Guo Aiyuan, Gu Jie, Yang Jiayi
Department of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Department of Geriatric Urology, Xiangya International Medical Center, Xiangya Hospital, Central South University, Changsha, China.
Front Surg. 2022 Nov 4;9:959573. doi: 10.3389/fsurg.2022.959573. eCollection 2022.
This study aims to systematically evaluate predictive factors for lung metastasis (LM) in patients with testicular cancer (TC) and to investigate cancer-specific survival (CSS) and overall survival (OS) of LM in TC patients based on a large population-cohort.
A total of 10,414 patients diagnosed with TC during 2010-2015 were adopted from the Surveillance, Epidemiology, and End Results (SEER). After propensity score matching (PSM), 493 patients with LM were included for subsequent analysis. Univariate and multivariate logistic regression analyses were employed to identify risk factors, a nomogram was developed, and the receiver operating characteristic (ROC) curve was utilized to confirm the validation of the nomogram. Prognostic factors for OS and CSS among TC patients with LM were estimated Cox proportional hazards models.
Postmatching indicated that 11 parameters were successfully balanced between both groups ( > 0.05). After PSM, TC patients with LM presented an undesirable prognosis in both CSS and OS than those without LM ( < 0.001). The logistic regression model showed that tumor size; T stage; N stage; liver, brain, and bone metastases; and histology were positively associated with LM ( < 0.05). A nomogram was developed to predict diagnostic possibilities based on the independent risk variables, and the ROC curve verified the predictive capacity of the logistic regression model [area under the curve (AUC) = 0.910].
The selected variates in the nomogram can be predictive criteria for TC patients with LM. Brain metastasis, liver metastasis, and larger tumor size were prognostic factors for CCS and OS among TC patients with LM.
本研究旨在系统评估睾丸癌（TC）患者肺转移（LM）的预测因素，并基于大规模人群队列研究调查TC患者LM的癌症特异性生存（CSS）和总生存（OS）情况。
从监测、流行病学和最终结果（SEER）数据库中纳入了2010年至2015年期间诊断为TC的10414例患者。经过倾向评分匹配（PSM）后，纳入493例发生LM的患者进行后续分析。采用单因素和多因素逻辑回归分析确定危险因素，绘制列线图，并利用受试者工作特征（ROC）曲线验证列线图的有效性。采用Cox比例风险模型估计TC合并LM患者的OS和CSS的预后因素。
匹配后表明两组间11个参数成功达到平衡（P>0.05）。PSM后，发生LM的TC患者的CSS和OS均较未发生LM的患者差（P<0.001）。逻辑回归模型显示，肿瘤大小、T分期、N分期、肝转移、脑转移和骨转移以及组织学与LM呈正相关（P<0.05）。基于独立风险变量绘制了列线图以预测诊断可能性，ROC曲线验证了逻辑回归模型的预测能力[曲线下面积（AUC）=0.910]。
列线图中选定的变量可作为TC合并LM患者的预测标准。脑转移、肝转移和较大的肿瘤大小是TC合并LM患者CSS和OS的预后因素。
