A digital tool for multidimensional assessment and prediction of treatment effectiveness in chronic pain management - Philippe Rigoard; Amine Ounajim; Maarten Moens; Lisa Goudman; Manuel Roulaud; Nicolas Naiditch; Raouf Boukenna; Philippe Page; Bénédicte Bouche; Bertille Lorgeoux; Sandrine Baron; Kevin Nivole; et al. (iScience)
Summary: Given the multidimensional aspect of pain, the assessment of treatment efficacy is challenging. The prospective observational multicenter PREDIBACK study aimed to assess, compare, and predict the effectiveness of different treatments for persistent spinal pain syndrome type 2 (PSPS-T2) using a digital tool and the Multidimensional Clinical Response Index (MCRI) including pain intensity, functional disability, quality of life, anxiety and depression, and pain surface. Results indicated that neurostimulation was the most effective treatment at 3-, 6-, 9-, and 12-month follow-up compared to baseline, leading to significant improvements in pain, function, and quality of life, whereas optimized medical management (OMM) and spinal reoperation showed no significant benefits. Additionally, the study identified pain surface, BMI, and smoking status as predictors of treatment outcomes. These findings highlight the potential of digital medicine to improve patient care by providing data-driven insights and personalized treatment recommendations for PSPS-T2.