PDF(Pubmed)
Abstract：
UNASSIGNED: Prognosis is crucial for personalized treatment and surveillance suggestion of the resected non-small-cell lung cancer (NSCLC) patients in stage I-III. Although the tumor-node-metastasis (TNM) staging system is a powerful predictor, it is not perfect enough to accurately distinguish all the patients, especially within the same TNM stage. In this study, we developed an intelligent prognosis evaluation system (IPES) using pre-therapy CT images to assist the traditional TNM staging system for more accurate prognosis prediction of resected NSCLC patients.
UNASSIGNED: 20,333 CT images of 6371 patients from June 12, 2009 to March 24, 2022 in West China Hospital of Sichuan University, Mianzhu People\'s Hospital, Peking University People\'s Hospital, Chengdu Shangjin Nanfu Hospital and Guangan Peoples\' Hospital were included in this retrospective study. We developed the IPES based on self-supervised pre-training and multi-task learning, which aimed to predict an overall survival (OS) risk for each patient. We further evaluated the prognostic accuracy of the IPES and its ability to stratify NSCLC patients with the same TNM stage and with the same EGFR genotype.
UNASSIGNED: The IPES was able to predict OS risk for stage I-III resected NSCLC patients in the training set (C-index 0.806; 95% CI: 0.744-0.846), internal validation set (0.783; 95% CI: 0.744-0.825) and external validation set (0.817; 95% CI: 0.786-0.849). In addition, IPES performed well in early-stage (stage I) and EGFR genotype prediction. Furthermore, by adopting IPES-based survival score (IPES-score), resected NSCLC patients in the same stage or with the same EGFR genotype could be divided into low- and high-risk subgroups with good and poor prognosis, respectively (p < 0.05 for all).
UNASSIGNED: The IPES provided a non-invasive way to obtain prognosis-related information from patients. The identification of IPES for resected NSCLC patients with low and high prognostic risk in the same TNM stage or with the same EGFR genotype suggests that IPES have potential to offer more personalized treatment and surveillance suggestion for NSCLC patients.
UNASSIGNED: This study was funded by the National Natural Science Foundation of China (grant 62272055, 92259303, 92059203), New Cornerstone Science Foundation through the XPLORER PRIZE, Young Elite Scientists Sponsorship Program by CAST (2021QNRC001), Clinical Medicine Plus X - Young Scholars Project, Peking University, the Fundamental Research Funds for the Central Universities (K.C.), Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Chinese Academy of Medical Sciences (2021RU002), BUPT Excellent Ph.D. Students Foundation (CX2022104).
UNASSIGNED: 20,333 CT images of 6371 patients from June 12, 2009 to March 24, 2022 in West China Hospital of Sichuan University, Mianzhu People\'s Hospital, Peking University People\'s Hospital, Chengdu Shangjin Nanfu Hospital and Guangan Peoples\' Hospital were included in this retrospective study. We developed the IPES based on self-supervised pre-training and multi-task learning, which aimed to predict an overall survival (OS) risk for each patient. We further evaluated the prognostic accuracy of the IPES and its ability to stratify NSCLC patients with the same TNM stage and with the same EGFR genotype.
UNASSIGNED: The IPES was able to predict OS risk for stage I-III resected NSCLC patients in the training set (C-index 0.806; 95% CI: 0.744-0.846), internal validation set (0.783; 95% CI: 0.744-0.825) and external validation set (0.817; 95% CI: 0.786-0.849). In addition, IPES performed well in early-stage (stage I) and EGFR genotype prediction. Furthermore, by adopting IPES-based survival score (IPES-score), resected NSCLC patients in the same stage or with the same EGFR genotype could be divided into low- and high-risk subgroups with good and poor prognosis, respectively (p < 0.05 for all).
UNASSIGNED: The IPES provided a non-invasive way to obtain prognosis-related information from patients. The identification of IPES for resected NSCLC patients with low and high prognostic risk in the same TNM stage or with the same EGFR genotype suggests that IPES have potential to offer more personalized treatment and surveillance suggestion for NSCLC patients.
