诊断概率函数和修改的趋势测试:在病例控制研究中识别,评估和验证非传统生物标志物
Hanna Lindner1, Phyllis A Gimotty1, Warren B Bilker1
1Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Statistics in medicine
|September 22, 2023
概括
本研究引入了一种使用离散诊断概率 (DLR) 函数识别和评估传统和非传统生物标志物的新方法,改善了生物标志物的发现和研究中的验证.
科学领域:
- 生物统计学 生物统计学
- 生物标志物发现发现
- 医疗信息学 医疗信息学
背景情况:
- 传统的生物标志物分析依赖于生物标志物值与疾病风险之间的单调关系的假设.
- 非传统的生物标志物,其中低值和高值都与结果相关,不太适合ROC曲线分析.
- 评估生物标记物的现有方法往往无法捕捉信息标记物的全部范围.
研究的目的:
- 提出一种新的统计框架,用于评估更广泛的信息生物标志物,包括非传统的生物标志物.
- 加强早期发现研究中的生物标志物的识别,评估和验证.
- 开发可以结合共变量的方法,以改善临床决策.
主要方法:
- 使用离散诊断概率 (DLR) 函数,通过多项逻辑回归 (MLR) 估计.
- 实施了概率比测试,用于识别有信息的传统和非传统生物标志物.
- 提出了修改后的Cochran-Armitage测试,用于对信息生物标志物的分类趋势.
主要成果:
- 拟议的DLR功能有效地评估了一个比传统的ROC-based方法更广泛的生物标志物类别.
- 概率比测试和修改的趋势测试显示了适用于生物标志物识别和分类的统计性质.
- 将共变量纳入MLR模型,就产生了对共变量调整的DLR函数,用于集成决策.
结论:
- 开发的统计方法使传统和非传统生物标志物的全面识别,评估和验证成为可能.
- 与共变量调整的DLR函数提供了一个强大的工具,用于在临床决策中整合各种信息.
- 这种方法成功地应用于高度血清性卵巢癌中的基因表达数据.
相关概念视频
The Mantel-Cox Log-Rank Test
418
The Mantel-Cox log-rank test is a widely used statistical method for comparing the survival distributions of two groups. It tests whether a statistically significant difference exists in survival times between the groups without assuming a specific distribution for the survival data, making it a non-parametric test. This flexibility makes the log-rank test particularly valuable in medical research and other fields where the timing of an event, such as death or disease recurrence, is of...
418
Sign Test for Matched Pairs
155
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
To conduct the sign test, we first calculate the differences in...
155
Hazard Ratio
152
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
For example, in a clinical trial...
152
Comparing the Survival Analysis of Two or More Groups
218
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...
218
Statistical Methods for Analyzing Epidemiological Data
400
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
400
Receiver Operating Characteristic Plot
280
A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
280


