Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis

Author:

Ahmad AbrarORCID,Lim Lee-LingORCID,Morieri Mario LucaORCID,Tam Claudia Ha-ting,Cheng Feifei,Chikowore Tinashe,Dudenhöffer-Pfeifer Monika,Fitipaldi Hugo,Huang Chuiguo,Kanbour Sarah,Sarkar Sudipa,Koivula Robert Wilhelm,Motala Ayesha A.ORCID,Tye Sok Cin,Yu Gechang,Zhang Yingchai,Provenzano Michele,Sherifali Diana,de Souza Russell J.,Tobias Deirdre Kay,Tobias Deirdre K.,Merino Jordi,Aiken Catherine,Benham Jamie L.,Bodhini Dhanasekaran,Clark Amy L.,Colclough Kevin,Corcoy Rosa,Cromer Sara J.,Duan Daisy,Felton Jamie L.,Francis Ellen C.,Gillard Pieter,Gingras Véronique,Gaillard Romy,Haider Eram,Hughes Alice,Ikle Jennifer M.,Jacobsen Laura M.,Kahkoska Anna R.,Kettunen Jarno L. T.,Kreienkamp Raymond J.,Lim Lee-Ling,Männistö Jonna M. E.,Massey Robert,Mclennan Niamh-Maire,Miller Rachel G.,Most Jasper,Naylor Rochelle N.,Ozkan Bige,Patel Kashyap Amratlal,Pilla Scott J.,Prystupa Katsiaryna,Raghavan Sridharan,Rooney Mary R.,Schön Martin,Semnani-Azad Zhila,Sevilla-Gonzalez Magdalena,Svalastoga Pernille,Takele Wubet Worku,Tam Claudia Ha-ting,Thuesen Anne Cathrine B.,Tosur Mustafa,Wallace Amelia S.,Wang Caroline C.,Wong Jessie J.,Yamamoto Jennifer M.,Young Katherine,Amouyal Chloé,Andersen Mette K.,Bonham Maxine P.,Chen Mingling,Chikowore Tinashe,Chivers Sian C.,Clemmensen Christoffer,Dabelea Dana,Dawed Adem Y.,Deutsch Aaron J.,Dickens Laura T.,DiMeglio Linda A.,Evans-Molina Carmella,Fernández-Balsells María Mercè,Fitzpatrick Stephanie L.,Gitelman Stephen E.,Goodarzi Mark O.,Grieger Jessica A.,Guasch-Ferré Marta,Habibi Nahal,Hansen Torben,Huang Chuiguo,Harris-Kawano Arianna,Ismail Heba M.,Hoag Benjamin,Johnson Randi K.,Jones Angus G.,Koivula Robert W.,Leong Aaron,Leung Gloria K. W.,Libman Ingrid M.,Liu Kai,Long S. Alice,Lowe William L.,Morton Robert W.,Onengut-Gumuscu Suna,Pankow James S.,Pathirana Maleesa,Pazmino Sofia,Perez Dianna,Petrie John R.,Powe Camille E.,Quinteros Alejandra,Jain Rashmi,Ray Debashree,Ried-Larsen Mathias,Saeed Zeb,Santhakumar Vanessa,Kanbour Sarah,Sarkar Sudipa,Monaco Gabriela S. F.,Scholtens Denise M.,Selvin Elizabeth,Sheu Wayne Huey-Herng,Speake Cate,Stanislawski Maggie A.,Steenackers Nele,Steck Andrea K.,Stefan Norbert,Støy Julie,Taylor Rachael,Ukke Gebresilasea Gendisha,Urazbayeva Marzhan,Van der Schueren Bart,Vatier Camille,Wentworth John M.,Hannah Wesley,White Sara L.,Yu Gechang,Zhang Yingchai,Zhou Shao J.,Beltrand Jacques,Polak Michel,Aukrust Ingvild,de Franco Elisa,Flanagan Sarah E.,Maloney Kristin A.,McGovern Andrew,Molnes Janne,Nakabuye Mariam,Njølstad Pål Rasmus,Pomares-Millan Hugo,Saint-Martin Cécile,Zhang Cuilin,Zhu Yeyi,Auh Sungyoung,de Souza Russell,Fawcett Andrea J.,Gruber Chandra,Mekonnen Eskedar Getie,Mixter Emily,Sherifali Diana,Eckel Robert H.,Nolan John J.,Philipson Louis H.,Brown Rebecca J.,Billings Liana K.,Boyle Kristen,Costacou Tina,Dennis John M.,Florez Jose C.,Gloyn Anna L.,Gottlieb Peter A.,Greeley Siri Atma W.,Griffin Kurt,Hattersley Andrew T.,Hirsch Irl B.,Hivert Marie-France,Hood Korey K.,Josefson Jami L.,Kwak Soo Heon,Laffel Lori M.,Lim Siew S.,Loos Ruth J. F.,Ma Ronald C. W.,Mathieu Chantal,Mathioudakis Nestoras,Meigs James B.,Misra Shivani,Mohan Viswanathan,Murphy Rinki,Oram Richard,Owen Katharine R.,Ozanne Susan E.,Pearson Ewan R.,Perng Wei,Pollin Toni I.,Pop-Busui Rodica,Pratley Richard E.,Redman Leanne M.,Redondo Maria J.,Reynolds Rebecca M.,Semple Robert K.,Sherr Jennifer L.,Sims Emily K.,Sweeting Arianne,Tuomi Tiinamaija,Udler Miriam S.,Vesco Kimberly K.,Vilsbøll Tina,Wagner Robert,Rich Stephen S.,Franks Paul W.,Gomez Maria F.ORCID,Ma Ronald C. W.,Mathioudakis NestorasORCID,

Abstract

Abstract 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.

Funder

U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

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