Healthcare Resource Utilization Trends over Time with Continuous Lenalidomide Treatment (Tx) in Patients (Pts) with Newly Diagnosed Multiple Myeloma (NDMM)
Bibliographic record
Abstract
Abstract Introduction: Multiple myeloma (MM) is an incurable hematologic condition that is associated with high Tx costs. Resource consumption is driven by hospitalization and medical utilization, which is highest during periods of uncontrolled disease, such as after diagnosis and during relapses (De Portu 2013). In the pivotal phase 3 FIRST trial, continuous Tx with lenalidomide plus low-dose dexamethasone (Rd) was compared with fixed-duration Rd (Rd18) or fixed-duration combination Tx with melphalan, prednisone, and thalidomide (MPT), each for 18 months (mos), in NDMM pts who were ineligible for stem cell transplantation. Continuous Rd extended progression-free survival (PFS) and overall survival (interim analysis) vs. MPT. However, it is still unclear whether extending Tx duration with Rd adversely affects healthcare resource utilization. This analysis quantifies the rates of hospitalizations and medical utilization with continuous Rd over time based on data collected in the FIRST trial. Methods: The FIRST trial (N = 1,623) was a pivotal multinational, randomized, open-label study with a median follow up of 37 mos. Non-protocol-driven resource-use data was collected until subjects discontinued study Tx. To assess whether continuous Rd increases healthcare resource utilization over time, the rates of resource utilization for subjects treated with continuous Rd (N = 535) were plotted for up to 48 mos. In addition, hospitalization and medical utilization rates during the Tx period (18 mos) were estimated and compared between the 2 fixed-duration Tx arms. Results: Resource utilization amongst pts treated with continuous Rd declined over time (Figure). The annualized hospitalization rate in the first 3 mos was 3.2 times higher than the average rate for the remaining 45 mos of follow-up (2.02 vs. 0.62), and 4.2 times higher for medical utilization (5.66 vs. 1.34). After 4 years (yrs) of continuous Rd Tx, hospitalization and medical utilization rates were estimated to be 83% and 84% lower than those observed in the first 3 mos of Tx, reflecting the long-term disease control observed with continuous Rd in the FIRST trial. The highest hospitalization rates were associated with infections (0.20 per patient year), cardiovascular disorders (0.06), and respiratory and thoracic disorders (0.05). The mean (standard deviation) length of stay per admission was 14.08 (21.19) days. The highest medical utilization rates were associated with blood transfusions (0.76 interventions per patient year), general imaging procedures (0.21), respiratory and thoracic imaging procedures (0.20), and therapeutic interventions (0.09).The hospitalization rates for the fixed dose Tx arms were 0.91 (Rd18) and 0.79 (MPT) per patient year of follow-up during the Tx period of 18 mos, resulting in a rate ratio (RR) of 1.15 (1.01–1.30). The equivalent rates for medical utilization were 3.00 (Rd18) and 2.86 (MPT) medical interventions per patient year (RR = 1.05 [0.98–1.12]). Conclusions: The rates of resource utilization among pts treated with continuous Rd dropped substantially after the first 3 mos of Tx, and then gradually declined as Tx duration increased. The findings suggest that continuous Tx with Rd does not further increase resource utilization in hospitalizations and medical utilization compared to fixed-duration Tx. A comparison between the 2 fixed arms showed a 15% increase in hospitalization with Rd18 vs. MPT, and no differences in medical utilization between the 2 arms. A limitation of this analysis is that the resources were collected only while pts were receiving their respective Txs. Future analysis should include all costs generated by healthcare resources throughout pts Tx, including Tx-free intervals, and the costs associated with relapses. Figure 1: Hospitalization and medical utilization rates per patient year for patients treated with continuous Rd Figure 1:. Hospitalization and medical utilization rates per patient year for patients treated with continuous Rd Disclosures Weisel: BMS: Consultancy; Onyx: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene Corporation: Consultancy, Honoraria; Noxxon: Consultancy. Off Label Use: Lenalidomide used in newly diagnosed multiple myeloma patients. Vogl:Amgen: Consultancy; Millennium/Takeda: Research Funding; GSK: Research Funding; Acetylon: Research Funding; Celgene Corporation: Consultancy. Delforge:Janssen: Honoraria; Celgene Corporation: Honoraria. Song:Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Dimopoulos:Celgene Corporation: Consultancy, Honoraria. Cavenagh:Celgene Corporation: Honoraria. Hulin:Celgene Corporation: Honoraria. Foá:Celgene Corporation: Consultancy. Oriol:Janssen: Consultancy, Speakers Bureau; Celgene Corporation: Consultancy, Speakers Bureau. Guo:Celgene Corporation: Consultancy. Monzini:Celgene Corporation: Employment, Equity Ownership. Van Oostendorp:Celgene: Employment. Ervin-Haynes:Celgene: Employment. Facon:Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".