Evidence map›Paper›PMID 38986047›Full record

ArticleJCO precision oncology2024

Quantitative Integrative Survival Prediction in Multiple Myeloma Patients Treated With Bortezomib-Based Induction, High-Dose Therapy and Autologous Stem Cell Transplantation.

Manuela Hummel, Thomas Hielscher, Martina Emde-Rajaratnam, Hans Salwender, Susanne Beck, Christof Scheid, Uta Bertsch, Hartmut Goldschmidt, Anna Jauch, Jérôme Moreaux and 2 more

Abstract read
In one paragraph

Article in JCO precision oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Manuela HummelDeutsches Krebsforschungszentrum, Abteilung für Biostatistik, Heidelberg, Germany.
Thomas HielscherDeutsches Krebsforschungszentrum, Abteilung für Biostatistik, Heidelberg, Germany.ORCID 0000-0003-1277-310X
Martina Emde-RajaratnamDepartment of Hematology and Immunology, Myeloma Center Brussels & Labor für Myelomforschung, Vrije Universiteit Brussel (VUB), Jette, Belgium.
Hans SalwenderAsklepios Tumorzentrum Hamburg, AK Altona and St Georg, Hamburg, Germany.ORCID 0000-0001-7803-0814
Susanne BeckDepartment of Hematology and Immunology, Myeloma Center Brussels & Labor für Myelomforschung, Vrije Universiteit Brussel (VUB), Jette, Belgium.ORCID 0000-0002-2652-8722
Christof ScheidDepartment I of Internal Medicine, University of Cologne, Cologne, Germany.ORCID 0009-0007-6539-226X
Uta BertschUniversitätsklinikum Heidelberg, Medizinische Klinik V, Heidelberg, Germany.
Hartmut GoldschmidtUniversitätsklinikum Heidelberg, Medizinische Klinik V, Heidelberg, Germany.ORCID 0000-0003-0961-0035
Anna JauchUniversität Heidelberg, Institut für Humangenetik, Heidelberg, Germany.
Jérôme MoreauxInstitute of Human Genetics, UMR 9002 CNRS-UM, Montpellier, France.ORCID 0000-0002-5717-3207
Anja SeckingerDepartment of Hematology and Immunology, Myeloma Center Brussels & Labor für Myelomforschung, Vrije Universiteit Brussel (VUB), Jette, Belgium.
Dirk HoseDepartment of Hematology and Immunology, Myeloma Center Brussels & Labor für Myelomforschung, Vrije Universiteit Brussel (VUB), Jette, Belgium.ORCID 0000-0003-0806-5223

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeGiven the high heterogeneity in survival for patients with multiple myeloma, it would be clinically useful to quantitatively predict the individual survival instead of attributing patients to two to four risk groups as in current models, for example, revised International Staging System (R-ISS), R2-ISS, or Mayo-2022-score. PATIENTS AND

methodsOur aim was to develop a quantitative prediction tool for individual patient's 3-/5-year overall survival (OS) probability. We integrated established clinical and molecular risk factors into a comprehensive prognostic model and evaluated and validated its risk discrimination capabilities versus R-ISS, R2-ISS, and Mayo-2022-score.

resultsA nomogram for estimating OS probabilities was built on the basis of a Cox regression model. It allows one to translate the individual risk profile of a patient into 3-/5-year OS probabilities by attributing points to each prognostic factor and summing up all points. The nomogram was externally validated regarding discrimination and calibration. There was no obvious bias or overfitting of the prognostic index on the validation cohort. Resampling-based and external evaluation showed good calibration. The c-index of the model was similar on the training (0.76) and validation cohort (0.75) and significantly higher than for the R-ISS (

conclusionIn summary, we developed and validated individual quantitative nomogram-based OS prediction. Continuous risk assessment integrating molecular prognostic factors is superior to R-ISS, R2-ISS, or Mayo-2022-score alone.

Indexed as

BortezomibMultiple MyelomaNomogramsTransplantation, AutologousAdultAgedAntineoplastic AgentsFemaleHematopoietic Stem Cell TransplantationHumansInduction ChemotherapyMaleMiddle AgedPrognosisSurvival RateAntineoplastic AgentsBortezomib

Identifiers

PMID38986047
PMCPMC11371111

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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.