Development of a Model for Predicting the Effectiveness of Low-Temperature Plasma on Zoster-Associated Pain

Zoster-associated pain (ZAP) is a condition characterized by severe, persistent pain caused by herpes zoster (HZ), which impacts the patient's daily activities, mental health, and quality of life significantly. Low-temperature plasma (LTP) technology, as an emerging therapeutic approach, has been applied widely in various biomedical fields. At our center, this technology has been utilized for the treatment of postherpetic neuralgia. Preliminary studies have demonstrated that LTP can effectively alleviate pain symptoms in patients with ZAP. However, a small subset of patients experiences suboptimal outcomes, with limited pain relief following LTP treatment.

This study was conducted to investigate the efficacy of LTP for treating ZAP, analyze the risk factors for poor therapeutic response, and establish a predictive model to provide clinical decision-making support.

A single-center prospective cohort study was conducted to analyze outcomes of using LTP to treat ZAP.

Patients treated at the Pain Department of Zhongda Hospital, Southeast University, between January 2018 and December 2023, were included.

Patients who received LTP treatment underwent a 6-month follow-up, during which their Visual Analog Scale (VAS) scores were recorded. A post-treatment VAS score ≥ 4 was defined as a poor therapeutic response. Risk factor analysis was performed on patients with poor therapeutic response, and a predictive model was developed. The model was evaluated using threefold cross-validation, with its performance assessed by the area under the receiver operating characteristic (ROC) curve (AUC). Calibration curves and decision curve analysis were used to assess the model's calibration and clinical applicability.

A total of 120 patients who underwent LTP treatment were included in the study, with an overall response rate of 67.5%. Analysis of 43 variables revealed that age, coronary heart disease (CHD), disease duration, albumin-to-globulin ratio (AGR), white blood cell (WBC) count, neutrophil count, and scores on the VAS, Dermatology Life Quality Index (DLQI), Pittsburgh Sleep Quality Index (PSQI), Hamilton Anxiety Rating Scale (HAMA1), HAMA2, and Barthel Index were significantly different between the groups (P < 0.05). Stepwise bidirectional regression identified 4 independent factors significantly associated with outcomes: CHD, AGR, PSQI, and HAMA1. Using logistic regression, a predictive model was constructed and validated through 3 cross-validation methods. The mean AUC for the training set was 0.768 (95% CI: 0.690-0.942), with a sensitivity of 68.7% and a specificity of 83.7%. The mean AUC for the validation set was 0.762 (95% CI: 0.589-0.935), with a sensitivity of 58.5% and a specificity of 76.4%.

The study was conducted at a single center with a small number of cases, which might have limited generalizability. Larger, multicenter prospective studies are needed to validate the findings.

For ZAP patients, CHD, AGR, and PSQI and HAMA1 scores are high-risk factors for the continuation of chronic pain after the administration of LTP treatment. The predictive model demonstrated relatively high sensitivity and specificity. This finding suggests that combining these indicators can, to some extent, predict patients' therapeutic response to LTP.