Randomized phase 3 trial of fluorouracil, epirubicin, and cyclophosphamide alone or followed by Paclitaxel for early breast cancer.

BACKGROUND Taxanes are among the most active drugs for the treatment of metastatic breast cancer, and, as a consequence, they have also been studied in the adjuvant setting. METHODS After breast cancer surgery, women with lymph node-positive disease were randomly assigned to treatment with fluorouracil, epirubicin, and cyclophosphamide (FEC) or with FEC followed by weekly paclitaxel (FEC-P). The primary endpoint of study-5-year disease-free survival (DFS)-was assessed by Kaplan-Meier analysis. Secondary endpoints included overall survival and analysis of the prognostic and predictive value of clinical and molecular (hormone receptors by immunohistochemistry and HER2 by fluorescence in situ hybridization) markers. Associations and interactions were assessed with a multivariable Cox proportional hazards model for DFS for the following covariates: age, menopausal status, tumor size, lymph node status, type of chemotherapy, tumor size, positive lymph nodes, HER2 status, and hormone receptor status. All statistical tests were two-sided. RESULTS Among the 1246 eligible patients, estimated rates of DFS at 5 years were 78.5% in the FEC-P arm and 72.1% in the FEC arm (difference = 6.4%, 95% confidence interval [CI] = 1.6% to 11.2%; P = .006). FEC-P treatment was associated with a 23% reduction in the risk of relapse compared with FEC treatment (146 relapses in the 614 patients in the FEC-P arm vs 193 relapses in the 632 patients in the FEC arm, hazard ratio [HR] = 0.77, 95% CI = 0.62 to 0.95; P = .022) and a 22% reduction in the risk of death (73 and 95 deaths, respectively, HR = 0.78, 95% CI = 0.57 to 1.06; P = .110). Among the 928 patients for whom tumor samples were centrally analyzed, type of chemotherapy (FEC vs FEC-P) (P = .017), number of involved axillary lymph nodes (P < .001), tumor size (P = .020), hormone receptor status (P = .004), and HER2 status (P = .006) were all associated with DFS. We found no statistically significant interaction between HER2 status and paclitaxel treatment or between hormone receptor status and paclitaxel treatment. CONCLUSIONS Among patients with operable breast cancer, FEC-P treatment statistically significantly reduced the risk of relapse compared with FEC as adjuvant therapy.

A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.