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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2013 July 1.
Published in final edited form as:
PMCID: PMC3470873

Prognostic Impact of Comorbidity among Long-Term Breast Cancer Survivors: Results from the LACE Study



Little is known about the long-term impact of comorbidity among women with breast cancer.


We studied a prospective cohort of 2132 women, who were recruited following initial breast cancer treatment. Associations of the Charlson Comorbidity Index (CCI) and hypertension with survival were evaluated in delayed entry Cox proportional hazards models.


During the median follow-up of nine years, higher CCI scores were independently associated with an increased risk of death from all causes (hazard ratio [HR] = 1.32, 95% confidence interval [CI] = 1.13 to 1.54) and from non-breast cancer causes (HR = 1.55, 95% CI = 1.19 to 2.02) but not from breast cancer (HR = 1.14, 95% CI = .93 to 1.41). Hypertension was also independently associated with an increased risk of death from all causes (HR = 1.55, 95% CI = 1.20 to 1.99), from non-breast cancer causes (HR = 1.67, 95% CI = 1.10 to 2.54) and from breast cancer specifically (HR = 1.47, 95% CI = 1.03 to 2.09). The relationship between the CCI and overall survival was the strongest among women with stage I breast cancer (stage I, HR = 1.65, 95% CI = 1.26 to 2.16 vs. stage III, HR = .53, 95% CI = .23 to 1.25).


Whereas the CCI and hypertension were independently associated with lower overall and non-breast cancer survival, hypertension was also independently associated with lower breast cancer-specific survival.


If the observed relationships are causal, treating comorbidities may improve outcomes.

Keywords: comorbidity, breast cancer, survival


Although breast cancer, the most common cancer among women in developed countries aside from non-melanoma skin cancer, remains one of the leading causes of cancer death, survival has markedly improved in recent decades1. Principally, 5-year survival rates are close to 90% for women with Stage I disease but considerable variations exist in the length of survival among breast cancer patients2, even presenting within the same disease stage, and one of the contributing reasons for these variations may be the presence of comorbidity or concurrent chronic conditions in some survivors36. Women with breast cancer, especially those aged 65 and older, often present with one or more comorbid conditions, such as heart disease, diabetes, hypertension, or arthritis, at the time of diagnosis79. Whereas comorbidity has been shown to have short-term effects among women with breast cancer10, any long-term effects on breast cancer-specific and overall health outcomes are unknown. A better understanding of these relationships may help not only to illuminate predictors of the variability in survival but also to identify opportunities to intervene for improved survival. Specifically, there is a need to identify high-risk populations that could be targeted with interventions to promote quality and lengthy survival11.

In this study of the long-term prognostic role of comorbidity, we considered death from breast cancer, non-breast cancer causes, and all causes among women in a population-based cohort of earlystage breast cancer survivors, the Life After Cancer Epidemiology (LACE12) study. Women with incident breast cancer were followed for a median of nine years since diagnosis. By including both middle-aged and elderly women with breast cancer, this large cohort of breast cancer survivors was suitable for examining the long-term consequences of comorbidity following initial breast cancer treatment while taking into account known prognostic factors in the clinical, lifestyle-related, and sociodemographic domains. We also evaluated the extent to which the effect of comorbidity on long-term survival differed as a function of women’s chronological age and tumor stage at diagnosis.


Study Population

The study population consisted of women diagnosed with stage I (≥1 cm), II, or IIIa breast cancer from 1997 to 2000 in the Kaiser Permanente Northern California Cancer Registry or the Utah Cancer Registry. Eligible women were diagnosed on average 21 months (range 9–39 months) prior to enrollment, had completed cancer treatment, and were free of any documented recurrence during that period. In addition, women who were eligible but declined participation in the Women’s Healthy Eating and Lifestyle (WHEL)13 study, a dietary intervention trial examining the prevention of breast cancer recurrence, were included. A total of 2,586 (45.7%) completed initial enrollment; subsequent review to confirm eligibility left 2,272 women in the cohort. The large majority of cohort members (82%) came from Kaiser Permanente, 12% from Utah, and 6% from WHEL. The upper age restriction for enrollment to the study was 79 years. Of 2,272 women included in the cohort, data on comorbidity were available from 2, 132 participants. This sample formed the final study population for the present analysis.

