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Enregistrement W4410715726 · doi:10.3899/jrheum.2025-0390.o030

DIRECT AND INDIRECT COSTS ASSOCIATED WITH DAMAGE ACCRUAL: RESULTS FROM THE SYSTEMIC LUPUS INTERNATIONAL COLLABORATING CLINICS (SLICC) INCEPTION COHORT

2025· article· en· W4410715726 sur OpenAlexaffvenueabout
Megan R.W. Barber, John Hanly, Murray B. Urowitz, Ian N Bruce, Yvan St. Pierre, Caroline Gordon, Sang‐Cheol Bae, Juanita Romero‐Díaz, Jorge Sánchez‐Guerrero, Sasha Bernatsky, Daniel J. Wallace, David Isenberg, Anisur Rahman, Joan T. Merrill, Paul R. Fortin, Dafna D. Gladman, Michelle Petri, Ellen M. Ginzler, Mary-Anne Dooley, Rosalind Ramsey‐Goldman, Susan Manzi, Andreas Jönsen, G S Alarcón, Ronald Van Vollenhoven, Cynthia Aranow, Meggan Mackay, Guillermo Ruiz‐Irastorza, S. Sam Lim, Murat İnanç, Kenneth Kalunian, Søren Jacobsen, Christine Peschken, Diane L Kamen, Anca Askanase, Ann E. Clarke

Notice bibliographique

RevueThe Journal of Rheumatology · 2025
Typearticle
Langueen
DomaineHealth Professions
ThématiqueQuality and Safety in Healthcare
Établissements canadiensUniversity of ManitobaUniversité LavalCentre hospitalier de l'Université LavalUniversity of TorontoDalhousie UniversityMcGill University Health CentreUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésMedicineAccrualSystemic lupusCohortSystemic lupus erythematosusCohort studyPhysical therapyInternal medicineDiseaseAccounting

Résumé

récupéré en direct d'OpenAlex

O030 / #400 Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes ABSTRACT CONCURRENT SESSION 05: EMERGING INSIGHTS ON THE MANAGEMENT OF LUPUS MANIFESTATIONS AND COMORBIDITIES 23-05-2025 1:40 PM - 2:40 PM Background/Purpose We described the direct healthcare costs associated with damage accrual in patients in the Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort.[1] However, our estimates only included partial direct costs and indirect costs from lost productivity were not included. We supplemented our primary data by querying a cohort subset on all healthcare use and lost time in paid/unpaid labor and provide estimates of complete direct and indirect costs for the full cohort, stratified by damage. Methods Between 1999 and 2011, SLE patients from 31 centers in 10 countries were enrolled into the SLICC Inception Cohort within 15 months of diagnosis and data on disease damage (SLICC/ACR Damage Index [SDI]) and limited healthcare use (ie, hospitalizations, medications, and dialysis) were collected annually through to July 2022. Starting in 2015, 18 sites collected supplemental economic data annually (ie, visits to physicians, nonphysician healthcare professionals, and the emergency room, laboratory tests, radiological/other diagnostic procedures, outpatient surgeries, help obtaining medical care, and lost time in paid/unpaid labor). Direct costs were calculated by multiplying each health resource by its corresponding 2023 Canadian unit cost. Total indirect costs included: 1) absenteeism (time lost from paid labor because of illness), 2) presenteeism (degree of patient self-reported productivity impairment in paid/unpaid labor, based on a visual analog scale), and 3) opportunity costs (additional time patients would be working in paid/unpaid labor if not ill). Opportunity costs were calculated as the difference between the time patients reported working vs that worked by an age, sex, and geographic-matched general population in paid/unpaid labor. Indirect costs from paid/unpaid labor were valued using age-and-sex-specific wages from Statistics Canada. Multiple imputation was used to predict missing cost values for the patients in the full cohort who provided only utilization data for hospitalizations, medications, and dialysis for all observations. At each assessment, patients were assigned to one of 6 damage states (ie, SDI = 0, 1, 2, 3, 4, ≥ 5) and annual costs, both unimputed and including imputations, were stratified by SDI score. Means and 95% confidence intervals were computed and compared. Results 1694 patients (88.8% female, 48.9% White, mean age at diagnosis 34.6 years, mean disease duration at cohort enrollment 0.5 years), were followed for a mean of 10.5 (SD 5.3) years. Of these 1694 patients, 766 (89.7% female, 41.4% White, mean age at diagnosis 33.0 years, mean disease duration at cohort enrollment 0.4 years) completed the supplemental economic questionnaire. Their mean disease duration at the time of introduction of the supplemental questionnaire was 10.9 (range 3.9-19.5) years and this cohort subset provided this additional economic data for a mean of 3.5 (SD 1.9) years. Among the cohort subset completing the supplemental economic questionnaire, on average, indirect costs, primarily from unpaid labor, accounted for 81.1% of total costs (Table 1). For the full cohort, annual direct and indirect costs increased with increasing SDI (SDI=0: total costs $33,812 [95% CI $31,088, $36,537]; SDI ≥ 5: total costs $90,839 [95% CI $82,275, $99,403]) (Table 2). Table 1. Annual complete direct, indirect, and total costs (in 2023 Canadian dollars) for the cohort subset providing complete cost data, stratified by SDI (n = 2414 observations). Values are means. Table 2. Annual imputed complete direct, indirect, and total costs (in 2023 Canadian dollars) for the full cohort, stratified by SDI (n = 15,106 observations). Conclusions Patients with the highest vs the lowest SDIs incurred complete direct costs that were 5.9-fold higher and indirect costs 2.1-fold higher. However, patients with no or minimal damage still experienced considerably reduced productivity. Indirect costs exceeded direct, on average, by 4.5-fold, underscoring the importance of incorporating lost productivity in estimating the economic burden of SLE. References: [1.] Barber MRW. Arthritis Care Res 2020;72:1800-8.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,011
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,053
Score d'incertitude au seuil0,105

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,011
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0020,003
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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.

Tête enseignante Opus0,044
Tête enseignante GPT0,402
Écart entre enseignants0,357 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission3
Résumé présentoui

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