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Record W3214512886 · doi:10.1182/blood-2021-153876

Outcomes of Maintenance Treatment Post Autologous Stem Cell Transplantation in Newly Diagnosed Multiple Myeloma Patients: A Canadian Single Center Experience

2021· article· en· W3214512886 on OpenAlexaffabout
Mina Dehghani, Shona Philip, Anthony Quint, Lenicio Siqueira, Selay Lam, Chai W. Phua, Anargyros Xenocostas, Uday Deotare, Martha Louzada

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsWestern UniversityLondon Health Sciences CentreSunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineMultiple myelomaLenalidomideInternal medicineAutologous stem-cell transplantationCohortMaintenance therapyOncologyTransplantationProportional hazards modelSingle CenterRetrospective cohort studyUnivariate analysisSurgeryMultivariate analysisChemotherapy

Abstract

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Abstract Introduction: Despite the significant advances in treatment of patients with multiple myeloma, therapy of patients with high risk disease remains challenging. Maintenance treatment with Lenalidomide following autologous stem cell transplant (ASCT) is the standard of care in patients with multiple myeloma; however its efficacy in patients with high risk features is conflicting. The efficacy of proteasome inhibitors (PI) ± lenalidomide (Len) maintenance in high risk patients has been evaluated in other studies with discrepant results with respect to improvement in long term outcomes. In this study we sought to assess the impact of various maintenance strategies on outcomes of transplant eligible newly diagnosed myeloma patients in the real world setting. Methods: This is a retrospective, single center Canadian cohort study (London, Canada) with the primary objective to compare the PFS in the high risk transplant eligible (TE) newly diagnosed multiple myeloma (NDMM) patients receiving maintenance treatment versus no maintenance post ASCT, diagnosed from January 1,2007 to April 30,2021. Secondary objectives are comparison of PFS, OS and overall response rate (ORR) based on risk group and various maintenance strategies. ORR is defined as partial response or better. To investigate the effect of different variables on survival outcomes we used Kaplan-Meier curves, univariate and multivariate cox regression analysis. Results: In total, 155 TE- NDMM patients were included. 61 (39%) were high risk defined as: deletion 17p, t (4; 14), t (14; 16), 1q amp. One hundred and thirty (84%) patients received PI or Len-based induction therapy. Of the entire cohort, 53 (34%) patients received maintenance treatment post ASCT: 41 Len to progression, 12 Len+Pi. In the entire cohort, ORR was 71% (38 of 53) for patients who received maintenance and 53% (55 of 102) for those who did not receive maintenance (p=0.7). In the 61 high risk patients, 33 received maintenance: 11 Len+PI and 22 Len single agent. ORR was significantly better for maintenance, 63% (21 of 33) compared to 11% (3 of 27) for no maintenance (p=0.0054). Maintenance therapy also influenced PFS. In total, median PFS was significantly higher in patients who received maintenance; with 63% of patients alive and on therapy at 60 months, compared to no maintenance with median PFS of 40 months (HR 0.46,95% CI(025-0.85),p= 0.011). A subgroup analysis of the impact of maintenance between the standard and high risk groups suggested excellent PFS for both: 56.8% for standard and 67.1% for high risk at 60 months. On the other hand, median PFS was dismal for the high risk no maintenance group: only 19 months versus 45.5 months in the standard group ( HR=0.14,95% CI(0.05-0.38), p <0.0001). Dual versus single drug maintenance strategy had no impact on PFS. Median PFS was the same for the patients who received Len+PI or Len single agent, not yet reached (NYR) in both (p=0.47). In the entire cohort there was no difference in the median OS, NYR in both groups at 60 months; 51% in maintenance, 53% in no maintenance (p=0.25). Similarly in the high risk patients median OS was not different, 61 months in maintenance vs NYR in no maintenance (45% vs 52% at 60 months, p=0.38). OS was also not different in high risk patients who received Len+PI vs Len single agent maintenance, NYR vs 61 months (p= 0.68). In the standard risk group median OS was NYR at 60 months in both maintenance and no maintenance groups (p=0.57) Conclusion: In this Canadian single center retrospective cohort study we compared PFS and OS in patients with TE-NDMM who received maintenance compared to those with no maintenance treatment post ASCT. We found PFS was significantly improved in the high risk patients who received maintenance treatment but we found no impact on dual versus single maintenance strategy. This further validates the findings of large phase 3 clinical trials illustrating a positive impact of maintenance treatment post ASCT irrespective of the cytogenetics risk in the real world setting. Although the maintenance treatment could not entirely overcome the worse outcome in the high risk group, more than 40% of the high risk patients who received maintenance were still alive at 60 months. The question of the best maintenance strategy for high risk myeloma patients remains open and further studies are warranted Figure 1 Figure 1. Disclosures Lam: Beigene: Honoraria, Membership on an entity's Board of Directors or advisory committees; SeaGen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Hoffmann-La Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Johnson & Johnson: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Meyers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees. Phua: Amgen: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; NovoNordisk: Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria. Louzada: Pfizer: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Celgene: Honoraria.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.254
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes2
Has abstractyes

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