The Institutional Review Boards at the University of California, San Francisco and Kaiser Permanente Northern California approved this study.

Assessment of Comorbidity

Figure 1 shows comorbidities that were used to construct the Charlson Comorbidity Index (CCI). The comorbidity burden was estimated using the interview-based version of the CCI14, the most common comorbidity index that summarizes many key health conditions15. Developed among patients admitted to an emergency department with respect to mortality at 1 year of follow-up as a function of comorbidity, the CCI was subsequently validated in a cohort of hypertensive patients16. Each condition included in the original CCI conferred an independent relative risk of death of 1.2. The comorbid conditions in the original CCI were weighted so that those leading to relative risks between 1.2 and <1.5 were scored as 1; between 1.5 and <2.5 as 2; between 2.5 and <3.5 as 3; and 2 conditions with a relative risk of 6 or more were scored as 6. The total scores calculated by tallying these weighted scores range from 1 to 6 (0 if the comorbidity is absent), are then collapsible into 4 summary categories: 0, 1–2, 3–4 and 5 points.

Figure 1
Formation of the Charlson Comorbidity Index*

In addition to the CCI, we assessed the independent effects of a common condition that is not included in this index, hypertension. Previous research indicated that hypertension was independently associated with survival among women with incident breast cancer17,18.

Outcome Ascertainment

To monitor breast cancer outcomes in the LACE cohort, a health status update questionnaire was mailed to participants semi-annually until April 2006 and annually thereafter. The questionnaire update asked women about any events that might have occurred in the preceding 6 months (or 12 months on the revised questionnaire), including recurrences or new primary breast cancer, hospitalizations, and other cancers. Those women who reported an event were then called on the telephone to obtain details about that event. In addition, non-respondents to the mailed health status update questionnaire were telephoned and asked about any new events. All reported deaths from any source, including date and cause, were confirmed by death certificate. A research associate (EW) categorized information on death certificates as breast cancer death or non-breast cancer death. Outcome ascertainment was updated regularly by surveillance of electronic outpatient, cancer registry, and mortality files for all participants, including those who dropped out (n = 90) or were lost to active follow-up (n = 15). In this analysis, the outcomes of interest were survival from non-breast cancer causes, survival from breast cancer-specific causes and overall survival.


Covariates in these analyses included sociodemographic, lifestyle-related, and clinical prognostic factors that could potentially confound or modify an association between comorbidity and survival based on the existing literature and a priori hypotheses. The sociodemographic covariates included age (calculated as the difference between date of enrollment and reported date of birth), race/ethnicity, and education, the last two being self-reported at baseline. Lifestyle-related factors included smoking status (never, former, current) and body mass index (BMI) at enrollment (calculated as weight/height [kg/m2] from self-reported weight and height). Three standard BMI categories (normal weight, < 25; overweight, 25–30; and obese, ≥ 30) were used 19; we also separately evaluated underweight women (BMI ≤ 18.5). Physical activity was assessed in the LACE study with a questionnaire based on the Arizona Activity Frequency Questionnaire 20. Standard metabolic equivalent task (MET) values were assigned to each activity and then frequency was multiplied by duration and MET value and summed over all activities (other than the sedentary recreational and transportation activities), providing a summary measure of total activity in MET hours per week 21. Medical factors were obtained from chart review for both Kaiser and non-Kaiser members. These factors included tumor size, histology, lymph node involvement and distant metastasis, estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor 2 receptor (HER2) status, and treatments (type of surgery, radiation, chemotherapy, and use of adjuvant tamoxifen). Stage at diagnosis was classified according to the Tumor, Node, Metastasis system based on the criteria of the American Joint Committee on Cancer22.

Statistical Analyses

Differences in means and proportions of each potential covariate by the CCI score (i.e. CCI=0, CCI=1, CCI≥2) were compared using Student t tests for continuous variables and Pearson Χ2 tests for categorical variables. Univariate and multivariable associations between comorbidity and survival were examined using Kaplan-Meier plots and Cox proportional hazards models. Guided by a priori considerations 23, separate delayed entry Cox proportional hazards models 24, 25 with time since diagnosis as the time scale were used to estimate the risk of each outcome associated with comorbidity, accounting for varying times of enrollment into the cohort and adjusting for covariates. Risk was expressed as a hazard ratio and 95% confidence interval. The type I error was set at .05 and all reported P-values are two-sided.

