Notes on the overlap measure as an alternative to the Youden index: How are they related?

Samawi, Hani M.; Yin, Jingjing; Rochani, Haresh; Panchal, Viral

doi:10.1002/sim.7435

Cited by 21 publications

(18 citation statements)

References 19 publications

(30 reference statements)

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“…Data were synthesized by using the random-effects model which was recommended in pooled estimates of diagnostic meta-analyses [25]. The area under the curve (AUC), Youden index and index Q* were used to measure test accuracy [26][27][28].…”

Section: Discussionmentioning

confidence: 99%

Diagnostic Test Accuracy of New Generation Tympanic Thermometry in Children: A Systematic Review and Meta-analysis

Shi¹,

Zhang²,

Li³

2020

Preprint

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Purposes: The purposes of this review were to compare sensitivity and specificity of the new generation tympanic thermometry under different cutoffs and to give the optimal cutoff. Methods: Articles were derived from a systematic search in PubMed, Web of science, and Embase, and were assessed for internal validity by QUADAS-Ⅱ. The figure of risk of bias was drew by Review Manager 5.3 and data were synthesized by MetaDisc 1.4. Results: Nineteen diagnostic studies, involving 4,639 pediatric patients, were included. The cut-offs varied from 37.0℃ to 38.0℃ among these studies. The cut-off 37.8 was with the highest sROC AUC (0.97) and Youden Index (0.83) and was deemed to be the optimal cutoff. Conclusion: New Generation Tympanic Thermometry is with high diagnostic accuracy in pediatric patients and can be an alternative for rectal measurements.

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Section: Discussionmentioning

confidence: 99%

Diagnostic Test Accuracy of New Generation Tympanic Thermometry in Children: A Systematic Review and Meta-analysis

Shi¹,

Zhang²,

Li³

2020

Preprint

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“…Chatproedprai et al [3] 2016 Thailand Pediatric outpatient clinic 0-2y Acikgoz et al [30] 2016 Turkey pediatric emergency department 3m-3y Duru et al [31] . 2012 Nigeria The neonatal wards 6.63±6.98d…”

Section: List Of Abbreviationsmentioning

confidence: 99%

Diagnostic Test Accuracy of New Generation Tympanic Thermometry in Children under Different Cutoffs: A Systematic Review and Meta-analysis

Shi

Zhang

2020

Preprint

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Purposes: To identify and quantify studies reporting the diagnostic accuracy of the new generation of infrared tympanic thermometer (IRTT) in children and to compare the sensitivity and specificity of IRTT under different cutoffs and give the optimal cutoff. Methods: Articles were derived from a systematic search in PubMed, Web of Science Core Collection, and Embase, and were assessed for internal validity by the Quality Assessment of Diagnostic Accuracy Studies-2　（QUADAS-Ⅱ）. The figure of risk of bias was created by Review Manager 5.3 and data were synthesized by MetaDisc 1.4. Results: Nineteen diagnostic studies, involving 4,639 pediatric patients, were included. The cut-offs varied from 37.0℃ to 38.0℃ among these studies. The cut-off 37.8℃ was with the highest sROC AUC (0.97) and Youden Index (0.83) and was deemed to be the optimal cutoff. Conclusion: The optimal cutoff for infrared tympanic thermometers is 37.8℃. New Generation Tympanic Thermometry is with high diagnostic accuracy in pediatric patients and can be an alternative for fever screening in children.

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“…Finally, the criticism that the AUC lacks clinical relevance and omits the consideration of costs and harms in weighing false positives against false negatives 13,14 is valid but concerns the inappropriate use of the measure rather than its shortcomings. The AUC is nothing more than a measure related to the separation of the risk distributions of diseased and non-diseased individuals.…”

Section: Reappraisal Of Auc Limitationsmentioning

confidence: 99%

A more intuitive interpretation of the area under the ROC curve

Janssens

2017

Preprint

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The area under the receiver operating characteristic (ROC) curve (AUC) is commonly used for assessing the discriminative ability of prediction models even though the measure is criticized for being clinically irrelevant and lacking an intuitive interpretation. Most of the criticism is traced back to the fact that the ROC curve was introduced as the discriminative ability of a binary classifier across all its possible thresholds. Yet, this is not the curve’s only interpretation. Every tutorial explains how the coordinates of the ROC curve are obtained from the risk distributions of diseased and non-diseased individuals, but it has not become common sense that the ROC plot is another way of presenting these risk distributions. This alternative perspective on the ROC plot invalidates most limitations of the AUC and attributes others to the underlying risk distributions. The separation of these distributions, represented by the area between the curves (AUC), is a more straightforward and intuitive measure of the inference of the discriminative ability of prediction models.

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Notes on the overlap measure as an alternative to the Youden index: How are they related?

Cited by 21 publications

References 19 publications

Diagnostic Test Accuracy of New Generation Tympanic Thermometry in Children: A Systematic Review and Meta-analysis

Diagnostic Test Accuracy of New Generation Tympanic Thermometry in Children: A Systematic Review and Meta-analysis

Diagnostic Test Accuracy of New Generation Tympanic Thermometry in Children under Different Cutoffs: A Systematic Review and Meta-analysis

A more intuitive interpretation of the area under the ROC curve

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