Clinical characteristics and prognosis of primary small cell carcinoma of the breast: a propensity score-matched, population-based study.

OBJECTIVE: The purpose of this study was to describe the clinicopathological characteristics and prognosis of primary small cell carcinoma of the breast (PSCCB) and compare PSCCB with breast invasive ductal carcinoma (IDC). DESIGN: A retrospective cohort study. SETTING: Data of patients with PSCCB and breast IDC were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2016. PARTICIPANTS: Eighty-three patients with PSCCB and 410 699 patients with breast IDC were enrolled in the present cohort study. MATERIALS AND METHODS: Patients with PSCCB and breast IDC were identified from the SEER database between 2004 and 2016. The clinicopathological characteristics and survival of patients with PSCCB and IDC were compared. Propensity score matching (PSM) analysis was performed to adjust for differences in baseline characteristics when comparing overall survival (OS) and cancer-specific survival (CSS). Moreover, OS-/CSS-specific nomograms were established to predict the prognosis of PSCCB. RESULTS: Compared with IDC, PSCCB was significantly correlated with older age, male, higher pathological grade, higher TNM (tumour, node, metastases) stage, a higher proportion of triple-negative breast cancer, a lower proportion of ER/PR positivity and significantly worse clinical outcome. The median OS and CSS of patients with PSCCB were 23.0 m (95%CI 13.0 to 56.0) and 28.0 m (95%CI 18.0 to 66.0), respectively. The 5-year OS and CSS rates in the PSCCB group were 36.1% and 42.4%, respectively. In the matched cohort after PSM analysis, patients with PSCCB had significantly worse OS and CSS than IDC patients. Multivariate Cox regression analysis demonstrated that T stage and administration of chemotherapy were independent prognostic factors for both OS and CSS in patients with PSCCB. The C-index for OS-/CSS-specific nomogram was 0.75 (95%CI 0.66 to 0.85)/0.79 (95%CI 0.69 to 0.89), respectively. The calibration curve in the ROC analysis indicated that the predicted value was consistent with the actual observation value. Decision curve analysis suggested that the nomogram model has a significant positive net benefit from the risk of death and are better than the traditional TNM staging system. CONCLUSION: PSCCB has distinct clinicopathological characteristics, and patients with PSCCB have significantly worse clinical outcomes than those with IDC.

Risk factors and survival prediction of young breast cancer patients with liver metastases: a population-based study.

Background: The risk and prognosis of young breast cancer (YBC) with liver metastases (YBCLM) remain unclear. Thus, this study aimed to determine the risk and prognostic factors in these patients and construct predictive nomogram models. Methods: This population-based retrospective study was conducted using data of YBCLM patients from the Surveillance, Epidemiology, and End Results database between 2010 and 2019. Multivariate logistic and Cox regression analyses were used to identify independent risk and prognostic factors, which were used to construct the diagnostic and prognostic nomograms. The concordance index (C-index), calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to assess the performances of the established nomogram models. Propensity score matching (PSM) analysis was used to balance the baseline characteristics between the YBCLM patients and non-young patients with BCLM when comparing overall survival (OS) and cancer-specific survival (CSS). Results: A total of 18,275 YBC were identified, of whom 400 had LM. T stage, N stage, molecular subtypes, and bone, lung, and brain metastases were independent risk factors for LM developing in YBC. The established diagnostic nomogram showed that bone metastases contributed the most risk of LM developing, with a C-index of 0.895 (95% confidence interval 0.877-0.913) for this nomogram model. YBCLM had better survival than non-young patients with BCLM in unmatched and matched cohorts after propensity score matching analysis. The multivariate Cox analysis demonstrated that molecular subtypes, surgery and bone, lung, and brain metastases were independently associated with OS and CSS, chemotherapy was an independent prognostic factor for OS, and marital status and T stage were independent prognostic factors for CSS. The C-indices for the OS- and CSS-specific nomograms were 0.728 (0.69-0.766) and 0.74 (0.696-0.778), respectively. The ROC analysis indicated that these models had excellent discriminatory power. The calibration curve also showed that the observed results were consistent with the predicted results. DCA showed that the developed nomogram models would be effective in clinical practice. Conclusion: The present study determined the risk and prognostic factors of YBCLM and further developed nomograms that can be used to effectively identify high-risk patients and predict survival outcomes.

Clinical characteristics and prognostic nomogram for patients with insular thyroid carcinoma: a population-based analysis.

BACKGROUND: Insular thyroid carcinoma (ITC) is an uncommon poorly differentiated thyroid malignancy. Due to its rarity, its demographic and clinicopathological features and survival remains unclear. The present study aimed to describe the features and survival of ITC, determine its prognostic factors, and establish a prognostic nomogram. METHODS: Patients with ITC were identified in the Surveillance, Epidemiology, and End Results database from 2004 to 2019. The features and survival of patients with ITC and other thyroid carcinomas were compared after balancing the baseline characteristics using propensity score matching (PSM). Univariate and multivariate Cox analyses were used to identify the prognostic factors for ITC. Moreover, overall survival (OS)- or cancer-specific survival (CSS)-specific nomograms were established to predict ITC prognosis. RESULTS: A total of 206 patients with ITCs were identified. The 1-, 2-, 5-, and 10-year OS rates of 206 patients with ITC were 90.3%, 82.0%, 62.2%, and 42.5%, respectively. The median OS was 93 months (95% CI, 73.0-140.0), while the median CSS was 141 months (95% CI, 93.0-173.0). After PSM analysis, the survival analysis of the matched cohort revealed that ITC had a worse clinical outcome than papillary thyroid cancer and follicular thyroid cancer, and better survival than anaplastic thyroid carcinoma. Multivariate Cox regression analysis demonstrated that age, N stage, M stage, and surgery were independent prognostic factors for both OS and CSS in ITC patients. The C-indices for the OS- and CSS-specific nomograms were 0.778 (95% CI, 0.724-0.832) and 0.808 (95% CI, 0.754-0.862), respectively. The calibration curve and ROC analysis indicated that the nomogram models exhibited a good discriminative ability. Decision curve analysis suggested that the nomogram models had a significant positive net benefit and were better than the traditional TNM staging system at predicting survival. CONCLUSION: ITC has distinct clinicopathological characteristics and survival compared to other thyroid carcinomas, and the established nomogram could predict the survival probability of patients with ITC accurately with a higher net benefit.