Preliminary efficacy of optimal pharmacotherapy and patient views in multiple myeloma.
Bibliographic record
Abstract
e20006 Background: As new agents are approved for multiple myeloma (MM) and existing drugs become generic, treatments that represent optimal use of healthcare funds need to be reassessed. A therapeutic review was initiated to compare the clinical and cost-effectiveness of treatments for newly diagnosed (NDMM) patients who are ineligible for stem cell transplantation and those who are relapsed and/or are refractory (RRMM). This abstract reports on the clinical efficacy of treatments for both populations along with patient experiences, expectations, and perspectives of treatment for MM. Methods: A systematic literature search of randomized controlled phase III trials (RCTs), published between January 1996 and April 2021, that met the eligibility criteria in either population were included. Two network meta-analyses (NMA), one per population, were conducted to compare the efficacy across treatments for the primary endpoint of progression-free survival (PFS). PFS was defined as the time from randomization to either disease progression or death. A random-effects model was used in both populations to estimate the hazard ratio (HR) and 95% credible intervals (CrIs) for PFS. Myeloma Canada conducted seven surveys between January 2016 and May 2021 that addressed expectations when selecting a treatment option in MM. A literature search of qualitative studies published between January 2016 and May 2021 was conducted on patients’ perspectives and experiences on treatment decisions in MM. Results: There were 29 RCTs in each NMA with an overall low risk of bias. The NDMM NMA identified 11 regimens that had numerically lower hazards for PFS compared to lenalidomide + dexamethasone (Rd), with HRs ranging from 0.38 to 0.99. The RRMM network showed 15 regimens that had numerically lower hazards for PFS compared to Rd, with HRs ranging from 0.44 to 0.99. Due to the wide 95% CrIs, conclusions on differences in PFS for each population are limited. Myeloma Canada collated data from 2,297 survey respondents. Ten qualitative studies of low to moderate quality were included. The survey data and qualitative studies found that choosing a treatment must involve a holistic approach beyond the efficacy of a therapy. Conclusions: The uncertainty in both NMAs limit firm conclusions on differences in PFS across treatment options in each population. Among the survey respondents, socioeconomic status was unclear which may influence patients’ expectations and preferences for treatment decisions in MM. Insufficient reporting in the qualitative studies makes it unclear how a patient’s treatment decisions changes over time. For Canadian payers to optimize the funding of treatment options available in MM, the results from the NMAs combined with Canadian real-world evidence will inform the development of an economic model to assess the cost-effectiveness of treatment sequences in NDMM.
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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 | 0.057 | 0.223 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".