Trajectory k-means clustering of 8945 patients in the UK Medical Cannabis Registry identified 10 distinct HRQoL response patterns over 24 months, with 77.72% of patients demonstrating improvements, and baseline patient characteristics being stronger predictors of favorable treatment response than product-specific factors.
Key Findings
Results
Ten distinct trajectory clusters of health-related quality of life outcomes were identified among patients prescribed cannabis-based medicinal products over 24 months.
8945 patients from the UK Medical Cannabis Registry were included in the analysis.
Longitudinal k-means clustering was performed on EQ-5D-5L index values.
The optimal number of clusters was selected via the gap statistic.
Eight of the ten clusters demonstrated HRQoL improvements, representing 77.72% of the cohort (n = 6952).
Outcome measures included EQ-5D-5L, GAD-7, and Single-Item Sleep Quality Scale (SQS) at baseline, 1, 3, 6, 12, 18, and 24 months.
Results
Over 70% of participants reported improved EQ-5D-5L index values at each measured timepoint.
EQ-5D-5L (EuroQol 5-Dimension 5-Level) was used as the primary health-related quality of life measure.
Improvements were sustained across all follow-up timepoints: 1, 3, 6, 12, 18, and 24 months.
The cohort included patients with any qualifying indication for medical cannabis.
Results
Clinically significant improvements in anxiety were reported by 54.21% of patients at 24 months.
54.21% (n = 4849) of patients achieved clinically significant improvements in GAD-7 (Generalized Anxiety Disorder-7) scores at 24 months.
GAD-7 was one of three patient-reported outcome measures completed at each timepoint.
This finding applied to the full cohort across all qualifying indications.
Results
Clinically significant improvements in sleep quality were reported by 44.07% of patients at 24 months.
44.07% (n = 3942) achieved clinically significant improvements in the Single-Item Sleep Quality Scale (SQS) at 24 months.
Sleep quality was measured using the Single-Item Sleep Quality Scale at each follow-up timepoint.
This represents a secondary patient-reported outcome in addition to general HRQoL and anxiety measures.
Results
Adverse events were reported by 13.65% of patients and were predominantly mild to moderate in severity.
Adverse events were reported by 13.65% (n = 1221) of patients.
The majority of adverse events were rated as mild (n = 4732; 42.31%) or moderate (n = 4860; 43.46%).
The adverse event profile was assessed across the full 24-month follow-up period.
Results
Baseline patient characteristics were stronger predictors of favorable treatment response than product-specific factors.
Univariable and multivariable logistic regression analyses were used to identify predictors of cluster membership.
Key baseline predictors of favorable treatment response included treatment indication, severe anxiety, poor sleep quality, female sex, and cannabis-naïve status.
Product-specific factors were less predictive of treatment outcomes compared to patient-level baseline characteristics.
These findings suggest patient selection criteria may be more important than specific CBMP product choice for predicting outcomes.
Results
Severe anxiety at baseline was identified as a predictor of favorable treatment response to cannabis-based medicinal products.
Severe anxiety was among the baseline characteristics identified through multivariable logistic regression as predicting cluster membership in favorable response groups.
This was assessed alongside other baseline predictors including treatment indication, poor sleep quality, female sex, and cannabis-naïve status.
The finding suggests patients with more severe anxiety symptoms at baseline may be more likely to experience meaningful improvement.
Results
Cannabis-naïve status at baseline was a predictor of favorable treatment response.
Cannabis-naïve status was identified as one of the stronger baseline predictors of favorable treatment response in the multivariable logistic regression analysis.
This predictor was identified alongside treatment indication, severe anxiety, poor sleep quality, and female sex.
The finding was derived from the UK Medical Cannabis Registry cohort of 8945 patients with any qualifying indication.
What This Means
This research suggests that most patients prescribed medical cannabis products in the United Kingdom experienced improvements in their overall health and wellbeing over a two-year period. The study analyzed data from nearly 9,000 patients enrolled in the UK Medical Cannabis Registry, tracking their self-reported quality of life, anxiety levels, and sleep quality at regular intervals from the start of treatment through 24 months. Using a statistical technique called k-means clustering, researchers identified 10 distinct patterns of how patients' health changed over time, and found that approximately 78% of patients fell into groups showing improvement in overall health-related quality of life. More than half of patients also reported meaningful reductions in anxiety, and about 44% reported meaningful improvements in sleep quality.
The study also found that side effects were relatively common — reported by about 14% of patients — but were mostly mild or moderate in severity. Importantly, researchers found that characteristics of the patient at the start of treatment were better predictors of who would respond well than the specific type of medical cannabis product they were prescribed. Patients who were more likely to benefit included those who had never used cannabis before, those with severe anxiety or poor sleep at the start of treatment, women, and those with certain medical conditions.
This research suggests that identifying the right patients for medical cannabis treatment may matter more than which specific product is chosen. However, because this was an observational registry study without a control group, it is not possible to determine how much of the improvement was due to the medical cannabis itself versus other factors such as natural recovery over time or the effect of receiving medical care. The findings provide useful information about real-world patterns of medical cannabis use in the UK and may help clinicians identify which patients are most likely to benefit from this treatment.
Erridge S, Clarke E, McLachlan K, Coomber R, Beri S, Khan S, et al.. (2026). Clinical Outcomes and Patient Profiles in the UK Medical Cannabis Registry: A k-Means Clustering Analysis.. Journal of clinical pharmacology. https://doi.org/10.1002/jcph.70151