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三叉神经 V3 分支手术后复发风险的列线图模型。

Nomogram Model for Predicting the Risk of Recurrence after Surgery of the V3 Branch of the Trigeminal Nerve.

机构信息

The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China; The Department of Anesthesiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.

The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China; The Department of Anesthesiology and Pain Research Center, the Affiliated Hospital of Jiaxing University, Jiaxing, China.

出版信息

Pain Physician. 2023 Sep;26(5):E583-E590.

PMID:37774196
Abstract

BACKGROUND

Factors influencing recurrence after V3 trigeminal nerve surgery remain unknown.

OBJECTIVES

To analyze the risk factors affecting recurrence after trigeminal nerve branch V3 surgery, construct a nomogram prediction model, and verify the predictive efficacy of the model.

STUDY DESIGN

A retrospective study.

SETTING

This study was performed at the Affiliated Hospital of Jiaxing University, China.

METHODS

Patients with mandibular nerve pain of the V3 branch of the trigeminal nerve treated with percutaneous puncture foramen ovale trigeminal mandibular nerve radiofrequency or trigeminal semilunar nerve microballoon compression at the Pain Department of the Affiliated Hospital of Jiaxing College, between January 2016 and April 2021, were enrolled and randomly divided into the training group (n = 108) and the test group (n = 47) according to the ratio of 7:3. The feasibility of the nomogram prediction model was further explored using multifactor logistic regression analysis based on the screening of independent predictors by the least absolute shrinkage and selection operator (LASSO) regression analysis using recurrence in one year after surgery as the outcome variable, and was assessed by the validation group. Finally, the discriminatory power, accuracy, and clinical utility of the prediction model were assessed using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA), respectively.

RESULTS

Among the 155 patients with trigeminal V3 pain, 128 had no recurrence and 27 had recurrence one year after surgery. LASSO regression combined with multifactorial logistic regression analysis showed that age, procedure, and duration were factors influencing recurrence one year after surgery (P < 0.05). A nomogram prediction model was developed using the above variables. The AUC of the nomogram prediction model was 0.749 (95% CI [0.618, 0.879]) in the training group and 0.793 (95% CI [0.584, 0.980]) in the test group for postoperative recurrence of V3. The DCA showed that the net benefit of using the nomogram prediction model to predict the risk of postoperative recurrence of the V3 branch of the trigeminal nerve was higher when patients had a threshold probability of 0 to 0.486.

LIMITATIONS

This was a single-center study.

CONCLUSIONS

This study successfully developed and validated a highly accurate nomogram prediction model (with age, procedure, and duration as predictive variables), which can improve the early identification and screening of patients at high risk of recurrence after trigeminal nerve V3 branch surgery.

KEY WORDS

Trigeminal neuralgia, mandibular nerve, risk factors, prediction model.

摘要

背景

影响三叉神经 V3 术后复发的因素尚不清楚。

目的

分析影响三叉神经分支 V3 手术后复发的危险因素,构建列线图预测模型,并验证模型的预测效能。

研究设计

回顾性研究。

设置

本研究在嘉兴学院附属医院进行。

方法

将 2016 年 1 月至 2021 年 4 月期间在嘉兴学院附属医院疼痛科接受经皮卵圆孔穿刺三叉神经下颌支射频或三叉半月神经微球囊压迫治疗的下颌神经 V3 支疼痛患者纳入研究,并按照 7:3 的比例随机分为训练组(n=108)和测试组(n=47)。基于手术后 1 年的复发情况作为因变量,采用最小绝对值收缩和选择算子(LASSO)回归分析筛选独立预测因子,采用多因素逻辑回归分析构建列线图预测模型。然后使用验证组进一步探讨列线图预测模型的可行性。最后,通过受试者工作特征曲线(ROC)下面积(AUC)、校准曲线和决策曲线分析(DCA)分别评估预测模型的区分度、准确性和临床实用性。

结果

在 155 例三叉神经 V3 疼痛患者中,128 例患者术后 1 年无复发,27 例患者复发。LASSO 回归结合多因素逻辑回归分析显示,年龄、手术方式和病程是影响术后 1 年复发的因素(P<0.05)。使用上述变量构建了列线图预测模型。该模型在训练组中的 AUC 为 0.749(95%CI[0.618,0.879]),在测试组中的 AUC 为 0.793(95%CI[0.584,0.980]),用于预测三叉神经 V3 术后复发的风险。DCA 显示,当患者的阈值概率在 0 到 0.486 之间时,使用列线图预测模型预测三叉神经 V3 分支术后复发风险的净收益更高。

局限性

这是一项单中心研究。

结论

本研究成功开发并验证了一种高度准确的列线图预测模型(以年龄、手术方式和病程为预测变量),该模型可提高三叉神经 V3 分支手术后复发高风险患者的早期识别和筛查能力。

关键词

三叉神经痛;下颌神经;危险因素;预测模型。

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