Infection and drug resistance · 2024
Advancing Precise Syphilis Diagnosis: A Nontreponemal IgM Antibody-Based Model for Latent Syphilis Staging.
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Xie Jia-Wen, Guo Yin-Feng, Zheng Ya-Wen, Wang Mao, Xu Qiu-Yan, Chen Yu-Yan, Lin Li-Rong
Аннотация
PURPOSE: Accurate differentiation between early and late latent syphilis stages is pivotal for patient management and treatment strategies. Nontreponemal IgM antibodies have shown potential in discriminating latent syphilis staging by differentiating syphilis activity. This study aimed to develop a predictive nomogram model for latent syphilis staging based on nontreponemal IgM antibodies.
PATIENTS AND METHODS: We explored the correlation between nontreponemal IgM antibodies and latent syphilis staging and developed a nomogram model to predict latent syphilis staging based on 352 latent syphilis patients. Model performance was assessed using AUC, calibration curve, Hosmer-Lemeshow χ2 statistics, C-index, Brier score, decision curve analysis, and clinical impact curve. Additionally, an external validation set was used to further assess the model's stability.
RESULTS: Nontreponemal IgM antibodies correlated with latent syphilis staging. The constructed model demonstrated a strong discriminative capability with an AUC of 0.743. The calibration curve displayed a strong fit, key statistics including Hosmer-Lemeshow χ² at 2.440 (P=0.486), a C-index score of 0.743, and a Brier score of 0.054, all suggesting favorable model calibration performance. Decision curve analysis and clinical impact curve highlighted the model's robust clinical applicability. The external validation set yielded an AUC of 0.776, Hosmer-Lemeshow χ² statistics of 2.440 (P=0.486), a C-index score of 0.767, and a Brier score of 0.054, further underscored the reliability of the model.
CONCLUSION: The nontreponemal IgM antibody-based predicted model could equip clinicians with a valuable tool for the precise staging of latent syphilis and enhancing clinical decision-making.
PATIENTS AND METHODS: We explored the correlation between nontreponemal IgM antibodies and latent syphilis staging and developed a nomogram model to predict latent syphilis staging based on 352 latent syphilis patients. Model performance was assessed using AUC, calibration curve, Hosmer-Lemeshow χ2 statistics, C-index, Brier score, decision curve analysis, and clinical impact curve. Additionally, an external validation set was used to further assess the model's stability.
RESULTS: Nontreponemal IgM antibodies correlated with latent syphilis staging. The constructed model demonstrated a strong discriminative capability with an AUC of 0.743. The calibration curve displayed a strong fit, key statistics including Hosmer-Lemeshow χ² at 2.440 (P=0.486), a C-index score of 0.743, and a Brier score of 0.054, all suggesting favorable model calibration performance. Decision curve analysis and clinical impact curve highlighted the model's robust clinical applicability. The external validation set yielded an AUC of 0.776, Hosmer-Lemeshow χ² statistics of 2.440 (P=0.486), a C-index score of 0.767, and a Brier score of 0.054, further underscored the reliability of the model.
CONCLUSION: The nontreponemal IgM antibody-based predicted model could equip clinicians with a valuable tool for the precise staging of latent syphilis and enhancing clinical decision-making.