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.

Keywords: Individual patient data meta-analysis; Prognostic factor research; Spiroflor SRL® gel; Treatment individualization.