INTERVAL-CENSORED OUTCOMES AND FLARE RISK AFTER HYDROXYCHLOROQUINE TAPERING/CESSATION: SENSITIVITY ANALYSES OF SYSTEMIC LUPUS INTERNATIONAL COLLABORATING CLINICS (SLICC) INCEPTION COHORT DATA
Notice bibliographique
Résumé
O052 / #245 Topic: AS24 - SLE-Treatment ABSTRACT CONCURRENT SESSION 09: SLE THERAPY – REVISITING OLD DRUGS AND UNLOCKING HIDDEN POTENTIAL OF NEW MEDICATIONS 24-05-2025 10:40 AM - 11:40 AM Background/Purpose We previously evaluated hydroxychloroquine (HCQ) tapering/cessation and risk of systemic lupus erythematosus (SLE) flare in the SLICC Inception cohort. However, in our approach we did not account for potential bias due to interval-censored (IC) outcomes, where exact timing of events are unknown. Our objective was to address this, with alternative approaches to defining timing of IC events, including the Simulation Extrapolation (SIMEX) approach. Methods We evaluated 1,543 members of the SLICC Inception cohort (January 1999 to January 2019). Adults (18+) with SLE were enrolled in this cohort within 15 months of diagnosis and followed annually with questionnaires and physician assessment. In our time-to-event analyses, time-zero was defined as cohort entry if a subject was taking HCQ at the time, or the first prescription of HCQ otherwise. HCQ tapering/cessation was defined as the first cessation or decreased dose of HCQ and modeled as a binary time-varying exposure. Multivariable proportional hazard regression assessed associations between HCQ tapering/cessation and time to SLE flare, controlling for demographics (age, sex, race/ethnicity, region, education), baseline medication (steroids, immunosuppressives, biologics), enrollment year, time between diagnosis and cohort entry, smoking status, end-stage renal disease, and body mass index. Lupus flare was defined as the earliest of: A. Increase (from prior score) of at least 4 points in the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K), B. Increase/initiation of SLE therapy (prednisone, immunosuppressive, or biologic), or C. SLE-related hospitalization. Since exact date of increased SLEDAI-2K was unknown, these represented IC events. We compared alternative analyses, imputing the IC event time at either the end- or the mid-point of the interval between the previous clinic visit and the visit when the outcome was reported. In sensitivity analyses we used SIMEX, a more sophisticated method based on simulations that allowed us to assess how the HR of interest changes with increasing time interval between adjacent visits. By extrapolating observed trends between the original and simulated data, we could correct the bias estimated to be within the original data, due to IC events.[1] Results Out of the total 1,543 subjects, 398 (25.8%) decreased or stopped their HCQ at some point during their follow-up and 1,187 experienced a disease flare (76.9%). When IC event times were imputed at the end of the relevant time interval, the adjusted HR for flare related to HCQ decrease/cessation was 1.43 (95% confidence interval, CI 1.24-1.66). When IC event times were imputed at the mid-point, the point estimate for the adjusted HR was slightly higher (1.53, 95% CI1.32-1.78). SIMEX correction yielded an even higher point estimate for the adjusted HR (1.68, bootstrapped 95% CI 1.44-2.02). Conclusions HCQ tapering/cessation was associated with greater flare risk regardless of how IC events were handled. Correcting imprecise timing of IC events tended to increase the strength of estimated associations, although confidence intervals overlapped. Limitations of these analyses include failure to account for disease status and/or other concomitant drug changes at tapering/cessation. Future analyses will address these issues (and stratify outcomes according to whether HCQ was tapered vs stopped). References: [1.] Abrahamowicz M. Biom J 2022;64(8):1467-85.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».