Notice bibliographique
Résumé
<h3>Background:</h3> Inhibiting a specific JAK may impede more than one pathway, explaining both the efficacy and adverse effects observed with JAK inhibitors (JAKi). Among those, there have been recent concerns about potential thromboembolic risks with these drugs. As patients enrolled are not representative of all patients who may receive JAKi, data from trials are unlikely to provide definitive answers. Real impact of JAKi in real life on major cardiovascular events is not known. <h3>Objectives:</h3> To evaluate the risk of venous and arterial thromboembolic events with the use of JAKi in a real-world setting. <h3>Methods:</h3> A self-controlled case series analysis (method in which individuals act as their own control) was performed using data from the French national healthcare insurance system SNDS (“Système National des Données de Santé”), which included all anonymized individual level data about sociodemographic data, outpatient healthcare dispensed, hospital discharge summaries, and registration status for a list of 30 long term diseases. All patients treated by JAKi (baricitinib or tofacitinib) for rheumatoid arthritis, psoriasis arthritis and/or inflammatory bowel disease, and with at least one thromboembolic event (venous (VTE): deep vein thrombosis (DVT), pulmonary embolism (PE), arterial (ATE): acute coronary syndrome (ACS), myocardial infarction (MI), transient ischemic attack (TIA) and stroke) between 2017/11/01 and 2019/06/30 were included in the study. Associations were evaluated by incidence rate ratios (IRR), which compare the rate of events during exposed periods with rate of event during all other observed time periods. Exposed periods were defined as i) exposure to JAKi, ii) the month following exposure (post-exposure 1-30 days), and iii) long-term post-exposure (31 to 60 days). A pre-exposure period of 7 days was individualized to identify event-dependent probabilities of exposure and potential reverse causality bias, and all other periods were considered as non-exposed periods. <h3>Results:</h3> Among the 5,870 patients treated with JAKi between 2017/11/01 and 2019/06/30, 94 presented an incident thromboembolic event and were included. Almost two thirds were female (n=61, 64.9%), and median age was 65.4 [IQR: 55.5; 75.8] years. Most of patients have a rheumatoid arthritis (n=91, 96.8%), 62 (66.0%) were treated by baricitinib, and 32 (34.0%) by tofacitinib. Almost half (n=42, 44.7%) presented a venous thromboembolism, mainly DVT (n=31, 33.0%), and 52 (55.3%) presented an arterial thromboembolism, mainly MI (n=16, 17.0%) and stroke (n=14, 14.9%). Eleven patients (11.7%) died during the study period. The median time of occurrence of VTE was 4.3 [IQR: 2.5; 8.9] months, and 6.1 [IQR: 3.3; 9.2] months for ATE. The median duration of exposure was 6.0 [IQR: 3.3; 10.1] months for VTE, and 12.0 [IQR: 4.8; 15.3] months for ATE. The IRR for VTE and ATE were increased during exposure, and during the 30 days following exposure (Table 1). The IRR for VTE was only increased during exposure and in the early post-exposure phase contrary to the IRR for ATE that was also increased in the pre-exposure 7-Day period. Analysis conducted on survival patients confirmed results. <h3>Conclusion:</h3> The present study found an increased risk of VTE and ATE for baricitinib and tofacitinib. The risk persists in the month following the discontinuation of treatment but disappears after day 30 post-exposure. <h3>Disclosure of Interests:</h3> Amandine Gouverneur: None declared, Jérôme Avouac Consultant of: JA has/had consultancy relationship and/or has received research funding in the area of potential treatments for rheumatoid arthritis from (last three years): Abbvie, Galapagos, Pfizer, Bristol Myers Squibb, Sanofi, Nordic Pharma, Chugai and MSD., Grant/research support from: JA has/had consultancy relationship and/or has received research funding in the area of potential treatments for rheumatoid arthritis from (last three years): Abbvie, Galapagos, Pfizer, Bristol Myers Squibb, Sanofi, Nordic Pharma, Chugai and MSD., Clément Prati: None declared, Jean-Luc Cracowski: None declared, Thierry Schaeverbeke Consultant of: TS consultancy and/or research fundings: Abbvie, Lilly, Pfizer, Galapagos, Novartis, BMS, Medac, NordicPharma, Biogen, Mylan, Janssen., Grant/research support from: TS consultancy and/or research fundings: Abbvie, Lilly, Pfizer, Galapagos, Novartis, BMS, Medac, NordicPharma, Biogen, Mylan, Janssen., Antoine Pariente Grant/research support from: AP reports acting as an independant expert towards the French Medicines Agency (Agence Nationale de Securité du Médicament et des Produits de Santé, ANSM) and the European Medicines Agency (EMA). AP coordinates the DRUGS Systematised Assessment in real-liFe EnviRonment (DRUGS-SAFER) programme funded by the Agence Nationale de Sécurité du Médicament et des Produits de Santé (ANSM)., Marie-Elise Truchetet Consultant of: has/had consultancy relationship and/or has received research funding in the area of potential treatments for rheumatoid arthritis and spondyloarthritis and their complications from (last three years): Abbvie, Galapagos, Lilly, Medac, Novartis, Pfizer, and Roche., Grant/research support from: has/had consultancy relationship and/or has received research funding in the area of potential treatments for rheumatoid arthritis and spondyloarthritis and their complications from (last three years): Abbvie, Galapagos, Lilly, Medac, Novartis, Pfizer, and Roche.
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 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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».