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. 2024 Mar 13;11:1363431. doi: 10.3389/fsurg.2024.1363431

Table 2.

Estimates of serum prolactin thresholds to discriminate between micro- and macroadenomas in a cohort of N = 133 prolactinoma patients and associated performance metrics.

Method All patients (N = 133) Female patients (N = 91) Male patients (N = 42)
Bayesian logistic regression Youden Index Bayesian logistic regression Youden Index Bayesian logistic regression Youden Index
Prolactin threshold (µg/L) 239.4 (44.0–451.2) 230.0 (203.0–466.1) 211.6 (29.0–426.2) 203.0 (189.8–243.2) 1,046.1 (582.2–2,325.9) 1,179.0 (596.2–1,510.0)
AUROC 0.91 (0.85–0.95) 0.87 (0.78–0.94) 0.93 (0.83–0.99)
Sensitivity
Global threshold 0.79 (0.72–0.99) 0.84 (0.70–0.94) 0.61 (0.47–0.99) 0.64 (0.42–0.75) 0.97 (0.97–0.99) 0.97 (0.97–0.97)
Gender threshold 0.69 (0.47–0.99) 0.75 (0.61–0.78) 0.74 (0.54–0.97) 0.74 (0.69–0.94)
Specificity
Global threshold 0.90 (0.10–0.97) 0.91 (0.81–0.99) 0.95 (0.09–0.99) 0.95 (0.89–0.99) 0.57 (0.14–0.71) 0.57 (0.43–0.71)
Gender threshold 0.91 (0.00–0.98) 0.89 (0.82–0.95) 0.99 (0.71–0.99) 0.99 (0.71–0.99)
Positive predictive value
Global threshold 0.91 (0.56–0.96) 0.92 (0.83–0.99) 0.89 (0.42–0.99) 0.88 (0.81–0.99) 0.92 (0.85–0.94) 0.92 (0.89–0.94)
Gender threshold 0.84 (0.40–0.94) 0.82 (0.74–0.88) 0.99 (0.94–0.99) 0.99 (0.94–0.99)
Negative predictive value
Global threshold 0.78 (0.74–0.94) 0.83 (0.72–0.93) 0.78 (0.74–0.93) 0.80 (0.72–0.84) 0.80 (0.50–0.99) 0.80 (0.75–0.83)
Gender threshold 0.82 (0.74–0.99) 0.84 (0.79–0.85) 0.43 (0.30–0.83) 0.44 (0.39–0.71)

AUROC, area under the receiver operating characteristic.

The most likely estimates and 95% credible intervals are shown for thresholds derived with a multilevel Bayesian logistic regression framework (BLRM). Median values and bootstrapped 95% confidence intervals are shown for the threshold estimates derived with the Youden Index. Median and 95% credible intervals (for thresholds derived with the BLRM) and 95% confidence intervals (for thresholds derived with the Youden Index) are shown for the performance metrics. For the female and male patients, performance metrics are shown for two cases: First, when a global (gender-unspecific) threshold is used to compute the confusion matrix. Second, when a gender-specific threshold is used compute the confusion matrix.