Impact of acquired comorbidities on all-cause mortality rates among older breast cancer survivors

Med Care. 2009 Jan;47(1):73-9. doi: 10.1097/MLR.0b013e318180913c.

Abstract

Background: Breast cancer survivors with higher numbers of comorbidities at the time of primary treatment suffer higher rates of all-cause mortality than comparatively healthier survivors. The effect of time-varying comorbidity status on mortality in breast cancer survivors, however, has not been well investigated.

Objective: We examined longitudinal comorbidity in a cohort of women treated for primary breast cancer to determine whether accounting for comorbidities acquired after baseline assessment influenced the hazard ratio of all-cause mortality compared with an analysis using only baseline comorbidity.

Methods: Cox proportional hazards adjusted for age, race/ethnicity, and exercise habits were modeled using (1) only a baseline Charlson index; (2) 4 Charlson index values collected longitudinally and entered as time-varying covariates, with missing values addressed by carrying forward the prior observation; and (3) the 4 longitudinal Charlson scores entered as time-varying covariates, with missing values multiply imputed.

Results: The 3 modeling strategies yielded similar results; Model 1 HR: 1.4 per unit increase in Charlson index, 95% confidence interval (CI): 1.2-1.7; Model 2 HR: 1.3, 95% CI: 1.1-1.5; and Model 3 HR: 1.4, 95% CI: 1.2-1.6.

Conclusions: Our findings indicate that a unit increase in the Charlson comorbidity index raises the hazard rate for all-cause mortality by approximately 1.4-fold in older women treated for primary breast cancer. The conclusion is essentially the same whether accounting only for baseline comorbidity or accounting for acquired comorbidity over a median follow-up period of 85 months.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Breast Neoplasms / complications*
  • Breast Neoplasms / mortality*
  • Cause of Death*
  • Chronic Disease
  • Comorbidity*
  • Female
  • Humans
  • Longitudinal Studies
  • Los Angeles / epidemiology
  • Minnesota / epidemiology
  • North Carolina / epidemiology
  • Proportional Hazards Models*
  • Prospective Studies
  • Rhode Island / epidemiology
  • Risk Factors
  • Survival Analysis
  • Survivors / statistics & numerical data*