相关实验视频
Updated: Jul 6, 2026

09:11
Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
Published on: April 9, 2019
21.5K
格里森模式3的数量并不能预测 2-4年级组的前列腺癌风险
Andrew J Vickers1, Melissa Assel1, Matthew R Cooperberg2
1Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
European urology
|January 26, 2024
概括
量化格里森模式4的数量,而不是其比例,更好地预测局部前列腺癌的不良病理. 这提高了治疗决策的等级组分配.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 在瘤学瘤学.
- 病理学 病理学 病理学
背景情况:
- 精确的前列腺癌分级对于治疗决策至关重要.
- 基于癌细胞生长模式的格里森分级是一个关键的预后因素.
- 当前的分级系统可能无法最佳地捕捉Gleason模式4的预测值.
研究的目的:
- 要确定总格里森模式3或活检上的格里森模式4的比例是否预测不良病理.
- 评估量化格里森模式4数量与比例对改善前列腺癌分级的实用性.
主要方法:
- 前列腺活检数据的回顾性分析.
- 格里森模式3数量和格里森模式4比例作为预测指标的比较.
- 与前列腺切除术后不良病理结果的相关性.
主要成果:
- 格里森模式4的数量,而不是其比例,是不良病理的重要预测因素.
- 与格里森模式4的数量相比,格里森模式3的数量显示出较少的预测价值.
- 量化格里森模式4的数量提高了分级组分配的准确性.
结论:
- 活检上的格里森模式4的数量是不良病理的更强有力的预测因素,而不是它的比例.
- 修改前列腺癌分级以纳入格里森模式4的数量可以提高局部疾病的临床决策.
相关概念视频
Probability Laws
Overview
Cancer Prevention
Several factors can increase the risk of cancer in an individual. About 50% of cancer cases can be prevented by adopting a healthy lifestyle, regular exercise, eating healthy, and following a modest cancer prevention diet. Epidemiological studies have consistently shown that populations with vegetable and fruit-rich diets have reduced the incidence of cancer. On the other hand, populations who have a diet rich in animal fat, red meat, junk food, or high calories are predisposed to cancer.
Some...
Some...
Barrett Esophagus-I: Introduction
Barrett's esophagus is a medical condition where the esophageal mucosa is significantly damaged by stomach acid or other digestive fluids, often due to long-term exposure associated with gastroesophageal reflux disease (GERD). In GERD, a weakened or abnormally relaxed lower esophageal sphincter allows stomach acid to flow persistently into the esophagus.
This constant acid exposure transforms the esophagus's pink mucosal lining (stratified squamous epithelium) into a type of lining more similar...
This constant acid exposure transforms the esophagus's pink mucosal lining (stratified squamous epithelium) into a type of lining more similar...
Comparing the Survival Analysis of Two or More Groups
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
Cancer Survival Analysis
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

