Precision prognostics for cardiovascular disease in Type 2 diabetes : a systematic review and meta-analysis
© 2024. The Author(s)..
BACKGROUND: Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D).
METHODS: We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies.
RESULTS: Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort.
CONCLUSIONS: Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.
| Errataetall: | |
|---|---|
| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:4 |
|---|---|
| Enthalten in: |
Communications medicine - 4(2024), 1 vom: 22. Jan., Seite 11 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Ahmad, Abrar [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| Anmerkungen: |
Date Revised 20.03.2024 published: Electronic UpdateOf: medRxiv. 2023 Aug 21;:. - PMID 37162891 Citation Status PubMed-not-MEDLINE |
|---|
| doi: |
10.1038/s43856-023-00429-z |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM367443139 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM367443139 | ||
| 003 | DE-627 | ||
| 005 | 20240320234009.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 240123s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1038/s43856-023-00429-z |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1337.xml |
| 035 | |a (DE-627)NLM367443139 | ||
| 035 | |a (NLM)38253823 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Ahmad, Abrar |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Precision prognostics for cardiovascular disease in Type 2 diabetes |b a systematic review and meta-analysis |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 20.03.2024 | ||
| 500 | |a published: Electronic | ||
| 500 | |a UpdateOf: medRxiv. 2023 Aug 21;:. - PMID 37162891 | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a © 2024. The Author(s). | ||
| 520 | |a BACKGROUND: Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D) | ||
| 520 | |a METHODS: We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies | ||
| 520 | |a RESULTS: Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort | ||
| 520 | |a CONCLUSIONS: Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D | ||
| 650 | 4 | |a Journal Article | |
| 700 | 1 | |a Lim, Lee-Ling |e verfasserin |4 aut | |
| 700 | 1 | |a Morieri, Mario Luca |e verfasserin |4 aut | |
| 700 | 1 | |a Tam, Claudia Ha-Ting |e verfasserin |4 aut | |
| 700 | 1 | |a Cheng, Feifei |e verfasserin |4 aut | |
| 700 | 1 | |a Chikowore, Tinashe |e verfasserin |4 aut | |
| 700 | 1 | |a Dudenhöffer-Pfeifer, Monika |e verfasserin |4 aut | |
| 700 | 1 | |a Fitipaldi, Hugo |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Chuiguo |e verfasserin |4 aut | |
| 700 | 1 | |a Kanbour, Sarah |e verfasserin |4 aut | |
| 700 | 1 | |a Sarkar, Sudipa |e verfasserin |4 aut | |
| 700 | 1 | |a Koivula, Robert Wilhelm |e verfasserin |4 aut | |
| 700 | 1 | |a Motala, Ayesha A |e verfasserin |4 aut | |
| 700 | 1 | |a Tye, Sok Cin |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Gechang |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Yingchai |e verfasserin |4 aut | |
| 700 | 1 | |a Provenzano, Michele |e verfasserin |4 aut | |
| 700 | 1 | |a Sherifali, Diana |e verfasserin |4 aut | |
| 700 | 1 | |a de Souza, Russell J |e verfasserin |4 aut | |
| 700 | 1 | |a Tobias, Deirdre Kay |e verfasserin |4 aut | |
