Objective There is limited information from population‐based cancer registries regarding prognostic features of bilateral primary breast cancer (BPBC). Methods Female patients diagnosed with BPBC between 2004 and 2014 were randomly divided into training (n = 7740) and validation (n = 2579) cohorts from the Surveillance, Epidemiology, and End Results Database. We proposed five various models. Multivariate Cox hazard regression and competing risk analysis were to explore prognosis factors in training cohort. Competing risk nomograms were constructed to combine significant prognostic factors to predict the 3‐year and the 5‐year survival of patients with BPBC. At last, in the validation cohort, the new score performance was evaluated with respect to the area under curve, concordance index, net reclassification index and calibration curve. Results We found out that age, interval time, lymph nodes invasion, tumor size, tumor grade and estrogen receptor status were independent prognostic factors in both multivariate Cox hazard regression analysis and competing risk analysis. Concordance index in the model of the worse characteristics was 0.816 (95% CI: 0.791‐0.840), of the bilateral tumors was 0.819 (95% CI: 0.793‐0.844), of the worse tumor was 0.807 (0.782‐0.832), of the first tumor was 0.744 (0.728‐0.763) and of the second tumor was 0.778 (0.762‐0.794). Net reclassification index of the 3‐year and the 5‐year between them was 2.7% and −1.0%. The calibration curves showed high concordance between the nomogram prediction and actual observation. Conclusion The prognosis of BPBC depended on bilateral tumors. The competing risk nomogram of the model of the worse characteristics may help clinicians predict survival simply and effectively. Metachronous bilateral breast cancer presented poorer survival than synchronous bilateral breast cancer.

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Background There is no clear consensus on the benefits of adjuvant chemotherapy for tumor-node-metastasis (TNM) stage T1 (T1N0M0) breast cancer (BC). Our study investigated the effects of adjuvant chemotherapy on T1N0M0 BC patients. Methods Seventy-five thousand one hundred thirty-nine patients diagnosed with T1N0M0 BC were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate Cox analyses were performed to investigate the effects of adjuvant chemotherapy on T1a, T1b, and T1cN0M0 BC, including various tumor grades, and four molecular subtypes. Propensity score matching (PSM) was used to eliminate confounding factors and further compare the results between adjuvant chemotherapy and no adjuvant chemotherapy. Additionally, 545 T1N0M0 BC patients treated at the Northern Jiangsu People’s Hospital were included as an independent external validation cohort. Univariate and multivariate Cox analyses were used to confirm the effects of adjuvant chemotherapy in T1a, T1b, and T1cN0M0 BC. Survival curves for the different tumor grades and molecular subtypes were plotted using the Kaplan–Meier method. Results Adjuvant chemotherapy demonstrated a statistically significant improvement in overall survival (OS) in T1b and T1c BC, but not in T1a BC. Within T1b BC, adjuvant chemotherapy was found to have effects on grade III, and hormone receptor + (HoR +)/human epidermal growth factor receptor 2 + (HER2 +), HoR-/HER2 + , and HoR-/HER2- molecular subtypes, respectively. Adjuvant chemotherapy was beneficial to OS for grade II/III and T1c BC. Identical results were obtained after PSM. We also obtained similar results with external validation cohort, except that adjuvant chemotherapy made a difference in grade II and T1b BC of the external validation dataset. Conclusions Partial T1N0M0 BC patients with grade III T1bN0M0, patients with tumor grade II and III T1cN0M0, and excluding those with HoR + /HER2- subtype tumors, could obtain OS benefits from adjuvant chemotherapy.

PURPOSE: Multi-gene predictors (MGPs) of response to multidrug chemotherapy regimens were developed using an in vitro chemoresponse assay in which cell lines were exposed to chemotherapy. The goal of this study was to assess the predictive value of these MGPs using clinical breast cancer patient gene expression data from a clinical trial. METHOD: US Oncology 02-103 was a phase II trial in which women with stage II/III breast cancer were treated with neoadjuvant chemotherapy consisting of four cycles of fluorouracil/epirubicin/cyclophosphamide (FEC) followed by four cycles of docetaxel/capecitabine (TX). Most HER-2 positive patients also received trastuzumab. MGPs of FEC, TX and TFEC (docetaxel/fluorouracil/epirubicin/cyclophosphamide) sensitivity were developed using in vitro assay results from breast cancer cell lines exposed to these drug combinations and publicly-available gene expression data for the same cell lines. MGPs were not developed for trastuzumab treatment. Area under the receiver-operator curve (AUC) was used to evaluate the performance of the three MGPs’ to predict patient pathologic complete response (pCR). Patients who did or did not receive trastuzumab were evaluated separately. Validation was performed blindly and the predictors were applied without knowledge of patient clinical outcome. RESULTS: Eighty-six patients had genomic data available and were included in this analysis. The predictive performance of the FEC, TX and TFEC MGPs were AUCs of 0.72, 0.69, and 0.73, respectively, in the patients who received FEC-TX chemotherapy without trastuzumab (n=61). Within this group, higher AUCs were observed in ER-negative patients compared to ER-positive patients (0.69, 0.72, 0.74 vs. 0.64, 0.54, 0.62, respectively). The prediction accuracies were low (AUCs = 0.43, 0.56 and 0.43) for patients who received trastuzumab together with chemotherapy (n=25) as expected, indicating that the MGPs may have the potential to be regimen-specific. CONCLUSION: Cell line-derived MGPs of multidrug chemotherapy regimens showed promising performance in this blinded validation study, particularly among patients with ER-negative breast cancers. Further clinical data are needed to confirm this finding. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-09-39.

Background There is no definitive, unified view on chemotherapy for T1 pN0M0 breast cancer. Our study explored the effects of chemotherapy on T1 pN0M0 breast cancer. Methods 75,139 patients diagnosed with T1 pN0M0 breast cancer were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate Cox analyses were performed to investigate the effects of chemotherapy on T1a, T1b, and T1c pN0M0 breast cancer, various tumor grades, and four molecular subtypes. Propensity score matching (PSM) was used to eliminate confounding factors and further verify the results between chemotherapy and no chemotherapy. Finally, 545 T1pN0M0 breast cancer patients treated at the Northern Jiangsu People’s Hospital were included for external validation. Univariate and multivariate Cox analyses were used to confirm the role of chemotherapy in T1a, T1b, and T1c pN0M0 breast cancer. Survival curves were plotted using the Kaplan–Meier method for tumor grades and molecular subtypes. Results Chemotherapy demonstrated a statistically significant improvement in T1b and T1c breast cancer, not in T1a breast cancer. With T1b breast cancer, chemotherapy had effects on grade III and molecular subtypes hormone receptor+ [HR+]/human epidermal growth factor receptor 2+ [HER2+], HR-/HER2+, and HR-/HER2-. Chemotherapy was beneficial to overall survival for grade II/III and T1c breast cancer. After PSM, identical results were obtained. We also obtained similar results with external validation, except that chemotherapy made a difference in grade II and T1b breast cancer of external validation. Conclusion Partial T1 pN0M0 breast cancer patients with tumor grade III T1b pN0M0 except HR+/HER2-, those with tumor grade II and III T1c pN0M0 can obtain overall survival benefits from chemotherapy.