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.

Background: It is well known that the prognosis of cancer patients after tumor resection is closely related to the patient's autoimmune ability and nutritional status. A large number of studies have shown that the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and Onodera's prognostic nutritional index (OPNI) are signi cantly correlated with the prognosis of various tumors. In this study, we analyzed the prognostic value of NLR, PLR and OPNI for hepatocellular carcinoma (HCC) for the rst time.Patients and Methods: Data of hepatocellular carcinoma patients undergoing hepatectomy in Changzhi People's Hospital (Changzhi, China) from 2011 to 2017 were retrospectively analyzed. A total of 286 patients with hepatocellular carcinoma were included in the analysis. The Optimum cut-off values of OPNI, NLR and PLR were determined by using the X-tile program. The overall survival (OS) was analyzed by Kaplan-Meier method and veri ed by log-rank test. Multivariate analysis was performed using Cox Proportional Hazard Regression model to determine independent prognostic indicators for HCC.Results: Univariate and multivariate analysis showed that OPNI (p<0.001), Treatment (Surgery, p=0.04;Interventional therapy, p=0.002), Postoperative treatment (YES, p=0.004) and Stage can be used as independent prognostic maker for HCC. Comparing the P values and hazard ratios, we found out that the OPNI has greatest in uence on prognosis in these preoperative indexes. The optimal cut-off values of NLR, PLR and OPNI were 2.5, 133.3 and 39.5, respectively. Compared with the low OPNI group, the high OPNI group had a better prognosis. In the correlation analysis between OPNI and clinicopathological features, only Age and NLR showed statistical differences, while others did not.Conclusions: OPNI can be used as a simple and effective independent prognostic marker for hepatocellular carcinoma.

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.

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