An International Collaborative Study of Outcome and Prognostic Factors in Patients with Secondary CNS Involvement By Diffuse Large B-Cell Lymphoma
Notice bibliographique
Résumé
Abstract Background: Secondary CNS involvement (SCNS) is a detrimental complication seen in ~5% of patients with diffuse large B-cell lymphoma (DLBCL) treated with modern immunochemotherapy. Data from older series report short survival following SCNS, typically <6 months. However, data in patients that develop SCNS following primary therapy that contains a rituximab-based-regimen as well as the impact of more intensified treatment for SCNS are limited. Aims: The aims of this study were to i) describe the natural history of SCNS in a large cohort of patients treated with immunochemotherapy, and ii) determine prognostic factors after SCNS. Patients and methods: We performed a retrospective study of patients diagnosed with SCNS during or after frontline immunochemotherapy (R-CHOP or equivalently effective regimens). SCNS was defined as new involvement of the CNS (parenchymal, leptomeningeal, and/or eye) in patients without known CNS involvement at the time of first pathologic diagnosis of DLBCL. Patients were identified from local databases and/or regional/national registries in Denmark, Canada (British Columbia), Australia, Israel, US (University of Iowa/Mayo Clinic SPORE), and England (Guy's and St. Thomas' Hospital, London). Clinico-pathologic and treatment characteristics at the time of SCNS were collected from medical records. Results: In total, 281 patients with SCNS diagnosed between 2001 and 2016 were included. Median age at SCNS was 64 (range 20-93) years and male:female ratio was 1.3. SCNS occurred as part of first relapse in 244 (87%) patients and 112 (40%) had documented concurrent systemic disease at the time of SCNS. The median time from initial DLBCL diagnosis to SCNS was 9 months, which was similar for patients treated with (N=76, 27%) or without upfront CNS prophylaxis (N=205, 73%) (10 vs 9 Mo; P=0.3). The median post-SCNS OS was 4 months (interquartile range 2-13) and the 2yr survival rate was 20% (95% CI 15-25) for the entire cohort. Associations between clinicopathologic features, management strategy, and post-SCNS survival are shown in Table 1, which excludes patients who did not receive any treatment against SCNS, patients treated with steroids alone, and a patient with unavailable treatment information (n=43, 15%). In multivariable analysis, performance status >1, concurrent leptomeningeal and parenchymal involvement, SCNS developing before completion of 1st line treatment, and combined systemic and CNS involvement by DLBCL were associated with inferior outcomes. Upfront CNS prophylaxis did not influence post-SCNS OS. High-dose methotrexate (HDMTX) and/or platinum based treatment regimens (i.e. ICE, DHAP, or GDP [+/- IT treatment and/or radiotherapy], N=163) for SCNS were associated with reduced risk of death (HR 0.45 [0.32-0.62, P<0.01]). The 2yr post-SCNS survival for patients treated with HDMTX and/or platinum-based regimens (N=163) was 29% (95% CI 22-37). For patients with isolated parenchymal SCNS, single modality treatment with radiotherapy resulted in 2-yr OS of 19% (95% CI 8-35). For the subgroup of 49 patients treated with HDMTX- and/or platinum-based regimens for isolated SCNS after 1st line DLBCL treatment and with performance status 0 or 1, the 2yr post-SCNS survival was 46% (95% CI 31-59). Overall, 9% of the patients received HDT with ASCT as part of salvage therapy at the time of SCNS. Amongst 36 SCNS patients without systemic involvement and in CR following intensive treatment (HDMTX and/or platinum-based treatments), 11 patients consolidated with HDT had similar outcomes to 25 patients treated without consolidating HDT (P=0.9, Fig 1) Conclusions: Outcomes for patients with SCNS remain poor in this large international cohort of patients from the immunochemotherapy era. Combined parenchymal and leptomeningeal disease, presence of systemic disease concurrent with SCNS, performance status >1, and SCNS developing during first line treatment were independently associated with inferior OS. However, a significant fraction of patients with isolated SCNS after first line DLBCL treatment and with good performance status may achieve long-term remissions after intensive regimens for SCNS. Disclosures El-Galaly: Roche: Consultancy, Other: travel funding. Cheah:Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Gilead Sciences: Membership on an entity's Board of Directors or advisory committees; Janssen-Cilag: Membership on an entity's Board of Directors or advisory committees, Other: Speaker's Bureau. Kansara:Celgene: Honoraria. Connors:Bristol Myers Squib: Research Funding; NanoString Technologies: Research Funding; F Hoffmann-La Roche: Research Funding; Millennium Takeda: Research Funding; Seattle Genetics: Research Funding. Sehn:roche/genentech: Consultancy, Honoraria; amgen: Consultancy, Honoraria; seattle genetics: Consultancy, Honoraria; abbvie: Consultancy, Honoraria; TG therapeutics: Consultancy, Honoraria; celgene: Consultancy, Honoraria; lundbeck: Consultancy, Honoraria; janssen: Consultancy, Honoraria. Opat:Roche: Consultancy, Honoraria, Other: Provision of subsidised drugs, Research Funding. Seymour:Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Villa:Celgene: Honoraria; Lundbeck: Honoraria; Roche: Honoraria, Research Funding.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».