Is aggregate use of published case reports as a viable option for augmenting pharmacovigilance? An applied example of pembrolizumab-related adverse events in patients with non-small cell lung cancer receiving first-line treatment.
Notice bibliographique
Résumé
e18840 Background: Pharmacovigilance suffers from considerable underreporting, and causality is rarely confirmed. We aim to examine the validity of the aggregate use of published case reports as a viable option for augmenting pharmacovigilance. We explore the setting of first line pembrolizumab treatment for non-small cell lung cancer as safety signals in this cohort are relatively well documented and because drug-related adverse events are more easily confirmed with no previous drug treatments. Methods: We compared immune-related adverse event rates (Any and Severe) associated with pembrolizumab from three select first non-small lung cancer KEYNOTE clinical trials (024, 042, and 189) to clinician confirmed pembrolizumab-related adverse event rates from a synthetic cohort case report data from a matching population. The latter were retrieved from the OpenCaseTM database and included 126 non-small cell lung cancer patients, of which 110 had received pembrolizumab monotherapy and 16 pembrolizumab in combination with a platinum-based chemotherapy regimen. Baseline characteristics with respect to age, sex, smoking history, non-drug treatment history, PD-L1 tumor proportion score, and key genetic markers (e.g. EGFR, ALK) were acceptably similar (results will be presented in a table). Results: In the synthetic cohort of case reports, Immune-related adverse events, which were clinician confirmed to be related to pembrolizumab, occurred in 86/126 (68.2%). Life threatening and severe treatment-related AEs were 7.4% and 65% respectively. These were substantially higher than reported in clinical trials 8.0%-9.7% experienced severe immune-related events. The majority of the most frequently occurring immune-related AEs in the KEYNOTE trials had similar reported proportions to the case reports. For example, hypothyroidism (any grade) ranged from 6.7% to 9.1% in the KEYNOTE trials compared to 4.9% among the case reports, and pneumonitis (any grade) ranged from 4.4% to 12.0% in the trials compared to 5.5% in the case reports. Other events such as myositis, type 1 diabetes, liver dysfunction, kidney injury, and colitis were frequent in the cohort of case reports (3.1%-7.9%), but rare or unreported in all KEYNOTE trials (0.0%-2.2%). Conclusions: Overall, adverse event rates in the synthetic cohort of case reports were either similar or higher than observed in clinical trials of matching populations. This observation provides rationale for utilizing case reports in pharmacovigilance practice, specifically for rarer events.
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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 | 0,355 | 0,653 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,004 |
| Bibliométrie | 0,012 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,007 | 0,006 |
| Science ouverte | 0,004 | 0,006 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».