Suppr超能文献

基于术前血液学和临床参数的临床预后模型可预测世界卫生组织原发性II级脑膜瘤的进展。

A Clinical Prognostic Model Based on Preoperative Hematological and Clinical Parameters Predicts the Progression of Primary WHO Grade II Meningioma.

作者信息

Gao Peng, Kong Tengxiao, Zhu Xuqiang, Zhen Yingwei, Li Hongjiang, Chen Di, Yuan Shanpeng, Zhang Dongtao, Jiao Henan, Li Xueyuan, Yan Dongming

机构信息

Department of Neurosurgery, The First Affiliated Hospital of ZhengZhou University, Henan, China.

Department of Neurosurgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

出版信息

Front Oncol. 2021 Oct 11;11:748586. doi: 10.3389/fonc.2021.748586. eCollection 2021.

Abstract

PURPOSE

The purpose was to explore the correlation between hematological parameters and the progression of WHO grade II meningioma, and establish a clinical prognostic model based on hematological parameters and clinical prognostic factors to predict the progression-free survival (PFS) of patients.

METHODS

A total of 274 patients with WHO grade II meningiomas were included. Patients were randomly divided into a training cohort (192, 70%) and a test cohort (82, 30%). In the training cohort, the least absolute shrinkage and selection operator Cox regression analysis were used to screen for hematological parameters with prognostic value, and the hematological risk model (HRM) was constructed based on these parameters; univariate and multivariate Cox regression analyses were utilized to screen for clinical prognostic factors, and a clinical prognostic model was constructed based on clinical prognostic factors and HRM. The prognostic stability and accuracy of the HRM and clinical prognostic model were verified in the test cohort. Subgroup analysis was performed according to the patients' different clinical characteristics.

RESULTS

Preoperative neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, albumin-to-globulin ratio, D-dimer, fibrinogen, and lactate dehydrogenase were associated with the PFS of patients. The areas under curve of the HRM were 0.773 (95% confidence interval [CI] 0.707-0.839) and 0.745 (95% CI 0.637-0.852) in the training cohort and test cohort, respectively. The progression risk was higher in the high-risk group than that in the low-risk group categorized by the optimal cutoff value (2.05) of hematological risk scores. The HRM, age, tumor location, tumor size, peritumoral edema, extent of resection, Ki-67 index, and postoperative radiotherapy were the prognostic factors for the progression of meningiomas. The corrected C-index of the clinical prognosis model was 0.79 in the training cohort. Clinical decision analysis showed that the clinical prognostic model could be used to obtain favorable clinical benefits. In the subgroup analysis, the HRM displayed excellent prognostic stability and general applicability in different subgroups.

CONCLUSIONS

Preoperative hematological parameters are associated with the postoperative progression of WHO grade II meningiomas. The clinical prognosis model constructed based on hematological parameters and clinical prognostic factors has favorable predictive accuracy and clinical benefits.

摘要

目的

探讨血液学参数与世界卫生组织(WHO)Ⅱ级脑膜瘤进展之间的相关性,并基于血液学参数和临床预后因素建立临床预后模型,以预测患者的无进展生存期(PFS)。

方法

共纳入274例WHOⅡ级脑膜瘤患者。患者被随机分为训练队列(192例,70%)和测试队列(82例,30%)。在训练队列中,采用最小绝对收缩和选择算子Cox回归分析筛选具有预后价值的血液学参数,并基于这些参数构建血液学风险模型(HRM);采用单因素和多因素Cox回归分析筛选临床预后因素,并基于临床预后因素和HRM构建临床预后模型。在测试队列中验证HRM和临床预后模型的预后稳定性和准确性。根据患者不同的临床特征进行亚组分析。

结果

术前中性粒细胞与淋巴细胞比值、淋巴细胞与单核细胞比值、血小板与淋巴细胞比值、白蛋白与球蛋白比值、D-二聚体、纤维蛋白原和乳酸脱氢酶与患者的PFS相关。HRM在训练队列和测试队列中的曲线下面积分别为0.773(95%置信区间[CI]0.707-0.839)和0.745(95%CI0.637-0.852)。根据血液学风险评分的最佳临界值(2.05)分类,高危组的进展风险高于低危组。HRM、年龄、肿瘤位置、肿瘤大小、瘤周水肿、切除范围、Ki-67指数和术后放疗是脑膜瘤进展的预后因素。临床预后模型在训练队列中的校正C指数为0.79。临床决策分析表明,临床预后模型可用于获得良好的临床效益。在亚组分析中,HRM在不同亚组中显示出优异的预后稳定性和普遍适用性。

结论

术前血液学参数与WHOⅡ级脑膜瘤术后进展相关。基于血液学参数和临床预后因素构建的临床预后模型具有良好的预测准确性和临床效益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/673b/8542933/fd92d63c1612/fonc-11-748586-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验