Development and validation of a nomogram predicting the risk of recurrent lumbar disk herniation within 6 months after percutaneous endoscopic lumbar discectomy

建立和验证预测经皮内镜腰椎间盘切除术后6个月内腰椎间盘突出复发风险的列线图

阅读:1

Abstract

OBJECTIVE: To develop and validate a nomogram useful in predicting recurrent lumbar disk herniation (rLDH) within 6 months after percutaneous endoscopic lumbar discectomy (PELD). METHODS: Information on patients' lumbar disk herniation (LDH) between January 2018 and May 2019 in addition to 26 other features was collected from the authors' hospital. The least absolute shrinkage and selection operator (LASSO) method was used to select the most important risk factors. Moreover, a nomogram was used to build a prediction model using the risk factors selected from LASSO regression. The concordance index (C-index), the receiver operating characteristic (ROC) curve, and calibration curve were used to assess the performance of the model. Finally, clinical usefulness of the nomogram was analyzed using the decision curve and bootstrapping used for internal validation. RESULTS: Totally, 352 LDH patients were included into this study. Thirty-two patients had recurrence within 6 months while 320 showed no recurrence. Four potential factors, the course of disease, Pfirrmann grade, Modic change, and migration grade, were selected according to the LASSO regression model. Additionally, the C-index of the prediction nomogram was 0.813 (95% CI, 0.726-0.900) and the area under receiver operating characteristic curve (AUC) value was 0.798 while the interval bootstrapping validation C-index was 0.743. Hence, the nomogram might be a good predictive model. CONCLUSION: Each variable, the course of disease, Pfirrmann grade, Modic change, and migration grade in the nomogram had a quantitatively corresponding risk score, which can be used in predicting the overall recurrence rate of rLDH within 6 months.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。