Evidence map›Paper›PMID 40502745›Full record

ArticleResearch square2025

Enhanced Risk Stratification of Smoldering Multiple Myeloma with Dynamic Biomarkers: A Multinational, Multicenter Study including 2,270 Participants (PANGEA 2.0).

Floris Chabrun, Daniel Schwartz, Susanna Gentile, Elias Mai, Tulika Gupta, Jacqueline Perry, David Cordas Dos Santos, Thomas Hielscher, Annika Werly, Sophia Schmidt and 38 more

Abstract readPreprint
In one paragraph

Article in Research square, 2025. 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
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

48 authors.

Floris ChabrunAngers University Hospital.ORCID 0000-0001-6871-8711
Daniel SchwartzDana-Farber Cancer Institute.
Susanna GentileDana-Farber Cancer Institute.
Elias MaiHeidelberg University Hospital.ORCID 0000-0002-6226-1252
Tulika GuptaDana Farber Cancer Institute.
Jacqueline PerryDana-Farber Cancer Institute.
David Cordas Dos SantosDana-Farber Cancer Institute.ORCID 0000-0002-9198-8338
Thomas HielscherGerman Cancer Research Center (DKFZ).
Annika WerlyHeidelberg University Hospital and Medical Faculty Heidelberg.
Sophia SchmidtHeidelberg University Hospital and Medical Faculty Heidelberg.
Foteini TheodorakakouNational and Kapodistrian University of Athens.
Despina FotiouNational and Kapodistrian University of Athens.
Christine LiacosNational and Kapodistrian University of Athens.
Nikolaos KanelliasNational and Kapodistrian University of Athens.
Noelia GisbertCancer Center Clinica Universidad de Navarra.
Esperanza Martin-SanchezCancer Center Clinica Universidad de Navarra.
Rosalinda TerminiCancer Center Clinica Universidad de Navarra.
Johannes WaldschmidtUniversity Hospital Wuerzburg.
Selina ChavdaUniversity College London.
Louise AinleyUniversity College London.
Matteo Claudio Da ViàFondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico.
Claudio de MagistrisFondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico.
Loredana PettineFondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico.
Michael TimonianDana-Farber Cancer Institute, Harvard Medical School, Broad Institute of MIT & Harvard.ORCID 0000-0002-1014-3502
Jean-Baptiste AlbergeDana-Farber Cancer Institute.ORCID 0000-0002-4218-7294
Vidhi PatelDana-Farber Cancer Institute.
Patrick CostelloDana-Farber Cancer Institute.
Catherine TobiaDana-Farber Cancer Institute.
Sally PhanDana-Farber Cancer Institute.
Jennifer LambDana-Farber Cancer Institute.
Maria-Theresa SilverioDana-Farber Cancer Institute.
Maya DavisDana-Farber Cancer Institute.
Elizabeth O'DonnellDana-Farber Cancer Institute.
Catherine MarinacDana-Farber Cancer Institute.
Omar NadeemDana-Farber Cancer Institute.
Niccolo BolliDepartment of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy.ORCID 0000-0002-1018-5139
Kwee YongUniversity College London.ORCID 0000-0002-6487-276X
Martin KortümUniversity Hospital Würzburg.ORCID 0000-0002-7011-0286
Hermann EinseleUniversity Hospital Würzburg.ORCID 0000-0002-7680-0819
Maria Victoria Mateos MantecaHospital Universitario de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBASL), Centro de Investigación del Cáncer (IBMCC-USAL,CSIC).ORCID 0000-0003-2390-1218
Shaji KumarMayo clinic.ORCID 0000-0001-5392-9284
Jesus San MiguelUniversity of Navarra.ORCID 0000-0002-9183-4857
Bruno PaivaCancer Center Clinica Universidad de Navarra.ORCID 0000-0003-1977-3815
Efstathis KastritisNational and Kapodistrian University of Athens School of Medicine.
Meletios DimopoulosSchool of Medicine, National and Kapodistrian University of Athens.ORCID 0000-0001-8990-3254
Marc RaabHeidelberg University Hospital, German Cancer Research Center (DKFZ).ORCID 0000-0003-4181-6922
Lorenzo TrippaDana-Farber Cancer Institute.
Irene GhobrialDana-Farber Cancer Institute.ORCID 0000-0001-7361-3092

Funding

Training Grant in Quantitative Sciences for Cancer ResearchT32CA009337 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI QUACKENBUSH, JOHN, TRIPPA, LORENZO · 1986 to 2025
$12.3M
Molecular Prediction of Myeloma Initiation Molecular Prediction of Myeloma InitiationR35CA263817 · NCI · DANA-FARBER CANCER INST · PI Irene M. Ghobrial · 2022 to 2026
$5.1M
Molecular prediction of myeloma in African AmericansU01CA271492 · NCI · DANA-FARBER CANCER INST · PI Catherine Marinac · 2022 to 2026
$4.3M
NCI NIH HHS R35 CA263817NCI NIH HHS T32 CA009337NCI NIH HHS U01 CA271492
6 · The paper itself

Abstract

Accurate prediction of risk of progression from smoldering (SMM) to active multiple myeloma (MM) is paramount to individualized early therapeutic strategies with minimum risk of overtreatment. Current risk stratification models do not account for evolving biomarker trajectories. We assembled the largest cohort to date of 2,270 SMM patients from six international centers with longitudinal clinical and biological data to train and validate the PANGEA 2.0 risk models. Four evolving biomarkers were significantly associated with shorter time-to-progression: M-protein increase ≥0.2g/dL, involved:uninvolved serum free light chain ratio increase ≥20, creatinine increase >25%, and hemoglobin decrease ≥1.5g/dL. PANGEA 2.0 outperforms established models including the 20/2/20 and IMWG models by more accurately predicting progression (C-statistics=0.69-0.84), even without biomarker history (C-statistics=0.69-0.83) or recent bone marrow biopsy. PANGEA 2.0 is an easy-to-use, open-access tool (https://ghobrial.shinyapps.io/pangea_2_calculator) to improve and individualize SMM risk stratification. Validation tools are available to compare PANGEA 2.0 to established models (https://ghobrial.shinyapps.io/pangea_validation).

Indexed as

dynamic risk stratificationmultiple myelomarisk predictionSmoldering multiple myeloma

Identifiers

PMID40502745
PMCPMC12155220

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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.