Evidence map›Paper›PMID 39904814›Full record

ArticleClinical and experimental medicine2025

Clinicopathologic predictors of renal response and survival in newly diagnosed multiple myeloma with renal injury: a retrospective study.

Wei Wei, Haotian Shi, Haimin Chen, Xiaoling Chen, Rong Peng, Wenjun Yu, Lixia Wu, Nian Zhou, Wenhao Zhao, Weiwei Xu and 4 more

Abstract read
In one paragraph

Article in Clinical and experimental medicine, 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. Article
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

14 authors.

Wei Wei *Department of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Haotian Shi *Department of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Haimin Chen *Department of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Xiaoling ChenDepartment of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Rong PengDepartment of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Wenjun YuDepartment of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Lixia WuDepartment of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Nian ZhouDepartment of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Wenhao ZhaoDepartment of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Weiwei XuDepartment of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Yan ZhouDepartment of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Jingjing YuDepartment of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China.
Daolin WeiDepartment of Hematology, Shanghai Zhaxin Traditional Chinese & Western Medicine Hospital, Shanghai, China. daolinwei@hotmail.com.
Fan ZhouDepartment of Hematologic & Oncology, Zhabei Central Hospital in Shanghai Jing'an District, Shanghai, China. zfsh257@163.com.

Funding

Health Committee Foundation of Jing'an District, Shanghai 2021MS10National Natural Science Foundation of China 82070226
6 · The paper itself

Abstract

Renal impairment (RI) is a common complication of multiple myeloma (MM), which is associated with poor prognosis. Here, we revealed the association between regular examination data and RI incidence, RI response and survival in newly diagnosed multiple myeloma (NDMM) patients. A retrospective analysis was conducted on the initial clinical data of 647 NDMM patients, comprising 193 patients (29.83%, 193/647) with RI and 454 (70.17%, 454/647) without RI at diagnosis. Logistic regression analyses, both univariate and multivariate, were performed to identify the independent influencing factors of RI with bootstrap techniques and resampling. The model used to predict the RI response was established using the support vector machine-recursive feature elimination (SVM-RFE) machine learning algorithms. Six variables identified by multi-factorial logistic regression analysis were independently associated with the incidence of RI, including the secreted monoclonal immunoglobulin of IgG type (33.16% vs. 52.64%), deregulated serum free κ/λ light chain (58.12% vs. 33.93%), elevated serum calcium (> 2.65 mmol/L, 31.61% vs. 11.01%), elevated urea (≥ 8.3 mmol/L, 92.23% vs. 20.26%), elevated uric acid (≥ 340 μmol/L, 74.61% vs. 35.46%), and ISS (International Staging System) stage of III (90.16% vs. 31.50%). The lactate dehydrogenase (≥ 250 U/L; HR = 1.786, P = 0.005) and CKD (chronic kidney disease) stage (G4-G5; HR = 5.830, P = 0.016) were the independent adverse factors of the overall survival of NDMM patients with RI. In addition, this study provided a model to predict the response of RI using 5 clinical features, including calcium, Durie-Salmon (DS) stage, creatinine level before treatment, age and gender. The sensitivity, specificity, area under the curve (AUC) and accuracy were 86.75%, 51.15%, 78.30% and 72.99% in the training group, while 79.31%, 52.94%, 72.40% and 69.57% in the validation group. In conclusion, this study clarified the relationship between clinicopathologic characteristics and the incidence of renal injury, response and survival of NDMM patients, supporting clinical decision-making, and offering significant clinical application value.

Indexed as

Multiple MyelomaAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesSurvival AnalysisMultiple myelomaRenal impairmentResponseSurvival support vector machine-recursive feature elimination

Identifiers

PMID39904814
PMCPMC11794406

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.