Outcomes Following Biochemical or Clinical Progression in Patients with Multiple Myeloma
Notice bibliographique
Résumé
Abstract Background Multiple Myeloma (MM) remains incurable with current approaches and eventually relapses in nearly all patients. At relapse, patients may present with increasing serum and/or urine monoclonal (M) protein or with clinical features suggestive of progression. The outcomes of different progression patterns need to be better understood to provide insight about the optimal time to intervene with salvage therapy. This study aimed to describe the prevalence and outcome of biochemical (BP) versus clinical progression (CP) in a real-world setting. Methods We retrospectively assessed 1347 relapsed MM patients seen at Mayo Clinic between February 2001 and December 2018. CP was defined as per IMWG criteria (increase ≥50% in size or new plasmacytomas/bone lesions, hypercalcemia ≥11.5 mg/dl, decrease in hemoglobin ≥2 g/dl or to ≤10 g/dl, rise in serum creatinine ≥2g/dl, hyperviscosity), while BP was defined as increase in serum or urine M protein leading to initiation of a new line of therapy without meeting criteria for CP. Aggressive relapse was defined as new extramedullary disease (EMD), plasma cell leukemia or hyperviscosity requiring plasmapheresis. The overall survival (OS) was defined as the time from 1 st relapse to last follow-up or death. Time to next treatment (TTNT) was defined as the time between initiation of 2 nd and 3 rd line therapy. Results Prevalence of different patterns of relapse is presented in Table 1. The majority of progressions were BP (60.4%); among the CP (39.6%), the most common presentation was a new bone lesion. Similar proportions of BP and CP patients were diagnosed before 2013 (70% and 73%; p=0.2). The median time from diagnosis to 1 st relapse was 22.8 months (range, 0.4-154.7) and was shorter in the CP group in comparison to BP (20.8 [range, 1.0-152.1] vs 23.7 [range, 0.4-154.7] months, p=0.001). With the exception of ISS stage, patients in the CP group had higher risk features at MM diagnosis including: high-risk (HR) FISH ([4;14], t[14;16], t[14;20], deletion 17p or p53 mutation; 29% vs 20%, p=0.01); elevated LDH (23% vs 17%, p=0.03); and EMD (19% vs 10%, p<0.001). CP patients more often had non-secretory disease at baseline (6% vs 2%, p<0.001). At 1 st line, patients with eventual CP were less likely to have received novel agents (78% vs 85%, p<0.001), upfront autologous stem cell transplantation (ASCT, 43% vs 51%, p=0.004), and lenalidomide-based maintenance (11% vs 16%, p=0.01). While patients in the CP group were less likely to have achieved very good partial remission (VGPR) or better to the 1 st line therapy (53% vs 60%, p=0.01), the percentage of patients who achieved CR was similar between the groups (22% vs 24%, p=0.4). Relapse while on primary treatment/maintenance was more prevalent in the CP (46% vs 40%, p=0.04). On multivariable logistic regression model male sex, plasma cell labeling index (PCLI) ≥2% and EMD at diagnosis were associated with higher risk of CP, whereas achieving VGPR or better after 1 st line treatment was associated with decreased risk of CP. Patients with CP had shorter median TTNT from 2 nd line therapy compared to BP (9.6 vs 17.0 months, p<0.001) as well as shorter median OS from 1 st relapse (26.2 vs 59.4 months, p<0.001; Figure 1). Amongst patients with CP, those presenting with typical "aggressive" versus "CRAB" features at relapse had a significantly shorter median TTNT (6.0 vs 11.0 months, p<0.001) and OS (17.2 vs 28.1 months, p<0.001). Using a multivariable Cox proportional hazard model, CP (vs BP) was a predictor of shorter TTNT from 2 nd line therapy (HR 1.40, 95% CI 1.20-1.62, p<0.001), along with ISS stage III, HR FISH at diagnosis and relapse while on primary treatment/maintenance, whereas the use of upfront ASCT was a predictor of longer TTNT from 2 nd line therapy. CP was also a predictor of shorter OS from 1 st relapse (HR 1.53, 95% CI 1.29-1.81, p<0.001) along with age >65 years, male sex, ISS stage III, HR FISH at diagnosis, EMD at diagnosis and relapse while on primary treatment/maintenance. Conclusions Patients with clinical features at relapse have a worse prognosis after 1 st relapse than patients who relapsed solely biochemically. Approximately half of CP presented while on active treatment, which suggests that even patients monitored closely may develop CRAB features at relapse. Factors that help predict the occurrence of CP include male sex, PCLI ≥2% and EMD at diagnosis. Patients with deeper response to 1 st line treatment are less likely to develop CP. Figure 1 Figure 1. Disclosures Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dispenzieri: Sorrento Therapeutics: Consultancy; Pfizer: Research Funding; Oncopeptides: Consultancy; Janssen: Consultancy, Research Funding; Takeda: Research Funding; Alnylam: Research Funding. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Aurora Biopharma: Other: Stock option; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy. Dingli: Apellis: Consultancy; Sanofi: Consultancy; GSK: Consultancy; Novartis: Research Funding; Alexion: Consultancy; Janssen: Consultancy. Kumar: Antengene: Consultancy, Honoraria; Sanofi: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Tenebio: Research Funding; Beigene: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Carsgen: Research Funding; Oncopeptides: Consultancy; Roche-Genentech: Consultancy, Research Funding; Novartis: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, 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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».