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利用临床和病理变量预测肺癌手术后的生存:LNC-PATH 评分的建立和验证。

Predicting survival following surgical resection of lung cancer using clinical and pathological variables: The development and validation of the LNC-PATH score.

机构信息

Manchester Thoracic Oncology Centre, North West Lung Centre, Manchester University NHS Foundation Trust, Wythenshawe Hospital, Southmoor Road, Manchester, UK; Institute of Infection, Immunity and Respiratory Medicine, University of Manchester, Oxford Road, Manchester, UK.

Department of Medical Statistics, Manchester University NHS Foundation Trust, Wythenshawe Hospital, Southmoor Road, Manchester, UK.

出版信息

Lung Cancer. 2018 Nov;125:29-34. doi: 10.1016/j.lungcan.2018.08.026. Epub 2018 Aug 31.

Abstract

INTRODUCTION

The aim of this study was to develop and validate a simple prognostic scoring system using readily available clinical and pathological variables that could stratify patients according to the risk of death following lung cancer resection. We hypothesized that by using additional pathological variables not accounted for by pathological stage alone coupled with markers of overall fitness a new prognostic tool could be developed.

METHODS

Multivariable logistic regression analysis of pathological and other clinical variables from patients undergoing surgical resection of non-small cell lung cancer (NSCLC) were used to determine factors independently associated with 2-year overall survival and so derive the scoring system. The model was then validated in an external multi-centre dataset.

RESULTS

Using multivariable logistic regression on a large dataset (n = 1,421) the 'LNC-PATH' (Lymphovascular invasion, N-stage, adjuvant Chemotherapy, Performance status, Age, T-stage, Histology) prognostic score was devised and then validated using an external dataset (n = 402). This can be used to risk stratify patients into low, moderate and high-risk groups with a statistically significant difference between the three groups in their survival distributions. 83.8% of patients in the low-risk group survived two years after surgery compared to 55.6% in the moderate-risk group and 26.2% in the high-risk group. The score was shown to perform moderately well with an Area Under the Receiver Operating Characteristic curve (AUROC) value of 0.76 (95% CI: 0.73-0.79) and 0.70 (95% CI: 0.64-0.76) in the derivation and validation cohorts respectively.

DISCUSSION

The LNC-PATH score predicts 2-year overall survival after surgery for NSCLC. This may allow the development of risk stratified follow-up protocols in survivorship clinics which could be the subject of future prospective studies.

摘要

简介

本研究旨在开发和验证一种简单的预后评分系统,该系统使用易于获得的临床和病理变量,根据肺癌切除术后死亡风险对患者进行分层。我们假设,通过使用单独的病理分期未涵盖的其他病理变量以及整体健康状况的标志物,可以开发出新的预后工具。

方法

对接受非小细胞肺癌(NSCLC)手术切除的患者的病理和其他临床变量进行多变量逻辑回归分析,以确定与 2 年总生存率独立相关的因素,并由此得出评分系统。然后在外部多中心数据集验证该模型。

结果

使用多变量逻辑回归对大型数据集(n=1421)进行分析,得出了“LNC-PATH”(淋巴管侵犯、N 期、辅助化疗、体能状态、年龄、T 期、组织学)预后评分,然后使用外部数据集(n=402)进行验证。这可用于将患者风险分层为低危、中危和高危组,三组患者的生存分布存在统计学显著差异。低危组 83.8%的患者在手术后两年内存活,中危组为 55.6%,高危组为 26.2%。该评分的表现相当不错,在推导队列中的 AUC 值为 0.76(95%CI:0.73-0.79),在验证队列中的 AUC 值为 0.70(95%CI:0.64-0.76)。

讨论

LNC-PATH 评分可预测 NSCLC 手术后 2 年的总生存率。这可能允许在生存诊所中制定风险分层随访方案,这可能是未来前瞻性研究的主题。

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