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1. Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies

Author

Pennells, Lisa, Kaptoge, Stephen, Wood, Angela, Sweeting, Mike, Zhao, Xiaohui, White, Ian, Burgess, Stephen, Willeit, Peter, Bolton, Thomas, Moons, Karel G M, van der Schouw, Yvonne T, Selmer, Randi, Khaw, Kay-Tee, Gudnason, Vilmundur, Assmann, Gerd, Amouyel, Philippe, Salomaa, Veikko, Kivimaki, Mika, Nordestgaard, Børge G, Blaha, Michael J, Kuller, Lewis H, Brenner, Hermann, Gillum, Richard F, Meisinger, Christa, Ford, Ian, Knuiman, Matthew W, Rosengren, Annika, Lawlor, Debbie A, Völzke, Henry, Cooper, Cyrus, Marín Ibañez, Alejandro, Casiglia, Edoardo, Kauhanen, Jussi, Cooper, Jackie A, Rodriguez, Beatriz, Sundström, Johan, Barrett-Connor, Elizabeth, Dankner, Rachel, Nietert, Paul J, Davidson, Karina W, Wallace, Robert B, Blazer, Dan G, Björkelund, Cecilia, Donfrancesco, Chiara, Krumholz, Harlan M, Nissinen, Aulikki, Davis, Barry R, Coady, Sean, Whincup, Peter H, Jørgensen, Torben, Ducimetiere, Pierre, Trevisan, Maurizio, Engström, Gunnar, Crespo, Carlos J, Meade, Tom W, Visser, Marjolein, Kromhout, Daan, Kiechl, Stefan, Daimon, Makoto, Price, Jackie F, Gómez de la Cámara, Agustin, Wouter Jukema, J, Lamarche, Benoît, Onat, Altan, Simons, Leon A, Kavousi, Maryam, Ben-Shlomo, Yoav, Gallacher, John, Dekker, Jacqueline M, Arima, Hisatomi, Shara, Nawar, Tipping, Robert W, Roussel, Ronan, Brunner, Eric J, Koenig, Wolfgang, Sakurai, Masaru, Pavlovic, Jelena, Gansevoort, Ron T, Nagel, Dorothea, Goldbourt, Uri, Barr, Elizabeth L M, Palmieri, Luigi, Njølstad, Inger, Sato, Shinichi, Monique Verschuren, W M, Varghese, Cherian V, Graham, Ian, Onuma, Oyere, Greenland, Philip, Woodward, Mark, Ezzati, Majid, Psaty, Bruce M, Sattar, Naveed, Jackson, Rod, Ridker, Paul M, Cook, Nancy R, D'Agostino, Ralph B, Thompson, Simon G, Danesh, John, Di Angelantonio, Emanuele, Simpson, Lara M, Pressel, Sara L, Couper, David J, Nambi, Vijay, Matsushita, Kunihiro, Folsom, Aaron R, Shaw, Jonathan E, Magliano, Dianna J, Zimmet, Paul Z, Wannamethee, S Goya, Willeit, Johann, Santer, Peter, Egger, Georg, Casas, Juan Pablo, Amuzu, Antointtte, Tikhonoff, Valérie, Sutherland, Susan E, Cushman, Mary, Søgaard, Anne Johanne, Håheim, Lise Lund, Ariansen, Inger, Tybjærg-Hansen, Anne, Jensen, Gorm B, Schnohr, Peter, Giampaoli, Simona, Vanuzzo, Diego, Panico, Salvatore, Balkau, Beverley, Bonnet, Fabrice, Marre, Michel, de la Cámara, Agustin Gómez, Rubio Herrera, Miguel Angel, Friedlander, Yechiel, McCallum, John, McLachlan, Stela, Guralnik, Jack, Phillips, Caroline L, Wareham, Nick, Schöttker, Ben, Saum, Kai-Uwe, Holleczek, Bernd, Tolonen, Hanna, Vartiainen, Erkki, Jousilahti, Pekka, Harald, Kennet, D’Agostino, Ralph B, Massaro, Joseph M, Pencina, Michael, Vasan, Ramachandran, Kayama, Takamasa, Kato, Takeo, Oizumi, Toshihide, Jespersen, Jørgen, Møller, Lars, Bladbjerg, Else Marie, Chetrit, A, Wilhelmsen, Lars, Lissner, Lauren, Dennison, Elaine, Kiyohara, Yutaka, Ninomiya, Toshiharu, Doi, Yasufumi, Nijpels, Giel, Stehouwer, Coen D A, Kazumasa, Yamagishi, Iso, Hiroyasu, Kurl, Sudhir, Tuomainen, Tomi-Pekka, Salonen, Jukka T, Deeg, Dorly J