The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors
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 Meta...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
van Holstein, Yara [verfasserIn] Mooijaart, Simon P. [verfasserIn] van Oevelen, Mathijs [verfasserIn] van Deudekom, Floor J. [verfasserIn] Vojinovic, Dina [verfasserIn] Bizzarri, Daniele [verfasserIn] van den Akker, Erik B. [verfasserIn] Noordam, Raymond [verfasserIn] Deelen, Joris [verfasserIn] van Heemst, Diana [verfasserIn] de Glas, Nienke A. [verfasserIn] Holterhues, Cynthia [verfasserIn] Labots, Geert [verfasserIn] van den Bos, Frederiek [verfasserIn] Beekman, Marian [verfasserIn] Slagboom, P. Eline [verfasserIn] van Munster, Barbara C. [verfasserIn] Portielje, Johanneke E. A. [verfasserIn] Trompet, Stella [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2024 |
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| Übergeordnetes Werk: |
Enthalten in: GeroScience - Springer International Publishing, 2017, 46(2024), 6 vom: 04. Juli, Seite 5615-5627 |
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| Übergeordnetes Werk: |
volume:46 ; year:2024 ; number:6 ; day:04 ; month:07 ; pages:5615-5627 |
| Links: |
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| DOI / URN: |
10.1007/s11357-024-01261-6 |
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| Katalog-ID: |
SPR057932204 |
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| 100 | 1 | |a van Holstein, Yara |e verfasserin |0 (orcid)0000-0002-6882-639X |4 aut | |
| 245 | 1 | 0 | |a The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors |
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| 520 | |a 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. | ||
| 650 | 4 | |a Geriatric oncology |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Geriatric assessment |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Metabolomics |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Biomarkers |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Mortality |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Mooijaart, Simon P. |e verfasserin |4 aut | |
| 700 | 1 | |a van Oevelen, Mathijs |e verfasserin |4 aut | |
| 700 | 1 | |a van Deudekom, Floor J. |e verfasserin |4 aut | |
| 700 | 1 | |a Vojinovic, Dina |e verfasserin |4 aut | |
| 700 | 1 | |a Bizzarri, Daniele |e verfasserin |4 aut | |
| 700 | 1 | |a van den Akker, Erik B. |e verfasserin |4 aut | |
| 700 | 1 | |a Noordam, Raymond |e verfasserin |4 aut | |
| 700 | 1 | |a Deelen, Joris |e verfasserin |4 aut | |
| 700 | 1 | |a van Heemst, Diana |e verfasserin |4 aut | |
| 700 | 1 | |a de Glas, Nienke A. |e verfasserin |4 aut | |
| 700 | 1 | |a Holterhues, Cynthia |e verfasserin |4 aut | |
| 700 | 1 | |a Labots, Geert |e verfasserin |4 aut | |
| 700 | 1 | |a van den Bos, Frederiek |e verfasserin |4 aut | |
| 700 | 1 | |a Beekman, Marian |e verfasserin |4 aut | |
| 700 | 1 | |a Slagboom, P. Eline |e verfasserin |4 aut | |
| 700 | 1 | |a van Munster, Barbara C. |e verfasserin |4 aut | |
| 700 | 1 | |a Portielje, Johanneke E. A. |e verfasserin |4 aut | |
| 700 | 1 | |a Trompet, Stella |e verfasserin |4 aut | |
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10.1007/s11357-024-01261-6 doi (DE-627)SPR057932204 (SPR)s11357-024-01261-6-e DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ PHARM DE-84 fid 44.68 bkl van Holstein, Yara verfasserin (orcid)0000-0002-6882-639X aut The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 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. Geriatric oncology (dpeaa)DE-He213 Geriatric assessment (dpeaa)DE-He213 Metabolomics (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Mooijaart, Simon P. verfasserin aut van Oevelen, Mathijs verfasserin aut van Deudekom, Floor J. verfasserin aut Vojinovic, Dina verfasserin aut Bizzarri, Daniele verfasserin aut van den Akker, Erik B. verfasserin aut Noordam, Raymond verfasserin aut Deelen, Joris verfasserin aut van Heemst, Diana verfasserin aut de Glas, Nienke A. verfasserin aut Holterhues, Cynthia verfasserin aut Labots, Geert verfasserin aut van den Bos, Frederiek verfasserin aut Beekman, Marian verfasserin aut Slagboom, P. Eline verfasserin aut van Munster, Barbara C. verfasserin aut Portielje, Johanneke E. A. verfasserin aut Trompet, Stella verfasserin aut Enthalten in GeroScience Springer International Publishing, 2017 46(2024), 6 vom: 04. Juli, Seite 5615-5627 Online-Ressource (DE-627)881285536 (DE-600)2886418-9 (DE-576)484664158 2509-2723 nnns volume:46 year:2024 number:6 day:04 month:07 pages:5615-5627 https://dx.doi.org/10.1007/s11357-024-01261-6 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER FID-PHARM SSG-OLC-PHA SSG-OPC-PHA SSG-OPC-DE-84 GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 44.68 Gerontologie Geriatrie VZ AR 46 2024 6 04 07 5615-5627 |
| spelling |
