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Validation of Predictive Models for Response to Erythropoiesis-Stimulating Agents in Myelodysplastic Syndromes

2015· article· en· W2561937338 on OpenAlexaff
Zachary Gowanlock, Swetha Sriram, Alison Martin, Alejandro Lazo‐Langner

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineInternational Prognostic Scoring SystemCohortInternal medicineMyelodysplastic syndromesAnemiaDarbepoetin alfaEpoetin alfaErythropoietinRetrospective cohort studyBone marrowOncology

Abstract

fetched live from OpenAlex

Abstract Background: Erythropoiesis-stimulating agents (ESAs) increase hemoglobin, reduce transfusion requirements and improve quality of life in myelodysplastic syndromes (MDS), but many patients do not respond to treatment. Various scoring systems have been developed to predict which patients with MDS will respond to ESAs. The Nordic score derived by Hellstrom-Lindberg et al. stratifies patients based on the erythropoietin (EPO) level and transfusion frequency. Houston et al. have proposed another score which is based on EPO and the International Prognostic Scoring System (IPSS) risk group. The latter score has not yet been validated. We assessed the validity of these scoring systems in an independent cohort of patients with MDS. Patients and methods: We conducted a retrospective cohort study including all patients with confirmed MDS based on bone marrow biopsy, aspirate or cytogenetic findings who were treated with ESAs at our institution from 2005 to 2013 and who had available follow-up information. Both the International Working Group (IWG) 2006 criteria and the Nordic study response criteria were used to assess treatment response. Statistical significance of both scores was assessed using Pearson's chi-squared test. Analysis was repeated with the score by Houston et al. dichotomized to low (0 or 1) or high (2 or 3). Results: Of 180 patients diagnosed with MDS, 44 patients met our inclusion criteria. Forty patients were treated with epoetin alfa and 4 were treated with darbepoetin alfa. The mean age was 76.4 years and 61% were male. The mean pretreatment hemoglobin was 85.3 g/L. There was a significant difference in the treatment response between the Nordic score groups using the Nordic response criteria but the difference was insignificant using the IWG criteria (Table 1). We found no difference in treatment response between the scores by Houston et al. using either response criteria, however a low score (0 or 1) predicted a significantly better response than a high score (2 or 3). An EPO level less than 100 IU/L was a statistically significant predictor of treatment response but the IPSS designation was not. Conclusion: Our results have validated the Nordic score using the same response criteria as the original study, but our population size was not adequate to validate the Nordic score using IWG criteria. We have confirmed that patients with EPO levels below 100 IU/L respond to treatment significantly better than patients above 100 IU/L. Our data does not support the use of the IPSS risk group in predicting treatment response, but this result may be limited by the relatively small number of patients. Further studies exploring the predictive variables in MDS treatment with ESAs are warranted. Table 1. ESA Response in MDS Scoring Systems Score N Nordic criteriaa IWG criteriab ResponseN (%) p-valuec Response N (%) p-valuec Nordic Score Good (> +1) 19 10 (53) 0.033d 9 (47) 0.141 Int. (-1 to +1) 24 4 (17) 5 (21) Poor (< -1) 1 0 (0) 0 (0) Score by Houston et al. 0 8 3 (38) 0.347 3 (38) 0.080 1 15 7 (47) 8 (53) 2 4 1 (25) 0 (0) 3 17 3 (18) 3 (18) Dichotomized Score by Houston et al. Low (0 - 1) 23 10 (43) 0.082 11 (48) 0.017d High (2 - 3) 21 4 (19) 3 (14) EPO < 100 IU/L 23 - - 11 (48) 0.017d ≥ 100 IU/L 21 - 3 (14) IPSS Risk Group Low 12 - - 3 (25) 0.552 Int-1 or Int-2 32 - 11 (34) a Increase in hemoglobin to >115 g/L, increase in hemoglobin of >15 g/L, or 100% decrease in transfusion requirements b Increase in hemoglobin of ≥15 g/L, or ≥4 less transfusions (for hemoglobin ≤90 g/L) in 8 weeks compared to 8 weeks pretreatment c Group comparison using Pearson's chi-squared test d p < 0.05 Disclosures Lazo-Langner: Pfizer: Honoraria; Bayer: 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)0.012
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.087
GPT teacher head0.355
Teacher spread0.268 · 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 designSimulation or modeling
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
Published2015
Admission routes1
Has abstractyes

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