H, Nilsson, Peter M, Hedblad, Bo, Melander, Olle, De Boer, Ian H, DeFilippis, Andrew Paul, Verschuren, W M Monique, Watt, Graham, Tverdal, Aage, Kirkland, Susan, Shimbo, Daichi, Shaffer, Jonathan, Bakker, Stephan J L, van der Harst, Pim, Hillege, Hans L, Dallongeville, Jean, Schulte, Helmut, Trompet, Stella, Smit, Roelof A J, Stott, David J, Després, Jean-Pierre, Cantin, Bernard, Dagenais, Gilles R, Laughlin, Gail, Wingard, Deborah, Aspelund, Thor, Eiriksdottir, Gudny, Gudmundsson, Elias Freyr, Ikram, Arfan, van Rooij, Frank J A, Franco, Oscar H, Rueda-Ochoa, Oscar L, Muka, Taulant, Glisic, Marija, Tunstall-Pedoe, Hugh, Howard, Barbara V, Zhang, Ying, Jolly, Stacey, Davey-Smith, George, Can, Günay, Yüksel, Hüsniye, Nakagawa, Hideaki, Morikawa, Yuko, Miura, Katsuyuki, Ingelsson, Martin, Giedraitis, Vilmantas, Gaziano, J Michael, Shipley, Martin, Arndt, Volker, Cook, Nancy, Ibañez, Alejandro Marín, Geleijnse, Johanna M, Epidemiology, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, Pennells, Lisa [0000-0002-8594-3061], Kaptoge, Stephen [0000-0002-1155-4872], Wood, Angela [0000-0002-7937-304X], Sweeting, Michael [0000-0003-0980-8965], Zhao, Xiaohui [0000-0001-9922-2815], Burgess, Stephen [0000-0001-5365-8760], Danesh, John [0000-0003-1158-6791], Di Angelantonio, Emanuele [0000-0001-8776-6719], Apollo - University of Cambridge Repository, Nutrition and Health, APH - Aging & Later Life, APH - Societal Participation & Health, APH - Health Behaviors & Chronic Diseases, Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Life Course Epidemiology (LCE), AGEM - Endocrinology, metabolism and nutrition, Internal medicine, Epidemiology and Data Science, İÜC, Lisa, Pennell, Stephen, Kaptoge, Angela, Wood, Mike, Sweeting, Xiaohui, Zhao, Ian, White, Stephen, Burge, Peter, Willeit, Thomas, Bolton, Karel G M, Moon, Yvonne T, van der Schouw, Randi, Selmer, Kay-Tee, Khaw, Vilmundur, Gudnason, Gerd, Assmann, Philippe, Amouyel, Veikko, Salomaa, Mika, Kivimaki, Børge G, Nordestgaard, Michael J, Blaha, Lewis H, Kuller, Hermann, Brenner, Richard F, Gillum, Christa, Meisinger, Ian, Ford, Matthew W, Knuiman, Annika, Rosengren, Debbie A, Lawlor, Henry, Völzke, Cyrus, Cooper, Alejandro, Marín Ibañez, Edoardo, Casiglia, Jussi, Kauhanen, Jackie A, Cooper, Beatriz, Rodriguez, Johan, Sundström, Elizabeth, Barrett-Connor, Rachel, Dankner, Paul J, Nietert, Karina W, Davidson, Robert B, Wallace, Dan G, Blazer, Cecilia, Björkelund, Chiara, Donfrancesco, Harlan M, Krumholz, Aulikki, Nissinen, Barry R, Davi, Sean, Coady, Peter H, Whincup, Torben, Jørgensen, Pierre, Ducimetiere, Maurizio, Trevisan, Gunnar, Engström, Carlos J, Crespo, Tom W, Meade, Marjolein, Visser, Daan, Kromhout, Stefan, Kiechl, Makoto, Daimon, Jackie F, Price, Agustin, Gómez de la Cámara, J, Wouter Jukema, Benoît, Lamarche, Altan, Onat, Leon A, Simon, Maryam, Kavousi, Yoav, Ben-Shlomo, John, Gallacher, Jacqueline M, Dekker, Hisatomi, Arima, Nawar, Shara, Robert W, Tipping, Ronan, Roussel, Eric J, Brunner, Wolfgang, Koenig, Masaru, Sakurai, Jelena, Pavlovic, Ron T, Gansevoort, Dorothea, Nagel, Uri, Goldbourt, Elizabeth L M, Barr, Luigi, Palmieri, Inger, Njølstad, Shinichi, Sato, W M, Monique