Systemic agent use and mental health outcomes among patients with psoriasis
Notice bibliographique
Résumé
Psoriasis is a chronic immune-mediated skin condition affecting 2.5% of the Canadian population. Moderate-to-severe psoriasis is associated with high risks of depression and anxiety. In randomized controlled trials, biologic agents had better efficacy for skin clearance and anxio-depressive symptom reduction than conventional systemic agents (CSA) in patients with moderate-to-severe psoriasis. However, because of their high acquisition costs, biologic agents are covered by the Quebec public drug plan only if CSA treatment fails or is contraindicated. The goal of my thesis was to assess patterns of CSA and biologic agents (tumor necrosis factor inhibitors and ustekinumab [TNFi/UST]) use and their association with mental health outcomes and costs among patients with psoriasis.In my four manuscripts, I used data from the province of Quebec health administrative databases (1997-2015) and conducted retrospective cohort studies of patients with psoriasis initiating a CSA. In manuscripts 1 and 2, I used the same cohort to describe patterns of CSA and TNFi/UST use and assess sex disparities in factors associated with treatment switch and discontinuation. My cohort included 1,644 patients. In manuscript 1, I examined the CSA as a class. The rates of switch (or add) TNFi/UST and CSA discontinuation were 44.5 and 364.9 per 1,000 person-years, respectively, with no differences between sexes. Older age was associated with a reduced risk of switch in both sexes. Obesity and longer psoriasis duration in males and NSAID use, and adjustment, somatoform and dissociative disorders in females were associated with increased risks of switch, while rheumatoid arthritis was associated with a reduced risk in females. Patients at lower risks of CSA discontinuation were those followed by a rheumatologist and those with an all-cause hospitalization in the previous year among males; and those with rheumatoid arthritis, those receiving hypoglycemic and lipid-lowering agents and those initiated on methotrexate (versus any other CSA) among females. In manuscript 2, I studied each CSA, separately. During follow-up, 312 patients switched to a different systemic agent, with 82.7% receiving another CSA and 17.3% a TNFi/UST.In manuscript 3, I described the trajectories of CSA and TNFi/UST use over a 2-year period and compared depression and anxiety-related health care costs between trajectory clusters. My cohort included 781 patients with no history of anxio-depressive disorders. Using sequence and hierarchical cluster analyses, I identified eight treatment trajectory clusters. The overall predicted mean annual cost per-patient was CAN$ 60. Compared to the cluster persistent methotrexate users, the clusters adding a TNFi/UST (cost ratio 3.63, 95% confidence interval, CI 1.47-5.97) and CSA discontinuation then restart on acitretin or multiple switches between CSA (cost ratio 13.30, 95% CI 5.76-22.47) had higher predicted mean costs. Female (versus male) patients had higher predicted mean costs (cost ratio 1.89, 95% CI 1.11-2.69). Results remained unchanged when adjustment disorder-related costs were also considered.In manuscript 4, I assessed the risk of mental health disorders (depression, anxiety and adjustment disorder) in patients initiated on a CSA who subsequently switched/added TNFi/UST (TNFi/UST users) versus (vs) those who did not (TNFi/UST non-users). TNFi/UST users were included in the cohort at the date of TNFi/UST initiation and TNFi/UST non-users were included at a matched date. I separated the TNFi/UST non-user group into those who were currently using a CSA (current CSA users) and those who were not (previous CSA users). My cohort included 183 TNFi/UST users, 625 current CSA users and 525 previous CSA users. Using marginal structural models, TNFi/UST (vs. previous CSA) users were at lower risk for mental health disorders (HR 0.48, 95% CI 0.28-0.94). The result for TNFi/UST vs current CSA users pointed to a non-significant lower risk
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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 ».