Ruoyun Yang, Min Wei, Xin Yu, Wei Su, Xiaoying Zhou, Han Chen, Guoxin Zhang
{"title":"浅表食管鳞状细胞癌患者长期生存风险预测模型","authors":"Ruoyun Yang, Min Wei, Xin Yu, Wei Su, Xiaoying Zhou, Han Chen, Guoxin Zhang","doi":"10.7150/jca.99042","DOIUrl":null,"url":null,"abstract":"<p><p><b>Objectives</b>: Given the data regarding the long-term prognosis of superficial esophageal squamous cell carcinoma (SESCC) is still lacking, we aimed to identify reliable prognostic factors and establish a high-precision prognosis model for patients with SESCC. <b>Methods</b>: A retrospective cohort study was conducted including patients with SESCC at a high-volume tertiary medical center. The primary outcome was disease-specific survival (DSS) at the end of follow-up (minimum of 29 months). Independent prognostic factors including innovative hematological and clinicopathological parameters were identified using comprehensive and novel statistical methods including best subset regression (BSR), the univariate and multivariate Cox analysis, lasso regression, and a dynamic nomogram model was established. <b>Results</b>: A total of 1,171 patients were finally enrolled. The median follow-up time is 83 months (range 29-149 months). Ten independent prognostic risk factors for a poor DSS were identified as follows: male (<i>P=</i>0.127), higher Charlson Comorbidity Index (CCI) (<i>P=</i>0.006), poorly differentiated tumor (<i>P</i><0.001), lymphovascular invasion (LVI) (<i>P</i><0.001), lymph node metastasis (LNM) (<i>P</i><0.001), additional treatment (<i>P</i>=0.007), neutrophils over 32.2x10<sup>9</sup>/L (<i>P</i>=0.003), red blood cell (RBC) lower than 4.45x10<sup>12</sup>/L (<i>P</i><0.001), hemoglobin (Hb) lower than or equal to 98 g/L (<i>P</i>=0.023), alpha-fetoprotein (AFP) higher than 3.24 ng/ml (<i>P</i>=0.034). Subsequently, an online dynamic nomogram was established <i>(https://yryouzu-tools.shinyapps.io/DynNomapp/)</i>. This prediction model showed favourable discrimination ability (area under the curve (AUC) was 0.913 (95% CI: 88.0 - 94.6) and a well-fitted calibration curve. <b>Conclusions</b>: We successfully established a long-term prognosis model for SESCC, which can be applied to effectively predict survival risks for patients, thus strengthening follow-up strategies.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540495/pdf/","citationCount":"0","resultStr":"{\"title\":\"A Long-term Survival Risk Prediction Model for Patients with Superficial Esophageal Squamous Cell Carcinoma.\",\"authors\":\"Ruoyun Yang, Min Wei, Xin Yu, Wei Su, Xiaoying Zhou, Han Chen, Guoxin Zhang\",\"doi\":\"10.7150/jca.99042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Objectives</b>: Given the data regarding the long-term prognosis of superficial esophageal squamous cell carcinoma (SESCC) is still lacking, we aimed to identify reliable prognostic factors and establish a high-precision prognosis model for patients with SESCC. <b>Methods</b>: A retrospective cohort study was conducted including patients with SESCC at a high-volume tertiary medical center. The primary outcome was disease-specific survival (DSS) at the end of follow-up (minimum of 29 months). Independent prognostic factors including innovative hematological and clinicopathological parameters were identified using comprehensive and novel statistical methods including best subset regression (BSR), the univariate and multivariate Cox analysis, lasso regression, and a dynamic nomogram model was established. <b>Results</b>: A total of 1,171 patients were finally enrolled. The median follow-up time is 83 months (range 29-149 months). Ten independent prognostic risk factors for a poor DSS were identified as follows: male (<i>P=</i>0.127), higher Charlson Comorbidity Index (CCI) (<i>P=</i>0.006), poorly differentiated tumor (<i>P</i><0.001), lymphovascular invasion (LVI) (<i>P</i><0.001), lymph node metastasis (LNM) (<i>P</i><0.001), additional treatment (<i>P</i>=0.007), neutrophils over 32.2x10<sup>9</sup>/L (<i>P</i>=0.003), red blood cell (RBC) lower than 4.45x10<sup>12</sup>/L (<i>P</i><0.001), hemoglobin (Hb) lower than or equal to 98 g/L (<i>P</i>=0.023), alpha-fetoprotein (AFP) higher than 3.24 ng/ml (<i>P</i>=0.034). Subsequently, an online dynamic nomogram was established <i>(https://yryouzu-tools.shinyapps.io/DynNomapp/)</i>. This prediction model showed favourable discrimination ability (area under the curve (AUC) was 0.913 (95% CI: 88.0 - 94.6) and a well-fitted calibration curve. <b>Conclusions</b>: We successfully established a long-term prognosis model for SESCC, which can be applied to effectively predict survival risks for patients, thus strengthening follow-up strategies.</p>\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540495/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.7150/jca.99042\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.7150/jca.99042","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
A Long-term Survival Risk Prediction Model for Patients with Superficial Esophageal Squamous Cell Carcinoma.
Objectives: Given the data regarding the long-term prognosis of superficial esophageal squamous cell carcinoma (SESCC) is still lacking, we aimed to identify reliable prognostic factors and establish a high-precision prognosis model for patients with SESCC. Methods: A retrospective cohort study was conducted including patients with SESCC at a high-volume tertiary medical center. The primary outcome was disease-specific survival (DSS) at the end of follow-up (minimum of 29 months). Independent prognostic factors including innovative hematological and clinicopathological parameters were identified using comprehensive and novel statistical methods including best subset regression (BSR), the univariate and multivariate Cox analysis, lasso regression, and a dynamic nomogram model was established. Results: A total of 1,171 patients were finally enrolled. The median follow-up time is 83 months (range 29-149 months). Ten independent prognostic risk factors for a poor DSS were identified as follows: male (P=0.127), higher Charlson Comorbidity Index (CCI) (P=0.006), poorly differentiated tumor (P<0.001), lymphovascular invasion (LVI) (P<0.001), lymph node metastasis (LNM) (P<0.001), additional treatment (P=0.007), neutrophils over 32.2x109/L (P=0.003), red blood cell (RBC) lower than 4.45x1012/L (P<0.001), hemoglobin (Hb) lower than or equal to 98 g/L (P=0.023), alpha-fetoprotein (AFP) higher than 3.24 ng/ml (P=0.034). Subsequently, an online dynamic nomogram was established (https://yryouzu-tools.shinyapps.io/DynNomapp/). This prediction model showed favourable discrimination ability (area under the curve (AUC) was 0.913 (95% CI: 88.0 - 94.6) and a well-fitted calibration curve. Conclusions: We successfully established a long-term prognosis model for SESCC, which can be applied to effectively predict survival risks for patients, thus strengthening follow-up strategies.