Verschuren, Cherian V, Varghese, Ian, Graham, Oyere, Onuma, Philip, Greenland, Mark, Woodward, Majid, Ezzati, Bruce M, Psaty, Sattar, W Tipping, Naveerobert, M Simpson, Lara, L Pressel, Sara, J Couper, David, Nambi, Vijay, Matsushita, Kunihiro, R Folsom, Aaron, E Shaw, Jonathan, J Magliano, Dianna, Z Zimmet, Paul, W Knuiman, Matthew, H Whincup, Peter, Goya Wannamethee, S, Willeit, Johann, Santer, Peter, Egger, Georg, Pablo Casas, Juan, Amuzu, Antoinette, Ben-Shlomo, Yoav, Gallacher, John, Tikhonoff, Valérie, Casiglia, Edoardo, E Sutherland, Susan, J Nietert, Paul, Cushman, Mary, M Psaty, Bruce, Johanne Søgaard, Anne, Lund Håheim, Lise, Ariansen, Inger, Tybjærg-Hansen, Anne, B Jensen, Gorm, Schnohr, Peter, Giampaoli, Simona, Vanuzzo, Diego, Panico, Salvatore, Palmieri, Luigi, Balkau, Beverley, Bonnet, Fabrice, Marre, Michel, Gómez de la Cámara, Agustin, Angel Rubio Herrera, Miguel, Friedlander, Yechiel, Mccallum, John, Mclachlan, Stela, Guralnik, Jack, L Phillips, Caroline, Khaw, Kay-Tee, Wareham, Nick, Schöttker, Ben, Saum, Kai-Uwe, Holleczek, Bernd, Nissinen, Aulikki, Tolonen, Hanna, Donfrancesco, Chiara, Vartiainen, Erkki, Jousilahti, Pekka, Harald, Kennet, B D’Agostino, Ralph, M Massaro, Joseph, Pencina, Michael, Vasan, Ramachandran, Kayama, Takamasa, Kato, Takeo, Oizumi, Toshihide, Jespersen, Jørgen, Møller, Lar, Marie Bladbjerg, Else, Chetrit, A, Rosengren, Annika, Wilhelmsen, Lar, Björkelund, Cecilia, Lissner, Lauren, Nagel, Dorothea, Dennison, Elaine, Kiyohara, Yutaka, Ninomiya, Toshiharu, Doi, Yasufumi, Rodriguez, Beatriz, Nijpels, Giel, A Stehouwer, Coen D, Sato, Shinichi, Kazumasa, Yamagishi, Iso, Hiroyasu, Goldbourt, Uri, Salomaa, Veikko, Kurl, Sudhir, Tuomainen, Tomi-Pekka, T Salonen, Jukka, Visser, Marjolein, H Deeg, Dorly J, W Meade, Tom, M Nilsson, Peter, Hedblad, Bo, Melander, Olle, H De Boer, Ian, Paul DeFilippis, Andrew, M Monique Verschuren, W, Sattar, Naveed, Watt, Graham, Meisinger, Christa, Koenig, Wolfgang, H Kuller, Lewi, Tverdal, Aage, F Gillum, Richard, A Cooper, Jackie, Kirkland, Susan, Shimbo, Daichi, Shaffer, Jonathan, Ducimetiere, Pierre, L Bakker, Stephan J, van der Harst, Pim, L Hillege, Han, J Crespo, Carlo, Amouyel, Philippe, Dallongeville, Jean, Assmann, Gerd, Schulte, Helmut, Trompet, Stella, J Smit, Roelof A, J Stott, David, T van der Schouw, Yvonne, Després, Jean-Pierre, Cantin, Bernard, R Dagenais, Gille, Laughlin, Gail, Wingard, Deborah, Trevisan, Maurizio, Aspelund, Thor, Eiriksdottir, Gudny, Freyr Gudmundsson, Elia, Ikram, Arfan, A van Rooij, Frank J, H Franco, Oscar, L Rueda-Ochoa, Oscar, Muka, Taulant, Glisic, Marija, Tunstall-Pedoe, Hugh, Völzke, Henry, V Howard, Barbara, Zhang, Ying, Jolly, Stacey, Davey-Smith, George, Can, Günay, Yüksel, Hüsniye, Nakagawa, Hideaki, Morikawa, Yuko, Miura, Katsuyuki, Njølstad, Inger, Ingelsson, Martin, Giedraitis, Vilmanta, M Ridker, Paul, Michael Gaziano, J, Kivimaki, Mika, Shipley, Martin, J Brunner, Eric, Arndt, Volker, Brenner, Hermann, Cook, Nancy, Ford, Ian, Marín Ibañez, Alejandro, M Geleijnsed, Johanna, Rod, Jackson, Paul M, Ridker, Nancy R, Cook, Ralph B, D'Agostino, Simon G, Thompson, John, Danesh, and Emanuele, Di Angelantonio

