cohorts.
abstract: BACKGROUND
  A substantial proportion of cancer-related mortality is attributable to recurrent, not de novo metastatic disease, yet we know relatively little about these patients. To fill this gap, investigators often use administrative codes for secondary malignant neoplasm or chemotherapy to identify recurrent cases in population-based datasets. However, these algorithms have not been validated in large, contemporary, routine care cohorts.
  
  
  OBJECTIVE
  To evaluate the validity of secondary malignant neoplasm and chemotherapy codes as indicators of recurrence after definitive local therapy for stage I-III lung, colorectal, breast, and prostate cancer.
  
  
  METHODS
  We assessed the sensitivity, specificity, and positive predictive value (PPV) of these codes 14 and 60 months after diagnosis using 2 administrative datasets linked with gold-standard recurrence status information: CanCORS/Medicare (diagnoses 2003-2005) and HMO/Cancer Research Network (diagnoses 2000-2005).
  
  
  RESULTS
  We identified 929 CanCORS/Medicare patients and 5298 HMO/CRN patients. Sensitivity, specificity, and PPV ranged widely depending on which codes were included and the type of cancer. For patients with lung, colorectal, and breast cancer, the combination of secondary malignant neoplasm and chemotherapy codes was the most sensitive (75%-85%); no code-set was highly sensitive and highly specific. For prostate cancer, no code-set offered even moderate sensitivity (≤ 19%).
  
  
  CONCLUSIONS
  Secondary malignant neoplasm and chemotherapy codes could not identify recurrent cancer without some risk of misclassification. Findings based on existing algorithms should be interpreted with caution. More work is needed to develop a valid algorithm that can be used to characterize outcomes and define patient cohorts for comparative effectiveness research studies.
authors.affiliation: *Department of Medical Oncology, Center for Outcomes & Policy Research, Dana-Farber Cancer Institute †Harvard Medical School, Boston, MA ‡Institute for Health Research, Kaiser Permanente Colorado, Denver, CO §Division of Biostatistics, The University of Toronto, Toronto, ON, Canada ∥The Dana-Farber Cancer Institute, Boston, MA ¶The National Cancer Institute, Bethesda, MD #Center for Health Research, Kaiser Permanente Northwest, Portland, OR.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Hassett
authors.forename: Debra P
authors.initials: DP
authors.lastname: Ritzwoller
authors.forename: Nathan
authors.initials: N
authors.lastname: Taback
authors.forename: Nikki
authors.initials: N
authors.lastname: Carroll
authors.forename: Angel M
authors.initials: AM
authors.lastname: Cronin
authors.forename: Gladys V
authors.initials: GV
authors.lastname: Ting
authors.forename: Deb
authors.initials: D
authors.lastname: Schrag
authors.forename: Joan L
authors.initials: JL
authors.lastname: Warren
authors.forename: Mark C
authors.initials: MC
authors.lastname: Hornbrook
authors.forename: Jane C
authors.initials: JC
authors.lastname: Weeks
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification / Q000401:mortality* / Q000473:pathology; D059019:Clinical Coding / Q000706:statistics & numerical data*; D015331:Cohort Studies; D015179:Colorectal Neoplasms / Q000145:classification / Q000401:mortality* / Q000473:pathology; D005260:Female; D005544:Forecasting; D006279:Health Maintenance Organizations / Q000706:statistics & numerical data; D006305:Health Status Indicators; D006801:Humans; D008175:Lung Neoplasms / Q000145:classification / Q000401:mortality* / Q000473:pathology; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local / Q000401:mortality*; D009367:Neoplasm Staging; D011471:Prostatic Neoplasms / Q000145:classification / Q000401:mortality* / Q000473:pathology; D015203:Reproducibility of Results; D014481:United States