Development and validation of the systemic nutrition/inflammation index for improving perioperative management of non-small cell lung cancer.

IF 8.3 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL BMC Medicine Pub Date : 2025-02-24 DOI:10.1186/s12916-025-03925-2
Peiyu Wang, Shaodong Wang, Qi Huang, Xiankai Chen, Yongkui Yu, Ruixiang Zhang, Mantang Qiu, Yin Li, Xue Pan, Xiao Li, Xiangnan Li
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Abstract

Background: Systemic nutrition and inflammation status is recognized for its influence on cancer survival, yet its role in perioperative outcomes remains poorly defined. This study aimed to refine the assessment of systemic nutrition and inflammation status in non-small cell lung cancer (NSCLC) patients and to elucidate its impact on perioperative outcomes.

Methods: All patients underwent video-assisted thoracoscopic lobectomy, with their nutrition and inflammation status assessed based on preoperative blood tests. The development cohort, comprising 1497 NSCLC patients from two centers, evaluated the predictive value of systemic nutrition/inflammation indicators for perioperative endpoints and formulated the systemic nutrition-inflammation index (SNII). The tertiles of SNII were used to classify the nutrition/inflammation risk as high (< 15.6), moderate (15.6-23.1), and low (> 23.1). An external validation cohort of 505 NSCLC patients was utilized to confirm the effectiveness of SNII in guiding perioperative management.

Results: In the development cohort, the SNII tool, calculated as the product of total cholesterol and total lymphocytes divided by total monocytes, demonstrated a stronger correlation with perioperative outcomes compared to 11 existing nutrition/inflammation indicators. A low SNII score, indicative of high nutrition/inflammation risk, was independently predictive of increased complication incidence and severity, as well as prolonged chest tube duration and hospital stay. These findings were corroborated in the validation cohort. Upon combining the development and validation cohorts, the superiority of the SNII in predicting perioperative outcomes was further confirmed over the existing nutrition/inflammation indicators. Additionally, comprehensive subgroup analyses revealed the moderately variable efficacy of SNII across different patient populations.

Conclusions: This study developed and validated the SNII as a tool for identifying systemic nutrition and inflammation risk, which can enhance perioperative managements in NSCLC patients. Patients identified with high risk may benefit from prehabilitation and intensive treatments, highlighting the need for further research.

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开发和验证全身营养/炎症指数,改善非小细胞肺癌围手术期管理。
背景:全身性营养和炎症状态被认为对癌症生存有影响,但其在围手术期结局中的作用仍不明确。本研究旨在完善非小细胞肺癌(NSCLC)患者全身营养和炎症状态的评估,并阐明其对围手术期预后的影响。方法:所有患者接受电视胸腔镜肺叶切除术,术前血液检查评估营养和炎症状况。该发展队列包括来自两个中心的1497名NSCLC患者,评估了全身营养/炎症指标对围手术期终点的预测价值,并制定了全身营养-炎症指数(SNII)。SNII的分位数被用来将营养/炎症风险划分为高(23.1)。通过505例NSCLC患者的外部验证队列来证实SNII在指导围手术期管理中的有效性。结果:在发展队列中,SNII工具(计算为总胆固醇和总淋巴细胞除以总单核细胞的乘积)与现有的11项营养/炎症指标相比,与围手术期预后的相关性更强。低SNII评分,表明营养/炎症风险高,独立预测并发症发生率和严重程度增加,胸管持续时间和住院时间延长。这些发现在验证队列中得到了证实。将开发队列和验证队列相结合,进一步证实了SNII在预测围手术期预后方面优于现有的营养/炎症指标。此外,综合亚组分析显示,SNII在不同患者群体中的疗效存在中度差异。结论:本研究开发并验证了SNII作为识别全身营养和炎症风险的工具,可以增强NSCLC患者的围手术期管理。确定为高风险的患者可能受益于康复和强化治疗,这突出了进一步研究的必要性。
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来源期刊
BMC Medicine
BMC Medicine 医学-医学:内科
CiteScore
13.10
自引率
1.10%
发文量
435
审稿时长
4-8 weeks
期刊介绍: BMC Medicine is an open access, transparent peer-reviewed general medical journal. It is the flagship journal of the BMC series and publishes outstanding and influential research in various areas including clinical practice, translational medicine, medical and health advances, public health, global health, policy, and general topics of interest to the biomedical and sociomedical professional communities. In addition to research articles, the journal also publishes stimulating debates, reviews, unique forum articles, and concise tutorials. All articles published in BMC Medicine are included in various databases such as Biological Abstracts, BIOSIS, CAS, Citebase, Current contents, DOAJ, Embase, MEDLINE, PubMed, Science Citation Index Expanded, OAIster, SCImago, Scopus, SOCOLAR, and Zetoc.
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