| 700 | 0 | |a ADA/EASD PMDI |e verfasserin |4 aut | |
| 700 | 1 | |a Gomez, Maria F |e verfasserin |4 aut | |
| 700 | 1 | |a Ma, Ronald C W |e verfasserin |4 aut | |
| 700 | 1 | |a Mathioudakis, Nestoras |e verfasserin |4 aut | |
| 700 | 1 | |a Tobias, Deirdre K |e investigator |4 oth | |
| 700 | 1 | |a Merino, Jordi |e investigator |4 oth | |
| 700 | 1 | |a Aiken, Catherine |e investigator |4 oth | |
| 700 | 1 | |a Benham, Jamie L |e investigator |4 oth | |
| 700 | 1 | |a Bodhini, Dhanasekaran |e investigator |4 oth | |
| 700 | 1 | |a Clark, Amy L |e investigator |4 oth | |
| 700 | 1 | |a Colclough, Kevin |e investigator |4 oth | |
| 700 | 1 | |a Corcoy, Rosa |e investigator |4 oth | |
| 700 | 1 | |a Cromer, Sara J |e investigator |4 oth | |
| 700 | 1 | |a Duan, Daisy |e investigator |4 oth | |
| 700 | 1 | |a Felton, Jamie L |e investigator |4 oth | |
| 700 | 1 | |a Francis, Ellen C |e investigator |4 oth | |
| 700 | 1 | |a Gillard, Pieter |e investigator |4 oth | |
| 700 | 1 | |a Gingras, Véronique |e investigator |4 oth | |
| 700 | 1 | |a Gaillard, Romy |e investigator |4 oth | |
| 700 | 1 | |a Haider, Eram |e investigator |4 oth | |
| 700 | 1 | |a Hughes, Alice |e investigator |4 oth | |
| 700 | 1 | |a Ikle, Jennifer M |e investigator |4 oth | |
| 700 | 1 | |a Jacobsen, Laura M |e investigator |4 oth | |
| 700 | 1 | |a Kahkoska, Anna R |e investigator |4 oth | |
| 700 | 1 | |a Kettunen, Jarno L T |e investigator |4 oth | |
| 700 | 1 | |a Kreienkamp, Raymond J |e investigator |4 oth | |
| 700 | 1 | |a Lim, Lee-Ling |e investigator |4 oth | |
| 700 | 1 | |a Männistö, Jonna M E |e investigator |4 oth | |
| 700 | 1 | |a Massey, Robert |e investigator |4 oth | |
| 700 | 1 | |a Mclennan, Niamh-Maire |e investigator |4 oth | |
| 700 | 1 | |a Miller, Rachel G |e investigator |4 oth | |
| 700 | 1 | |a Most, Jasper |e investigator |4 oth | |
| 700 | 1 | |a Naylor, Rochelle N |e investigator |4 oth | |
| 700 | 1 | |a Ozkan, Bige |e investigator |4 oth | |
| 700 | 1 | |a Patel, Kashyap Amratlal |e investigator |4 oth | |
| 700 | 1 | |a Pilla, Scott J |e investigator |4 oth | |
| 700 | 1 | |a Prystupa, Katsiaryna |e investigator |4 oth | |
| 700 | 1 | |a Raghavan, Sridharan |e investigator |4 oth | |
| 700 | 1 | |a Rooney, Mary R |e investigator |4 oth | |
| 700 | 1 | |a Schön, Martin |e investigator |4 oth | |
| 700 | 1 | |a Semnani-Azad, Zhila |e investigator |4 oth | |
| 700 | 1 | |a Sevilla-Gonzalez, Magdalena |e investigator |4 oth | |
| 700 | 1 | |a Svalastoga, Pernille |e investigator |4 oth | |
| 700 | 1 | |a Takele, Wubet Worku |e investigator |4 oth | |
| 700 | 1 | |a Tam, Claudia Ha-Ting |e investigator |4 oth | |
| 700 | 1 | |a Thuesen, Anne Cathrine B |e investigator |4 oth | |
| 700 | 1 | |a Tosur, Mustafa |e investigator |4 oth | |
| 700 | 1 | |a Wallace, Amelia S |e investigator |4 oth | |
| 700 | 1 | |a Wang, Caroline C |e investigator |4 oth | |
| 700 | 1 | |a Wong, Jessie J |e investigator |4 oth | |
| 700 | 1 | |a Yamamoto, Jennifer M |e investigator |4 oth | |
| 700 | 1 | |a Young, Katherine |e investigator |4 oth | |
| 700 | 1 | |a Amouyal, Chloé |e investigator |4 oth | |
| 700 | 1 | |a Andersen, Mette K |e investigator |4 oth | |
| 700 | 1 | |a Bonham, Maxine P |e investigator |4 oth | |
| 700 | 1 | |a Chen, Mingling |e investigator |4 oth | |