10.1007/s11357-024-01261-6 doi (DE-627)SPR057932204 (SPR)s11357-024-01261-6-e DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ PHARM DE-84 fid 44.68 bkl van Holstein, Yara verfasserin (orcid)0000-0002-6882-639X aut The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 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. Geriatric oncology (dpeaa)DE-He213 Geriatric assessment (dpeaa)DE-He213 Metabolomics (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Mooijaart, Simon P. verfasserin aut van Oevelen, Mathijs verfasserin aut van Deudekom, Floor J. verfasserin aut Vojinovic, Dina verfasserin aut Bizzarri, Daniele verfasserin aut van den Akker, Erik B. verfasserin aut Noordam, Raymond verfasserin aut Deelen, Joris verfasserin aut van Heemst, Diana verfasserin aut de Glas, Nienke A. verfasserin aut Holterhues, Cynthia verfasserin aut Labots, Geert verfasserin aut van den Bos, Frederiek verfasserin aut Beekman, Marian verfasserin aut Slagboom, P. Eline verfasserin aut van Munster, Barbara C. verfasserin aut Portielje, Johanneke E. A. verfasserin aut Trompet, Stella verfasserin aut Enthalten in GeroScience Springer International Publishing, 2017 46(2024), 6 vom: 04. Juli, Seite 5615-5627 Online-Ressource (DE-627)881285536 (DE-600)2886418-9 (DE-576)484664158 2509-2723 nnns volume:46 year:2024 number:6 day:04 month:07 pages:5615-5627 https://dx.doi.org/10.1007/s11357-024-01261-6 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER FID-PHARM SSG-OLC-PHA SSG-OPC-PHA SSG-OPC-DE-84 GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 44.68 Gerontologie Geriatrie VZ AR 46 2024 6 04 07 5615-5627 |
| allfields_unstemmed |
10.1007/s11357-024-01261-6 doi (DE-627)SPR057932204 (SPR)s11357-024-01261-6-e DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ PHARM DE-84 fid 44.68 bkl van Holstein, Yara verfasserin (orcid)0000-0002-6882-639X aut The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 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. Geriatric oncology (dpeaa)DE-He213 Geriatric assessment (dpeaa)DE-He213 Metabolomics (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Mooijaart, Simon P. verfasserin aut van Oevelen, Mathijs verfasserin aut van Deudekom, Floor J. verfasserin aut Vojinovic, Dina verfasserin aut Bizzarri, Daniele verfasserin aut van den Akker, Erik B. verfasserin aut Noordam, Raymond verfasserin aut Deelen, Joris verfasserin aut van Heemst, Diana verfasserin aut de Glas, Nienke A. verfasserin aut Holterhues, Cynthia verfasserin aut Labots, Geert verfasserin aut van den Bos, Frederiek verfasserin aut Beekman, Marian verfasserin aut Slagboom, P. Eline verfasserin aut van Munster, Barbara C. verfasserin aut Portielje, Johanneke E. A. verfasserin aut Trompet, Stella verfasserin aut Enthalten in GeroScience Springer International Publishing, 2017 46(2024), 6 vom: 04. Juli, Seite 5615-5627 Online-Ressource (DE-627)881285536 (DE-600)2886418-9 (DE-576)484664158 2509-2723 nnns volume:46 year:2024 number:6 day:04 month:07 pages:5615-5627 https://dx.doi.org/10.1007/s11357-024-01261-6 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER FID-PHARM SSG-OLC-PHA SSG-OPC-PHA SSG-OPC-DE-84 GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 44.68 Gerontologie Geriatrie VZ AR 46 2024 6 04 07 5615-5627 |
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10.1007/s11357-024-01261-6 doi (DE-627)SPR057932204 (SPR)s11357-024-01261-6-e DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ PHARM DE-84 fid 44.68 bkl van Holstein, Yara verfasserin (orcid)0000-0002-6882-639X aut The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 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. Geriatric oncology (dpeaa)DE-He213 Geriatric assessment (dpeaa)DE-He213 Metabolomics (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Mooijaart, Simon P. verfasserin aut van Oevelen, Mathijs verfasserin aut van Deudekom, Floor J. verfasserin aut Vojinovic, Dina verfasserin aut Bizzarri, Daniele verfasserin aut van den Akker, Erik B. verfasserin aut Noordam, Raymond verfasserin aut Deelen, Joris verfasserin aut van Heemst, Diana verfasserin aut de Glas, Nienke A. verfasserin aut Holterhues, Cynthia verfasserin aut Labots, Geert verfasserin aut van den Bos, Frederiek verfasserin aut Beekman, Marian verfasserin aut Slagboom, P. Eline verfasserin aut van Munster, Barbara C. verfasserin aut Portielje, Johanneke E. A. verfasserin aut Trompet, Stella verfasserin aut Enthalten in GeroScience Springer International Publishing, 2017 46(2024), 6 vom: 04. Juli, Seite 5615-5627 Online-Ressource (DE-627)881285536 (DE-600)2886418-9 (DE-576)484664158 2509-2723 nnns volume:46 year:2024 number:6 day:04 month:07 pages:5615-5627 https://dx.doi.org/10.1007/s11357-024-01261-6 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER FID-PHARM SSG-OLC-PHA SSG-OPC-PHA SSG-OPC-DE-84 GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 44.68 Gerontologie Geriatrie VZ AR 46 2024 6 04 07 5615-5627 |
