Patterns of Relapse and Progression in Multiple Myeloma Patients Treated with Conventional and Novel Agent-Based Therapy: A Single Centre Experience
Notice bibliographique
Résumé
Abstract Background The incorporation of novel agents (NA) for multiple myeloma (MM) has improved the response rates (RR), overall survival (OS), and progression free survival (PFS) when compared to conventional agents (CA). Unfortunately, relapse is inevitable and few studies focus on patterns of relapse, especially in non-transplant patients (pts). We aim to describe the different patterns of relapse in non-transplant MM pts and determine if any pre-treatment clinical or disease characteristics can predict the patterns relapse. We will evaluate whether NA treated pts have higher rates of aggressive relapse with plasmacytomas or plasma cell leukemia (Leuk Res. 2009 Aug;33(8):1137-40). Secondly, RR and PFS for pts treated with CA vs NA will be described. Methods A retrospective evaluation of 156 consecutive newly diagnosed non-transplant eligible MM pts at Princess Margaret Cancer Centre receiving at least two consecutive cycles of CA or NA from 1999 to 2015. CA included steroids and alkylators while NA had immunomodulatory (IMiD) drugs (thalidomide, lenalidomide) and proteasome inhibitors (PI) (bortezomib). Response type was defined by the revised International Myeloma Working Group criteria (Leukemia. 2006 Sep;20(9):1467-73. Epub 2006 Jul 20); relapse patterns as defined in the Spanish Registry (Haematologica. 2002 Jun;87(6):609-14) Results For 156 non-transplant MM pts: 81 (52%) male, average age 76 yrs, 87 (56%) treated with NA (thalidomide=15; PI=52). Baseline characteristics were not significantly different between groups (Table 1). Sixty three (52%) pts had a clinical relapse, 37 (30%) pts had a biochemical relapse, and 22 (18%) were switched immediately to second line therapy given suboptimal response (lack of clinical benefit or PD). Six pts relapsed with isolated plasmacytomas (4 CA vs 2 NA). There was one case of plasma cell leukemia relapse in an IMiD-treated pt.Twenty seven (17.3%) pts had not relapsed at the time of analysis and had ongoing follow-up. There was no significant difference in the types of relapse patterns for pts treated with CA versus NA (p=0.26) or for CA versus IMiD versus PI therapy (p=0.22). Pts with insufficient response to first line chemotherapy were more likely to have a 17p deletion (p=0.07). All pts with a biochemical relapse did not have a 17p deletion. The median follow-up time was 16.4 (range 0.6 to 99) months (mo) for CA vs. 19.6 (range 0.4 to 107) mo for NA. Table 1. Patient Characteristics Relapse Pattern - Mean (sd) Clinicaln =63 Biochemicaln =37 Insufficient n=22 p -value Hgb 108 (17) 99 (21) 110 (18) 0.08 WBC 6.1 (2.4) 6.4 (3.3) 5.6 (1.9) 0.72 Plt 231 (107) 224 (117) 237 (103) 0.64 Ca 2.5 (0.3) 2.5 (0.4) 2.4 (0.3) 0.58 Cr 125 (92) 130 (87) 136 (133) 0.92 B2M 492 (537) 596 (448) 618 (618) 0.19 Alb 37 (7) 36 (6) 36 (5) 0.29 CRP 6.7 (7.4) 9.3 (19.1) 13.0 (17.5) 0.56 Relapse Pattern - Count (%) ConventionalNovel 35 (56)28 (44) 15 (41)22 (59) 13 (59)9 (41) 0.26 IgGIgAFLCOther 34 (54)17 (27)10 (16) 2 (3) 23 (62) 6 (16) 8 (22) 0 (0) 14 (63) 4 (18) 4 (18) 0 (0) 0.78 KappaLambda 32 (58)23 (42) 19 (59)13 (41) 12 (57)9 (43) 0.99 Chr 13 Del 8/29 (28) 7/10 (41) 3/9 (33) 0.64 t(4,14) 2/29 (7) 3/15 (20) 0/8 (0) 0.34 17p Del 4/28 (14) 0/15 (0) 3/9 (33) 0.07 Extramed. Inv. 4 (6) 1 (3) 1 (5) 0.85 Sixty (38%) pts achieved VGPR/CR/sCR, 53 (34%) PR, 35 (22%) SD, and 8 (5%) PD with upfront therapy. VGPR/CR/sCR was seen in 13 (21%) pts with CA vs 47 (78%) with NA (p<0.01). For NA, 28 (47%) pts in the PI-based group achieved VGPR/CR/sCR compared to 19 (32%) in IMiD-based (p<0.01). The median PFS for all pts was 21 (95% CI 17-23) mo, with 17 (95% CI 13-23) mo for CA vs 23 (95% CI 17-29) mo in NA. There is a statistically significant difference between CA and NA in PFS (p=0.0045; Figure 1). Discussion In non-transplant MM pts, we did not find a significant difference in the patterns of disease relapse between those treated with CA versus NA. Baseline characteristics such as renal failure or type of treatment do not seem to predict for the pattern of relapse; except the presence of 17p deletion trended toward more treatment failure. We note that the number of pts with aggressive relapses (plasmacytomas or plasma cell leukemia) was low and this limits our ability to detect differences in outcomes and baseline factors. Pts treated with NA continue to have better RR and PFS than those treated with CA. Future work with longer follow-up intervals is needed in order to capture late relapses, better describe relapse patterns with NA as well as understanding disease biology. Disclosures Chen: Celgene: Consultancy, Honoraria, Research Funding. Prica:Janssen: Honoraria; Celgene: Honoraria. Reece:Lundbeck: Honoraria; Janssen-Cilag: Consultancy, Honoraria, Research Funding; Merck: Research Funding; Millennium Takeda: Research Funding; Bristol-Myers Squibb: Research Funding; Otsuka: Research Funding; Novartis: Honoraria, Research Funding; Onyx: Consultancy; Amgen: Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Tiedemann:Janssen Ortho: Honoraria; Celgene: Honoraria; Amgen: Honoraria. Kukreti:Celgene: Honoraria; Amgen: Honoraria; Lundbeck: Honoraria; Roche: Honoraria; Janssen Ortho: Honoraria.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 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 ».