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Commentary on Hickman <i>et al.</i> (2009): The place of risk in drug policies

2009· letter· en· W1907299044 on OpenAlexaff
Robin Room, Jürgen Rehm

Bibliographic record

VenueAddiction · 2009
Typeletter
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsNumber needed to treatAbsolute risk reductionPopulationCannabisPsychologyRelative riskPsychiatryMedicineConfidence intervalEnvironmental health

Abstract

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The calculations by Hickman and colleagues [1] are necessarily approximate. They rely on general population surveys concerning incidence of psychiatric conditions and on cohort studies, through meta-analyses, for the relative risks based on the association of cannabis use with psychosis. This is an association where, as they and major reviews [e.g. 2, 3] acknowledge, the causal connection remains in contention. But the calculations are nevertheless very useful, giving us a sense of the order of magnitude of the potential risks and allowing us to put them in a comparative perspective with other risks from substance use and common behaviours. Are the risks as Hickman et al. calculate them high or low? There is of course no absolute answer to the question, but we can put them into perspective by comparing them with other risks of daily life. Hickman and colleagues do, themselves, provide a comparative frame in terms of ‘number needed to treat’ (NNT) to prevent cases of various diseases. By this comparison, the NNT in preventing cannabis use to prevent one case of schizophrenia is more than an order of magnitude higher than the NNTs for the three preventive scenarios they cite for other diseases. But in considering drug policy, particularly a prohibitive policy as in the UK for cannabis, it is arguably more relevant to consider the relative risk of the behaviour itself. One standard comparison here is in terms of lifetime risk of death from a behaviour. The outcome in terms of which Hickman et al. are calculating is the onset of a mental illness, which is less final and usually considered a lesser adverse fate than death. Recasting their calculation in terms of the risk of death would probably make the odds at least a further order of magnitude smaller. But if we accept their frame and make calculations based on the numbers they give for absolute risk of psychotic and schizophrenic disorders, and on the relative risks from the meta-analyses, then the lifetime risk for developing schizophrenic disorders given adult lifetime heavy cannabis use would be about 1.1% for men and 0.4% for women, and given adult lifetime lighter cannabis use would be 0.7% for men, and 0.3% for women. These calculations assume that the cannabis use is ongoing at the level described from age 16 to age 39 inclusive without any interruption, obviously a very unrealistic assumption. For psychotic disorders, the respective lifetime risks were 2.5% (M) and 1.6% (W) for heavy cannabis consumption, and 1.6% (M) and 1.0% (W) for lighter use. Up-to-date calculations for lifetime risks of death are surprisingly scarce. But if we take a compilation in the US in 1979 [4] as a basis, each of the following weekly behaviours if kept up for 50 years would carry a risk of death of 1 in 100: travelling 6189 km by jet plane every week; 1857 km by car; 62 km by bicycle; one hour by canoe; or smoking 5 cigarettes per week. Recent calculations underlying the new Australian guidelines on low-risk alcohol consumption [5, 6] imply that the risk of dying of an alcohol-related cause for a man drinking up to the current UK ‘sensible drinking’ guideline [7] for males of no more than four UK standard drinks per day is about 3.1 in 100, and for a woman drinking up to the guideline for females of three UK standard drinks per day about 1.4 in 100 [6, pp. 48–49]. By these standards, the risks that Hickman et al. calculate are well within the range of what is commonly found to be acceptable risks for voluntary risky behaviours. However, it should be noted that possible adverse effects of cannabis are not limited to schizophrenia and psychosis. Risks are better established, in fact, for other adverse outcomes of cannabis use, such as driving casualties [8], although the total risks seem to be substantially less than for alcohol, for instance [9, 10]. So why the current focus on schizophrenia, which seems to have been a key consideration, as Hickman and colleagues note, in the British government's decision to reclassify cannabis back to a more ‘dangerous’ category? One possible answer is in the quandaries of a particular profession: psychiatry. When it comes to behavioural preventive approaches, psychiatry has had relatively little to offer, at least in its heartland of serious mental illness such as schizophrenia or psychosis. Preventing schizophrenia by tackling cannabis use may have thus seemed an opportunity for psychiatrists to make the most of. A second answer, clearly, is that values trump risk calculations. When there is a pre-existing normative position, calculating actual levels of risk is brushed aside and seen as irrelevant or even an impediment. Any level of risk, however small, becomes an apparently scientific justification for the desired policy outcome. But risk is a part of the human condition, and a rational drug policy cannot be based on its complete elimination. Calculations like those of Hickman et al. point the way to a more reasoned discussion of drug policies. None

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.279
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2009
Admission routes1
Has abstractyes

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