Comorbidity and breast cancer survival: A comparison between black and white women

The presence of concurrent health conditions (comorbidity) at the time of breast cancer diagnosis has an adverse effect on survival. It is unclear, however, whether the strength of the association between comorbidity and survival varies in different populations of breast cancer patients. It is necessary, therefore, to establish (I) whether a comorbidity index derived From a general population of patients (mostly white) would Predict survival in a black population, and (2) whether comorbidity would have the same degree of relationship to mortality in black as in white populations. We studied 1196 breast cancer patients who were members of the Kaiser Permanente Medical Care Program and were diagnosed with local (n = 708), regional (n = 446), or remote (n = 49) stage breast cancer from 1973 to 1986. Mortality follow-up was completed to December 1994. Ten-year survival was studied in relation to the Charlson comorbidity index for black women and for white women, and for both groups of women combined. Compared to women with a Charlson comorbidity score of 0 (no comorbidity), patients with scores of 1, 2, and 3+ had risk ratios for ten-year mortality of 1.23 (P = 0.10), 2.58 (P < 0.001), and 3.44 (P < 0.001), respectively. This Pattern of risk associated with comorbidity was similar to that found in the original Charlson study. The pattern of risk ratios for different levels of comorbidity was very similar for black and white patients. The results confirm previous studies indicating that comorbidity (in particular, the Charlson Comorbidity Index) predicts the survival of women with breast cancer, independently of other factors, such as stage of breast cancer at diagnosis. The Charlson index has prognostic significance for both black and white populations. Research is needed to determine whether the Charlson index can be improved by including health conditions that are particularly prevalent or severe in specific subgroups of women. (C) 1996 by Elsevier Science Inc.