Evidence map›Paper›PMID 39054795›Full record

ArticleAnnals of laboratory medicine2025

Assessing the Relevance of Non-molecular Prognostic Systems for Myelodysplastic Syndrome in the Era of Next-Generation Sequencing.

Marco Lincango, Verónica Andreoli, Hernán García Rivello, Andrea Bender, Ana I Catalán, Marilina Rahhal, Rocío Delamer, Mariana Asinari, Adrián Mosquera Orgueira, María Belén Castro and 7 more

Abstract read
In one paragraph

Article in Annals of laboratory medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Marco LincangoLaboratorio de Genética Hematológica, Instituto de Medicina Experimental (IMEX-CONICET)/Academia Nacional de Medicina, Ciudad de Buenos Aires, Argentina.ORCID https://orcid.org/0000-0001-8769-6538
Verónica AndreoliHospital Universitario Privado de Córdoba, Córdoba, Argentina.ORCID https://orcid.org/0009-0003-1995-8518
Hernán García RivelloHospital Italiano de Buenos Aires, Ciudad de Buenos Aires, Argentina.ORCID https://orcid.org/0000-0003-2056-464X
Andrea BenderLaboratorio de Especialidades Bioquímicas, Bahía Blanca, Argentina.ORCID https://orcid.org/0009-0002-6208-3043
Ana I CatalánHospital de Clínicas "Dr. Manuel Quintela," Facultad de Medicina, Universidad de la República, Montevideo, Uruguay.ORCID https://orcid.org/0009-0003-2458-7272
Marilina RahhalHospital de Alta Complejidad "El Cruce Nestor Kirchner," Florencio Varela, Argentina.ORCID https://orcid.org/0009-0001-7379-2622
Rocío DelamerFundaleu, Ciudad de Buenos Aires, Argentina.ORCID https://orcid.org/0009-0005-3725-6960
Mariana AsinariHospital Universitario Privado de Córdoba, Córdoba, Argentina.ORCID https://orcid.org/0000-0002-2230-5038
Adrián Mosquera OrgueiraUniversity Hospital of Santiago de Compostela, IDIS, Spain.ORCID https://orcid.org/0000-0003-4838-6750
María Belén CastroHospital Universitario Privado de Córdoba, Córdoba, Argentina.ORCID https://orcid.org/0000-0002-6067-6470
María José Mela OsorioFundaleu, Ciudad de Buenos Aires, Argentina.ORCID https://orcid.org/0000-0002-1871-5798
Alicia NavickasHospital de Alta Complejidad "El Cruce Nestor Kirchner," Florencio Varela, Argentina.ORCID https://orcid.org/0009-0009-1849-4065
Sofia GrilleHospital de Clínicas "Dr. Manuel Quintela," Facultad de Medicina, Universidad de la República, Montevideo, Uruguay.ORCID https://orcid.org/0000-0002-0590-7109
Evangelina AgrielloLaboratorio de Especialidades Bioquímicas, Bahía Blanca, Argentina.ORCID https://orcid.org/0009-0003-1154-9103
Jorge ArbelbideHospital Italiano de Buenos Aires, Ciudad de Buenos Aires, Argentina.ORCID https://orcid.org/0000-0003-2367-6161
Ana Lisa BasquieraHospital Universitario Privado de Córdoba, Córdoba, Argentina.ORCID https://orcid.org/0000-0001-9892-5543
Carolina B BelliLaboratorio de Genética Hematológica, Instituto de Medicina Experimental (IMEX-CONICET)/Academia Nacional de Medicina, Ciudad de Buenos Aires, Argentina.ORCID https://orcid.org/0000-0001-5034-1055

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The Molecular International Prognostic Scoring System (IPSS-M) has improved the prediction of clinical outcomes for myelodysplastic syndromes (MDS). The Artificial Intelligence Prognostic Scoring System for MDS (AIPSS-MDS), based on classical clinical parameters, has outperformed the IPSS, revised version (IPSS-R). For the first time, we validated the IPSS-M and other molecular prognostic models and compared them with the established IPSS-R and AIPSS-MDS models using data from South American patients. Methods: Molecular and clinical data from 145 patients with MDS and 37 patients with MDS/myeloproliferative neoplasms were retrospectively analyzed. Results: Prognostic power evaluation revealed that the IPSS-M (Harrell's concordance [C]-index: 0.75, area under the receiver operating characteristic curve [AUC]: 0.68) predicted overall survival better than the European MDS (EuroMDS; C-index: 0.72, AUC: 0.68) and Munich Leukemia Laboratory (MLL) (C-index: 0.70, AUC: 0.64) models. The IPSS-M prognostic discrimination was similar to that of the AIPSS-MDS model (C-index: 0.74, AUC: 0.66) and outperformed the IPSS-R model (C-index: 0.70, AUC: 0.61). Considering simplified low- and high-risk groups for clinical management, after restratifying from IPSS-R (57% and 32%, respectively, hazard ratio [HR]: 2.8; Conclusions: The IPSS-M and AIPSS-MDS models provide more accurate survival prognoses than the IPSS-R, EuroMDS, and MLL models. The AIPSS-MDS model is a valid option for assessing risks for all patients with MDS, especially in resource-limited centers where molecular testing is not currently a standard clinical practice.

Indexed as

Area Under CurveHigh-Throughput Nucleotide SequencingMyelodysplastic SyndromesROC CurveAdultAgedAged, 80 and overFemaleHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsRetrospective StudiesArtificial Intelligence Prognostic Scoring SystemModelMolecular International Prognostic Scoring SystemMyelodysplastic syndromePrognosticRisk assessmentSouth AmericaSurvival analysisTherapy

Identifiers

PMID39054795
PMCPMC11609712

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.