PB2090: SYSTEMATIC LITERATURE REVIEW OF PROGNOSTIC FACTORS FOR RELAPSED/REFRACTORY MULTIPLE MYELOMA
Notice bibliographique
Résumé
Topic: 14. Myeloma and other monoclonal gammopathies - Clinical Background: Multiple myeloma (MM) is a highly heterogenous and incurable malignancy, with nearly all patients eventually relapsing and/or becoming refractory to treatment. Patients with relapsed and/or refractory MM (RRMM) have a poor prognosis; those who are exposed and/or refractory to multiple therapies experience even poorer outcomes. Several studies have identified factors prognostic of outcomes in patients with RRMM; however, an up-to-date synthesis of available evidence is lacking. It is important to have a systematic and evidence-based process to identify relevant prognostic factors to support MM research in a rapidly changing treatment landscape. Aims: The objective of this study was to conduct a systematic literature review (SLR) of prognostic factors associated with objective response rate (ORR), overall survival (OS), progression free survival (PFS), complete response (CR), partial response (PR), or duration of response (DOR) in patients with RRMM. Methods: Database searches were conducted in Ovid MEDLINE and Embase for clinical trials and observational studies published between January 1, 2016 and April 14, 2022. Studies were eligible if they included RRMM patients and an assessment of prognostic significance of any factor on an outcome of interest via multivariate analysis. Eligibility was assessed by two independent reviewers, with discrepancies resolved by consensus or a third independent reviewer. Data from included records were collected using standardized data extraction templates. Factors that were statistically significantly associated with an outcome of interest (p < 0.05, or confidence interval excluding the null value) were extracted. Study quality was assessed using the Quality in Prognosis Studies (QUIPS) tool. Data were summarized descriptively. Results: Of 5,349 records identified through the database and hand searches, a total of 130 records reporting on 125 unique studies were included. Twenty-three (18%) studies were clinical trials, and 102 (82%) were observational cohort studies. The most common limitations in study quality were related to sample representativeness and control of confounders. Ninety-seven factors were statistically significantly associated with at least one outcome in at least one study. The most commonly investigated factors across the 125 included studies were disease stage (n = 27 studies), age (n = 20 studies), prior lines of therapy (n = 20 studies), best response to index therapy (n = 20 studies), cytogenetic risk (n = 19 studies), lactate dehydrogenase (LDH; n = 12 studies), extramedullary disease/plasmacytoma (EMP) (n = 12 studies), and performance status (PS) (n = 10 studies). Worse survival was associated with higher disease stage, older age, more prior lines of therapy, poorer response, high-risk cytogenetics, elevated LDH levels, EMP presence, and worse PS, while worse response was associated with higher disease stage, younger age, more prior lines of therapy, high-risk cytogenetics, and worse PS. Associations between factors and outcomes were largely consistent across studies, although conflicting associations were noted in <10% of studies, and in some studies, poor reporting limited the ability to ascertain the direction of associations. Summary/Conclusion: To our best knowledge, this is the first SLR to investigate prognostic factors for an RRMM population. Using a broad approach to identify relevant studies and adhering to best practices for conducting and reporting of SLRs, this work provides a comprehensive evidence base for factors prognostic of response and survival outcomes in patients with RRMM. Keywords: Prognosis, Systematic review, relapsed/refractory, Multiple myeloma
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 | 0,000 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 ».