ArticleStatistics in medicine2018
Combining multiple biomarkers linearly to maximize the partial area under the ROC curve.
Article in Statistics in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Transformation Discriminant Analysis for Constructing Optimal Biomarker Combinations.Statistics in medicine · 2026Article
- A Gene Expression Tumor Signature Optimizing Partial Area-Under-the-Curve (pAUC) to Improve Specificity for Indolent Prostate Cancer.The Prostate · 2026Article
- Identification of predictive pretreatment biomarkers for neoadjuvant chemotherapy response in Latino invasive breast cancer patients.Molecular medicine (Cambridge, Mass.) · 2025Article
- Combining multiple biomarkers linearly to minimize the Euclidean distance of the closest point on the receiver operating characteristic surface to the perfection corner in trichotomous settings.Statistical methods in medical research · 2024Article
- Likelihood ratio combination of multiple biomarkers via smoothing spline estimated densities.Statistics in medicine · 2024Article
- Comparison of diagnostic accuracy of models combining the renal biomarkers in predicting renal scarring in pediatric population with vesicoureteral reflux (VUR).Irish journal of medical science · 2023Article
- Conditional concordance-assisted learning under matched case-control design for combining biomarkers for population screening.Statistics in medicine · 2023Article
- Statistical assessment of the prognostic and the predictive value of biomarkers-A biomarker assessment framework with applications to traumatic brain injury biomarker studies.Research methods in medicine & health sciences · 2023Article
- LINEAR BIOMARKER COMBINATION FOR CONSTRAINED CLASSIFICATION.Annals of statistics · 2022Article
- Biomarkers of Alzheimer syndrome and related dementias: A&D author's guide.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2022Article
- Combining biomarkers by maximizing the true positive rate for a fixed false positive rate.Biometrical journal. Biometrische Zeitschrift · 2021Article
- Chromatin accessibility of circulating CD8Nature communications · 2021Article
- Adding Rigor to Biomarker Evaluations-EDRN Experience.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Predicting Islet Cell Autoimmunity and Type 1 Diabetes: An 8-Year TEDDY Study Progress Report.Diabetes care · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
It is now common in clinical practice to make clinical decisions based on combinations of multiple biomarkers. In this paper, we propose new approaches for combining multiple biomarkers linearly to maximize the partial area under the receiver operating characteristic curve (pAUC). The parametric and nonparametric methods that have been developed for this purpose have limitations. When the biomarker values for populations with and without a given disease follow a multivariate normal distribution, it is easy to implement our proposed parametric approach, which adopts an alternative analytic expression of the pAUC. When normality assumptions are violated, a kernel-based approach is presented, which handles multiple biomarkers simultaneously. We evaluated the proposed as well as existing methods through simulations and discovered that when the covariance matrices for the disease and nondisease samples are disproportional, traditional methods (such as the logistic regression) are more likely to fail to maximize the pAUC while the proposed methods are more robust. The proposed approaches are illustrated through application to a prostate cancer data set, and a rank-based leave-one-out cross-validation procedure is proposed to obtain a realistic estimate of the pAUC when there is no independent validation set available.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.