Evidence map›Paper›PMID 38963649›Full record

ArticleGeroScience2024

The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors.

Yara van Holstein, Simon P Mooijaart, Mathijs van Oevelen, Floor J van Deudekom, Dina Vojinovic, Daniele Bizzarri, Erik B van den Akker, Raymond Noordam, Joris Deelen, Diana van Heemst and 9 more

Abstract read
In one paragraph

Article in GeroScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Urinary metabolic age from high-resolution nuclear magnetic resonance spectroscopy reveals longitudinal aging patterns.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
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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

19 authors.

Yara van HolsteinDepartment of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO box 9600, 2300 RC, Leiden, The Netherlands. Y.van_Holstein@lumc.nl.ORCID 0000-0002-6882-639X
Simon P MooijaartDepartment of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO box 9600, 2300 RC, Leiden, The Netherlands.
Mathijs van OevelenDepartment of Internal Medicine, Section of Nephrology, Leiden University Medical Center, Leiden, The Netherlands.
Floor J van DeudekomDepartment of Geriatric Medicine, OLVG Hospitals Amsterdam, Amsterdam, The Netherlands.
Dina VojinovicDepartment of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Daniele BizzarriDepartment of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Erik B van den AkkerDepartment of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Raymond NoordamDepartment of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO box 9600, 2300 RC, Leiden, The Netherlands.
Joris DeelenMax Planck Institute for Biology of Ageing, Cologne, Germany.
Diana van HeemstDepartment of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO box 9600, 2300 RC, Leiden, The Netherlands.
Nienke A de GlasDepartment of Medical Oncology, Leiden University Medical Center, Leiden, The Netherlands.
Cynthia HolterhuesDepartment of Internal Medicine, Haga Hospital, The Hague, The Netherlands.
Geert LabotsDepartment of Internal Medicine, Haga Hospital, The Hague, The Netherlands.
Frederiek van den BosDepartment of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO box 9600, 2300 RC, Leiden, The Netherlands.
Marian BeekmanDepartment of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
P Eline SlagboomDepartment of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Barbara C van MunsterDepartment of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands.
Johanneke E A PortieljeDepartment of Medical Oncology, Leiden University Medical Center, Leiden, The Netherlands.
Stella TrompetDepartment of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO box 9600, 2300 RC, Leiden, The Netherlands.

Funding

ZonMw 457001001
6 · The paper itself

Abstract

Prognostic information is needed to balance benefits and risks of cancer treatment in older patients. Metabolomics-based scores were previously developed to predict 5- and 10-year mortality (MetaboHealth) and biological age (MetaboAge). This study aims to investigate the association of MetaboHealth and MetaboAge with 1-year mortality in older patients with solid tumors, and to study their predictive value for mortality in addition to established clinical predictors. This prospective cohort study included patients aged ≥ 70 years with a solid malignant tumor, who underwent blood sampling and a geriatric assessment before treatment initiation. The outcome was all-cause 1-year mortality. Of the 192 patients, the median age was 77 years. With each SD increase of MetaboHealth, patients had a 2.32 times increased risk of mortality (HR 2.32, 95% CI 1.59-3.39). With each year increase in MetaboAge, there was a 4% increased risk of mortality (HR 1.04, 1.01-1.07). MetaboHealth and MetaboAge showed an AUC of 0.66 (0.56-0.75) and 0.60 (0.51-0.68) for mortality prediction accuracy, respectively. The AUC of a predictive model containing age, primary tumor site, distant metastasis, comorbidity, and malnutrition was 0.76 (0.68-0.83). Addition of MetaboHealth increased AUC to 0.80 (0.74-0.87) (p = 0.09) and AUC did not change with MetaboAge (0.76 (0.69-0.83) (p = 0.89)). Higher MetaboHealth and MetaboAge scores were associated with 1-year mortality. The addition of MetaboHealth to established clinical predictors only marginally improved mortality prediction in this cohort with various types of tumors. MetaboHealth may potentially improve identification of older patients vulnerable for adverse events, but numbers were too small for definitive conclusions. The TENT study is retrospectively registered at the Netherlands Trial Register (NTR), trial number NL8107. Date of registration: 22-10-2019.

Indexed as

Geriatric AssessmentMetabolomicsNeoplasmsAgedAged, 80 and overFemaleHumansMalePredictive Value of TestsPrognosisProspective StudiesRisk AssessmentBiomarkersGeriatric assessmentGeriatric oncologyMetabolomicsMortality

Identifiers

PMID38963649
PMCPMC11493906

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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.