78% of UK Medical Cannabis Patients Showed Quality of Life Improvement | Research

The takeaway

The largest UK medical cannabis registry study found 78% of 8,945 patients showed improved quality of life over 24 months, with patient characteristics predicting response better than specific cannabis products.

Medical cannabis patients and prospective patients, prescribing clinicians, cannabis medicine researchers, and health policymakers.

What the researchers found

K-means clustering identified 10 trajectory groups, with 8 (representing 77.72% of patients) showing quality of life improvements. Over 70% reported improved EQ-5D-5L at each timepoint. At 24 months, 54.21% achieved clinically significant anxiety improvement and 44.07% significant sleep improvement. Adverse events were reported by 13.65%, mostly mild-moderate. Baseline patient characteristics predicted outcomes better than product type.

Why it matters

This is the largest and longest real-world medical cannabis outcomes study in the UK. The finding that patient characteristics matter more than specific products suggests prescribing should focus more on identifying likely responders than on product selection.

The numbers in context

8,945 patients. 10 trajectory clusters identified. 77.72% (6,952) in improving clusters. >70% improved EQ-5D-5L at each timepoint. 54.21% clinically significant GAD-7 improvement at 24 months. 44.07% significant SQS improvement. 13.65% reported AEs. 42.31% mild, 43.46% moderate.

How the study worked

Cohort study of 8,945 patients in the UK Medical Cannabis Registry with any qualifying indication. Patient-reported outcomes (EQ-5D-5L, GAD-7, SQS) collected at baseline, 1, 3, 6, 12, 18, and 24 months. Longitudinal k-means clustering on quality of life trajectories. Logistic regression identified response predictors.

What this study cannot tell us

Registry study without control group — can't separate treatment effect from natural disease course. Self-selected patients who stayed in the registry may be responders (survivorship bias). No placebo comparison. Self-reported outcomes. UK-specific regulatory context.

How to read the evidence

Large registry with long follow-up and sophisticated clustering analysis, but lacks control group and has survivorship bias.

When this study was published

Published in 2026, providing the most comprehensive UK real-world medical cannabis outcomes data available.

The bigger picture

Finding that treatment indication, severe anxiety, poor sleep, female sex, and cannabis-naïve status predict better response offers practical clinical guidance. Rather than trying different products until one works, clinicians can identify patients most likely to benefit upfront.

Questions still open

Would a controlled trial confirm these real-world response rates? Can the predictor profile be validated prospectively? Why does cannabis-naïve status predict better response?

Common questions

Does medical cannabis improve quality of life?

In this UK registry of nearly 9,000 patients, 78% showed quality of life improvements over 24 months, with over half achieving clinically meaningful improvements in anxiety and 44% in sleep. However, without a control group, some improvement may have occurred naturally.

Who responds best to medical cannabis?

Patients with severe anxiety, poor sleep quality, and those who were cannabis-naïve (hadn't used cannabis before) showed the best responses. Female patients and certain treatment indications also predicted better outcomes. Specific product type mattered less than these patient characteristics.

Read the original research

Clinical Outcomes and Patient Profiles in the UK Medical Cannabis Registry: A k-Means Clustering Analysis.

Journal of clinical pharmacology, 66(1), e70151

View on PubMed ↗Publisher’s paper ↗

Citation

Erridge, Simon; Clarke, Evonne; McLachlan, Katy; Coomber, Ross; Beri, Sushil; Khan, Shaheen; Weatherall, Mark W; Platt, Michael W; Rucker, James J; Mediano, Pedro A M; Sodergren, Mikael H. (2026). Clinical Outcomes and Patient Profiles in the UK Medical Cannabis Registry: A k-Means Clustering Analysis.. Journal of clinical pharmacology, 66(1), e70151. https://doi.org/10.1002/jcph.70151