A comprehensive prognostic index to predict survival based on multiple comorbidities: a focus on breast cancer.
BACKGROUND
The presence of comorbidities often influences clinical decision-making, although many studies exclude patients with comorbid disease for the sake of analysis.


OBJECTIVE
The purpose of this study was to develop a Comprehensive Prognostic Index (CPI), designed specifically for breast cancer patients.


METHODS
This study linked Medicare claims with the Kentucky Cancer Registry and developed two models based on 1 year survival; one focused on deaths caused by breast cancer and the other on deaths from all causes. Comorbidities were derived from inpatient and ambulatory claims for up to 2 years before the diagnosis of breast cancer.


METHODS
Subjects included a cohort of 848 elderly women first diagnosed with breast cancer in the state of Kentucky in 1993.


METHODS
Each model identified the comorbidities specific to breast cancer that were detrimental to survival, and generated a refined comorbidity index. The CPI integrated these measures with age and stage of cancer into a comprehensive prognostic index.


RESULTS
Nearly two-thirds of the patients had evidence of at least one comorbidity. Survival rates decreased with age, more advanced stage, and increased comorbidity burden, as expected. The interaction of comorbidity burden with either age or stage was particularly strong for the older and more advanced stage of cancer.


CONCLUSIONS
The CPI could be a useful tool in breast cancer intervention studies and a prognostic aid for clinicians.
Fleming
S T
ST
Health Services Management, Lexington, KY 40536-0003, USA. stflem@pop.uky.edu
Rastogi
A
A
Dmitrienko
A
A
Johnson
K D
KD
D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000150:complications* / Q000401:mortality*; D002423:Cause of Death; D015897:Comorbidity; D005260:Female; D006801:Humans; D007344:Insurance Claim Reporting / Q000706:statistics & numerical data; D007629:Kentucky / Q000453:epidemiology; D008498:Medical Record Linkage; D006278:Medicare / Q000706:statistics & numerical data; D009367:Neoplasm Staging; D011159:Population Surveillance; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D012042:Registries; D015203:Reproducibility of Results; D012307:Risk Factors; D012720:Severity of Illness Index; D016019:Survival Analysis; D014481:United States