Risk factors and prediction model for elevated ki-67 index in pituitary neuroendocrine tumors

Yuling ZHANG; Rufei SHEN; Pian HONG; Guiliang PENG; Ling ZHOU; Min LONG; Hongting ZHENG

doi:10.16016/j.2097-0927.202206106

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Risk factors and prediction model for elevated ki-67 index in pituitary neuroendocrine tumors

Clinical Medicine | 更新时间：2026-01-09

- Risk factors and prediction model for elevated ki-67 index in pituitary neuroendocrine tumors
- Journal of Army Medical University Vol. 45, Issue 2, Pages: 173-179(2023)
- 作者机构：
  
  400037 重庆，陆军军医大学(第三军医大学)第二附属医院内分泌科
- 作者简介：
- 基金信息：
  
  the Natural Science Foundation for Outstanding Young Scholars of Chongqing(cstc2020jcyj-jqX0017)
- DOI：10.16016/j.2097-0927.202206106
  CLC： R181.23;R730.7;R736.4
- Received：17 June 2022，
  
  Revised：2022-08-02，
  
  Published：30 January 2023
- 稿件说明：
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Yuling ZHANG, Rufei SHEN, Pian HONG, et al. Risk factors and prediction model for elevated ki-67 index in pituitary neuroendocrine tumors[J]. Journal of Army Medical University, 2023, 45(2): 173-179.
DOI：

Yuling ZHANG, Rufei SHEN, Pian HONG, et al. Risk factors and prediction model for elevated ki-67 index in pituitary neuroendocrine tumors[J]. Journal of Army Medical University, 2023, 45(2): 173-179. DOI： 10.16016/j.2097-0927.202206106.

摘要

目的

根据初次确诊垂体神经内分泌肿瘤(pituitary neuroendocrine tumors，PitNETs)患者ki-67指数升高的危险因素的验证结果，构建术前预测瘤体组织ki-67指数的预测模型。

方法

采用病例-对照研究设计方案，收集2015年1月至2019年12月在陆军军医大学第二附属医院初次确诊的449名PitNETs患者术前的临床资料及瘤体组织标本病理结果。以7∶3的比例随机分为训练集(

=314)和验证集(

=135)。以ki-67表达水平≥3%为标准分为低水平组和高水平组，分析

比较两组患者的临床资料。在训练集中进行多因素LASSO回归和二元Logistic回归识别ki-67指数的独立危险因素并构建列线图，应用受试者操作曲线下面积(area under the subject curve，AUC)、校准曲线(采用1 000次的Bootstrap法获得)和决策曲线(decision curve analysis，DCA)来评估该模型的预测效能；在验证集中进行外部验证。

结果

经LASSO回归和二元Logistic回归筛选后结果显示：年龄(

=0.97，95%

: 0.95~0.99)、肿瘤最大直径(

=1.56，95%

: 1.21~2.03)及游离甲状腺素(free thyroxine，FT4；

=0.93，95%

: 0.87~0.99)为ki-67指数升高的独立危险因素，并根据上述3个变量构建列线图模型；该模型在训练集和验证集中的AUC分别为0.692(95%

: 0.629 4~0.755 1)和0.691(95%

: 0.591 3~0.790 1)，校准曲线均显示预测值与实测值拟合性良好，临床决策曲线表明在0.1~0.35阈值范围内有净收益率提示该模型有一定临床意义。

结论

初诊

itNETs患者的年龄、肿瘤最大直径及FT4为ki-67指数升高的独立危险因素；构建列线图模型在术前预测出ki-67指数表达水平的区分度和校准度较高，对手术方案选择和术后管理有一定帮助。

Abstract

Objective

To investigate the risk factors of elevated ki-67 index in patients with newly diagnosed pituitary neuroendocrine tumors (PitNETs) so as to construct a nomogram model for preoperative prediction of ki-67 index.

Methods

Preoperative clinical data and pathological results of tumor tissue samples of 449 patients with PitNETs who were initially diagnosed at our hospital from January 2015 to December 2019 were collected and retrospectively analyzed. All the patients were randomly enrolled at a ratio of 7:3 to either the training cohort (

=314) or the validation cohort (

=135). According to the level of ki-67 index

they were divided into low level (ki-67

3%) and high level (ki-67 ≥3%) groups

and the clinical data were compared between them. Multivariate LASSO regression and binary logistic regression analyses were adopted in the training cohort to identify independent risk factors of ki-67 index

and a nomogram prediction model was accordingly established. The predictive performance of the model was evalua

ted using receiver operating characteristic-area under the curve (ROC-AUC)

calibration curve (obtained by Bootstrap method in 1000 internal validation)

and decision curve analysis (DCA)

followed by external validation in the validation cohort.

Results

Regression analyses showed that age (

=0.97

95%

: 0.95~0.99)

maximum tumor diameter (

=1.56

95%

: 1.21~2.03)

and free thyroxine (FT4;

=0.93

95%

: 0.87~0.99) were the independent risk factors for the increase of ki-67 index. Then based on the above 3 variables

a nomogram model was constructed

whose ROC-AUC values in the training and validation cohorts were 0.692 (95%

: 0.629 4~0.755 1) and 0.691 (95%

: 0.591 3~0.790 1)

respectively. The calibration curves indicated that the predicted value was in good conformity with the measured value

and the DCA showed a net return within a threshold range of 0.1~0.35

suggesting certain clinical significance of the model.

Conclusion

Age

maximum tumor diameter and FT4 are the independent risk factors for elevated ki-67 index in newly diagnosed PitNETs patients. Our constructed nomogram model possesses high differentiation and good calibration in predicting ki-67 index preoperatively

which is helpful for surgical protocol selection and postoperative management.

关键词

Keywords

references

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