Subjects
Male, Cardiac & Cardiovascular Systems, Nutrition and Disease, Prevention and Epidemiology, PREDICTION, Áhættuþættir, 030204 cardiovascular system & hematology, GUIDELINES, 0302 clinical medicine, Risk Factors, Voeding en Ziekte, FRAMINGHAM, Discrimination, Medicine, Cardiac and Cardiovascular Systems, Blóðrásarsjúkdómar, Prospective Studies, Prospective cohort study, Non-U.S. Gov't, 1102 Cardiorespiratory Medicine and Haematology, CALIBRATION, Kardiologi, Framingham Risk Score, Emerging Risk Factors Collaboration, SCORES, Research Support, Non-U.S. Gov't, Incidence (epidemiology), Middle Aged, Cardiovascular disease, Justice and Strong Institutions, Risk prediction, ddc, 3. Good health, Cardiovascular Diseases, Meta-analysis, Cohort, Calibration, Female, Risk assessment, Cardiology and Cardiovascular Medicine, Algorithm, Life Sciences & Biomedicine, Algorithms, SDG 16 - Peace, Risk algorithms, DISEASE PREVENTION, Research Support, Risk Assessment, VALIDATION, 03 medical and health sciences, Clinical Research, Journal Article, Humans, ddc:610, Risk factor, VLAG, Aged, Science & Technology, business.industry, SDG 16 - Peace, Justice and Strong Institutions, 030229 sport sciences, R1, STATIN USE, Cardiovascular System & Hematology, Cardiovascular System & Cardiology, business, PRIMARY PREVENTION, TASK-FORCE
Abstract

