Diagnostic Potential of the Risk Factors Associated With Peripheral Neuropathy in Multiple Myeloma: Evidence From...

Aims/Background Peripheral neuropathy (PN) is a common and debilitating complication in patients with multiple myeloma (MM), which results from both disease-related mechanisms and treatment-induced neurotoxicity. Despite its clinical significance, comprehensive investigations assessing PN risk in MM, along with examining demographic, clinical, nutritional, and inflammatory factors, remain limited. Therefore, this study aimed to investigate independent risk predictors associated with PN in MM patients using univariate and multivariate logistic regression analysis, thereby enhancing clinical risk management and improving treatment outcomes. Methods This retrospective observational study included 161 MM patients who were treated at Ganzhou People's Hospital between February 2020 and February 2024. Study participants were divided into the PN (n = 45) and non-PN (n = 116) groups. PN diagnosis was conducted based on new neurological signs and symptoms post-treatment, confirmed through abnormal sensory, motor, autonomic, or nerve conduction assessments. Baseline characteristics, including demographic information, clinical features, and laboratory parameters, were compared between the two groups using Mann-Whitney U and Chi-square tests. Univariate logistic regression analysis evaluated potential parameters associated with PN. Furthermore, a multivariate logistic model was used to assess independent risk predictors. Finally, model performance was evaluated via receiver operating characteristic (ROC) curve analysis. Results This study analyzed 161 patients, of whom 45 (27.95%) developed PN. Patients in the PN group were significantly older, and had higher body mass index (BMI), increased immunoglobulin G (IgG) and interleukin-6 (IL-6) levels, and increased diabetes prevalence than the non-PN group. However, they exhibited lower hemoglobin (Hb) and serum 25-hydroxyvitamin D [25(OH)D] levels (p < 0.05). Multivariate logistic regression analysis identified older age (odds ratio [OR] = 1.49, 95% confidence interval [CI]: 1.07-2.08), higher BMI (OR = 2.05, 95% CI: 1.01-4.17), reduced 25(OH)D levels (OR = 0.54, 95% CI: 0.29-0.97), elevated IgG (OR = 1.64, 95% CI: 1.12-2.41), and increased IL-6 (OR = 2.07, 95% CI: 1.10-3.88) as independent PN predictor. The model showed excellent discrimination capability (area under the curve [AUC] = 0.998, 95% CI: 0.996-1.000, p < 0.001). Conclusion This study identified older age, higher BMI, vitamin D deficiency, elevated IgG, and increased IL-6 levels as independent risk predictors for PN. Assessing these parameters in the early stages facilitates the identification of high-risk patients, allowing for targeted preventive strategies and personalized nursing interventions in MM patients which can reduce PN incidence and enhance overall clinical outcomes.