Gimema Seifem Real-Life Study VS Randomized CPX-351 Registrative Trial for Older Patients with Secondary ACUTE Myeloid Leukemia: An Unanchored Matching-Adjusted Indirect Comparison of Infection Rates and Survival Outcomes
Notice bibliographique
Résumé
Background: Unanchored MAIC (Matching-Adjusted Indirect Comparison) is an ITC (Indirect Treatment Comparison) method adjusting for cross-trial heterogeneity in patient demographic or disease that are believed to be either prognostic or treatment effect modifiers. In this analysis, two trials for adults with secondary acute myeloid leukemia (AML) were compared by an unanchored MAIC. Aims: The GIMEMA (Gruppo Italiano Malattie EMatologiche dell'Adulto)-SEIFEM (Sorveglianza Epidemiologica Infezioni nelle Emopatie) real-life study on the use of CPX-351 (Fianchi et al- Cancers 2023) was weighted for the aggregated patients characteristics from the standard arm(“7+3”) of the CPX-351 trial (cytarabine and daunorubicin Liposome for Injection Versus Conventional Cytarabine Plus Daunorubicin in Older Patients With Newly Diagnosed Secondary Acute Myeloid Leukemia, Lancet et al - JCO 2018). This analysis aimed to test the feasibility to compare individual patients' data with aggregated published results and evaluate the rate of infections of CPX-351 in real life vs the “3+7” regimen and their impact on the survival outcomes. Methods: Patients-level data from GIMEMA-SEIFEM on the use of CPX-351 (n=202) and aggregated data from CPX-351 (“3+7” arm, n=156) trials were used to conduct an unanchored MAIC. GIMEMA-SEIFEM study included included all consecutive patients with AMLfrom 30 Italian hematologic centers who received at least 1 course of CPX-351 from July 2018 to June 2021 according to clinical practice. Patients from the GIMEMA-SEIFEM study were weighted to balance with baseline characteristics from the USA and Canada cohoort. Accordingly, weighted Overall and Event-free survival (w-OS, w-EFS) estimates, as well as rates of febrile neutropenia, pneumonia, CR, and the interval of PMN recovery, were computed. Results: Four potential effect modifiers were identified and used for adjustment: age, sex, AML subtype (tAML, sAML, MRC), and prior HMA exposure. Median w-OS and w-EFS were 14.2 (95%CI: 11.6-18.7) and 7.4 (95%CI: 3.0-10.6) months, respectively. These estimates were slightly lower than those documented in the most recent report of the GIMEMA-SEIFEM trial (median OS 17.7 months and median EFS 9.8 months) and higher than the results obtained by the standard arm of the CPX-351 trial (median OS 5.9 months, median EFS 1.3 months). Weighted rates of febrile neutropenia, pneumonia, CR, and interval of PMN recovery were comparable to the observed values and better than observed in the standard arm of the CPX-351 trial for all considered variables, except for febrile neutropenia (Table 1). Conclusions: The MAIC method allowed a robust comparison of two clinical trials for the treatment of AML patients. After adjustment, survival outcomes of the real-life cohort were slightly lower than the observed estimates and higher than the observed in the standard arm of the CPX-351 trial. Pneumonia risk was confirmed lower in GIMEMA-SEIFEM CPX-351 matched group than in “3+7” arm. This pilot analysis underlined the potentiality of this statistical method. Indeed, it could be useful to compare with high accuracy studies with strong differences in the selection of patients.
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 | 0,008 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,005 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».