Publisher's version (útgefin grein), Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after 'recalibration', a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at 'high' 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29-39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22-24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms. Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need., The work of the co-ordinating centre was funded by the UK Medical Research Council (G0800270), British Heart Foundation (SP/09/ 002), British Heart Foundation Cambridge Cardiovascular Centre of Excellence, UK National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council (268834), and European Commission Framework Programme 7 (HEALTH-F2-2012-279233). The Emerging Risk Factor Collaboration’s website https://www.phpc.cam.ac.uk/ceu/erfc/list-of-studies/ has compiled a list provided by investigators of some of the funders of the component studies in this analysis. I.W. was supported by the Medical Research Council Unit Programme MC_UU_12023/21. M.K. is supported by the Netherlands Organization for Scientific Research (NWO) Veni grant (Veni, 91616079). J.P. is supported by Erasmus Mundus Western Balkans (ERAWEB), a project funded by the European Commission.

Published
2019
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2. Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction : An Individual-Participant-Data Meta-Analysis

Author

Paige, Ellie, Barrett, Jessica, Pennells, Lisa, Sweeting, Michael, Willeit, Peter, Di Angelantonio, Emanuele, Gudnason, Vilmundur, Nordestgaard, Børge G, Psaty, Bruce M, Goldbourt, Uri, Best, Lyle G, Assmann, Gerd, Salonen, Jukka T, Nietert, Paul J, Verschuren, W M Monique, Brunner, Eric J, Kronmal, Richard A, Salomaa, Veikko, Bakker, Stephan J L, Dagenais, Gilles R, Sato, Shinichi, Jansson, Jan-Håkan, Willeit, Johann, Onat, Altan, de la Cámara, Agustin Gómez, Roussel, Ronan, Völzke, Henry, Dankner, Rachel, Tipping, Robert W, Meade, Tom W, Donfrancesco, Chiara, Kuller, Lewis H, Peters, Annette, Gallacher, John, Kromhout, Daan, Iso, Hiroyasu, Knuiman, Matthew, Casiglia, Edoardo, Kavousi, Maryam, Palmieri, Luigi, Sundström, Johan, Davis, Barry R, Njølstad, Inger, Couper, David, Danesh, John, Thompson, Simon G, Wood, Angela, Clinicum, Department of Public Health, University of Helsinki, Barrett, Jessica [0000-0003-1889-9803], Pennells, Lisa [0000-0002-8594-3061], Sweeting, Michael [0000-0003-0980-8965], Di Angelantonio, Emanuele [0000-0001-8776-6719], Danesh, John [0000-0003-1158-6791], Thompson, Simon [0000-0002-5274-7814], Wood, Angela [0000-0002-7937-304X], Apollo - University of Cambridge Repository, and Epidemiology

Subjects
Adult, MODELS, Blood Pressure, Cholesterol/blood, Risk Assessment, risk prediction, Systematic Reviews, Meta- and Pooled Analyses, SDG 3 - Good Health and Well-being, cardiovascular disease, MULTIPLE, Humans, risk factors, CORONARY-HEART-DISEASE, longitudinal measurements, Cardiac and Cardiovascular Systems, Risk Assessment/methods, repeated measurements, Human Nutrition & Health, Aged, Cardiovascular Disease, Longitudinal Measurements, Repeated Measurements, Risk Factors, Risk Prediction, repeated risk factors, Kardiologi, Cardiovascular Diseases/epidemiology, Humane Voeding & Gezondheid, Blood Pressure Determination, Public Health, Global Health, Social Medicine and Epidemiology, Middle Aged, 3142 Public health care science, environmental and occupational health, VARIABILITY, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Cholesterol, Cardiovascular Diseases, Female
Abstract

The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.

