Comorbidity Assessment in the National Cancer Database for Patients With Surgically Resected Breast, Colorectal, or Lung Cancer (AFT-01, -02, -03)

Purpose Accurate comorbidity measurement is critical for cancer research. We evaluated comorbidity assessment in the National Cancer Database (NCDB), which uses a code-based Charlson-Deyo Comorbidity Index (CCI), and compared its prognostic performance with a chart-based CCI and individual comorbidities in a national sample of patients with breast, colorectal, or lung cancer. Patients and Methods Through an NCDB Special Study, cancer registrars re-abstracted perioperative comorbidities for 11,243 patients with stage II to III breast cancer, 10,880 with stage I to III colorectal cancer, and 9,640 with stage I to III lung cancer treated with definitive surgical resection in 2006-2007. For each cancer type, we compared the prognostic performance of the NCDB code-based CCI (categorical: 0 or missing data, 1, 2+), Special Study chart-based CCI (continuous), and 18 individual comorbidities in three separate Cox proportional hazards models for postoperative 5-year overall survival. Results Comorbidity was highest among patients with lung cancer (13.2% NCDB CCI 2+) and lowest among patients with breast cancer (2.8% NCDB CCI 2+). Agreement between the NCDB and Special Study CCI was highest for breast cancer (rank correlation, 0.50) and lowest for lung cancer (rank correlation, 0.40). The NCDB CCI underestimated comorbidity for 19.1%, 29.3%, and 36.2% of patients with breast, colorectal, and lung cancer, respectively. Within each cancer type, the prognostic performance of the NCDB CCI, Special Study CCI, and individual comorbidities to predict postoperative 5-year overall survival was similar. Conclusion The NCDB underestimated comorbidity in patients with surgically resected breast, colorectal, or lung cancer, partly because the NCDB codes missing data as CCI0. However, despite underestimation of comorbidity, the NCDB CCI was similar to the more complete measures of comorbidity in the Special Study in predicting overall survival.