UNASSIGNED: This study was funded by the National Natural Science Foundation of China (grant 62272055, 92259303, 92059203), New Cornerstone Science Foundation through the XPLORER PRIZE, Young Elite Scientists Sponsorship Program by CAST (2021QNRC001), Clinical Medicine Plus X - Young Scholars Project, Peking University, the Fundamental Research Funds for the Central Universities (K.C.), Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Chinese Academy of Medical Sciences (2021RU002), BUPT Excellent Ph.D. Students Foundation (CX2022104).
摘要：
■预后对于I-III期切除的非小细胞肺癌（NSCLC）患者的个性化治疗和监测建议至关重要。尽管肿瘤淋巴结转移（TNM）分期系统是一个强有力的预测指标，它还不够完美，无法准确区分所有患者，特别是在同一TNM阶段。在这项研究中,我们使用治疗前CT图像开发了一种智能预后评估系统(IPES),以辅助传统的TNM分期系统,从而对切除的NSCLC患者进行更准确的预后预测.
■2009年6月12日至2022年3月24日四川大学华西医院6371例患者的20,333CT图像绵竹市人民医院,北京大学人民医院,成都上津南府医院和广安市人民医院纳入本回顾性研究。我们开发了基于自我监督预训练和多任务学习的IPES，旨在预测每位患者的总体生存（OS）风险。我们进一步评估了IPES的预后准确性及其对具有相同TNM分期和相同EGFR基因型的NSCLC患者进行分层的能力。
■IPES能够预测训练集中I-III期切除的NSCLC患者的OS风险（C指数0.806；95％CI：0.744-0.846），内部验证集（0.783；95%CI：0.744-0.825）和外部验证集（0.817；95%CI：0.786-0.849）。此外,IPES在早期（I期）和EGFR基因型预测中表现良好。此外，通过采用基于IPES的生存评分(IPES评分)，相同阶段或具有相同EGFR基因型的切除的NSCLC患者可分为低危亚组和高危亚组,预后良好和不良,分别为(p<0.05)。
■IPES提供了一种非侵入性的方式来从患者那里获得与预后相关的信息。在相同的TNM分期或具有相同的EGFR基因型的低和高预后风险的切除的NSCLC患者中，IPES的鉴定表明IPES有可能为NSCLC患者提供更个性化的治疗和监测建议。
■本研究由国家自然科学基金资助(授予62272055,92259303,92059203),通过XPLORERPRIZE的新基石科学基金会，CAST青年精英科学家赞助计划（2021QNRC001），临床医学加X-青年学者项目，北京大学,中央大学基础研究基金（K.C.），早期非小细胞肺癌智能诊断与治疗研究单位,中国医学科学院(2021RU002),BUPT优秀博士生基金会（CX2022104）。
■2009年6月12日至2022年3月24日四川大学华西医院6371例患者的20,333CT图像绵竹市人民医院,北京大学人民医院,成都上津南府医院和广安市人民医院纳入本回顾性研究。我们开发了基于自我监督预训练和多任务学习的IPES，旨在预测每位患者的总体生存（OS）风险。我们进一步评估了IPES的预后准确性及其对具有相同TNM分期和相同EGFR基因型的NSCLC患者进行分层的能力。
■IPES能够预测训练集中I-III期切除的NSCLC患者的OS风险（C指数0.806；95％CI：0.744-0.846），内部验证集（0.783；95%CI：0.744-0.825）和外部验证集（0.817；95%CI：0.786-0.849）。此外,IPES在早期（I期）和EGFR基因型预测中表现良好。此外，通过采用基于IPES的生存评分(IPES评分)，相同阶段或具有相同EGFR基因型的切除的NSCLC患者可分为低危亚组和高危亚组,预后良好和不良,分别为(p<0.05)。
■IPES提供了一种非侵入性的方式来从患者那里获得与预后相关的信息。在相同的TNM分期或具有相同的EGFR基因型的低和高预后风险的切除的NSCLC患者中，IPES的鉴定表明IPES有可能为NSCLC患者提供更个性化的治疗和监测建议。
■本研究由国家自然科学基金资助(授予62272055,92259303,92059203),通过XPLORERPRIZE的新基石科学基金会，CAST青年精英科学家赞助计划（2021QNRC001），临床医学加X-青年学者项目，北京大学,中央大学基础研究基金（K.C.），早期非小细胞肺癌智能诊断与治疗研究单位,中国医学科学院(2021RU002),BUPT优秀博士生基金会（CX2022104）。
