Opioids in COPD: the ‘whole picture’ includes results from real‐world, population‐based observational studies
Notice bibliographique
Résumé
We thank Currow et al. for their interest in our work 1 and for their comments. We respectfully point out that we did not condemn in our paper the careful prescription of low dose opioids for refractory dyspnoea in selected patients with advanced COPD. We have also not used exaggerated language in our paper, such as ‘disasters await clinicians who prescribe opioids in people with COPD’, as Currow et al. have written. On the contrary, we have acknowledged in our introduction the results of several clinical trials showing that systemic opioids can safely reduce dyspnoea in individuals with advanced COPD and that several respiratory guidelines support the use of opioids in COPD for refractory dyspnoea 1. The purpose of our paper was explicitly stated: ‘to describe the scope, pattern, and patient characteristics associated with incident opioid use among older adults with COPD’ 1. While selected COPD patients may indeed benefit from carefully prescribed opioids for refractory dyspnoea, the results of our ‘real-world’, population-based study show that opioids are not being used in such a manner among older adults with COPD. Our study results show that frequent drug use, patterns potentially indicative of excessive usage, drug receipt during periods of acute respiratory exacerbation and drug receipt among individuals with concerning comorbidities characterize incident opioid use in the older adult COPD population in Ontario, Canada 1. We feel that these drug use patterns in opioid-naive individuals do raise potential safety concerns. Previously published observational research by Currow et al. using Swedish health administrative data also support the observation that carefully prescribed, low dose opioids are not the norm in vulnerable patients with advanced COPD. The majority of opioid recipients (298/509 or 59%) were receiving what the authors defined as high dose opioids (>30 mg oral morphine equivalents day–1) and this was found to be associated with increased all-cause mortality risk 2. There is nothing sinister about the fact that we did not present data relating to possible adverse respiratory outcomes associated with incident opioid drug use in our paper. We were explicit about the purpose of the present study and our future plans: ‘our present focus was on describing patterns of opioid use in the older adult COPD population. Examining for potential respiratory-related health outcomes of opioid use among older adults with COPD will be undertaken next’ 1. We kindly ask that Currow et al. stay tuned for our future work. While several clinical trials demonstrate that opioids can reduce refractory dyspnoea in advanced COPD, it is also important to consider the features of these trials that limit their ability to evaluate adequately and comprehensively for possible drug harms: small numbers of subjects, selected subjects (e.g. individuals with certain comorbidities or individuals with a history of previous adverse reactions to opioids were sometimes excluded), low or single opioid dosing levels, short follow-up durations and subjects who perceived no benefit, experienced adverse events or died, were sometimes excluded from final analyses. In contrast, population-based observational studies are well-suited to evaluate for possible drug-related adverse events, as they typically include larger numbers of subjects, individuals that clinical trials often exclude (e.g. those with comorbidities), longer follow-up durations, ‘real-world’ drug dosing and use and less subject drop-out. While we agree that confounding by indication cannot be entirely eliminated in observational studies evaluating drug harm, this bias can be minimized by employing certain methods, such as evaluating for adverse outcomes among individuals with differing disease severity, including those with the least severe disease, in whom confounding by indication is less likely to be an issue 3. Results of ‘real-world’, population-based, observational studies complement the results of clinical trials and help give a more complete picture regarding the use, and potential benefits and adverse effects, of drug therapy 4. All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare NTV had support from The Lung Association-Canadian Thoracic Society National Grant Review/Grant-In-Aid for the submitted work, SSG and DO had no support from any organization for the submitted work, DO received grants and personal fees from Boehringer Ingelheim, grants and personal fees from Astra Zeneca, grants from GlaxoSmithKline, personal fees from Novartis, in the previous 3 years and NTV and SSG had no financial relationships with any organizations that might have an interest in the submitted work in the previous 3 years. NTV, SSG and DO had no other relationships or activities that could appear to have influenced the submitted work.
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 | 0,126 | 0,366 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,006 |
| Bibliométrie | 0,004 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,006 | 0,009 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,006 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».