Sales of over-the-counter products containing codeine in 31 countries, 2013-2019: a retrospective observational study
Notice bibliographique
Résumé
ABSTRACT Introduction Opioid prescribing trends have been investigated in many countries. However, the patterns of over-the-counter purchases of opioids without a prescription, such as codeine combinations, are mostly unknown. Objective We aimed to assess national sales and expenditure trends of over-the-counter codeine-containing products purchased in countries with available data over six years. Methods We conducted a retrospective observational study using electronic point-of-sale data from the human data science company, IQVIA , for countries that had such data, including Argentina, Belgium, Brazil, Bulgaria, Canada, Croatia, Estonia, Finland, France, Germany, Greece, Ireland, Italy, Japan, Latvia, Lithuania, Mexico, The Netherlands, Poland, Portugal, Romania, Russia, Serbia, Slovakia, Slovenia, South Africa, Spain, Switzerland, Thailand, the UK, and the USA. We calculated annual mean sales (dosage units per 1000 of the population) and public expenditure (GBP, £ per 1000 population) for each country between April 2013 and March 2019 and adjusted for data coverage reported by IQVIA . We quantified changes over time and the types of products sold. Results 31.5 billion dosage units (adjusted: 42.8 billion dosage units) of codeine, costing £2.55 billion (adjusted: £3.68 billion), were sold over-the-counter in 31 countries between April 2013 and March 2019. Total adjusted sales increased by 11% (3911 dosage units/1000 population in 2013 to 4358 in 2019) and adjusted public expenditure increased by 72% (£263/1000 in 2013 to £451/1000 in 2019). Sales were not equally distributed; South Africa sold the most (36 mean dosage units/person), followed by Ireland (30 mean dosage units/person), France (20 mean dosage units/person), the UK (17.2 mean dosage units/person), and Latvia (16.8 mean dosage units/person). Types of products (n=569) and formulations (n=12) sold varied. Conclusion In many parts of the world, substantial numbers of people may be purchasing and consuming codeine from over-the-counter products. Clinicians should ask patients about their use of over-the-counter products, and public health measures are required to improve the collection of sales data and the safety of such products. Study protocol pre-registration https://osf.io/ay4mc The pre-print version of this work is available on medRxiv: https://doi.org/10.1101/2021.04.21.21255888 Key points Codeine is one of the most accessible pain medicines available worldwide, yet data on its use as an over-the-counter drug has been limited. We found that total sales and expenditure of over-the-counter products containing codeine increased from April 2013 to March 2019, but there was substantial variation in mean sales between countries and the coverage of data reported by IQVIA , with South Africa, France, Japan, the UK, and Poland accounting for 90% of all sales data. In countries with access to over-the-counter codeine products, sales data should be collected, made available, and reviewed to inform regulatory decisions and public health measures to ensure safety.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».