Construction of an efficacy prediction model for active ulcerative colitis

WANG Xuehui; CHEN Yunru; ZHENG Youyou; WANG Xinyue; SUN Huiyi; WANG Jianyun; LI Junxiang; SONG Zhenmei; LIU Fang; BU Zhijun; LIU Jianping; LIU Zhaolan

doi:10.3969/j.issn.1006-2157.2023.04.012

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Construction of an efficacy prediction model for active ulcerative colitis

Chinese Medical Informatics | 更新时间：2023-05-09

- Construction of an efficacy prediction model for active ulcerative colitis
- Journal of Beijing University of Traditional Chinese Medicine Vol. 46, Issue 4, Pages: 528-535(2023)
- 作者机构：
  
  1.北京中医药大学循证医学中心　北京　100029
  2.北京中医药大学第三附属医院
  3.北京中医药大学东直门医院
  4.北京中医药大学东方医院
  5.中日友好医院
- 作者简介：
  
  Prof. LIU Zhaolan, Ph.D., Doctoral Supervisor.Centre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, No.11, Beisanhuan Donglu Road, Chaoyang District, Beijing 100029. E-mail: lzl1019@163.com
- 基金信息：
  
  National Natural Science Foundation of China(81904052);National Key Research and Development Program of China(2018YFC1705401－1)
- DOI：10.3969/j.issn.1006-2157.2023.04.012
  CLC： R211
- Received：15 November 2022，
  
  Online First：09 March 2023，
  
  Published：30 April 2023
- 稿件说明：
移动端阅览
WANG Xuehui, CHEN Yunru, ZHENG Youyou, et al. Construction of an efficacy prediction model for active ulcerative colitis[J]. Journal of Beijing University of Traditional Chinese Medicine, 2023, 46(4): 528-535.
DOI：

WANG Xuehui, CHEN Yunru, ZHENG Youyou, et al. Construction of an efficacy prediction model for active ulcerative colitis[J]. Journal of Beijing University of Traditional Chinese Medicine, 2023, 46(4): 528-535. DOI： 10.3969/j.issn.1006-2157.2023.04.012.

摘要

目的

基于五味苦参肠溶胶囊治疗溃疡性结肠炎的患者数据，探讨中医药疗效预测模型构建的可行性及其方法要点。

方法

选择五味苦参肠溶胶囊Ⅲ期临床试验的试验组(五味苦参肠溶胶囊)作为研究对象，经过8周试验后，数据资料完整的患者共274例。统计分析软件使用R语言4.1.0，纳入全部待筛选变量构建多因素Logistic回归模型，筛选

0.05的变量纳入最终模型；绘制列线图；采用Bootstrap法重复抽样1 000次对模型进行内部验证，计算C指数并绘制校准图，评价模型的区分度及校准度；并进行Hosmer-Lemeshow拟合优度检验和外部验证，对模型进行总体评价。

结果

筛选出溃疡性结肠炎完全缓解的促进因素为：患者(15～65岁)接受治疗时年龄小(

＝0.96

95%

CI:

0.94～0.99

＝0.002 )、非慢性持续型(与初发型比，

＝0.36

95%

：0.18～0.74

＝0.005)、镜下无出血(

＝0.42，95%

：0.22～0.82，

＝0.011)、红细胞沉降率降低(

＝0.97，95%

：0.95～0.99，

＝0.006)。使用上述变量构建最终模型，并绘制列线图，校正后的C指数为0.735(95%

：0.672～0.797)，模型区分度尚可；绘制校准图可见校准曲线与标准线大致贴合，模型校准度尚可。对模型进行Hosmer-Lemeshow拟合优度检验(

＝7.07，

＝0.53)，模型拟合良好。对模型进行外部检证，C指数及置信区间为0.54(95%

：0.44～0.65)。

结论

利用随机对照试验的数据进行预测模型构建具有一定可行性；根据本研究的数据所建立的预测模型，经过大样本验证后，有可能为临床监测和针对性治疗提供有效的测评工具。

Abstract

Objective

Based on the data of patients with ulcerative colitis treated with Five-Flavor Sophora Flavescens Radix Enteric-coated Capsules

we discuss the feasibility and methodology of constructing a prediction model of the efficacy of traditional Chinese medicine.

Methods

Based on phase Ⅲ clinical trial data of Five-Flavor Sophora Flavescens Radix Enteric-coated Capsules

a total of 274 patients with active ulcerative colitis with complete population data after 8 weeks of treatment in the experimental group (Five-Flavor Sophora Flavescens Radix Enteric-coated Capsules) were selected. R 4.1.0 was used for statistical analysis. First

all the variables to be screened were included to construct a multivariate Logistic regression model. Then

variables with

0.05 were screened for inclusion in the final model. The nomogram was plotted. The bootstrap method was used to resample 1 000 times for internal validation of the model

the C index was calculated

and the calibration chart was plotted to evaluate the discrimination and calibration of the model. The model was evaluated by the Hosmer-Lemeshow goodness of fit test and external validation. The overall evaluation of the model was performed by the above methods.

Results

The prognostic factors for complete remission of ulcerative colitis were younger age (15-65 years old) (

=0.96

95%

: 0.94-0.99

=0.002)

non-chronic persistent (compared with primary type) (

=0.36

95%

: 0.18-0.74

=0.005)

no microscopic bleeding (

=0.42

95%

: 0.22-0.82

=0.011)

and decreased erythrocyte sedimentation rate (

=0.97

95%

: 0.95-0.99

=0.006). We used the above variables to construct the final model and drew a nomogram. The corrected C index was 0.735 (95%

: 0.672-0.797)

indicating that the model’s discrimination was acceptable. The calibration diagram shows that the calibration curve and the standard line roughly fit

indicating the calibration model is acceptable. The Hosmer-Lemeshow goodness of fit test (χ

=7.07

=0.53) showed that the model was well fitted. We conducted an external test of the prediction model. The C index and confidence interval were 0.54(95%

: 0.44-0.65).

Conclusion

It is feasible to construct a prediction model by using data from randomized controlled trials. A prediction model based on the study data may provide an effective evaluation tool for clinical monitoring and targeted therapy after large sample validation.

关键词

Keywords

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