Weight Gain After Breast Cancer Diagnosis and All-Cause Mortality: Systematic Review and Meta-Analysis

Abstract

Background: Overweight and obesity are associated with breast cancer mortality. However, the relationship between postdiagnosis weight gain and mortality is unclear. We conducted a systematic review and meta-analysis of weight gain after breast cancer diagnosis and breast cancer-specific, all-cause mortality and recurrence outcomes.

Methods: Electronic databases identified articles up through December 2014, including: PubMed (1966-present), EMBASE (1974-present), CINAHL (1982-present), and Web of Science. Language and publication status were unrestricted. Cohort studies and clinical trials measuring weight change after diagnosis and all-cause/breast cancer-specific mortality or recurrence were considered. Participants were women age 18 years or older with stage I-IIIC breast cancer. Fixed effects analysis summarized the association between weight gain (≥5.0% body weight) and all-cause mortality; all tests were two-sided.

Results: Twelve studies (n = 23 832) were included. Weight gain (≥5.0%) compared with maintenance (<±5.0%) was associated with increased all-cause mortality (hazard ratio [HR] = 1.12, 95% confidence interval [CI] = 1.03 to 1.22, P = .01, I(2) = 55.0%). Higher risk of mortality was apparent for weight gain ≥10.0% (HR = 1.23, 95% CI = 1.09 to 1.39, P < .001); 5% to 10.0% weight gain was not associated with all-cause mortality (P = .40). The association was not statistically significant for those with a prediagnosis body mass index (BMI) of less than 25 kg/m(2) (HR = 1.14, 95% CI = 0.99 to 1.31, P = .07) or with a BMI of 25 kg/m(2) or higher (HR = 1.00, 95% CI = 0.86 to 1.16, P = .19). Weight gain of 10.0% or more was not associated with hazard of breast cancer-specific mortality (HR = 1.17, 95% CI = 1.00 to 1.38, P = .05).

Conclusions: Weight gain after diagnosis of breast cancer is associated with higher all-cause mortality rates compared with maintaining body weight. Adverse effects are greater for weight gains of 10.0% or higher.

Figure 1.

PRISMA flow diagram. BC = breast cancer; BMI = body mass index.

Figure 2.

Forrest plot: Fixed effects meta-analysis of the association between weight gain ≥ 5.0% and all-cause mortality. The black squares and horizontal lines represent study-specific hazard ratios (HR) and their 95% confidence intervals (CI). The P-values were calculated using Z- score for overall effect and Chi² test for heterogeneity. All tests were two-sided (P < .05). KG kilograms; LACE = Life After Cancer Epidemiology; NHS = Nurse’s Health Study; SBCSS = Shanghai Breast Cancer Survival Study; WG Weight Gain; WHEL = Women’s Healthy Eating and Living.

Figure 3.

Forest plot: Fixed effects meta-analysis of the association between weight gain and all-cause mortality, stratified by level of weight gain. The black squares and horizontal lines represent study-specific hazard ratios (HR) and their 95% confidence intervals (CI). The P-values were calculated using Z- score for overall effect and Chi² test for heterogeneity. All tests were two-sided (P < .05). KG kilograms; LACE = Life After Cancer Epidemiology; NHS = Nurse’s Health Study; SBCSS = Shanghai Breast Cancer Survival Study; WG Weight Gain; WHEL = Women’s Healthy Eating and Living.

Figure 4.

Forest plot: Fixed effects meta-analysis of the association between weight gain > 5.0% and all-cause mortality, stratified by pre-diagnosis body mass index (BMI). The black squares and horizontal lines represent study-specific hazard ratios (HR) and their 95% confidence intervals (CI). The P-values were calculated using Z- score for overall effect and Chi² test for heterogeneity. All tests were two-sided (P < .05). KG kilograms; LACE = Life After Cancer Epidemiology; NHS = Nurse’s Health Study; SBCSS = Shanghai Breast Cancer Survival Study; WG Weight Gain; WHEL = Women’s Healthy Eating and Living.

Figure 5.

Forest plot: Fixed effects meta-analysis of the association between weight gain and breast cancer-specific mortality, stratified by level of weight gain. The black squares and horizontal lines represent study-specific hazard ratios (HR) and their 95% confidence intervals (CI). The P-values were calculated using Z-score for overall effect and Chi² test for heterogeneity. All tests were two-sided (P < .05). KG kilograms; LACE = Life After Cancer Epidemiology; NHS = Nurse’s Health Study; SBCSS = Shanghai Breast Cancer Survival Study; WG Weight Gain; WHEL = Women’s Healthy Eating and Living.

Figure 6.

Forest plot: Fixed effects meta-analysis of the association between weight gain and breast cancer recurrence. The black squares and horizontal lines represent study-specific hazard ratios (HR) and their 95% confidence intervals (CI). The P-values were calculated using Z-score for overall effect and Chi² test for heterogeneity. All tests were two-sided (P <.05). LACE = Life After Cancer Epidemiology; NHS = Nurse’s Health Study; SBCSS = Shanghai Breast Cancer Survival Study; WG Weight Gain; WHEL = Women’s Healthy Eating and Living.