Innovative Statistical Model Uncover Effective Herbal Medicines Among Personalized Treatment Plans in Persian Medicine: A Small-Scale Study in Type 2 Diabetes

In holistic medicine, developing personalized treatment plans is challenging due to the multitude of possible therapy combinations. This study introduces the use of a statistical approach to identify the most effective herbal medicines prescribed in Persian medicine (PM) in a small-scale sample of patients with type 2 diabetes mellitus (T2DM). This prospective observational cohort study was conducted with 47 patients with T2DM referred to Behesht Clinic in Tehran, Iran. A physician prescribed individualized PM treatment for T2DM and related systemic issues. The fasting blood sugar (FBS) level of each patient was recorded at initial and two follow-up visits, with visit intervals and treatment modifications determined by patient health status. Patients who completed two follow-up visits were included in the final analysis ( = 27). Data were analyzed using R software. A general linear model was assumed for the mean response, along with an exponential covariance pattern model, to manage irregularly timed measurements. Two fitted models showed that, after adjusting for confounders, the use of the "Diabetes Capsule" significantly reduced the average FBS by 17.14 mmol/L ( = 0.046). For each unit increase in the consumption of "Diabetes Capsule" or "Hab-e-Amber Momiai," the average FBS decreased by 15.22 mmol/L ( = 0.015) and 14.14 mmol/L ( = 0.047), respectively. It is possible to observe which medications are most effective, even when treatments are applied in a holistic and personalized fashion. Preliminary studies such as these may identify promising products for testing in clinical trials conducted under standardized conditions, to inform initial choices for future personalized treatments.