构建一种用于预测未接受手术的乳头状甲状腺癌患者癌症特异性生存的新工具
Construction of a new tool for predicting cancer-specific survival in papillary thyroid cancer patients who have not received surgery
                    
                        DOI 原文链接
                    
                    
                    
                
                
                        
                        
                            用sci-hub下载
                        
                        
                            
                            
                    
                
                                如无法下载,请从 Sci-Hub 选择可用站点尝试。
                            
                        
                                影响因子:4.6                            
                                                        
                                分区:医学3区 / 内分泌学与代谢3区                            
                                                    
                            发表日期:2024                         
                        
                            作者:
                            Sanjun Chen, Yanmei Tan, Xinping Huang, Yanfei Tan
                        
                                                
                            DOI:
                            10.3389/fendo.2024.1417528
                        
                                            摘要
                        乳头状甲状腺癌的发病率逐渐上升,且年轻化趋势明显。一些患者因身体或经济原因可能无法接受手术治疗,而手术是主要治疗方式。因此,预测未手术乳头状甲状腺癌患者的癌症特异性生存(CSS)具有重要意义。我们从“监测、流行病学与最终结果”数据库中提取患者的人口统计学和临床信息,使用SPSS软件进行Cox回归分析和倾向评分匹配分析,并利用R软件构建和验证列线图模型(nomogram)。X-tile软件用于筛选患者风险分层的最佳临界值。共纳入1319例回顾性研究患者。经过Cox回归分析,年龄、分级、T分期、M分期、放疗和化疗被用于构建列线图模型。C指数、校准曲线和受试者工作特征(ROC)曲线均验证了模型的高预测准确性。决策曲线分析显示,患者可通过此预测模型获益。倾向评分匹配后生存曲线分析表明,放疗对未手术患者的CSS具有积极影响。本研究成功建立了准确预测未手术乳头状甲状腺癌患者CSS的列线图模型,并证明放疗对手术患者仍有改善预后的作用。这些发现有助于临床制定更优的治疗方案。                    
                    
                    Abstract
                        The prevalence of papillary thyroid cancer is gradually increasing and the trend of youthfulness is obvious. Some patients may not be able to undergo surgery, which is the mainstay of treatment, due to physical or financial reasons. Therefore, the prediction of cancer-specific survival (CSS) in patients with non-operated papillary thyroid cancer is necessary.Patients' demographic and clinical information was extracted from the Surveillance, Epidemiology, and End Results database. SPSS software was used to perform Cox regression analyses as well as propensity score matching analyses. R software was used to construct and validate the nomogram. X-tile software was used to select the best cutoff point for patient risk stratification.A total of 1319 patients were included in this retrospective study. After Cox regression analysis, age, grade, T stage, M stage, radiotherapy, and chemotherapy were used to construct the nomogram. C-index, calibration curves, and receiver operating characteristic curves all verified the high predictive accuracy of the nomogram. The decision curve analysis demonstrated that patients could gain clinical benefit from this predictive model. Survival curve analysis after propensity score matching demonstrated the positive effects of radiotherapy on CSS in non-operated patients.Our retrospective study successfully established a nomogram that accurately predicts CSS in patients with non-operated papillary thyroid cancer and demonstrated that radiotherapy for operated patients can still help improve prognosis. These findings can help clinicians make better choices.                    
                