Visualizing a marker's degrees of necessity and of sufficiency in the predictiveness curve.

IF 3.9 3区医学 Q1 HEALTH CARE SCIENCES & SERVICES

BMC Medical Research Methodology Pub Date : 2025-04-23 DOI:10.1186/s12874-025-02544-y

Andreas Gleiss

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引用次数: 0

Abstract

Background: The degrees to which a factor is necessary or sufficient for an event have been proposed as generalizations of attributable risk based on simple functions of unconditional and conditional event probabilities. Predictiveness curves show the risk for an event, as derived by a model with one or more predictors, depending on risk percentiles that represent the predictors' distribution in the underlying population.

Methods: Connections between the degrees of necessity and of sufficiency and explained variation on the one hand and the predictiveness curve on the other hand are mathematically proved and exemplified using data of in-hospital death of Covid- 19 patients.

Results: We show that the degrees of necessity and of sufficiency can be represented as proportions of areas easily identifiable in the plot of the predictiveness curve. In addition, we show that the proportion of explained variation, a common measure of predictiveness and relative importance of prognostic factors, is also closely connected to these areas.

Conclusion: Our investigations demonstrate that the predictiveness curve extended by these new interpretations of areas provides a comprehensive evaluation of markers or sets of markers for prediction.

Trial registration: Austrian Coronavirus Adaptive Clinical Trial (ACOVACT); ClinicalTrials.gov, identifier NCT04351724.

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在预测曲线中可视化标记的必要性和充分性程度。

背景：某一因素对某一事件的必要或充分程度已被提出作为基于无条件和条件事件概率的简单函数的归因风险的概括。预测曲线显示事件的风险，由一个或多个预测因子的模型导出，取决于代表预测因子在潜在人群中的分布的风险百分位数。方法：利用新冠肺炎住院死亡病例数据，用数学方法证明必要性、充分性和可解释变异与预测曲线之间的关系，并举例说明。结果：我们发现，必要性和充分性的程度可以表示为预测曲线中易于识别的区域的比例。此外，我们表明，解释变异的比例，预测性和预后因素的相对重要性的共同措施，也与这些领域密切相关。结论：我们的研究表明，这些新的区域解释延伸的预测曲线提供了对预测标记或标记集的综合评价。试验注册：奥地利冠状病毒适应性临床试验（ACOVACT）；ClinicalTrials.gov，标识号NCT04351724。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMC Medical Research Methodology 医学-卫生保健

CiteScore

6.50

自引率

2.50%

发文量

298

审稿时长

3-8 weeks

期刊介绍： BMC Medical Research Methodology is an open access journal publishing original peer-reviewed research articles in methodological approaches to healthcare research. Articles on the methodology of epidemiological research, clinical trials and meta-analysis/systematic review are particularly encouraged, as are empirical studies of the associations between choice of methodology and study outcomes. BMC Medical Research Methodology does not aim to publish articles describing scientific methods or techniques: these should be directed to the BMC journal covering the relevant biomedical subject area.