A Systematic Literature Review of Predictors of Erythropoiesis-Stimulating Agent Failure in Lower-Risk Myelodysplastic Syndromes
Bibliographic record
Abstract
Erythropoiesis-stimulating agents (ESAs) are the first-line treatment option for anemia in patients with lower-risk myelodysplastic syndromes (LR-MDS). A systematic literature review was conducted to identify evidence of the association between prognostic factors and ESA response/failure in LR-MDS. MEDLINE, Embase, and relevant conferences were searched systematically for studies assessing the association between prognostic factors and ESA response/failure in adult patients. Of 1566 citations identified, 38 were included. Patient risk status in studies published from 2000 onwards was commonly assessed using the International Prognostic Scoring System (IPSS) or revised IPSS. ESA response was generally assessed using the International Working Group MDS criteria. Among the included studies, statistically significant relationships were found, in both univariate and multivariate analyses, between ESA response and the following prognostic factors: higher hemoglobin levels, lower serum erythropoietin levels, and transfusion independence. Furthermore, other prognostic factors such as age, bone marrow blasts, serum ferritin level, IPSS risk status, and karyotype status did not demonstrate statistically significant relationships with ESA response. This systematic literature review has confirmed prognostic factors of ESA response/failure. Guidance to correctly identify patients with these characteristics could be helpful for clinicians to provide optimal treatment.
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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".