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一项针对接受辅助放疗的宫颈癌患者的、涉及营养-炎症指标的生存列线图。

A survival nomogram involving nutritional-inflammatory indicators for cervical cancer patients receiving adjuvant radiotherapy.

作者信息

Wang Shanshan, Zhao Mengli, Gao Zhongrong, Yang Xiaojing, Wang Yudong, Hua Keqin, Fu Jie

机构信息

Department of Radiation Oncology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Department of Gynecologic Oncology the International Peace Maternity and Child Health Hospital School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China.

出版信息

J Cancer. 2024 Sep 9;15(17):5773-5785. doi: 10.7150/jca.100564. eCollection 2024.

Abstract

The combined impact of nutritional and inflammatory status on survival of cervical cancer patients remained unclear. This study aimed to construct a survival nomogram involving both nutritional and inflammatory indicators and evaluate their potential correlation. This retrospective study included 325 cervical cancer patients who received adjuvant radiotherapy between September 2010 and September 2020. Baseline nutritional indicators such as body mass index (BMI), controlling nutritional status (CONUT) and serum albumin were assessed. Inflammatory indicators of platelet/lymphocyte ratio (PLR), neutrophil/lymphocyte ratio (NLR), systemic immune inflammation index (SII) and system inflammation response index (SIRI) were evaluated respectively. The LASSO regression and Cox regression models were applied for variable selection and nomogram building. The predictive accuracy and superiority of prognostic model were assessed by area under curve (AUC), C-index, decision curve analysis (DCA), integrated discrimination improvement (IDI) and net reclassification improvement (NRI). Patients with high inflammatory indicators (PLR, NLR and SII) and poor nutritional status (CONUT scores > 2) suffered poorer prognosis compared to these with well nutritional status and lower inflammation levels. Our study unveiled a positive correlation between malnutrition and hyperinflammation. Even after accounting for baseline inflammatory level, malnutrition remained a significant risk factor for patients. Notably, the inflammatory level and nutritional status were further modulated by the clinical features of patients. Patients with poorer nutritional status exhibited higher levels of PLR, NLR, SII and SIRI, particularly for those in advanced clinical stages and with non-squamous cell carcinoma. In addition, our study found elevated levels of circulating basophil and serum carbohydrate antigen 125 (CA125) were associated with the poor prognosis. The prognostic nomogram which incorporated the nutritional-inflammatory indicators of PLR and CONUT showed a favorable performance with the AUC value of 0.76 at 5-year survival prediction. The DCA, IDI and NRI consistently demonstrated the favorable superiority of the model. Moreover, the nomogram-based risk stratification system could effectively classify patients into three mortality risks subgroups. Poorer nutritional and high inflammatory status collectively contributed to the poorer prognosis. The prognostic nomogram which incorporated nutritional-inflammatory indicators significantly improved the prediction of long-term outcomes of cervical cancer patients undergoing adjuvant radiotherapy.

摘要

营养状况和炎症状态对宫颈癌患者生存的综合影响仍不明确。本研究旨在构建一个包含营养和炎症指标的生存列线图,并评估它们之间的潜在相关性。这项回顾性研究纳入了2010年9月至2020年9月期间接受辅助放疗的325例宫颈癌患者。评估了基线营养指标,如体重指数(BMI)、控制营养状况(CONUT)和血清白蛋白。分别评估了血小板/淋巴细胞比率(PLR)、中性粒细胞/淋巴细胞比率(NLR)、全身免疫炎症指数(SII)和系统炎症反应指数(SIRI)等炎症指标。应用LASSO回归和Cox回归模型进行变量选择和列线图构建。通过曲线下面积(AUC)、C指数、决策曲线分析(DCA)、综合判别改善(IDI)和净重新分类改善(NRI)评估预后模型的预测准确性和优越性。与营养状况良好且炎症水平较低的患者相比,炎症指标高(PLR、NLR和SII)且营养状况差(CONUT评分>2)的患者预后较差。我们的研究揭示了营养不良与炎症反应过度之间存在正相关。即使考虑了基线炎症水平,营养不良仍然是患者的一个重要危险因素。值得注意的是,炎症水平和营养状况会受到患者临床特征的进一步调节。营养状况较差的患者表现出较高水平的PLR、NLR、SII和SIRI,尤其是那些处于临床晚期和非鳞状细胞癌的患者。此外,我们的研究发现循环嗜碱性粒细胞水平升高和血清糖类抗原125(CA125)与预后不良有关。纳入PLR和CONUT营养炎症指标的预后列线图在5年生存预测时表现良好,AUC值为0.76。DCA、IDI和NRI一致证明了该模型的良好优越性。此外,基于列线图的风险分层系统可以有效地将患者分为三个死亡风险亚组。较差的营养状况和高炎症状态共同导致了较差的预后。纳入营养炎症指标的预后列线图显著改善了接受辅助放疗的宫颈癌患者长期预后的预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6cbe/11414624/125a198169af/jcav15p5773g001.jpg

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