Prognostic Factor Research in Homeopathy: Overview of the Method, with Insights from Condition-Confined Studies

A prognostic factor (PF) refers to any feature of a disease or a characteristic of a patient that can be used to predict the likely outcome or course of a disease in an individual. Prognostic factor research (PFR), which is relatively new in homeopathy, focuses on investigating PFs and helps in therapeutic decision-making. The main challenge is the large number of eligible symptoms, but these can be reduced by condition-confined assessment, in which PFR is restricted to sub-populations of patients suffering from the same disease or condition. Condition-confined PFR (CC-PFR) identifies useful medicines for a given disease and compares with great precision different medicines regarding their relationship with common symptoms.

To overview PFR and the findings from CC-PFR studies in homeopathy to date.

A review of PFR, followed by a summary of six CC-PFR studies in homeopathy for coronavirus disease 2019 (COVID-19) was performed, outlining the methods, the challenges, the interpretation of outcomes and the lessons learned from each of the six studies in considering the further development of this model.

The six CC-PFR studies during COVID-19 identified PFs for the 10 most frequently used medicines: Bry, Ars, Puls, Gels, Bell, Hep, Nux-v, Phos, Puls and Rhus-t. These PFs usually contain common symptoms, which in combination become 'specific' enough to select a medicine. These PFs or symptoms also helped to differentiate between these 10 medicines. This model was reproducible and the outcomes were verifiable in the subsequent waves of COVID-19. The outcomes of CC-PFR studies were mostly generalisable and resulted in the preparation of a mini-repertory and repertorisation app. However, these studies revealed key issues. The main problems were the reliability of observations, identification of biases and assessing causality. The quality of PFR data depends on the scientific skills of practitioners, who are typically not trained researchers. Thus, they require additional training in data collection, methods, management of bias and causal analysis.

CC-PFR improves the reliable use of common symptoms and thus reduces the inappropriate use of peculiar symptoms based on confirmation bias. CC-PFR studies may be helpful in diseases where rare and peculiar symptoms are difficult to find, for example in one-sided ailments, and in epidemic diseases. PFR, however, requires reliable observations by the participating practitioners. Hence, training and encouragement of clinicians is needed to develop the existing data and integrate research into everyday clinical practice.