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Record W2990080012 · doi:10.1093/alcalc/agz083

Baclofen and Alcohol Use Disorders: Breakthrough or Great White Elephant?

2019· article· en· W2990080012 on OpenAlexaffabout
Alain Braillon, Florian Naudet, Ioana A. Cristea, Joel Lexchin

Bibliographic record

VenueAlcohol and Alcoholism · 2019
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsYork University
Fundersnot available
KeywordsBaclofenMedicineAnesthesiaPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

On 23 October 2018, the French drug agency granted Ethypharm, a French corporation, marketing authorization for baclofen in the treatment of alcohol use disorders (AUD). This is most unusual as applications for therapeutic improvements almost always proceed through a centralized process at the European Medicines Agency (EMA) and cover the entire European Union. Here, we recount the history of baclofen for AUD in France. The use of baclofen for AUD began a decade ago when a cardiologist, Olivier Ameisen, published a book, ‘Le Dernier Verre’ [The Last Glass], reporting his own experience with baclofen in withdrawing from alcohol use. Following this and other publications, many general practitioners and psychiatrists endorsed off-label use, with some promoting it on social networks. As a result, off-label use became increasingly frequent. In addition, baclofen was reputed to reduce harm by slightly reducing the volume of alcohol consumed by people, despite them having a long pattern of harmful consumption. In 2013, the independent French drug bulletin Prescrire International concluded that more data were ‘needed on the efficacy and adverse effects of baclofen in alcohol dependence, compared with other options. Patients who … decide to try baclofen as a last resort should be included in comparative clinical studies’ (Prescrire Editorial Staff, 2013). Despite that conclusion, a year later, the French Agency granted a Temporary Use Recommendation (TUR) to allow oversight of the widespread off-label use of baclofen. The TUR was restricted to highly selected patients who had failed recommended treatments and had no other comorbidities and where prescribers were required to use Electronic Health Records (ERH) for monitoring. The TUR was a temporary policy pending results of two adequately sized French trials, but it was renewed twice in 2017. This renewal occurred although only 5300 individuals from a population of tens of thousands receiving baclofen were being monitored with ERH by 2015 (Degrassat-Théas et al., 2015) and the negative results of a large-scale French pharmacoepidemiological study in patients with AUD. The results of that study, which were publicly available in early July 2017, demonstrated a twofold increase in dose-dependent mortality with baclofen vs. approved drugs (acamprosate and naltrexone), a conclusion that the authors felt was justified despite acknowledging some limitations in their data (Chaignot et al., 2018). A meta-analysis, available in September 2017, failed to show any convincing benefit from baclofen in harm reduction (Palpacuer et al., 2018). Although there are a number of other meta-analyses looking at the effectiveness of baclofen, Cochrane reviews are generally considered methodologically the strongest. A 2018 Cochrane review of 12 randomized controlled trials concluded that compared with placebo, baclofen made little or no difference to participants who dropped out from treatment or dropped out due to adverse events and that it probably made little difference to the number of participants who start drinking again or to how much or how often they drank (Minozzi et al., 2018). In July 2018, the Agency held a 2-day public hearing on the use of baclofen for AUD, although a Special Scientific Committee had already concluded that the benefit/harm ratio of baclofen in AUD was negative (Naudet and Braillon, 2018). The Committee’s assessment was based on the two French large trials. In the first, the percentage of abstinent patients over 20 consecutive weeks was not significantly different between baclofen and placebo (OR 1.20; 95% CI 0.58–2.50; P = 0.62) (Reynaud et al., 2017). The second (NCT01604330) was completed in October 2015, but is still unpublished. Preliminary results presented at a conference in Berlin in 2016 showed a twofold increase in mortality with baclofen. Seemingly ignoring the finding of the Special Scientific Committee, in October 2018, the Agency’s director gave approval for the use of baclofen in alcohol-dependent patients (at 80 mg dose) (Naudet and Braillon, 2018). Although the still unpublished study was partly funded by the French Department of Health, the sponsor (Assistance Publique Hôpitaux de Paris) contractually transferred the data to Ethypharm, which performed its own statistical analysis, dropping the original primary outcome registered at the time of the funding application (the proportion of patients who abstain from alcohol consumption and patients with low-risk consumption at 12 months) and substituting an unplanned outcome (the variation in total alcohol consumption between 1 and 6 months of treatment). (Naudet and Braillon, 2018) We (A.B. and F.N.) failed to get access to trial data from the Agency and Ethypharm when we called for an independent reanalysis as part of the Restoring Invisible and Abandoned Trials initiative. Pierre Ducimetière, the Chairman of the Special Scientific Committee, stated ‘[he] well understood that the benefit-risk assessment [of baclofen] was only one element, among others, [behind the Agency’s decision]’ (A Braillon, personal communication). A full assessment of the results awaits publication of the trial’s results. Drug approvals are being conducted more rapidly and with poorly relevant surrogates in highly selected patients, while withdrawals are too slow when there is evidence of serious safety issues (Onakpoya et al., 2015). The French Agency went even further, blatantly ignoring the motto ‘first do not harm’. None. A.B. and F.N. are unpaid experts at the French drug agency. They were not invited to the so-called public hearing about baclofen although their early application for participating was acknowledged. A.B. and F.N. are among industry independent experts from Jeanne Lenzer’s list (https://jeannelenzer.com/list-independent-experts). In 2016–2019, J.L. was a paid consultant on two projects: one looking at developing principles for conservative diagnosis (Gordon and Betty Moore Foundation) and a second deciding what drugs should be provided free of charge by general practitioners (Government of Canada, Ontario Supporting Patient Oriented Research Support Unit and the St Michael’s Hospital Foundation). He also received payment for being on a panel at the American Diabetes Association, for a talk at the Toronto Reference Library, for writing a brief in an action for side effects of a drug for Michael F. Smith, Lawyer and from the Canadian Institutes of Health Research for presenting at a workshop on conflict-of-interest in clinical practice guidelines. He is currently a member of research groups that are receiving money from the Canadian Institutes of Health Research and the Australian National Health and Medical Research Council. He is a member of the Foundation Board of Health Action International and the Board of Canadian Doctors for Medicare. He receives royalties from University of Toronto Press and James Lorimer & Co. Ltd. for books he has written.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.004
Scholarly communication0.0060.007
Open science0.0010.002
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0170.007

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 head0.033
GPT teacher head0.282
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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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Citations10
Published2019
Admission routes2
Has abstractyes

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