PDF(Pubmed)
Abstract：
UNASSIGNED: Primary tumor resection is associated with survival benefits in patients with metastatic lung adenocarcinoma (mLUAD). However, there are no established methods to determine which individuals would benefit from surgery. Therefore, we developed a model to predict the patients who are likely to benefit from surgery in terms of survival.
UNASSIGNED: Data on patients with mLUAD were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Depending on whether surgery was performed on the primary tumor, patients were categorized into two groups: cancer-directed surgery (CDS) and no-cancer-directed surgery (No-CDS). Propensity Score Matching (PSM) was utilized to address bias between the CDS and No-CDS groups. The prognostic impact of CDS was assessed using Kaplan-Meier analysis and Cox proportional hazard models. Subsequently, we constructed a nomogram to predict the potential for surgical benefits based on multivariable logistic regression analysis using preoperative factors.
UNASSIGNED: A total of 89,039 eligible patients were identified, including 6.4% (5705) who underwent surgery. Following PSM, the CDS group demonstrated a significantly longer median overall survival (mOS) compared with the No-CDS group (23 [21-25] vs. 7 [7-8] months; P < 0.001). The nomogram showed robust performance in both the training and validation sets (area under the curve [AUC]: 0.698 and 0.717, respectively), and the calibration curves exhibited high consistency. The nomogram proved clinically valuable according to decision curve analysis (DCA). According to this nomogram, surgical patients were categorized into two groups: no-benefit candidates and benefit candidates groups. Compared with the no-benefit candidate group, the benefit candidate group was associated with longer survival (mOS: 25 vs. 6 months, P < 0.001). Furthermore, no difference in survival was observed between the no-benefit candidates and the no-surgery groups (mOS: 6 vs. 7 months, P = 0.9).
UNASSIGNED: A practical nomogram was developed to identify optimal CDS candidates among patients with mLUAD.
UNASSIGNED: Data on patients with mLUAD were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Depending on whether surgery was performed on the primary tumor, patients were categorized into two groups: cancer-directed surgery (CDS) and no-cancer-directed surgery (No-CDS). Propensity Score Matching (PSM) was utilized to address bias between the CDS and No-CDS groups. The prognostic impact of CDS was assessed using Kaplan-Meier analysis and Cox proportional hazard models. Subsequently, we constructed a nomogram to predict the potential for surgical benefits based on multivariable logistic regression analysis using preoperative factors.
UNASSIGNED: A total of 89,039 eligible patients were identified, including 6.4% (5705) who underwent surgery. Following PSM, the CDS group demonstrated a significantly longer median overall survival (mOS) compared with the No-CDS group (23 [21-25] vs. 7 [7-8] months; P < 0.001). The nomogram showed robust performance in both the training and validation sets (area under the curve [AUC]: 0.698 and 0.717, respectively), and the calibration curves exhibited high consistency. The nomogram proved clinically valuable according to decision curve analysis (DCA). According to this nomogram, surgical patients were categorized into two groups: no-benefit candidates and benefit candidates groups. Compared with the no-benefit candidate group, the benefit candidate group was associated with longer survival (mOS: 25 vs. 6 months, P < 0.001). Furthermore, no difference in survival was observed between the no-benefit candidates and the no-surgery groups (mOS: 6 vs. 7 months, P = 0.9).
UNASSIGNED: A practical nomogram was developed to identify optimal CDS candidates among patients with mLUAD.
摘要：
■原发性肿瘤切除与转移性肺腺癌（mLUAD）患者的生存获益相关。然而,目前还没有确定的方法来确定哪些个体将从手术中受益.因此,我们建立了一个模型来预测可能从手术中获益的患者的生存率.
■从监测中提取mLUAD患者的数据，流行病学,和结束结果(SEER)数据库。根据是否对原发肿瘤进行手术，患者分为两组:癌症定向手术(CDS)和非癌症定向手术(No-CDS).利用倾向评分匹配(PSM)来解决CDS组和无CDS组之间的偏差。使用Kaplan-Meier分析和Cox比例风险模型评估CDS的预后影响。随后，我们使用术前因素,根据多变量logistic回归分析,构建了一个列线图来预测手术获益的可能性.
■总共确认了89,039名合格患者，其中6.4%(5705例)接受手术。在PSM之后,与无CDS组相比，CDS组的中位总生存期（mOS）明显更长（23[21-25]vs.7[7-8]个月；P<0.001）。列线图在训练集和验证集中均显示出稳健的性能（曲线下面积[AUC]：分别为0.698和0.717），校准曲线表现出较高的一致性。根据决策曲线分析（DCA），列线图证明具有临床价值。根据这个列线图,手术患者分为两组:无获益候选人和获益候选人组.与无福利候选人组相比，受益候选组与更长的生存期相关(mOS：25vs.6个月,P<0.001)。此外，无益处候选人和无手术组之间的生存率没有差异(mOS：6vs.7个月,P=0.9)。
■开发了实用的列线图以确定mLUAD患者中的最佳CDS候选项。
■从监测中提取mLUAD患者的数据，流行病学,和结束结果(SEER)数据库。根据是否对原发肿瘤进行手术，患者分为两组:癌症定向手术(CDS)和非癌症定向手术(No-CDS).利用倾向评分匹配(PSM)来解决CDS组和无CDS组之间的偏差。使用Kaplan-Meier分析和Cox比例风险模型评估CDS的预后影响。随后，我们使用术前因素,根据多变量logistic回归分析,构建了一个列线图来预测手术获益的可能性.
■总共确认了89,039名合格患者，其中6.4%(5705例)接受手术。在PSM之后,与无CDS组相比，CDS组的中位总生存期（mOS）明显更长（23[21-25]vs.7[7-8]个月；P<0.001）。列线图在训练集和验证集中均显示出稳健的性能（曲线下面积[AUC]：分别为0.698和0.717），校准曲线表现出较高的一致性。根据决策曲线分析（DCA），列线图证明具有临床价值。根据这个列线图,手术患者分为两组:无获益候选人和获益候选人组.与无福利候选人组相比，受益候选组与更长的生存期相关(mOS：25vs.6个月,P<0.001)。此外，无益处候选人和无手术组之间的生存率没有差异(mOS：6vs.7个月,P=0.9)。
■开发了实用的列线图以确定mLUAD患者中的最佳CDS候选项。
