Convergence Behavior of Optimal Cut-Off Points Derived from Receiver Operating Characteristics Curve Analysis: A Simulation Study
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Convergence Behavior of Optimal Cut-Off Points Derived from Receiver Operating Characteristics Curve Analysis: A Simulation Study. / Gerke, Oke; Zapf, Antonia.
In: MATHEMATICS-BASEL, Vol. 10, No. 22, 4206, 10.11.2022.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Convergence Behavior of Optimal Cut-Off Points Derived from Receiver Operating Characteristics Curve Analysis: A Simulation Study
AU - Gerke, Oke
AU - Zapf, Antonia
PY - 2022/11/10
Y1 - 2022/11/10
N2 - The area under the receiver operating characteristics curve is a popular measure of the overall discriminatory power of a continuous variable used to indicate the presence of an outcome of interest, such as disease or disease progression. In clinical practice, the use of cut-off points as benchmark values for further treatment planning is greatly appreciated, despite the loss of information that such a dichotomization implies. Optimal cut-off points are often derived from fixed sample size studies, and the aim of this study was to investigate the convergence behavior of optimal cut-off points with increasing sample size and to explore a heuristic and path-based algorithm for cut-off point determination that targets stagnating cut-off point values. To this end, the closest-to-(0,1) criterion in receiver operating characteristics curve analysis was used, and the heuristic and path-based algorithm aimed at cut-off points that deviated less than 1% from the cut-off point of the previous iteration. Such a heuristic determination stopped after only a few iterations, thereby implicating practicable sample sizes; however, the result was, at best, a rough estimate of an optimal cut-off point that was unbiased and positively and negatively biased for a prevalence of 0.5, smaller than 0.5, and larger than 0.5, respectively.
AB - The area under the receiver operating characteristics curve is a popular measure of the overall discriminatory power of a continuous variable used to indicate the presence of an outcome of interest, such as disease or disease progression. In clinical practice, the use of cut-off points as benchmark values for further treatment planning is greatly appreciated, despite the loss of information that such a dichotomization implies. Optimal cut-off points are often derived from fixed sample size studies, and the aim of this study was to investigate the convergence behavior of optimal cut-off points with increasing sample size and to explore a heuristic and path-based algorithm for cut-off point determination that targets stagnating cut-off point values. To this end, the closest-to-(0,1) criterion in receiver operating characteristics curve analysis was used, and the heuristic and path-based algorithm aimed at cut-off points that deviated less than 1% from the cut-off point of the previous iteration. Such a heuristic determination stopped after only a few iterations, thereby implicating practicable sample sizes; however, the result was, at best, a rough estimate of an optimal cut-off point that was unbiased and positively and negatively biased for a prevalence of 0.5, smaller than 0.5, and larger than 0.5, respectively.
UR - https://www.mdpi.com/2227-7390/10/22/4206/pdf
U2 - 10.3390/math10224206
DO - 10.3390/math10224206
M3 - SCORING: Journal article
VL - 10
JO - MATHEMATICS-BASEL
JF - MATHEMATICS-BASEL
SN - 2227-7390
IS - 22
M1 - 4206
ER -