The inconsistency of "optimal" cutpoints obtained using two criteria based on the receiver operating characteristic curve.

By Neil Perkins, Enrique F. Schisterman. American Journal of Epidemiology, 2006

1,690 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/af7ac8387f401ff5dd72e116014272c7e0162b94

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization (2012, methodology): “We believe that this is a consequence of the high concordance between gene expression and immunohistology in this use case, while in other situations cutoffs determined by different methods can differ substantially [6].”
OptimalCutpoints: An R Package for Selecting Optimal Cutpoints in Diagnostic Tests (2014, methodology): “The slope of the ROC curve at the optimal cutpoint obtained using this index is equal to 1 (Perkins and Schisterman 2006), which is equivalent to having a prevalence equal to 0.5 and a costs ratio equal to 1.”
Insights into the area under the receiver operating characteristic curve (AUC) as a discrimination measure in species distribution modelling (2012, background): “Actually, the point identified as such is not the one with the minimum overall error rate and does not have to coincide with j (Perkins & Schisterman, 2006).”
Detection of Differential Item Functioning Using the Lasso Approach (2015, methodology): “The average area is thus a global comparative tool, sometimes referred to as the area under the curve (AUC; e.g., Perkins & Schisterman, 2006).”
Assessment of Clinical Criteria for Sepsis (2016, neutral): “(%) 17 327 (12) 2153 (27) 6517 (10) 2171 (27) 6486 (10)”
Predictive validity performance indicators in violence risk assessment: a methodological primer. (2013, background): “However, once the practical considerations of misclassi ﬁ cation costs and prevalence are added, and sensitivity and speci ﬁ city pairs on the ROC curve are weighted accordingly, the “ optimal ” cut-off threshold can change dramatically (Perkins & Schisterman, 2006).”