Bibliographic record
Abstract
Canada’s Drug Agency (CDA-AMC) recommends that Talvey not be reimbursed by public drug plans for the treatment of adult patients with relapsed or refractory multiple myeloma (RRMM) who have received at least 3 prior lines of therapy, including a proteasome inhibitor (PI), an immunomodulatory drug (IMiD), and an anti-CD38 monoclonal antibody (mAb), and who have demonstrated disease progression on or after the last therapy. Evidence from 1 clinical study showed that Talvey may improve treatment response rates in adults with RRMM who have received at least 3 prior lines of therapy. However, no causal conclusions could be drawn about the effect of Talvey on the outcomes important to patients and clinicians (e.g., progression-free survival and overall survival) based on the weak evidence from 1 noncomparative clinical trial. The evidence is insufficient to determine whether Talvey meets patient needs for effective, accessible, and portable treatment options that can extend life, delay worsening or spreading of disease, improve quality of life, and reduce side effects. Talvey’s adverse effect profile may not align with patient values regarding side effects. Notably, dysgeusia — an unfavourable side effect from the patient perspective — was 1 of the most frequently reported adverse events with Talvey in the submitted clinical trial. Other frequently reported side effects may be considered unfavourable by patients, as the patient group input reported infections and nail, skin, and oral issues as the least bearable side effects.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.056 | 0.013 |
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".