PURPOSE: Survival is considered an important indicator of the quality of cancer care, but the validity of different methodologies to measure comparative survival rates is less well understood. We explored whether the National Cancer Data Base (NCDB) could serve as a source of unadjusted and risk-adjusted cancer survival data and whether these data could be used as quality indicators for individual hospitals or in the aggregate by hospital type. METHODS: The NCDB, an aggregate of > 1,500 hospital cancer registries, was queried to analyze unadjusted and risk-adjusted hazards of death for patients with stage III breast cancer (n = 116,787) and stage IIIB or IV non-small-cell lung cancer (n = 252,392). Data were analyzed at the individual hospital level and by hospital type. RESULTS: At the hospital level, after risk adjustment, few hospitals had comparative risk-adjusted survival rates that were statistically better or worse. By hospital type, National Cancer Institute-designated comprehensive cancer centers had risk-adjusted survival ratios that were statistically significantly better than those of academic cancer centers and community hospitals. CONCLUSION: Using the NCDB as the data source, survival rates for patients with stage III breast cancer and stage IIIB or IV non-small-cell lung cancer were statistically better at National Cancer Institute-designated comprehensive cancer centers when compared with other hospital types. Compared with academic hospitals, risk-adjusted survival was lower in community hospitals. At the individual hospital level, after risk adjustment, few hospitals were shown to have statistically better or worse survival, suggesting that, using NCDB data, survival may not be a good metric to determine relative quality of cancer care at this level.
PURPOSE: Survival is considered an important indicator of the quality of cancer care, but the validity of different methodologies to measure comparative survival rates is less well understood. We explored whether the National Cancer Data Base (NCDB) could serve as a source of unadjusted and risk-adjusted cancer survival data and whether these data could be used as quality indicators for individual hospitals or in the aggregate by hospital type. METHODS: The NCDB, an aggregate of > 1,500 hospital cancer registries, was queried to analyze unadjusted and risk-adjusted hazards of death for patients with stage III breast cancer (n = 116,787) and stage IIIB or IV non-small-cell lung cancer (n = 252,392). Data were analyzed at the individual hospital level and by hospital type. RESULTS: At the hospital level, after risk adjustment, few hospitals had comparative risk-adjusted survival rates that were statistically better or worse. By hospital type, National Cancer Institute-designated comprehensive cancer centers had risk-adjusted survival ratios that were statistically significantly better than those of academic cancer centers and community hospitals. CONCLUSION: Using the NCDB as the data source, survival rates for patients with stage III breast cancer and stage IIIB or IV non-small-cell lung cancer were statistically better at National Cancer Institute-designated comprehensive cancer centers when compared with other hospital types. Compared with academic hospitals, risk-adjusted survival was lower in community hospitals. At the individual hospital level, after risk adjustment, few hospitals were shown to have statistically better or worse survival, suggesting that, using NCDB data, survival may not be a good metric to determine relative quality of cancer care at this level.
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Authors: Amy C Moreno; Ning Zhang; Sharon H Giordano; Zhongxing Liao; Daniel Gomez; Joe Y Chang; Steven H Lin Journal: Int J Part Ther Date: 2018-11-30
Authors: Nancy L Keating; Jessica L F Cleveland; Alexi A Wright; Gabriel A Brooks; Laurie Meneades; Lauren Riedel; Jose R Zubizarreta; Mary Beth Landrum Journal: JAMA Netw Open Date: 2021-03-01
Authors: Thomas C Tucker; Mary E Charlton; Mary C Schroeder; Jason Jacob; Cheri L Tolle; B Mark Evers; Timothy W Mullett Journal: Ann Surg Oncol Date: 2020-07-25 Impact factor: 5.344
Authors: Zachary A K Frosch; Nicholas Illenberger; Nandita Mitra; Daniel J Boffa; Matthew A Facktor; Heidi Nelson; Bryan E Palis; Justin E Bekelman; Lawrence N Shulman; Samuel U Takvorian Journal: JAMA Netw Open Date: 2021-07-01