Follow-up time ended at the date of first confirmed date of death, depending on the specific analysis. Individuals who did not die were censored at date of last contact (either most recent questionnaire on health status update or electronic surveillance). When death due to non-breast cancer causes was analyzed, breast cancer–specific deaths were censored. After computing unadjusted Cox proportional hazards models for comorbidity, known prognostic variables and those that showed statistically significant relations with either the independent or dependent variable were added to the model (if P < .10 in a model including all other significant predictors). All Cox proportional hazards models were tested for proportionality of hazards using Schoenfeld residuals 26. When this assumption was violated, stratified proportional hazards models were fitted; no material differences in hazard ratios were observed. Multivariable models were stratified by age at diagnosis and tumor stage, and interaction terms were considered. To avoid collinearity in modeling, tamoxifen use and ER status were entered into the same model by creating variables, "ER positive/no tamoxifen" and "ER positive/tamoxifen”. Stata version 11.0 software (StataCorp LP, College Station, Texas, USA) was used to conduct statistical analyses.


Characteristics of Study Participants by Comorbidity

We included 2132 women with breast cancer. The majority of the women were early-stage breast cancer survivors with 80% having stage I or IIa breast cancer at the time of diagnosis (Table 1). The median age was 57 years (SD = 13.2 years; range 21–79 years) at the time of study entry. The sample was ethnically and socioeconomically diverse: 20% of participants were non-white, and nearly 30% had a high school education or less.

Table 1
Characteristics of the study population by comorbidity based on the Charlson Comorbidity Index (CCI)

A CCI score of ≥1 was present in 54% of patients. The proportion of women with a CCI score of ≥1 generally increased with age; 18.2% of women with a CCI score of 0 were aged 65–79 versus 34.8% of women with a CCI score of 1 and 41.4% of women with a CCI score of ≥ 2 (P < .001, Table 1). Women with higher CCI scores were more likely to be overweight or obese; 33.9% women with a CCI score of 2 or more had a BMI of at least 30 and 27.5% women with a CCI score of 1 versus 22.4% of women with a CCI score of 0 (P < .001, Table 1). Women with higher CCI scores were also disproportionately less educated; 31.3% women with a CCI score of ≥ 2 and 26.6% women with a CCI score of 1 had a high school education or less, compared with 24.6% of women with a CCI score of 0 (P < .001). In addition, women with a CCI score of ≥ 2 were less physically active compared with women with a CCI score of 0 (MET h/wk: mean = 49.0 vs. 53.8, respectively; P = .03). There were also differences in breast cancer treatment by comorbidity; patients with a CCI score of ≥ 2 were less likely to receive chemotherapy (47.9% vs. 64.9%, respectively, P < .001), and radiotherapy (62.6% vs. 66%, respectively, P = .05). However, there were no significant differences in the proportions of women with adverse stage, nodal status, and ER/PR/HER2 status by comorbidity level. While proportions of breast cancer death did not differ by women’s comorbidity level, proportionately more women with CCI scores of ≥ 2 than those with the scores of 0 died of non-breast cancer causes (9.5% vs. 2.7% respectively, P < .001, Table 1).

Survival Data

The median follow-up in the entire LACE cohort of 2132 women was nine years (SD = 1.5 years, range = 1–11 years); 95% of the women were followed for a minimum of 6.3 years. Of the total of 264 deaths, 120 were attributable to non-breast cancer causes (5% of the cohort) and 164 to breast cancer causes (7% of the cohort).

