BACKGROUND: Cancer registries use algorithms to process cause of death (COD) data from death certificates, but uncertainties remain regarding the accuracy and utility of those data in calculating cancer-specific survival (CSS). Because it is impractical to reconfirm the COD through meticulous review of the primary medical records, the observed cancer deaths could be compared with the number of attributed deaths, as estimated by using a relative survival (RS) approach, to determine utility in CSS estimation. METHODS: Six major cancer types were evaluated using Surveillance, Epidemiology, and End Results (SEER) data (1988-1999 cohort). The COD utility was quantified by using the observed-to-expected ratio (O/E ratio) approach, which was calculated as the SEER-documented observed number of cancer-specific deaths divided by the number of expected deaths attributed to the malignancies as estimated using a RS approach. Favorable utility would have an O/E ratio close to 1. RESULTS: In total, 338,445 patients were identified; and their O/E ratios were 0.97, 0.98, 0.90, 1.07, 1.02, and 0.92 for breast, colorectal, lung, melanoma, prostate, and pancreas cancer, respectively. O/E ratios varied slightly with patients' age, race, and tumor stage, but not by sex. CSS for patients with lung cancer appeared to be overestimated considerably. Patients with multiple cancer diagnoses had poor O/E ratios compared with those who had only 1 cancer. CONCLUSIONS: The utility of COD in calculating CSS depended variously on the risk of cancer-related mortality and nontumor factors. However, the impact of this variation on CSS generally was small. The current results indicated that the COD assigned by cancer registries has acceptable validity, and CSS is considered an acceptable surrogate for RS in most circumstances.
BACKGROUND:Cancer registries use algorithms to process cause of death (COD) data from death certificates, but uncertainties remain regarding the accuracy and utility of those data in calculating cancer-specific survival (CSS). Because it is impractical to reconfirm the COD through meticulous review of the primary medical records, the observed cancer deaths could be compared with the number of attributed deaths, as estimated by using a relative survival (RS) approach, to determine utility in CSS estimation. METHODS: Six major cancer types were evaluated using Surveillance, Epidemiology, and End Results (SEER) data (1988-1999 cohort). The COD utility was quantified by using the observed-to-expected ratio (O/E ratio) approach, which was calculated as the SEER-documented observed number of cancer-specific deaths divided by the number of expected deaths attributed to the malignancies as estimated using a RS approach. Favorable utility would have an O/E ratio close to 1. RESULTS: In total, 338,445 patients were identified; and their O/E ratios were 0.97, 0.98, 0.90, 1.07, 1.02, and 0.92 for breast, colorectal, lung, melanoma, prostate, and pancreas cancer, respectively. O/E ratios varied slightly with patients' age, race, and tumor stage, but not by sex. CSS for patients with lung cancer appeared to be overestimated considerably. Patients with multiple cancer diagnoses had poor O/E ratios compared with those who had only 1 cancer. CONCLUSIONS: The utility of COD in calculating CSS depended variously on the risk of cancer-related mortality and nontumor factors. However, the impact of this variation on CSS generally was small. The current results indicated that the COD assigned by cancer registries has acceptable validity, and CSS is considered an acceptable surrogate for RS in most circumstances.
Authors: George J Chang; Chung-Yuan Hu; Cathy Eng; John M Skibber; Miguel A Rodriguez-Bigas Journal: J Clin Oncol Date: 2009-10-05 Impact factor: 44.544
Authors: Nader N Massarweh; Alex B Haynes; Yi-Ju Chiang; George J Chang; Y Nancy You; Barry W Feig; Janice N Cormier Journal: Ann Surg Date: 2015-08 Impact factor: 12.969
Authors: Matthew Castelo; Justin Lu; Lawrence Paszat; Zachary Veitch; Kuan Liu; Adena S Scheer Journal: Breast Cancer Res Treat Date: 2022-06-22 Impact factor: 4.624
Authors: Helen E Dinkelspiel; Miriam Champer; June Hou; Ana Tergas; William M Burke; Yongmei Huang; Alfred I Neugut; Cande V Ananth; Dawn L Hershman; Jason D Wright Journal: Gynecol Oncol Date: 2015-06-05 Impact factor: 5.482
Authors: Peter D Baade; Patrick Royston; Philipa H Youl; Martin A Weinstock; Alan Geller; Joanne F Aitken Journal: BMC Cancer Date: 2015-01-31 Impact factor: 4.430
Authors: A Woehrer; M Hackl; T Waldhör; S Weis; J Pichler; A Olschowski; J Buchroithner; H Maier; G Stockhammer; C Thomé; J Haybaeck; F Payer; G von Campe; A Kiefer; F Würtz; G H Vince; R Sedivy; S Oberndorfer; F Marhold; K Bordihn; W Stiglbauer; U Gruber-Mösenbacher; R Bauer; J Feichtinger; A Reiner-Concin; W Grisold; C Marosi; M Preusser; K Dieckmann; I Slavc; B Gatterbauer; G Widhalm; C Haberler; J A Hainfellner Journal: Br J Cancer Date: 2013-11-19 Impact factor: 7.640
Authors: Salma Shariff-Marco; Scarlett L Gomez; Meera Sangaramoorthy; Juan Yang; Jocelyn Koo; Andrew Hertz; Esther M John; Iona Cheng; Theresa H M Keegan Journal: Health Place Date: 2015-11-21 Impact factor: 4.931