549 | PROSPECTIVE PATIENT PREFERENCE STUDY FOR CHRONIC LYMPHOCYTIC LEUKEMIA TREATMENT ATTRIBUTES IMPACTING PATIENT SHARED‐DECISION MAKING
Notice bibliographique
Résumé
Introduction: CLL is the most common leukemia in adults in Western countries, incidence 5/100,000 in US/Europe, and significantly lower in Asia (0.48).Latin America (LATAM) presents a complex and variable landscape for CLL incidence, with some countries like Uruguay and Argentina exhibiting rates similar to Europe, while others (Mexico, Peru, Chile) reporting lower incidences.The region's ethnic, cultural, and economic heterogeneity leads to disparities in access to diagnostic and prognostic tools, as well as therapeutic options, especially with the increasing use of targeted agents.In 2022, the GELL-CLL cohort presented initial data from 459 patients across six countries, here, we provide an updated analysis, expanding the cohort.Methodology: retrospective cohort study of CLL patients aged ≥ 18 years, diagnosed and treated between 2010 and 2024, or diagnosed since 2000 and treated from 2010 onwards, from centers participating in the GELL-CLL registry.Results: 981 patients from ten countries (Argentina, Chile, Colombia, Cuba, Guatemala, Mexico, Paraguay, Peru, Uruguay, Venezuela) were included, with 883 eligible.Of these, 66% were treated in private institutions.Median age 68 years (30-95), 40.4% female.Racial distribution: 89.8% White, 1.5% Africanancestry, 1.2% Indigenous, 7.2% mixed-race, and 0.1% Asian.At diagnosis, 91.4% ECOG 0-1, 46% Rai 0; III-IV: 14.2%.Key prognostic factors revealed that 13.8% were CD38þ, and elevated B2 was found in 28%.IgVH mutational status was studied in 29.6% of patients, with 47% unmutated.At diagnosis, 77% of patients were under observation, with 51% requiring treatment after a median of 9 months.Of those treated, only 33% underwent cytogenetic or FISH analysis prior to therapy.Del17p was identified in 3.7% of patients, while P53 mutations were found in 1.5%.First-line treatment included chemo-immunotherapy (55.2%), chemotherapy (28.4%), iBTK (12.3%), and Venetoclax-based (4.1%).Remarkably, 70% of patients receiving chemotherapy had no prior cytogenetic or FISH testing.Differences in biomarker testing between countries were stark, ranging from 0% in Venezuela to 45% in Uruguay.Median follow-up 67 months (0-362), overall survival (OS) differed significantly by treatment era: OS was 116 months for 2010-2014, 127 months for 2015-2019, and was not reached for 2020-2024 (p = 0.015).Four-year OS rates were 65% for chemotherapy, 81% for chemo-immunotherapy, 84% for iBTK, and 90% for Venetoclax-based.Conclusions: This real-world analysis highlights significant disparities in CLL management across LATAM.Despite recent shifts toward targeted therapies, many patients still lack access to essential prognostic testing, potentially leading to suboptimal treatment choices.Efforts to improve biomarker availability and targeted therapy access are crucial for enhancing outcomes across the region.Expanding this cohort will further elucidate regional variations and support initiatives to address treatment inequities.
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 | 0,007 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 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) | 0,009 | 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 ».