Evidence map›Paper›PMID 41316358›Full record

ArticleEuropean journal of medical research2025

Development and validation of a novel frailty model for the patients with newly diagnosed multiple myeloma.

Biao Tian, Li Xu, Shuangshuang Jia, Wenrui Sun, Chunyan Zhang, Juan Feng, Juan Hui, Miaoyu Li, Wanting Xiao, Lulu Wang and 7 more

Abstract readValidation Study
In one paragraph

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

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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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

17 authors.

Biao Tian *Department of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Li Xu *Department of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Shuangshuang Jia *Department of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Wenrui SunDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Chunyan ZhangDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Juan FengDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Juan HuiDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Miaoyu LiDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Wanting XiaoDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Lulu WangDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Ruochen WuDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Yanxia WengDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Zhenyang LiDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Jiao JiaDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Zeyi AiDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
Hailong TangDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China. thl19880713@163.com.
Guangxun GaoDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China. gaoguangxun@fmmu.edu.cn.

Funding

Shaanxi Province Health Blood Tumor Disease Scientific Research Innovation Project (No.2023TD-03the National Natural Science Foundation of China No. 82470203
6 · The paper itself

Abstract

backgroundThe predominance of ageing in patients with multiple myeloma (MM) results in at least 30% of patients being classified as frail at diagnosis. Compared with healthy individuals, frail individuals exhibit reduced treatment tolerance and lower quality of life, which are correlated with decreased survival rates. Although various frailty models for MM have been developed, challenges remain in their broad application and timely adjustment of treatment based on frailty evaluations across heterogeneous patient groups.

methodsThis retrospective study analysed data from 606 patients with newly diagnosed MM at Xijing Hospital between May 2006 and August 2022. The dataset was randomly divided into a development set (N = 424) and a validation set (N = 182). A novel frailty model (Fmodel) was developed using LASSO regression, random survival forest, and both univariate and multivariate Cox regression analyses. The model can predict overall survival (OS) and progression-free survival (PFS) in patients with MM while distinguishing frail subgroups. Its performance was compared with the previously established frailty model (Smodel) and the Revised International Staging System (RISS).

resultsThe Fmodel incorporates five variables: age, HCT-CI, ECOG-PS, ISS, and PNI. It stratified patients into three categories: fit, intermediate fit, and frail. Compared with the Smodel and RISS, the Fmodel exhibited robust discrimination and stability in predicting OS and PFS in both the development and validation sets and demonstrated superior calibration, discrimination, clinical applicability, and predictive ability. Frail patients were found to be at a greater risk for grade ≥ 2 nonhematologic adverse events (AEs) when receiving conventional-dose treatment (p < 0.05). Furthermore, the Fmodel provided accurate predictions of early mortality in patients with MM.

conclusionWe developed a novel frailty model for patients with MM based on age, HCT-CI, ECOG-PS, ISS, and PNI, effectively identifying the frail population.

Indexed as

FrailtyMultiple MyelomaAgedAged, 80 and overFemaleHumansMaleMiddle AgedPrognosisQuality of LifeRetrospective StudiesECOG-PSFrailty modelHCT-CIMultiple myelomaPNI

Identifiers

PMID41316358
PMCPMC12817602

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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.