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已发表论文
带状疱疹患者发生带状疱疹后神经痛的风险因素及基于列线图的风险预测
Received 29 July 2025
Accepted for publication 21 December 2025
Published 30 December 2025 Volume 2025:18 Pages 7287—7297
DOI https://doi.org/10.2147/JPR.S554371
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Professor King Hei Stanley Lam
Bocheng Peng,1 Rui Min2
1Department of Pain, Wuhan Fourth Hospital, Wuhan, People’s Republic of China; 2Department of Geriatrics, Wuhan Fourth Hospital, Wuhan, People’s Republic of China
Correspondence: Rui Min, Department of Geriatrics, Wuhan Fourth Hospital, Wuhan, People’s Republic of China, Email mminrrui@163.com
Objective: Postherpetic neuralgia (PHN) is considered as the most common complication of herpes zoster, and its incidence is increasing. The aim of this study was to explore the risk factors of postherpetic neuralgia (PHN) (ICD-10: B02.29) and to construct a predictive line graph model for early identification and prevention of PHN.
Methods: In this study, we focused on a cohort of 650 patients who had been diagnosed with herpes zoster (HZ)(ICD-10: B02) and subsequently admitted to Wuhan Fourth Hospital over a span of seven years, specifically from January 2018 to June 2025. The study cohort was randomly divided into a training set (n=458) and a validation set (n=192), with an average age of 57.31± 12.64 years in both groups. The Nomogram model, designed to predict the elevated risk of PHN in individuals with HZ was constructed through the R4.2.1 software “rms” package. The nomogram model’s predictive performance was evaluated using the decision curve, while the calibration curve was utilized for internal validation. The model was also externally validated using a validation set of data.
Results: The logistic regression analysis revealed that independent risk factors for PHN included age, the course of HZ, herpes in specific areas, VAS score, severity of skin damage, and temperature rising > 1°C. The proposed Nomogram model, developed with the previously mentioned indicators, exhibits ROC curve area values of 0.943 for the training set and 0.900 for the validation set. The correction curve suggests that the model maintains high accuracy. Furthermore, the DCA outcomes reveal that the model possesses enhanced clinical utility at risk thresholds ranging from 0 to 0.99 for the training data and from 0.04 to 0.89 for the validation data.
Conclusion: Our study confirms that age, the course of herpes zoster, herpes in special sites, VAS score, the severity of skin lesions, and a temperature increase of > 1°C are independent risk factors for the occurrence of Postherpetic neuralgia (PHN). The nomogram model established based on these six indicators demonstrates good developmental potential and exhibits high discriminative predictive performance for Postherpetic neuralgia (PHN)in patients with herpes zoster.
Keywords: postherpetic neuralgia, nomogram model, prediction, risk factors, herpes zoster
1Department of Pain, Wuhan Fourth Hospital, Wuhan, People’s Republic of China; 2Department of Geriatrics, Wuhan Fourth Hospital, Wuhan, People’s Republic of China
Correspondence: Rui Min, Department of Geriatrics, Wuhan Fourth Hospital, Wuhan, People’s Republic of China, Email mminrrui@163.com
Objective: Postherpetic neuralgia (PHN) is considered as the most common complication of herpes zoster, and its incidence is increasing. The aim of this study was to explore the risk factors of postherpetic neuralgia (PHN) (ICD-10: B02.29) and to construct a predictive line graph model for early identification and prevention of PHN.
Methods: In this study, we focused on a cohort of 650 patients who had been diagnosed with herpes zoster (HZ)(ICD-10: B02) and subsequently admitted to Wuhan Fourth Hospital over a span of seven years, specifically from January 2018 to June 2025. The study cohort was randomly divided into a training set (n=458) and a validation set (n=192), with an average age of 57.31± 12.64 years in both groups. The Nomogram model, designed to predict the elevated risk of PHN in individuals with HZ was constructed through the R4.2.1 software “rms” package. The nomogram model’s predictive performance was evaluated using the decision curve, while the calibration curve was utilized for internal validation. The model was also externally validated using a validation set of data.
Results: The logistic regression analysis revealed that independent risk factors for PHN included age, the course of HZ, herpes in specific areas, VAS score, severity of skin damage, and temperature rising > 1°C. The proposed Nomogram model, developed with the previously mentioned indicators, exhibits ROC curve area values of 0.943 for the training set and 0.900 for the validation set. The correction curve suggests that the model maintains high accuracy. Furthermore, the DCA outcomes reveal that the model possesses enhanced clinical utility at risk thresholds ranging from 0 to 0.99 for the training data and from 0.04 to 0.89 for the validation data.
Conclusion: Our study confirms that age, the course of herpes zoster, herpes in special sites, VAS score, the severity of skin lesions, and a temperature increase of > 1°C are independent risk factors for the occurrence of Postherpetic neuralgia (PHN). The nomogram model established based on these six indicators demonstrates good developmental potential and exhibits high discriminative predictive performance for Postherpetic neuralgia (PHN)in patients with herpes zoster.
Keywords: postherpetic neuralgia, nomogram model, prediction, risk factors, herpes zoster