By Dr. Benjamin Caplan, MD | Board-Certified Family Physician, CMO at CED Clinic | Evidence Watch
An international panel of 12 experts reached consensus on 40 factors that should be assessed before rheumatology patients use cannabis, including age, mental health history, substance use history, and details about how cannabis is consumed. While this fills a genuine gap in rheumatology-specific cannabis guidance, the resulting tool has not yet been tested in real patients and cannot yet be relied upon to predict harm.
Expert Panel Identifies Key Risk Factors for Cannabis Use in Rheumatology Patients
A Delphi consensus study outlines what a structured cannabis risk assessment tool for rheumatology should include, drawing on international expert opinion across demographics, medical history, lifestyle, and consumption patterns, but the tool itself has not yet been clinically validated against patient outcomes and remains at the item-generation stage of development.
#72
Strong Clinical Relevance
Addresses a meaningful gap in rheumatology cannabis guidance, though the tool requires validation before clinical deployment.
Rheumatology
Delphi Consensus
Drug Interactions
Clinical Tool Development
Cannabis use is rising among people living with rheumatologic diseases, driven by unmet needs in pain management and by increasingly permissive legal environments. Yet clinicians who encounter these patients have no disease-specific tool to guide risk assessment before or during cannabis use. Existing general-purpose cannabis screening instruments were not designed to account for the immunosuppressive therapies, biologic agents, and neuropsychiatric manifestations that define rheumatology practice. The absence of a structured, validated framework leaves risk conversations unmoored from evidence and inconsistent across clinical settings.
Rheumatology patients who use cannabis face a complex clinical landscape in which autoimmune disease activity, polypharmacy with disease-modifying antirheumatic drugs and biologics, and neuropsychiatric comorbidities all intersect with the pharmacology of cannabinoids. Recognizing that no existing cannabis screening tool addresses these disease-specific variables, an international research team conducted a three-round Delphi consensus study to identify and refine candidate items for a rheumatology-tailored cannabis risk assessment instrument. Statements were generated from a prior systematic literature review, patient and provider focus groups, and multidisciplinary team input, then pilot-tested with patient partners before being formally rated by experts recruited from professional networks and literature searches.
Twelve experts participated with a 100% response rate in round one. Of the 45 candidate items assessed, 32 reached the 75% consensus threshold in the first round and an additional 8 achieved consensus in the second, yielding 40 agreed-upon items across domains including demographics (age, gender), medical history (substance use disorders, schizophrenia), cannabis consumption patterns (age of first use, route, frequency, THC-to-CBD ratio), lifestyle factors, and socioeconomic conditions. All 40 items were confirmed in a third validation round. Five items did not reach consensus, reflecting genuine areas of expert uncertainty. The primary limitation is fundamental: consensus on what should be assessed is not the same as evidence that these items predict cannabis-related harm. The authors explicitly identify clinical validation against real patient outcomes as the necessary next step before this tool can be implemented.
This study asks exactly the right question. In rheumatology, where patients are often on methotrexate, biologics, or combination immunosuppressive regimens, the risk profile of adding cannabis is genuinely different from what a general-purpose screening tool can capture. The Delphi process here was well-structured, and the domains they identified, particularly around consumption route, frequency, and age of first use, reflect the kinds of variables I find clinically meaningful when counseling patients. But the distance between an expert-generated item list and a validated bedside tool is enormous. We have seen consensus instruments stall at this stage before, and clinicians should not mistake this for a tool that is ready for deployment.
In practice, I already assess many of the variables these experts identified, including psychiatric history, substance use history, concurrent medications, and the specifics of what a patient is actually consuming. What I do not yet have is a scoring system that tells me, with any empirical precision, which combination of risk factors should change my recommendation. That is the part this study promises but cannot yet deliver. I look forward to the validation phase and would encourage rheumatologists to engage with the investigators when that work begins.
For clinicians managing rheumatologic disease, this study sits at the very beginning of the tool-development arc. It belongs alongside other Delphi-derived clinical instruments that required years of subsequent validation before earning a place in practice. The 40 consensus items provide a useful mental framework for what to ask patients about, and clinicians may find value in reviewing the domain categories to ensure their own intake conversations are thorough. However, the absence of weighting, scoring, or outcome data means no individual item or combination of items can be assigned a predictive value at this time.
From a pharmacological standpoint, the inclusion of drug interaction considerations is particularly important. THC and CBD are metabolized through cytochrome P450 pathways, notably CYP3A4 and CYP2C9, which overlap with the metabolism of methotrexate, leflunomide, and several biologic agents. Clinicians should be alert to potential changes in drug levels, hepatotoxicity risk, and immunomodulatory effects when patients add cannabinoids to existing regimens. Until a validated risk instrument exists, the most defensible clinical approach remains a thorough, individualized assessment that documents psychiatric history, substance use patterns, concurrent medications, and the specific cannabis product characteristics, including THC-to-CBD ratio, route, and frequency of use.

