Evidence map›Paper›PMID 40783547›Full record

ArticleCancer cell international2025

Predicting survival of persons with newly-diagnosed multiple myeloma.

Limei Zhang, Yun Wang, Robert Peter Gale, Yang Liang

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Article in Cancer cell international, 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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5 · Who and what money

Authors and funding

4 authors.

Limei Zhang *Department of Hematological Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Centre for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
Yun Wang *Department of Hematological Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Centre for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
Robert Peter GaleCentre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, UK.
Yang LiangDepartment of Hematological Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Centre for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China. liangyang@sysucc.org.cn.

Funding

National Natural Science Foundation of China 81873428Sun Yat-sen University Start-up Funding 201603the Ministry of Science and Technology of China 84000-51200002
6 · The paper itself

Abstract

backgroundPredicting survival in newly diagnosed multiple myeloma (NDMM) patients accurately remains challenging. Although mSMART3.0 is widely used it has not been rigorously tested for prediction accuracy.

methodsWe analysed clinical and laboratory variables in 1,008 NDMM patients, randomly split into a training set (n = 704) and a validation set (n = 304). Univariable and multivariable Cox regression analyses identified independent prognostic factors, forming a baseline survival model. For patients with available mSMART3.0 data, we integrated it with the baseline nomogram to enhance predictive accuracy. Time-dependent area under the receiver-operator characteristic curve (timeROC), calibration plots as well as comparisons with other survival prediction systems were used to estimated model performance.

resultsThe baseline models, incorporating eight factors, achieved 5-year survival AUCs of 0.77 (95% CI: 0.72–0.81) in the training set and 0.73 (95% CI: 0.66–0.80) in the validation set. In the training set, 5-year survival was 34% (95% CI: 28–41%) in the high-risk group versus 72% (95% CI: 67–78%) in the low-risk group (p < 0.001), with similar differences observed in the validation set. The model exhibited excellent discrimination and calibration in both sets. In the training cohort the merged nomogram increased the 5-year survival AUCs of mSMART3.0 from 0.64 (0.57, 0.71) to 0.75 (0.67, 0.83; p = 0.003), better than the other staging systems of MM.

conclusionsThe proposed nomograms increased the survival prediction accuracy in patients with NDMM.

Indexed as

mSMART 3.0.Multiple myelomaNomogramSurvival

Identifiers

PMID40783547
PMCPMC12335180

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