Whether unplanned excision on synovial sarcoma will influence the prognosis? An retrospective analysis of prognostic factors in 54 synovial sarcoma cases at a single center.

OBJECTIVE: In this study, we examined the reason and prognosis of unplanned excision on synovial sarcoma. METHODS: We retrospectively analyzed 54 patients diagnosed with synovial sarcoma between March 2013 and February 2021, including 26 cases of unplanned excision surgery. Patients were divided into two groups based on whether they underwent unplanned excision. Then, factors such as gender, age, tumor size, tumor location, American Joint Committee on Cancer (AJCC) staging, unplanned excision, time of onset, duration of disease, radiotherapy, chemotherapy, amputation, local recurrence factors, and death were statistically evaluated. RESULTS: The results of a multivariate analysis revealed that the AJCC staging is an independent factor for patient prognosis. When patients were divided into two groups, those who had undergone unplanned excision and those who had not, statistical analysis revealed that there was no difference of survival between two groups, but tumor size and AJCC staging had statistical difference. To further explore the influences of unplanned excision, we performed propensity score analysis with 1:1 matching using the nearest neighbor matching method to balance the covariates between the two groups. There was no difference of survival between two groups after propensity score matching. CONCLUSION: Unplanned excision is commonly performed in synovial sarcoma and do not impact the prognosis after extensive resection.

Survival nomogram for patients with bone metastatic renal cell carcinoma: A population-based study

ABSTRACT Purpose: Increased attention has been focused on the survival of renal cell carcinoma (RCC) patients with bone metastasis. This study proposed to establish and evaluate a nomogram for predicting the overall survival (OS) and cancer-specific survival (CSS) of RCC patients with bone metastasis. Materials and Methods: RCC patients with bone metastasis between 2010 and 2015 were captured from the surveillance, epidemiology and end results (SEER) database. Univariate and multivariate cox regressions were performed to assess the effects of clinical variables on OS and CSS. The nomogram based on the Cox hazards regression model was developed. Concordance index (C-index) and calibration curve were performed to evaluate the accuracy of nomogram models, receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were conducted to assess the predict performance. Results: A total of 2.471 eligible patients were enrolled in this study. The patients were assigned to primary (n=1.672) and validation (n=799) cohorts randomly. The 1-, 2-, and 3-year OS and CSS nomogram models were constructed based on age at diagnosis, sex, marital status, pathological grade, T-stage, N-stage, brain/liver/lung metastasis, surgery, radiotherapy and chemotherapy. The c for OS and CSS prediction was 0.730 (95% confidence interval [CI]: 0.719-0.741) and 0.714 (95%CI:0.702-0.726). The calibration curves showed significant agreement between nomogram models and actual observations. ROC and DCA indicated nomograms had better predict performance. Conclusions: The nomograms for predicting prognosis provided an accurate prediction of OS and CSS in RCC patients with bone metastasis, and contributed clinicians to optimize individualized treatment plans.

Survival nomogram for patients with bone metastatic renal cell carcinoma: A population-based study.

PURPOSE: Increased attention has been focused on the survival of renal cell carcinoma (RCC) patients with bone metastasis. This study proposed to establish and evaluate a nomogram for predicting the overall survival (OS) and cancer-specific survival (CSS) of RCC patients with bone metastasis. MATERIALS AND METHODS: RCC patients with bone metastasis between 2010 and 2015 were captured from the surveillance, epidemiology and end results (SEER) database. Univariate and multivariate cox regressions were performed to assess the effects of clinical variables on OS and CSS. The nomogram based on the Cox hazards regression model was developed. Concordance index (C-index) and calibration curve were performed to evaluate the accuracy of nomogram models, receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were conducted to assess the predict performance. RESULTS: A total of 2.471 eligible patients were enrolled in this study. The patients were assigned to primary (n=1.672) and validation (n=799) cohorts randomly. The 1-, 2-, and 3-year OS and CSS nomogram models were constructed based on age at diagnosis, sex, marital status, pathological grade, T-stage, N-stage, brain/liver/lung metastasis, surgery, radiotherapy and chemotherapy. The c for OS and CSS prediction was 0.730 (95% confidence interval [CI]: 0.719-0.741) and 0.714 (95%CI:0.702-0.726). The calibration curves showed significant agreement between nomogram models and actual observations. ROC and DCA indicated nomograms had better predict performance. CONCLUSIONS: The nomograms for predicting prognosis provided an accurate prediction of OS and CSS in RCC patients with bone metastasis, and contributed clinicians to optimize individualized treatment plans.