| 700 | 1 | |a Chikowore, Tinashe |e investigator |4 oth | |
| 700 | 1 | |a Chivers, Sian C |e investigator |4 oth | |
| 700 | 1 | |a Clemmensen, Christoffer |e investigator |4 oth | |
| 700 | 1 | |a Dabelea, Dana |e investigator |4 oth | |
| 700 | 1 | |a Dawed, Adem Y |e investigator |4 oth | |
| 700 | 1 | |a Deutsch, Aaron J |e investigator |4 oth | |
| 700 | 1 | |a Dickens, Laura T |e investigator |4 oth | |
| 700 | 1 | |a DiMeglio, Linda A |e investigator |4 oth | |
| 700 | 1 | |a Evans-Molina, Carmella |e investigator |4 oth | |
| 700 | 1 | |a Fernández-Balsells, María Mercè |e investigator |4 oth | |
| 700 | 1 | |a Fitzpatrick, Stephanie L |e investigator |4 oth | |
| 700 | 1 | |a Gitelman, Stephen E |e investigator |4 oth | |
| 700 | 1 | |a Goodarzi, Mark O |e investigator |4 oth | |
| 700 | 1 | |a Grieger, Jessica A |e investigator |4 oth | |
| 700 | 1 | |a Guasch-Ferré, Marta |e investigator |4 oth | |
| 700 | 1 | |a Habibi, Nahal |e investigator |4 oth | |
| 700 | 1 | |a Hansen, Torben |e investigator |4 oth | |
| 700 | 1 | |a Huang, Chuiguo |e investigator |4 oth | |
| 700 | 1 | |a Harris-Kawano, Arianna |e investigator |4 oth | |
| 700 | 1 | |a Ismail, Heba M |e investigator |4 oth | |
| 700 | 1 | |a Hoag, Benjamin |e investigator |4 oth | |
| 700 | 1 | |a Johnson, Randi K |e investigator |4 oth | |
| 700 | 1 | |a Jones, Angus G |e investigator |4 oth | |
| 700 | 1 | |a Koivula, Robert W |e investigator |4 oth | |
| 700 | 1 | |a Leong, Aaron |e investigator |4 oth | |
| 700 | 1 | |a Leung, Gloria K W |e investigator |4 oth | |
| 700 | 1 | |a Libman, Ingrid M |e investigator |4 oth | |
| 700 | 1 | |a Liu, Kai |e investigator |4 oth | |
| 700 | 1 | |a Long, S Alice |e investigator |4 oth | |
| 700 | 1 | |a Lowe, William L |c Jr |e investigator |4 oth | |
| 700 | 1 | |a Morton, Robert W |e investigator |4 oth | |
| 700 | 1 | |a Onengut-Gumuscu, Suna |e investigator |4 oth | |
| 700 | 1 | |a Pankow, James S |e investigator |4 oth | |
| 700 | 1 | |a Pathirana, Maleesa |e investigator |4 oth | |
| 700 | 1 | |a Pazmino, Sofia |e investigator |4 oth | |
| 700 | 1 | |a Perez, Dianna |e investigator |4 oth | |
| 700 | 1 | |a Petrie, John R |e investigator |4 oth | |
| 700 | 1 | |a Powe, Camille E |e investigator |4 oth | |
| 700 | 1 | |a Quinteros, Alejandra |e investigator |4 oth | |
| 700 | 1 | |a Jain, Rashmi |e investigator |4 oth | |
| 700 | 1 | |a Ray, Debashree |e investigator |4 oth | |
| 700 | 1 | |a Ried-Larsen, Mathias |e investigator |4 oth | |
| 700 | 1 | |a Saeed, Zeb |e investigator |4 oth | |
| 700 | 1 | |a Santhakumar, Vanessa |e investigator |4 oth | |
| 700 | 1 | |a Kanbour, Sarah |e investigator |4 oth | |
| 700 | 1 | |a Sarkar, Sudipa |e investigator |4 oth | |
| 700 | 1 | |a Monaco, Gabriela S F |e investigator |4 oth | |
| 700 | 1 | |a Scholtens, Denise M |e investigator |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |t Communications medicine |d 2021 |g 4(2024), 1 vom: 22. Jan., Seite 11 |w (DE-627)NLM330650033 |x 2730-664X |7 nnns |
| 773 | 1 | 8 | |g volume:4 |g year:2024 |g number:1 |g day:22 |g month:01 |g pages:11 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1038/s43856-023-00429-z |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 4 |j 2024 |e 1 |b 22 |c 01 |h 11 | ||