Selective estrogen receptor modulator-associated nonalcoholic fatty liver disease improved survival in patients with breast cancer a retrospective cohort analysis

Abstract

Selective estrogen receptor modulator (SERM)-associated nonalcoholic fatty liver disease (NAFLD) might be related to treatment efficacy in patients with breast cancer because of circulating estrogen antagonism. The aim of the study was to investigate the relationship between NAFLD and survival outcomes in patients with breast cancer who were treated with tamoxifen or toremifene. This single-center, retrospective, cohort study included 785 eligible patients who received tamoxifen or toremifene, after curative resection for breast cancer, at the Sun Yat-sen University Cancer Center between January 2005 andDecember 2009. Datawere extracted from patient medical records. All patients underwent abdominal ultrasonography, at least once, at baseline and at the annual followup. Patients who were diagnosed with NAFLD on ultrasonography were classified into the NAFLD or the non-NAFLD arm at the 3-year follow-up visit. Univariate and multivariate Cox regression analyses were conducted to evaluate any associations between NAFLD and disease-free survival (DFS) or overall survival (OS). One hundred fifty-eight patients were diagnosed with NAFLD. Patients who developed NAFLD had better DFS and OS compared with those who did not. Univariate analyses revealed that the 5-year DFS rates were 91.56% and 85.01% for the NAFLD and non-NAFLD arms, respectively (hazard ratio [HR], 0.59; 95% confidence interval [CI], 0.37-0.96; log-rank P=0.032). The 5-year OS rates were 96.64% and 93.31% for the NAFLD and non-NAFLD arms, respectively (HR, 0.39; 95% CI, 0.16-0.99; log-rank P=0.039). Multivariate analysis revealed that NAFLD was an independent prognostic factor for DFS, improving the DFS rate by 41% compared with that in the non-NAFLD arm (HR, 0.59; 95% CI, 0.36-0.96; P=0.033). SERM-associated NAFLD was independently associated with improved DFS and might be useful for predicting treatment responses in breast cancer patients treated with SERMs.