Development of a Prognostic Factor Prediction Model in Patients with Musculoskeletal Pain Treated with Homeopathy: An Individual Patient Data Meta-Analysis of Three Randomized Clinical Trials.

BACKGROUND Prognostic factor research methodology has not yet been applied to randomized clinical trial data of homeopathic medicines. OBJECTIVES To investigate the principle of individualization in homeopathy by developing a prognostic factor prediction model. METHOD A pooled, in-dividual patient data meta-analysis of 3 randomized trials -investigating the efficacy of a homeopathic gel (Spiroflor SRL®) containing Rhus toxicodendron as a key ingredient in osteoarthritis of the knee and acute low back pain. The prognostic value of a predefined set of 5 typical R. toxicodendron symptoms was investigated by assessing treatment-by-symptom interactions on pain as an outcome measure in a regression model. RESULTS The pooled dataset consisted of 284 patients in the Spiroflor SRL group and 275 patients in the control group. Adjusted for pain at baseline, a statistically significant effect modification for the symptoms "numbness or tingling of the affected part" (+2.0 mm VAS; p = 0.02), "amelioration by movement" (-5.6 mm VAS; p = 0.01), and "amelioration of pain by local heat" (+7.0 mm VAS; p = 0.02) was found. CONCLUSIONS Investigating aspects of treatment individualization in homeopathy using randomized trial data and standard meta-analytical techniques is possible. The symptom amelioration by local heat is of possible value as a homeopathic symptom (prognostic factor) predicting an increased likelihood of pain relief following treatment with the homeopathic product.