Predictive validity of five comorbidity indices in prostate carcinoma patients treated with curative intent

• Published in: Cancer Vol. 106; no. 8; pp. 1804 - 1814
• Main Authors: Boulos, David L., Groome, Patti A., Brundage, Michael D., Siemens, D. Robert, Mackillop, William J., Heaton, Jeremy P.W., Schulze, Karleen M., Rohland, Susan L.
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 15-04-2006; Wiley-Liss
• Subjects: Aged; Aged, 80 and over; Biological and medical sciences; Case-Control Studies; Cause of Death; Cohort Studies; Comorbidity; health status indicators; Humans; Male; Medical sciences; Middle Aged; Nephrology. Urinary tract diseases; predictive value of tests; Proportional Hazards Models; prostatic neoplasms; Prostatic Neoplasms - mortality; Prostatic Neoplasms - therapy; reproducibility of results; Risk; Survival Analysis; survival rate; Treatment Outcome; Tumors; Tumors of the urinary system; Urinary tract. Prostate gland; Human; Prostate carcinoma; Prostate tumor; Urinary system disease; Prostate disease; predictive value of tests; health status indicators; Malignant tumor; Survival; Indicator; reproducibility of results; Validity; Concomitant disease; Cancerology; Health status; Treatment; comorbidity; Reproducibility; prostatic neoplasms; Predictive value; survival rate; Male genital diseases; Prostate cancer
• ISSN: 0008-543X; 1097-0142
• DOI: 10.1002/cncr.21813

BACKGROUND
Comorbidity is important to consider in clinical research on curative prostate carcinoma because of the role of competing risks. Five chart‐based comorbidity indices were assessed for their ability to predict survival.
METHODS
This was a case‐cohort study of prostate carcinoma patient cohort treated with curative intent in Toronto and Southeast Cancer Care Ontario regions between 1990 and 1996; the subcohort was drawn from these men, whereas cases were cohort members who died from causes other than prostate carcinoma. Comorbidity data were obtained from medical charts (269 subjects). Vital status, age, area of residence, and socioeconomic status information were available. Predictive validity was quantified by the percent variance explained (PVE) over and above age using proportional hazards modeling.
RESULTS
The Chronic Disease Score (CDS) (PVE = 11.3%; 95% confidence interval [95% CI], 3.5‐22.8%), Index of Coexistent Disease (ICED) (PVE = 9.0%; 95% CI, 2.9‐17.9%), Cumulative Illness Rating Scale (CIRS) (PVE = 7.2%; 95% CI, 1.4‐17.1%), Kaplan‐Feinstein Index (PVE = 4.9%; 95% CI, 0.6‐12.8%), and Charlson Index (PVE = 3.8%; 95% CI, 0.3‐10.9%) each explained some outcome variability beyond age. PVE differences among indices were not statistically significant. A comorbidity identified at the time of cancer diagnosis was the cause of death in 59.2% of cases (75% for cardiac or vascular causes).
CONCLUSIONS
The better‐performing, more comprehensive indices (CDS, ICED, and CIRS) would be useful in measuring and controlling for comorbidity in this setting. The CDS was easiest to apply and explained the most outcome variability. Cancer 2006. © 2006 American Cancer Society.
Five chart‐based comorbidity indices were assessed for their ability to predict survival in a prostate carcinoma patient cohort treated with curative intent. The Chronic Disease Score (CDS), Index of Coexistent Disease (ICED), Cumulative Illness Rating Scale (CIRS), Kaplan‐Feinstein Index, and Charlson Index each explained some outcome variability beyond age, but differences among indices were not statistically significant. The CDS was the easiest index to apply and explained the most outcome variability.