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Multimodal Risk-Adapted Treatment in Surgical Patients With Synovial Sarcoma: A Preoperative Nomogram-Guided Adjuvant Treatment Strategy.

ABSTRACT: Background: Synovial sarcoma is characterized by heterogeneous clinical manifestations, making it difficult to evaluate individual patients' prognoses and design personal treatment schemes. We established an effective preoperative nomogram to predict cancer-specific survival (CSS) and present a risk-adapted adjuvant treatment strategy in surgical patients with synovial sarcoma. Methods: This retrospective study included patients from the Surveillance, Epidemiology, and End Results (SEER) database who were diagnosed with synovial sarcoma between 1996 and 2015. The patients were randomly divided into training and validation groups. The predictors were selected using univariate and multivariate Cox hazards models. The nomogram performance was verified for its discriminatory ability and calibration. We further stratified the patients into different risk groups according to the nomogram scores and compared the efficacy of chemotherapy, radiotherapy, and combination of radiotherapy and chemotherapy. Results: There were 915 patients enrolled in our study, with 874 patients either alive or dead due to synovial sarcoma. We established a nomogram to predict 5-year CSS based on independent factors, including sex, age, grade, tumor size, location, and extent (all p < 0.05). Our model showed a consistently good discriminatory ability and calibration for predicting 5-year CSS in both the training (c-index = 0.78, 95% CI 0.75-0.81) and validation (c-index = 0.73, 95% CI 0.68-0.78). Based on their nomogram scores, we divided patients into 5 groups. Compared to patients without adjuvant treatment, nomogram I patients with adjuvant treatment had no improvements in 5-year CSS (100.0% vs. 100.0%), nomogram II patients had higher 5-year CSS with radiotherapy or chemotherapy (92.9% vs. 72.2%, p = 0.015), nomogram III patients had higher 5-year CSS with combination of chemotherapy and radiotherapy (70.1% vs. 47.2%, p = 0.004), nomogram IV patients had higher 5-year CSS with radiotherapy (41.3% vs. 15.6%, p = 0.015), and nomogram V patients had no improvements in 5-year CSS rates with adjuvant treatment (28.9% vs. 16.9%, p = 0.18). Conclusion: The nomogram showed a satisfactory discriminatory ability and calibration for predicting 5-year CSS in synovial sarcoma patients. Based on this nomogram, we stratified synovial sarcoma patients according to risk levels, which enabled us to provide a useful grouping scheme that can inform multimodal risk-adapted treatment in synovial sarcoma.

SUBMITTER: Zeng Z

PROVIDER: S-EPMC7780852 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Multimodal Risk-Adapted Treatment in Surgical Patients With Synovial Sarcoma: A Preoperative Nomogram-Guided Adjuvant Treatment Strategy.

Zeng Ziliang Z Yao Hao H Lv Dongming D Jin Qinglin Q Bian Yiying Y Zou Yutong Y Tu Jian J Wang Bo B Wen Lili L Xie Xianbiao X

Frontiers in surgery 20201221

<b>Background:</b> Synovial sarcoma is characterized by heterogeneous clinical manifestations, making it difficult to evaluate individual patients' prognoses and design personal treatment schemes. We established an effective preoperative nomogram to predict cancer-specific survival (CSS) and present a risk-adapted adjuvant treatment strategy in surgical patients with synovial sarcoma. <b>Methods:</b> This retrospective study included patients from the Surveillance, Epidemiology, and End Results ...[more]

PMID: 33409290

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Project description:This study aimed to evaluate the feasibility of applying a clinical multimodal radiomics nomogram based on ultrasonography (US) and multiparametric magnetic resonance imaging (MRI) for the prediction of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) preoperatively. We performed retrospective evaluations of 133 patients with pathologically confirmed PTC, who were assigned to the training cohort and validation cohort (7 : 3), and extracted radiomics features from the preoperative US, T2-weighted (T2WI),diffusion-weighted (DWI), and contrast-enhanced T1-weighted (CE-T1WI) images. Optimal subsets were selected using minimum redundancy, maximum relevance, and recursive feature elimination in the support vector machine (SVM). For LNM prediction, the radiomics model was constructed by SVM, and Multi-Omics Graph cOnvolutional NETworks (MOGONET) was used for the effective classification of multiradiomics data. Multivariable logistic regression incorporating multiradiomics signatures and clinical risk factors was used to generate a nomogram, whose performance and clinical utility were assessed. Results showed that the nine most predictive features were separately selected from US, T2WI, DWI, and CE-T1WI images, and 18 features were selected in the combined model. The combined radiomics model showed better performance than models based on US, T2WI, DWI, and CE-T1WI. In a comparison of the combined radiomics and MOGONET model, receiver operating curve analysis showed that the area under the curve (AUC) value (95% CI) was 0.84 (0.76-0.93) and 0.84 (0.71-0.96) for the MOGONET model in the training and validation cohorts, respectively. The corresponding values (95% CI) for the combined radiomics model were 0.82 (0.74-0.90) and 0.77 (0.61-0.94), respectively. The MOGONET model had better performance and better prediction specificity compared with the combined radiomics model. The nomogram including the MOGONET signature showed a better predictive value (AUC: 0.81 vs. 0.88) in the training and validation (AUC: 0.74vs. 0.87) cohorts, as compared with the clinical model. Calibration curves showed good agreement in both cohorts. The applicability of the clinical multimodal radiomics (CMR) nomogram in clinical settings was validated by decision curve analysis. In patients with PTC, the CMR nomogram could improve the prediction of cervical LNM preoperatively and may be helpful in clinical decision-making.

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Dataset Information

Multimodal Risk-Adapted Treatment in Surgical Patients With Synovial Sarcoma: A Preoperative Nomogram-Guided Adjuvant Treatment Strategy.

Publications

Multimodal Risk-Adapted Treatment in Surgical Patients With Synovial Sarcoma: A Preoperative Nomogram-Guided Adjuvant Treatment Strategy.

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