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Using the best cutoff score (less than 4.2), presence of significant fibrosis (F2 to F4) could be excluded with high accuracy (negative predictive value of 96%) in 125 (36%) of 351 patients.
The discriminant power of these cut-off values (sensitivity, specificity, positive and negative predictive value (PNV, NPV), and likelihood ratio for positive (+LR) and negative (-LR)) are shown in Table 3. Kaplan-Meier survival curves using the best cutoff values of mt-DNA, H-FBAP, and n-DNA are presented in Figure 3 (A through C).
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We applied LCPI to this dataset, and since this cohort differed in platform, we used the best cutoff values to separate patients into different risk groups.
When the same analysis was used, the best cutoff value of plasma DNA at admission for 24-hour mortality was 4,340 GE/mL with a sensitivity of 76% and a specificity of 83%.
Two different approaches were used: (1) the best cutoff determined based on a 2 × 2 contingency table (with 24hP considered the gold standard test) and (2) logistic regression analysis.
In each case, counts were tallied using the best and worst performing SCA cutoff values.
The difference in AUCs is highly significant: p = 4.88 · 10-4 (one sided Wilcoxon rank-sum test) using the best combination of PWM and cutoff for CENTIPEDE.
For datasets obtained using different platforms, the best cutoff calculation was performed to obtain cutoff values for each risk group.
To improve clinical utility of significant continuous variables, Youden's index was used to calculate the best cutoff value for predicting hypocalcemia.[ 15] The AUC was used to measure the predictive accuracy.
Although evaluations of various search engines have been documented in terms of the number of true positives found at a fixed false positive rate or in terms of total number of true positive hits found [ 13], these data, while important, do not provide us with the best cutoff to use for each search engine.
The index has been used to calculate the best cutoff point in the ROC curve.
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