Evidence map›Paper›PMID 33563639›Full record

ArticleCMAJ open

Predictors of long-term use of prescription opioids in the community-dwelling population of adults without a cancer diagnosis: a retrospective cohort study.

Audrey Béliveau, Anne-Marie Castilloux, Cara Tannenbaum, Philippe Vincent, Cristiano Soares de Moura, Sasha Bernatsky, Yola Moride

Abstract read
In one paragraph

Article in CMAJ open. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Is otologic surgery contributing to the opioid epidemic?Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Audrey BéliveauFaculty of Pharmacy (Béliveau, Castilloux, Tannenbaum, Vincent, Moride), Université de Montréal; Institut universitaire de gériatrie de Montréal (Tannenbaum); Department of Pharmacy (Vincent), Institut universitaire en santé mentale de Montréal; Division of Clinical Epidemiology (Soares de Moura, Bernatsky), McGill University, Montréal, Que.; Rutgers, The State University of New Jersey (Moride), New Brunswick, NJ.
Anne-Marie CastillouxFaculty of Pharmacy (Béliveau, Castilloux, Tannenbaum, Vincent, Moride), Université de Montréal; Institut universitaire de gériatrie de Montréal (Tannenbaum); Department of Pharmacy (Vincent), Institut universitaire en santé mentale de Montréal; Division of Clinical Epidemiology (Soares de Moura, Bernatsky), McGill University, Montréal, Que.; Rutgers, The State University of New Jersey (Moride), New Brunswick, NJ.
Cara TannenbaumFaculty of Pharmacy (Béliveau, Castilloux, Tannenbaum, Vincent, Moride), Université de Montréal; Institut universitaire de gériatrie de Montréal (Tannenbaum); Department of Pharmacy (Vincent), Institut universitaire en santé mentale de Montréal; Division of Clinical Epidemiology (Soares de Moura, Bernatsky), McGill University, Montréal, Que.; Rutgers, The State University of New Jersey (Moride), New Brunswick, NJ.
Philippe VincentFaculty of Pharmacy (Béliveau, Castilloux, Tannenbaum, Vincent, Moride), Université de Montréal; Institut universitaire de gériatrie de Montréal (Tannenbaum); Department of Pharmacy (Vincent), Institut universitaire en santé mentale de Montréal; Division of Clinical Epidemiology (Soares de Moura, Bernatsky), McGill University, Montréal, Que.; Rutgers, The State University of New Jersey (Moride), New Brunswick, NJ.
Cristiano Soares de MouraFaculty of Pharmacy (Béliveau, Castilloux, Tannenbaum, Vincent, Moride), Université de Montréal; Institut universitaire de gériatrie de Montréal (Tannenbaum); Department of Pharmacy (Vincent), Institut universitaire en santé mentale de Montréal; Division of Clinical Epidemiology (Soares de Moura, Bernatsky), McGill University, Montréal, Que.; Rutgers, The State University of New Jersey (Moride), New Brunswick, NJ.
Sasha BernatskyFaculty of Pharmacy (Béliveau, Castilloux, Tannenbaum, Vincent, Moride), Université de Montréal; Institut universitaire de gériatrie de Montréal (Tannenbaum); Department of Pharmacy (Vincent), Institut universitaire en santé mentale de Montréal; Division of Clinical Epidemiology (Soares de Moura, Bernatsky), McGill University, Montréal, Que.; Rutgers, The State University of New Jersey (Moride), New Brunswick, NJ.
Yola MorideFaculty of Pharmacy (Béliveau, Castilloux, Tannenbaum, Vincent, Moride), Université de Montréal; Institut universitaire de gériatrie de Montréal (Tannenbaum); Department of Pharmacy (Vincent), Institut universitaire en santé mentale de Montréal; Division of Clinical Epidemiology (Soares de Moura, Bernatsky), McGill University, Montréal, Que.; Rutgers, The State University of New Jersey (Moride), New Brunswick, NJ yola.moride@umontreal.ca.

Funding

CIHR DES-149322
6 · The paper itself

Abstract

backgroundLong-term opioid use is a known risk factor for opioid-related harms. We aimed to identify risk factors for and predictors of long-term use of prescription opioids in the community-dwelling population of adults without a diagnosis of cancer, to inform practice change at the point of care.

methodsUsing Quebec administrative claims databases, we conducted a retrospective cohort study in a random sample of adult members (≥ 18 yr) of the public drug plan who did not have a cancer diagnosis and who initiated a prescription opioid in the outpatient setting between Jan. 1, 2012, and Dec. 31, 2016. The outcome of interest was long-term opioid use (≥ 90 consecutive days or ≥ 120 cumulative days over 12 mo). Potential predictors included sociodemographic factors, medical history, characteristics of the initial opioid prescription and prescriber's specialty. We used multivariable logistic regression to assess the association between each characteristic and long-term use. We used the area under the receiver operating characteristic curve to determine the predictive performance of full and parsimonious models.

resultsOf 124 664 eligible patients who initiated opioid therapy, 4172 (3.3%) progressed to long-term use of prescription opioids. The most important associated factors in the adjusted analysis were long-term prescription of acetaminophen-codeine (odds ratio [OR] 6.30, 95% confidence interval [CI] 4.99 to 7.96), prescription of a long-acting opioid at initiation (OR 6.02, 95% CI 5.31 to 6.84), initial supply of 30 days or more (OR 4.22, 95% CI 3.81 to 4.69), chronic pain (OR 2.41, 95% CI 2.16 to 2.69) and initial dose of at least 90 morphine milligram equivalents (MME) per day (OR 1.24, 95% CI 1.04 to 1.47). Our predictive model, including only the initial days' supply and chronic pain diagnosis, had area under the curve of 0.7618.

interpretationThis study identified factors associated with long-term prescription opioid use. Limiting the initial supply to no more than 7 days and limiting doses to 90 MME/day or less are actions that could be undertaken at the point of care.

Indexed as

Duration of TherapyAcetaminophenAcute PainAdolescentAdultAgedAge FactorsAnalgesics, OpioidChronic PainCodeineCohort StudiesDrug CombinationsFemaleHumansHydromorphoneIndependent LivingAcetaminophenacetaminophen, codeine drug combinationAnalgesics, OpioidCodeineDrug CombinationsHydromorphoneMorphineOxycodone

Identifiers

PMID33563639
PMCPMC8034379

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.