Journal Article10.1080/03610910903312219
Bayesian interval estimation for predictive values from case-control studies.
James D. Stamey,Melinda M. Holt +1 more
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TL;DR: This work allows for uncertainty in the estimate of the population prevalence and via simulation explore the impact of deviations from the assumed value of PPV and NPV.
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Abstract: Positive predictive and negative predictive values (PPV and NPV) are often used to assess the accuracy of binary diagnostic tests. Unlike sensitivity and specificity, PPV and NPV are functions of the accuracy of the test and the overall prevalence of the disease in the population. In many studies of performance of estimators of PPV and NPV the population prevalence is assumed known. We allow for uncertainty in the estimate of the population prevalence and via simulation explore the impact of deviations from the assumed value.
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Citations
Prospective Study of Diagnostic Accuracy Comparing Prostate Cancer Detection by Transrectal Ultrasound–Guided Biopsy Versus Magnetic Resonance (MR) Imaging with Subsequent MR-guided Biopsy in Men Without Previous Prostate Biopsies
Morgan Pokorny,Maarten de Rooij,Earl Duncan,Fritz H. Schröder,Robert Parkinson,Jelle O. Barentsz,Leslie C. Thompson +6 more
TL;DR: Comparing the diagnostic efficacy of the magnetic resonance imaging (MRI) pathway with transrectal ultrasound-guided biopsy in men with elevated prostate-specific antigen found that mpMRI/MRGB reduces the detection of low-risk PCa and reduces the number of men requiring biopsy while improving the overall rate of detection of intermediate/high- risk PCa.
543
Joint confidence region estimation on predictive values.
Braydon Schaible,Jingjing Yin +1 more
TL;DR: In this paper, the joint inference of positive predictive value and negative predictive value (NPV) is proposed to estimate the joint confidence region as well as the individual confidence intervals of PPV and NPV.
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Unreliable evidence in binary classification problems
David W. Flater
- 07 May 2019
TL;DR: This report explains the problem ofinary classification problems and explores options for accounting for the often-neglected uncertainty and concludes that a neat solution that does no harm to less uncertain cases remains elusive.
1
Interval Estimates for Predictive Values in Diagnostic Testing with Three Outcomes
Scott Clark,Lauren Mondin,Courtney Weber,Jessica Winborn +3 more
- 01 Jan 2011
TL;DR: Clark et al. as discussed by the authors derived classical Wald-type and Bayesian interval estimates of positive predictive value, negative predictive value and uncertain predictive value for diagnostic tests in which the disease state remains uncertain.
Statistical methods and software for validation studies on new in vitro toxicity assays.
TL;DR: Confidence intervals for predictive values are computed for a validation study of an in vitro test battery, and sample size calculation is illustrated for an acute toxicity assay using R, the free software.
References
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TL;DR: The number of persons with AD in the US population will continue to increase unless new discoveries facilitate prevention of the disease, according to current and future estimates of prevalence of clinically diagnosed AD.
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Understanding diagnostic tests 1: sensitivity, specificity and predictive values.
TL;DR: It is explained that while sensitivity and specificity are important measures of the diagnostic accuracy of a test, they are of no practical use when it comes to helping the clinician estimate the probability of disease in individual patients.
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Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures
Alan Agresti,Brian Caffo +1 more
TL;DR: This paper showed that simple adjustments of the standard confidence intervals based on adding four pseudo observations, half of each type, perform surprisingly well even for small samples, and used the same formulas with small and large samples in teaching with these adjusted intervals.
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Confidence intervals for predictive values with an emphasis to case-control studies.
TL;DR: A novel method for the estimation of PPV and NPV, as well as their confidence intervals, is developed and is applied to two case–control studies: a diagnostic test assessing the ability of the e4 allele of the apolipoprotein E gene (ApoE) on distinguishing patients with late‐onset Alzheimer's disease (AD) and a prognostic test assessingThe predictive ability of a 70‐gene signature on breast cancer metastasis.
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Association of late-onset Alzheimer's disease with genetic variation in multiple members of the GAPD gene family
Yonghong Li,Petra Nowotny,Peter Holmans,Scott Smemo,John S. K. Kauwe,Anthony L. Hinrichs,Kristina Tacey,Lisa Doil,Ryan van Luchene,Veronica Garcia,Charles M. Rowland,Steven J. Schrodi,Diane Leong,Goran Gogic,Joanne Chan,Anibal Cravchik,David A. Ross,Kit Lau,Shirley Kwok,Sheng-Yung Chang,Joseph J. Catanese,John J. Sninsky,Thomas J. White,John Hardy,John Powell,Simon Lovestone,John C. Morris,Leon J. Thal,Michael John Owen,Julie Williams,Alison Goate,Andrew Grupe +31 more
TL;DR: A large-scale single-nucleotide polymorphism (SNP)-based association study across the region of linkage on chromosome 12 in multiple case-control series raises the possibility that GAPD genes are AD risk factors, a hypothesis that is consistent with the role of GAPD in neuronal apoptosis.
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