Comorbidity and Survival

We calculated hazard ratios for the effect of the CCI and other non-CCI conditions on non-breast cancer, breast cancer-specific and overall survival (Table 2). In a multivariable model that included age, education, race/ethnicity, chemotherapy, radiation, tamoxifen, smoking, physical activity, BMI, tumor stage, hormone receptor status and nodal status, we found that women with comorbid conditions included in the CCI (i.e. CCI > 0) had a statistically significantly increased risk of death from all causes (hazard ratio [HR] = 1.32, 95% confidence interval [CI] = 1.13 to 1.54) and from non-breast cancer causes (HR = 1.55, 95% CI = 1.19 to 2.02) but not significantly from breast cancer (HR = 1.14, 95% CI = .93 to 1.41) (Table 2). In addition to the overall CCI, hypertension, was independently associated with an increased risk of breast cancer specific-death after adjustment for aforementioned covariates and the CCI (HR = 1.47, 95% CI = 1.03 to 2.09) as well as with the risk of all-cause death (HR = 1.55, 95% confidence interval = 1.20 to 1.99) and the risk of death from other causes (HR = 1.67, 95% CI = 1.10 to 2.54; Table 2). There was a dose-response relationship between the CCI score and overall survival as well as survival from non-breast cancer causes but not with breast cancer-specific survival (Table 3).

Table 2
Univariate and multivariable hazard ratios for Charlson Comorbidity Index (CCI) and hypertension
Table 3
Univariate and Multivariable Cox Regression Hazard Ratios by Charlson Comorbidity Index ( CCI)

Comorbidity and Survival by Women’s Age at Breast Cancer Diagnosis

We examined the possible disproportionate impact of comorbidity on survival by women’s age at breast cancer diagnosis (Table 4). Overall, higher CCI scores tended to have a greater adverse effect on overall and on non-breast cancer survival in younger age groups, after adjustment for other factors. In multivariable models, we found a decreasing trend with age in the association between the CCI and overall survival (HR=1.49, 95%CI .91–2.43, for age<50; HR=1.42, 95%CI 1.12–1.80, for ages 50–64 and HR=1.17 for ages 65–79, 95%CI .94–1.47) and non-breast cancer survival (HR=1.84, 95%CI 1.11–3.05, for ages 50–64 and HR=1.29, 95%CI .94–1.78 for ages 65–79). Similarly, in multivariable models, hazard ratios for the association of the CCI with survival from non-breast cancer causes were higher among women aged 50–65 years (HR = 1.84, 95% CI = 1.11 to 3.05) than among those aged ≥ 65 (adjusted HR = 1.29, 95% CI = .94–1.78). Although adjusted hazard ratios among women aged ≤ 50 were the highest, confidence intervals were wide in this group (Table 4). We found some evidence of a statistically significant interaction among women aged ≥ 65 with the CCI=1 in relation to overall survival (HR=.31, 95%CI .10–.96, p=.04)].

Table 4
Univariate and multivariable hazard ratios for Charlson Comorbidity Index (CCI) stratified by women’s age at breast cancer diagnosis and tumor stage

Comorbidity and Survival by Tumor Stage

To better understand the relationships among comorbidity, extent of disease, and survival, we performed analyses stratified by tumor stage (Table 4). In fully adjusted models, the effect of the CCI on overall survival was highest for women with stage I disease (HR = 1.65, 95% CI = 1.26 to 2.16) followed by those with stage IIa disease (HR = 1.33, 95% CI = 1.02 to 1.74), stage IIb (HR = 1.09, 95% CI = .80 to 1.49) and stage III disease (HR = .53, 95% CI = .23 to 1.25). In multivariable models, there were no statistically significant interactions between comorbidity and tumor stage.


We found that patient-reported comorbid conditions, assessed by the CCI following initial breast cancer treatment, were associated with a statistically significantly increased risk of death from overall and non-breast cancer causes but not from breast cancer specifically in this cohort of 2132 long-term breast cancer survivors. Notably, there was a dose-response relationship between the CCI and overall survival as well as that from non-breast cancer causes. Additionally, we found that comorbidity exerted most adverse effects among women with Stage I disease and younger age at diagnosis. In addition to the independent effects of the CCI, hypertension, a common condition not included in the CCI, was also associated with a statistically significantly increased risk of death from overall and from non-breast cancer causes, as well as breast cancer-specific death.

