Evidence map›Paper›PMID 40913625›Full record

ArticleAnnals of hematology2025

Comparison of prognostication by IPSS-M, IPSS-R and AIPSS-MDS in the context of limited availability of molecular data in daily clinical practice.

Felicitas Schulz, Carolin Kellersmann, Beate Betz, Barbara Hildebrandt, Annika Kasprzak, Corinna Strupp, Felicitas Thol, Michael Heuser, Christina Ganster, Fabian Beier and 11 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of hematology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

21 authors.

Felicitas SchulzDepartment of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany. FelicitasIsabel.Schulz@med.uni-duesseldorf.de.
Carolin KellersmannDepartment of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Beate BetzDepartment of Human Genetics, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
Barbara HildebrandtDepartment of Human Genetics, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
Annika KasprzakDepartment of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Corinna StruppDepartment of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Felicitas TholDepartment of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany.
Michael HeuserDepartment of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany.
Christina GansterDepartment of Hematology and Medical Oncology, INDIGHO laboratory University Medical Center Göttingen (UMG), Göttingen, Germany.
Fabian BeierDepartment of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty, RWTH Aachen University, Aachen, Germany.
Katja SockelMedical Clinic and Policlinic I, University Hospital Carl Gustav Carus Dresden, Dresden, Germany.
Wolf-Karsten HofmannDepartment of Hematology and Oncology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Andrea KuendgenDepartment of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Paul JaegerDepartment of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Michael Pfeilstoecker3rd Medical Department for Hematology and Oncology, Hanusch Hospital, Vienna, Austria.
Michael LausekerInstitute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.
Sascha DietrichDepartment of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Nobert GattermannDepartment of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Kathrin NachtkampDepartment of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Detlef HaaseDepartment of Hematology and Medical Oncology, INDIGHO laboratory University Medical Center Göttingen (UMG), Göttingen, Germany.
Ulrich GermingDepartment of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The IPSS-M was developed to revolutionize the prediction of MDS patients' survival by incorporating molecular data. To compensate for lack of access to molecular analyses, the AIPSS-MDS, a supervised machine learning algorithm exclusively based on clinical and cytogenetic data, was developed by the Spanish MDS Group. We used data of the Düsseldorf MDS Registry and included 207 of more than 8500 registry patients whose IPSS-M-requested complete molecular data were known to compare and validate prognostication regarding OS and LFS of the IPSS-M, IPSS-R and AIPSS-MDS. All three tools reliably prognosticated median OS of patients even in a comparatively small patient cohort. The IPSS-M provided the most accurate prediction of median OS while the frequent lack of molecular data persists as an obstacle in daily clinical practice. Due to these circumstances, the IPSS-R remains the prognostication tool with the widest applicability. Based on our data, prognostication using the AIPSS-MDS is also feasible but less precise.

Indexed as

Myelodysplastic SyndromesRegistriesAdultAgedAged, 80 and overAlgorithmsFemaleHumansMaleMiddle AgedPrognosisIPSSMDSMyelodysplastic syndromesPrognostication

Identifiers

PMID40913625
PMCPMC12552242

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Registered trials

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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.