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

Journal Article (2024)
Author(s)

Yara van Holstein (Leiden University Medical Center)

Simon P. Mooijaart (Leiden University Medical Center)

Mathijs van Oevelen (Leiden University Medical Center)

Floor J. van Deudekom (Onze Lieve Vrouwe Gasthuis)

Dina Vojinovic (Leiden University Medical Center, Erasmus MC)

D. Bizzarri (TU Delft - Pattern Recognition and Bioinformatics, Leiden University Medical Center)

Erik Ben van den Akker (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)

Raymond Noordam (Leiden University Medical Center)

Joris Deelen (University of Cologne, Max Planck Institute for Biology of Ageing)

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Research Group
Pattern Recognition and Bioinformatics
DOI related publication
https://doi.org/10.1007/s11357-024-01261-6
More Info
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Publication Year
2024
Language
English
Research Group
Pattern Recognition and Bioinformatics
Issue number
6
Volume number
46
Pages (from-to)
5615-5627
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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.