Construction and Validation of a Diagnostic Prediction Model for Prostate Cancer in Patients With PI-RADS Score 3: a Multicenter, Retrospective Study
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 460
- 试验地点
- 3
- 主要终点
- Multivariate logistic regression analyses and calculate the odds ratios (95% confidence interval ) of the clinical variables for clinically significant prostate cancer
研究概览
简要总结
The goal of this observational study is to construct a predictive model for improving the diagnostic accuracy in patients with PI-RADS score of 3. The main aims of this study are:
- Construct a diagnostic model of patients with PI-RADS of score.
- Internal and external validation of the model.
- Decision curve analysis. The data of participants was collected retrospectively.
详细描述
For patients with a PI-RADS score of 3, the diagnosis of prostate cancer is still use prostate biopsy, but the detection rates of prostate cancer and clinically significant prostate cancer are approximately 30% and 15%. It can be seen that most patients with PI-RADS 3 undergo unnecessary prostate biopsy and bear the risk of complications such as urinary tract infection. This makes most patients with PI-RADS 3 choose to refuse invasive prostate biopsy. Although researchers are committed to exploring biomarkers with high sensitivity and specificity, the application of biomarkers alone often cannot achieve the expected results. At present, the guidelines have recommended the use of diagnostic prediction models to assess patients' prostate cancer risk. Doctors and patients use diagnostic models to assess the risk of prostate cancer before prostate biopsy. For patients with a low probability of cancer, biopsy can be temporarily avoided, which to a certain extent reduces the phenomenon of prostate cancer overdiagnosis. This study plans to work with multiple medical centers to conduct statistical analysis based on existing prostate cancer screening markers combined with patients' clinical data such as prostate volume, prostate-specific antigen density, apparent diffusion coefficient, PI-RADS score and postoperative Gleason score, and then construct a prostate cancer diagnostic model to improve the diagnostic accuracy of prostate cancer for patients with PI-RADS score of 3. This will be of great significance for improving the early diagnosis of patients with PI-RADS 3 and reducing unnecessary prostate puncture biopsies.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- Male
- 接受健康志愿者
- 否
入选标准
- •Patients with clinically suspected prostate cancer (abnormal PSA level or DRE);
- •All patients have undergone mpMRI and have complete imaging data;
- •The PI-RADS score of patients was 3;
- •Prostate biopsy was performed and has clear pathological results.
排除标准
- •The patient's serum tPSA is <4ng/ml or >100ng/ml;
- •Repeated prostate biopsy;
- •The patient's clinical, imaging, or pathological data are incomplete.
结局指标
主要结局
Multivariate logistic regression analyses and calculate the odds ratios (95% confidence interval ) of the clinical variables for clinically significant prostate cancer
时间窗: through study completion, an average of 3 months
The clinically significant prostate cancer was defined as Gleason score ≥ 3+4
次要结局
- Validation by calculating the C-statistics, drawing ROC curves (AUC values) and calibration curves.(through study completion, an average of 3 months)
研究者
XiaoJun
Professor
Anhui Provincial Hospital
