Evidence map›Paper›PMID 42717545›Full record

ArticleCancer medicine2026

A Multivariable Prediction Model for Early Mortality in Multiple Myeloma Patients With Renal Impairment.

Menghan Liu, Yuan Jian, Huixing Zhou, Jing Jia, Jiachen Li, Chuanying Geng, Guangzhong Yang, Wenrong Huang, Xinan Cen, Wenming Chen and 2 more

Abstract readMulticenter Study
In one paragraph

Article in Cancer medicine, 2026. 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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0cells of the map it votes in
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

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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.

Menghan LiuDepartment of Hematology, Myeloma Research Center of Beijing, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-6189-7267
Yuan JianDepartment of Hematology, Myeloma Research Center of Beijing, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Huixing ZhouDepartment of Hematology, Myeloma Research Center of Beijing, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0001-5966-5523
Jing JiaDepartment of Hematology, Myeloma Research Center of Beijing, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0001-7457-3424
Jiachen LiDepartment of Evidence-Based Medicine Center, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Chuanying GengDepartment of Hematology, Myeloma Research Center of Beijing, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0001-6080-1983
Guangzhong YangDepartment of Hematology, Myeloma Research Center of Beijing, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-7289-5806
Wenrong HuangDepartment of Hematology, Fifth Medical Center, General Hospital of The People's Liberation Army, Beijing, China.
Xinan CenDepartment of Hematology, Peking University First Hospital, Beijing, China.
Wenming ChenDepartment of Hematology, Myeloma Research Center of Beijing, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0001-6298-8489
Honghu ZhuDepartment of Hematology, Myeloma Research Center of Beijing, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0003-2343-0436
Wen GaoDepartment of Hematology, Myeloma Research Center of Beijing, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0003-4600-099X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite therapeutic advances, early mortality remains a significant challenge in multiple myeloma (MM) patients with renal impairment (RI), with no validated prognostic models currently available for this high-risk subgroup. This multicenter, retrospective study aimed to develop and validate a practical nomogram for predicting early death (< 12 months) using readily accessible clinical parameters. We analyzed data from 285 newly diagnosed MM patients with RI treated between 2007 and 2020, divided into training (n = 222) and validation (n = 63) cohorts. Multivariate analysis identified five independent predictors of early mortality: age > 55 years (OR 3.48, 95% CI 1.10-11.01), serum calcium ≥ 2.5 mmol/L (OR 3.29, 95% CI 1.30-8.29), bone marrow plasma cell percentage ≥ 40% (OR 2.90, 95% CI 1.24-6.77), renal response less than partial response (OR 0.27, 95% CI 0.11-0.65), and hematologic response less than complete response (OR 20.93, 95% CI 4.61-95.10). The developed nomogram demonstrated excellent discrimination (AUC 0.858) and calibration in the training cohort, with consistent performance in validation (AUC 0.747). Risk stratification categorized patients into three distinct prognostic groups with significantly different early mortality rates: Low Risk (1.6%), Mid Risk (13.9%), and High Risk (43.9%). This validated model provides the first practical tool for early mortality risk stratification in MM patients with RI, enabling clinicians to identify high-risk patients who may benefit from more intensive interventions. Further prospective validation is warranted to confirm generalizability.

Indexed as

Multiple MyelomaNomogramsRenal InsufficiencyAgedFemaleHumansMaleMiddle AgedMultivariate AnalysisPrediction AlgorithmsPrognosisRetrospective Studies

Identifiers

PMID42717545
PMCPMC13559019

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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.