Our results are consistent with those of other prospective and retrospective cohort studies of breast cancer survivors35, 10, 17, 2730. We extend these results to show that the adverse effects of comorbidity, as reflected by higher CCI scores, exert long-term effects, particularly among women with early stage disease. Less data are available regarding the effect of individual comorbidities that are not included in the CCI. Consistent with our previous retrospective cohort study of African American and white women 17, in this prospective analysis we confirm the association of hypertension with breast cancer-specific survival as well as overall survival and that from non-breast cancer causes. Our ability to adjust for tumor characteristics, other comorbidity, BMI and lifestyle factors in the analysis was a strength; however, we were unable to evaluate other potential confounders, particularly the effect of antihypertensive treatment. A prior cohort study conducted in the 1970s also showed an association of diagnosed hypertension with cancer mortality31. To demonstrate that hypertension is truly causally associated with breast cancer, it will be important to elucidate underlying biologic mechanisms. For example, increased expression of inositol triphosphate and cytosolic calcium have been hypothesized to be involved in the pathogenesis of hypertension and in the early events of cell proliferation that are activated by endogenous oncogenes32. Another study has identified aberrant carcinogen binding to deoxyribonucleic acid in lymphocytes of hypertensive patients33. Cell death via apoptosis can also affect the growth of vascular smooth muscle cells, and related aberrations have also been found in hypertension34. Furthermore, neurohormones such as angiotensin II, catecholamines, vasopressin, insulin and growth hormone regulate blood pressure and have a mitogenic effect35.

That cancer stage and other tumor markers may modify the impact of comorbidity on survival among cancer patients, including those with breast cancer, was exemplified by Read et al.36, who showed that the effect of comorbidity was greatest among patients with localized disease at diagnosis and least in patients with advanced disease. Consistent with our results, survival was shown to be more variable among women with local disease, compared to those with regional and remote disease. Our finding that women with comorbidity, as reflected by higher CCI scores, were less likely to receive chemotherapy and radiotherapy is consistent with our previous report showing that breast cancer patients with functional limitations were also less likely to receive adjuvant therapy37. Furthermore, West et al.4 demonstrated that patients with substantial comorbidity, as assessed with the CCI15, 16, received less adjuvant breast cancer treatment including radiotherapy and chemotherapy. Moreover, several studies have indicated that comorbidity significantly affected treatment independent of age38, 39. For example, Frasci et al.40 demonstrated that severe comorbidity based on the CCI was related to early termination of treatment for older patients with advanced non-small cell lung cancer enrolled in a clinical chemotherapy trial.

The current study had design strengths and limitations. It included a large cohort of breast cancer patients from a large, Northern Californian integrated health care delivery system (whose members are representative of the general population with respect to most demographic and socioeconomic categories15) and the Utah Cancer Registry, with long follow-up and a broad age range at diagnosis. Comorbidity data were collected through patient questionnaires, which are deemed reliable and valid14, as shown in previous studies of breast cancer patients 41, 42. Although more than 2,000 cases of breast cancer were included in the cohort, we had limited statistical power to examine individual causes of death. Further detailing of the impact of comorbidity on cause-specific death (e.g. cardiovascular disease, diabetes) may reveal mechanisms by which comorbid conditions exert their effects. Comorbidity assessments were conducted after initial breast cancer treatment since information on comorbidity prior to breast cancer diagnosis was unavailable. Because this study is a prospective analysis of breast cancer survivors only, we were unable to determine whether the mortality increase due to comorbidity is higher in women with breast cancer than in their counterparts without the disease. Further validation in larger and more geographically, demographically and clinically diverse samples, including survivors of other cancers and with longitudinal assessments of comorbidity and underlying biological mechanisms over a longer follow-up period, is warranted.

In summary, in this prospective study of breast cancer survivors, a CCI score of ≥ 1 was present in 54% of women, and reported comorbidity following initial breast cancer treatment was associated with a reduction in overall survival and that from non-breast cancer causes. The adverse impact of comorbidity on survival was stronger among women with Stage I disease. Importantly, women with early stage breast cancer form the majority of contemporary breast cancer survivors in the developed world today 43. Our observations, combined with those of other investigators, suggest that failure to address comorbidity may have important consequences for longevity among breast cancer survivors.


This research was supported by a career development award to DB from the National Institutes of Health, National Cancer Institute, Bay Area Breast Cancer SPORE (P50 CA 58207) and the Hellman Fellowship at the University of California, San Francisco. The data are from the Life after Cancer Epidemiology (LACE) study, which is supported by the National Cancer Institute ( R01 CA129059).


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