基于术后短期PSA变化的前列腺癌根治术后生化复发预测模型及其验证

王子威; 连碧珺; 李晶; 高旭; 许传亮

doi:10.13201/j.issn.1001-1420.2021.06.006

基于术后短期PSA变化的前列腺癌根治术后生化复发预测模型及其验证

- 1. 长海医院泌尿外科(上海, 200433);
- 2. 903医院泌尿外科;
- 3. 海军军医大学转化医学中心

详细信息

通讯作者: 许传亮,E-mail:chuanliang_xu@126.com

中图分类号: R737.25

收稿日期: 2021-03-22

Prediction model for biochemical recurrence after radical prostatectomy based on short-term postoperative PSA changes

- 1. Department of Urology, Changhai Hospital, Shanghai, 200433, China;
- 2. Department of Urology, 903 Hospital;
- 3. Center for Translation Medicine, Naval Medical University

More Information

Corresponding author: XU Chuanliang, E-mail: chuanliang_xu@126.com

Received Date: 22 March 2021

摘要

摘要: 目的:探讨根治术后4周PSA水平对前列腺癌患者术后生化复发的预测能力,并与经典的Kattan列线图进行比较。方法:纳入PC-follow数据库中2004年10月—2018年8月期间1485例行前列腺癌根治术的患者,经筛选后313例纳入训练集用于建立模型(训练组),90例纳入验证集用于验证模型(验证组)。利用COX比例风险回归模型确定与生化复发相关的独立风险因素并纳入最终预测模型,绘制列线图便于临床应用。利用R软件计算模型的一致性指数(C-index),绘制模型预测值与实际值的校准曲线对模型进行评价。内部验证采用bootstrap方法重抽样,外部验证基于验证组数据。最后通过计算综合判别改善指数(integrated discrimination improvement, IDI)比较新模型和传统Kattan列线图的预测效能。结果:基于术后4周PSA水平和Gleason评分的新模型能较好地评估前列腺癌根治术后的生化复发风险(训练组C-index=0.819,验证组C-index=0.751),且预测值同实际发生情况具有较好的一致性。相较于传统Kattan列线图,新模型的IDI在训练组和验证组中分别为10.68%(P<0.001)和12.38%(P=0.016)。结论:利用患者术后4周PSA水平和术后Gleason评分能够很好地预测患者生化复发概率,且较经典Kattan列线图更加方便准确,能够为个体化随访策略的制定提供依据。
- 前列腺癌 /
- PSA /
- 生化复发 /
- 预后模型
Abstract: Objective: To establish a biochemical recurrence prediction model based on the PSA level 4 weeks after radical resection of patients with prostate cancer and compare it with the classic Kattan nomogram.Methods: A total of 1485 patients who underwent radical prostatectomy in the PC-follow database from October 2004 to August 2018 were screened. After screening, 313 patients were included for model discovery, and 90 patients were used for model validation. The COX regression proportional hazard model was used to determine the independent predictors related to biochemical recurrence, and finally, the PSA level 4 weeks after radical resection and Gleason scores were used to establish the novel model. R software was used to draw a nomogram, calculate the consistency index(C-index), and draw a calibration curve of the novel model. The internal validation was performed using 1000 times bootstrap, and the external validation is performed with the validation group data. Integrated discrimination improvement(IDI) was calculated to evaluate the prediction performance of the nomogram of the novel model and classical Kattan nomogram.Results: The C-index of the novel model was 0.819 and 0.751 in the training and validation set respectively. The calibration curve of the novel model showed good agreement. External verification further confirmed the applicability of the novel model. We thus proved that the novel model based on the PSA level 4 weeks after the operation could predict 1-year and 3-year postoperative biochemical recurrence. Comparing the novel nomogram with the Kattan nomogram by calculating IDI, it is found that the prediction performance of the novel model is 10.68% and 12.38% higher than that of the Kattan nomogram in the training and validation set respectively.Conclusion: The newly established nomogram model only uses the PSA level 4 weeks after radical resection and Gleason scores to predict postoperative biochemical recurrence and is more accurate than the classic Kattan nomogram, enhancing convenient clinical application. Our research served as a reference for developing personalized follow-up strategies.
- prostate cancer /
- PSA /
- biochemical recurrence /
- prognosis model

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