Published
2017
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3. Assessing Risk Prediction Models Using Individual Participant Data From Multiple Studies

Author

Pennells, Lisa, Kaptoge, Stephen, White, Ian R., Thompson, Simon G., Wood, Angela M., Tipping, Robert W., Folsom, Aaron R., Couper, David J., Ballantyne, Christie M., Coresh, Josef, Goya Wannamethee, S., Morris, Richard W., Kiechl, Stefan, Willeit, Johann, Willeit, Peter, Schett, Georg, Ebrahim, Shah, Lawlor, Debbie A., Yarnell, John W., Gallacher, John, Cushman, Mary, Psaty, Bruce M., Tracy, Russ, Tybjærg-Hansen, Anne, Price, Jackie F., Lee, Amanda J., McLachlan, Stela, Khaw, Kay-Tee, Wareham, Nicholas J., Brenner, Hermann, Schöttker, Ben, Müller, Heiko, Jansson, Jan-Håkan, Wennberg, Patrik, Salomaa, Veikko, Harald, Kennet, Jousilahti, Pekka, Vartiainen, Erkki, Woodward, Mark, D'Agostino, Ralph B., Bladbjerg, Else-Marie, Jørgensen, Torben, Kiyohara, Yutaka, Arima, Hisatomi, Doi, Yasufumi, Ninomiya, Toshiharu, Dekker, Jacqueline M., Nijpels, Giel, Stehouwer, Coen D. A., Kauhanen, Jussi, Salonen, Jukka T., Meade, Tom W., Cooper, Jackie A., Shea, Steven, Döring, Angela, Kuller, Lewis H., Grandits, Greg, Gillum, Richard F., Mussolino, Michael, Rimm, Eric B., Hankinson, Sue E., Manson, JoAnn E., Pai, Jennifer K., Kirkland, Susan, Shaffer, Jonathan A., Shimbo, Daichi, Bakker, Stephan J. L., Gansevoort, Ron T., Hillege, Hans L., Amouyel, Philippe, Arveiler, Dominique, Evans, Alun, Ferrières, Jean, Sattar, Naveed, Westendorp, Rudi G., Buckley, Brendan M., Cantin, Bernard, Lamarche, Benoît, Barrett-Connor, Elizabeth, Wingard, Deborah L., Bettencourt, Richele, Gudnason, Vilmundur, Aspelund, Thor, Sigurdsson, Gunnar, Thorsson, Bolli, Kavousi, Maryam, Witteman, Jacqueline C., Hofman, Albert, Franco, Oscar H., Howard, Barbara V., Zhang, Ying, Best, Lyle, Umans, Jason G., Onat, Altan, Sundström, Johan, Michael Gaziano, J., Stampfer, Meir, Ridker, Paul M., Marmot, Michael, Clarke, Robert, Collins, Rory, Fletcher, Astrid, Brunner, Eric, Shipley, Martin, Kivimäki, Mika, Buring, Julie, Cook, Nancy, Ford, Ian, Shepherd, James, Cobbe, Stuart M., Robertson, Michele, Walker, Matthew, Watson, Sarah, Alexander, Myriam, Butterworth, Adam S., Angelantonio, Emanuele Di, Gao, Pei, Haycock, Philip, Wormser, David, Danesh, John, MUMC+: HVC Pieken Maastricht Studie (9), Interne Geneeskunde, MUMC+: MA Interne Geneeskunde (3), and RS: CARIM - R3 - Vascular biology

Subjects
Male, Epidemiology, Practice of Epidemiology, Poison control, Coronary Disease, Weighting, Inverse variance, Risk Assessment, risk prediction, Meta-Analysis as Topic, Risk Factors, Statistics, Medicine, Humans, Prospective Studies, coronary heart disease, 10. No inequality, Prospective cohort study, Survival analysis, Proportional Hazards Models, Models, Statistical, business.industry, Proportional hazards model, C index, Individual participant data, inverse variance, individual participant data, Middle Aged, D measure, Risk prediction, Coronary heart disease, meta-analysis, Meta-analysis, C-Reactive Protein, Data Interpretation, Statistical, weighting, Female, business, Risk assessment
Abstract

Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous.

Published
2014
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