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10.1007/s11357-024-01261-6 doi (DE-627)SPR057932204 (SPR)s11357-024-01261-6-e DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ PHARM DE-84 fid 44.68 bkl van Holstein, Yara verfasserin (orcid)0000-0002-6882-639X aut The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 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. Geriatric oncology (dpeaa)DE-He213 Geriatric assessment (dpeaa)DE-He213 Metabolomics (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Mooijaart, Simon P. verfasserin aut van Oevelen, Mathijs verfasserin aut van Deudekom, Floor J. verfasserin aut Vojinovic, Dina verfasserin aut Bizzarri, Daniele verfasserin aut van den Akker, Erik B. verfasserin aut Noordam, Raymond verfasserin aut Deelen, Joris verfasserin aut van Heemst, Diana verfasserin aut de Glas, Nienke A. verfasserin aut Holterhues, Cynthia verfasserin aut Labots, Geert verfasserin aut van den Bos, Frederiek verfasserin aut Beekman, Marian verfasserin aut Slagboom, P. Eline verfasserin aut van Munster, Barbara C. verfasserin aut Portielje, Johanneke E. A. verfasserin aut Trompet, Stella verfasserin aut Enthalten in GeroScience Springer International Publishing, 2017 46(2024), 6 vom: 04. Juli, Seite 5615-5627 Online-Ressource (DE-627)881285536 (DE-600)2886418-9 (DE-576)484664158 2509-2723 nnns volume:46 year:2024 number:6 day:04 month:07 pages:5615-5627 https://dx.doi.org/10.1007/s11357-024-01261-6 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER FID-PHARM SSG-OLC-PHA SSG-OPC-PHA SSG-OPC-DE-84 GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 44.68 Gerontologie Geriatrie VZ AR 46 2024 6 04 07 5615-5627 |
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Enthalten in GeroScience 46(2024), 6 vom: 04. Juli, Seite 5615-5627 volume:46 year:2024 number:6 day:04 month:07 pages:5615-5627 |
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van Holstein, Yara @@aut@@ Mooijaart, Simon P. @@aut@@ van Oevelen, Mathijs @@aut@@ van Deudekom, Floor J. @@aut@@ Vojinovic, Dina @@aut@@ Bizzarri, Daniele @@aut@@ van den Akker, Erik B. @@aut@@ Noordam, Raymond @@aut@@ Deelen, Joris @@aut@@ van Heemst, Diana @@aut@@ de Glas, Nienke A. @@aut@@ Holterhues, Cynthia @@aut@@ Labots, Geert @@aut@@ van den Bos, Frederiek @@aut@@ Beekman, Marian @@aut@@ Slagboom, P. Eline @@aut@@ van Munster, Barbara C. @@aut@@ Portielje, Johanneke E. A. @@aut@@ Trompet, Stella @@aut@@ |
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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. 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van Holstein, Yara |
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van Holstein, Yara ddc 610 fid PHARM bkl 44.68 misc Geriatric oncology misc Geriatric assessment misc Metabolomics misc Biomarkers misc Mortality The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors |
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610 VZ PHARM DE-84 fid 44.68 bkl The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors Geriatric oncology (dpeaa)DE-He213 Geriatric assessment (dpeaa)DE-He213 Metabolomics (dpeaa)DE-He213 Biomarkers (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 |
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The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors |
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van Holstein, Yara Mooijaart, Simon P. van Oevelen, Mathijs van Deudekom, Floor J. Vojinovic, Dina Bizzarri, Daniele van den Akker, Erik B. Noordam, Raymond Deelen, Joris van Heemst, Diana de Glas, Nienke A. Holterhues, Cynthia Labots, Geert van den Bos, Frederiek Beekman, Marian Slagboom, P. Eline van Munster, Barbara C. Portielje, Johanneke E. A. Trompet, Stella |
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the performance of metabolomics-based prediction scores for mortality in older patients with solid tumors |
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The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors |
| abstract |
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. © The Author(s) 2024 |
| abstractGer |
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. © The Author(s) 2024 |
| abstract_unstemmed |
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. © The Author(s) 2024 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR057932204</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20241022064805.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">241022s2024 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11357-024-01261-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR057932204</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11357-024-01261-6-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">PHARM</subfield><subfield code="q">DE-84</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.68</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">van Holstein, Yara</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-6882-639X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2024</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2024</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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. 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| score |
7.402793 |