Serious Adverse Drug Reactions (sADRs) Involving Hematology and Resulting in Black Box Warnings or FDA Non-Approval: Results from the First Quarter Century of RADAR/Sonar
Notice bibliographique
Résumé
Background: Two National Cancer Institute-funded pharmacovigilance programs have identified 49 serious hematology-related ADRs since 1998. The programs, called RADAR (Research on Adverse Drug events and Reports) and then SONAR (Southern Network on Adverse Reactions) involve > 50 institutions and > 75 co-investigators worldwide. The work builds on three prior studies evaluating “Davids and Goliaths” in medical oncology and in cardiology (PLOS One, eClinicalMedicine, and Journal of Scientific and Professional Integrity). Here we review the hematology focused safety investigations of RADAR/SONAR. Methods: Data were based on initial safety signals being identified by a RADAR/SONAR co-investigator. Then, case-series were derived. Collaborations with basic scientists allowed for basic science correlative studies. Results were disseminated primarily as Brief Report in the literature and Black Box warnings on the related drug. In some instances, studies identified hematologic toxicities that prevent FDA from approving a submitted drug application. Results: sADRs were frequently identified based on very small case series, including ticlopidine-and clopidogrel associated thrombotic thrombocytopenic purpura (22 and 10 patients, respectively), thalidomide- and lenalidomide-associated venous thromboembolism (9 and 5 patients, respectively), rituximab-associated progressive multi-focal leukoencephalopathy (22 patients), peginesatide-associated fatal anaphylaxis (5 patients), and COVID-19 vaccine associated immune thrombocytopenia (1 patient). Meta-analyses provided data for epoetin- and darbepoetin-associated mortality among cancer patients and lenalidomide- and thalidomide-associated venous thromboembolism. Following the onset of the COVID-19 pandemic, RADAR/SONAR investigated social media and pre-prints (COVID-19 vaccine associated cerebral vein thrombosis and immune thrombocytopenia). Time from FDA approval to sADR discovery was a median of 5 years (range, 0 months (thalidomide-associated venous thromboembolism) to 34 years (ciprofloxacin-associated neuropsychiatric toxicity). Basic science correlative studies identified ADAMTS13 autoantibodies (ticlopidine), leachates that developed in a multi-dose vial (peginesatide), anti-red blood cell antibodies (epoetin-associated pure red cell aplasia), and high-risk genes (fluoroquinolones and rituximab). Overall, RADAR/SONAR studies are estimated to have saved over 1 million lives and also resulted in overall payments to the Department of Justice of $1.5 billion (related to marketing of unsafe drugs). Discussion: RADAR/SONAR has proven to be a very important adjunct to FDA and pharmaceutical manufacturer-led safety investigations for hematology, paralleling the success in medical oncology and in cardiology. Going forward, independent centers of excellence for safety-focused investigations such as the CERSI network and the SENTINEL network (both are NIH funded) should be broadened to include a hematology-focused safety center.
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 | 0,017 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».