Development of a parsimonious predictive model for height gain outcome in children with central precocious puberty following gonadotropin-releasing hormone agonist therapy.

Background: Central precocious puberty (CPP) is associated with compromised adult height if untreated, and gonadotropin-releasing hormone agonist (GnRHa) therapy remains the standard treatment. However, height gain during treatment varies considerably among patients, and clinically practical tools for early identification of children at risk for suboptimal growth response are lacking. This study aimed to identify prognostic determinants of suboptimal height gain during GnRHa therapy and to develop a parsimonious predictive model to facilitate evidence-based clinical decision-making and optimal intervention timing. Methods: A retrospective cohort study was conducted enrolling children with CPP treated with triptorelin. Baseline clinical and biochemical parameters were collected, including chronological age, height standard deviation score (SDS), body mass index (BMI) SDS, insulin-like growth factor-1 (IGF-1) SDS, bone age advancement [bone age minus chronological age (BA-CA)], Tanner stage, GnRH-stimulated luteinizing hormone (LH) peak, and serum estradiol concentrations. Patients were stratified into favorable and unfavorable outcome cohorts based on height gain during treatment. Univariate and multivariable logistic regression analyses were performed to identify independent predictors. Three predictive models were constructed: M0 (comprehensive model with five predictors: IGF-1 SDS, BMI SDS, BA-CA, Tanner stage, and age), M1 (univariate model with IGF-1 SDS), and M2 (parsimonious model with IGF-1 SDS and BA-CA). Model performance was assessed using receiver operating characteristic (ROC) curves, calibration plots, decision curve analysis (DCA; 1-50% risk thresholds), and bootstrap internal validation. Results: A total of 163 children with CPP were enrolled (favorable outcome: n=113; unfavorable outcome: n=50). Multivariable logistic regression identified BMI SDS [odds ratio (OR) =2.33, 95% confidence interval (CI): 1.14-4.76, P=0.02], IGF-1 SDS (OR =1.94, 95% CI: 1.24-3.02, P=0.004), and bone age advancement (OR =21.49, 95% CI: 5.41-85.30, P<0.001) as independent predictors for unfavorable outcome. The area under the curve (AUC) was 0.838 (95% CI: 0.774-0.903) for M0, 0.664 (95% CI: 0.573-0.754) for M1, and 0.815 (95% CI: 0.748-0.883) for M2. DeLong test revealed no significant difference between M2 and M0 (ΔAUC =-0.023, P=0.24). Bootstrap internal validation (1,000 iterations) demonstrated optimism-corrected AUC values of 0.810, 0.661, and 0.807 for M0, M1, and M2, respectively. M2 exhibited optimal calibration slope (0.957, 95% CI: 0.642-1.389) closest to unity. Brier scores were 0.160 for M0 and 0.167 for M2. DCA demonstrated comparable clinical net benefit for M0 and M2 across 1-50% risk thresholds. Conclusions: The parsimonious model (M2) incorporating IGF-1 SDS and bone age advancement demonstrates robust predictive capability for height gain outcome in children with CPP receiving GnRHa therapy, comparable to the comprehensive model. This model may support early risk stratification and closer growth monitoring in selected patients; however, external validation and confirmation against final adult height outcomes are required before it can inform decisions about adjunctive interventions.