ArticleClinics (Sao Paulo, Brazil)2026
Nomogram prediction model for the clinical efficacy of flunarizine hydrochloride in patients with vertigo based on 5-HT and oxidative stress indicators
Article in Clinics (Sao Paulo, Brazil), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveThis study aimed to develop and validate a nomogram model integrating 5-Hydroxytryptamine (5-HT) and oxidative stress markers to predict the efficacy of flunarizine hydrochloride in treating vertigo.
methodsA retrospective study included 244 vertigo patients treated with flunarizine hydrochloride from September 2022 to December 2024. Patients were divided into training (70%) and validation (30%) sets. Clinical data, 5-HT levels, and oxidative stress indicators (Superoxide Dismutase [SOD], Malondialdehyde [MDA], Glutathione Peroxidase [GSH-Px]) were collected and analyzed. The influencing factors of treatment efficacy were screened using univariate and multivariate logistic regression. Least Absolute Shrinkage and Selection Operator (LASSO) regression was implemented using the R 'glmnet' package with 10-fold cross-validation. A nomogram model was constructed by integrating the independent influencing factors of treatment efficacy. Model performance was assessed via calibration curves, Consistency index (C-index), Decision Curve Analysis (DCA), and Receiver Operating Characteristic (ROC) curve.
resultsThere were 176 cases in the effective group and 68 cases in the ineffective group. Age, 5-HT, SOD, MDA, and GSH-Px were identified as independent predictors of treatment efficacy (p < 0.05). After variable selection via LASSO regression, the reduced nomogram demonstrated strong discriminative ability, with C-indexes of 0.862 (in the training set) and 0.874 (in the validation set), and average absolute errors of 0.144 and 0.138, respectively. Hosmer-Lemeshow tests confirmed good fit of the model (training: χ² = 9.061, p = 0.337; validation: χ² = 8.034, p = 0.430). ROC analysis yielded Area Under the Curve (AUC) values of 0.861 (95% CI: 0.797-0.925) and 0.870 (95% CI: 0.798-0.973) for training and validation sets, with sensitivity/specificity values of 0.892/0.711 and 1.000/0.650, respectively.
conclusionThe simplified nomogram incorporating age and oxidative stress markers demonstrates robust predictive accuracy while enhancing clinical feasibility. Actionable thresholds were established, such that patients with a score > 70-points should be considered for alternative therapies due to a high predicted risk of treatment non-response.
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