The Prognostic Value of Preoperative Multi-model Diffusion MRI in Predicting Ki-67 Proliferation for Adult-type Diffuse Gliomas
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 200
- 主要终点
- A model for predicting glioma grade and the status of prognosis-related molecular mutations, constructed using multiparametric MRI
研究概览
简要总结
The goal of this observational study is to learn about the diagnostic value of preoperative MRI examination for adult-type diffuse gliomas. The main question it aims to answer is:
- Can preoperative MRI examination noninvasively predict genotype of gliomas?
- Can preoperative MRI examination noninvasively predict the overall survival of gliomas?
- Can preoperative MRI examination noninvasively predict Ki-67 proliferation status?
详细描述
Method for Determining the Required Sample Size
This study is observational and involves no intervention. Therefore, the sample size was estimated using the following formula:
where N is the sample size, Uα is the value of υ corresponding to the test level α, S is the overall standard deviation, and δ is the allowable error.
Since the specific value of δ could not be known in advance, the study referred to the literature and identified three widely accepted methods for estimating δ. Method ①: Conduct a pre-experiment before the study begins, using the inter-group difference as the δ value directly. Method ②: Consult relevant authorities in advance to determine a professionally meaningful δ value. Method ③: In the absence of pre-experiment results and expert opinions, it is permissible to use 0.25 or 0.50 times the standard deviation as δ. According to the allowable error δ reference flowchart by Ni Yanyan and Zhang Jinxin, this study used method ③ to determine δ. Therefore, at α = 0.05, the minimum sample size N can range from 16 to 62 cases. Considering a loss-to-follow-up rate of 15%-20%, the sample size can be expanded to 19-78 cases. Finally, considering that Logistic regression analysis will be used in statistical analysis with 15 quantitative indicators as independent variables, the estimated sample size should be at least 150 cases. Taking into account factors such as economy and time, the sample size for this study is determined to be 150-200 cases.
Research Content
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •First diagnosis of glioma, with no preoperative radiotherapy or chemotherapy.
- •Underwent multiparametric MRI examination in our hospital before surgery.
- •Tumor resection or biopsy was performed within 3 weeks after MRI examination.
- •Pathological examination confirmed glioma.
排除标准
- •Inability to cooperate during MRI examination, resulting in poor image quality that prevents image analysis.
- •Surgery or biopsy specimens were unqualified and could not be analyzed pathologically.
结局指标
主要结局
A model for predicting glioma grade and the status of prognosis-related molecular mutations, constructed using multiparametric MRI
时间窗: Through study completion, an average of 7 years
The prognosis-related molecular mutation status, such as IDH mutation, is classified as dichotomous data. Mutations, deletions, or amplifications are categorized into the positive group and are denoted as 1; the absence of mutation, deletion, or amplification is categorized into the negative group and is denoted as 0.
次要结局
未报告次要终点
研究者
Yingqian Huang
Ms.
First Affiliated Hospital, Sun Yat-Sen University