A multicenter prospective cohort study developing and validating a SIRI-based machine learning model and simplified risk score for predicting postherpetic neuralgia - Takeaways - MDSpire

A multicenter prospective cohort study developing and validating a SIRI-based machine learning model and simplified risk score for predicting postherpetic neuralgia

  • By

  • Mengying Mao

  • Fangzheng Cao

  • Yongxing Yan

  • Huili Liu

  • Wenjing Wu

  • Bin Xu

  • June 5, 2026

  • 0 min

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  • 1

    Postherpetic neuralgia (PHN) is a common complication of herpes zoster, with early identification of high-risk patients being crucial for effective intervention.

  • 2

    The systemic inflammatory response index (SIRI) has been identified as an independent predictive biomarker for the development of PHN.

  • 3

    A total of 1361 patients were analyzed, with 37.55% developing PHN, highlighting the significant risk associated with herpes zoster.

  • 4

    The eXtreme Gradient Boosting (XGBoost) model demonstrated optimal predictive performance, achieving an AUC of 0.900 in external validation.

  • 5

    A simplified risk scoring table based on SIRI and other factors was developed, recommending early intervention for patients with a score ≥18.

Original Source(s)

A multicenter prospective cohort study developing and validating a SIRI-based machine learning model and simplified risk score for predicting postherpetic neuralgia

  • by Mengying Mao, Fangzheng Cao, Yongxing Yan, Huili Liu, Wenjing Wu, Bin Xu

  • June 5, 2026

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