Sex dependent risk factors for mortality after myocardial infarction: individual patient data meta-analysis
详细信息 查看全文
- 作者：Hanna M van Loo (1)
Edwin R van den Heuvel (2)
Robert A Schoevers (1)
Matteo Anselmino (3)
Robert M Carney (4)
Johan Denollet (5)
Frank Doyle (6)
Kenneth E Freedland (4)
Sherry L Grace (7)
Seyed H Hosseini (8)
Kapil Parakh (9)
Louise Pilote (10)
Chiara Rafanelli (11)
Annelieke M Roest (1)
Hiroshi Sato (12)
Richard P Steeds (13)
Ronald C Kessler (14)
Peter de Jonge (1)
1. Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE) ; Department of Psychiatry ; University of Groningen ; University Medical Center Groningen ; Hanzeplein 1 ; PO box 30.001 ; 9700 RB ; Groningen ; The Netherlands
2. Department of Mathematics and Computer Science ; Eindhoven University of Technology ; Den Dolech 2 ; 5612 AZ ; Eindhoven ; The Netherlands
3. Division of Cardiology ; Department of Medical Sciences ; Citt脿 della Salute e della Scienza ; University of Turin ; C.so A.M. Dogliotti ; 14 ; 10126 ; Turin ; Italy
4. Department of Psychiatry ; Washington University School of Medicine ; 4320 Forest Park Avenue ; St. Louis ; Missouri ; 63108 ; USA
5. CoRPS-Center of Research on Psychology in Somatic diseases ; Tilburg University ; Warandelaan 2 ; 5000 LE ; Tilburg ; The Netherlands
6. Division of Population Health Sciences (Psychology) ; Royal College of Surgeons in Ireland ; 123 St Stephen鈥檚 Green ; Dublin 2 ; Ireland
7. Faculty of Health ; York University and University Health Network ; 368 Norman Bethune ; 4700 Keele Street ; Toronto ; M3J 1P3 ; Canada
8. Psychiatry and Behavioral Sciences Research Center ; Addiction Institute ; Mazandaran University of Medical Sciences ; Psychosomatic department ; Imam hospital ; Sari ; Iran
9. John Hopkins School of Medicine ; John Hopkins Bloomberg School of Public Health ; John Hoplins Bayview Medical Center ; 4940 Eastern Avenue ; Baltimore ; Maryland ; 21224 ; USA
10. Division of General Internal Medicine ; McGill University ; McGill University Health Centre ; 687 Pine Avenue West ; V Building ; V2.17 ; Montreal ; H3A 1A1 ; Canada
11. Department of Psychology ; University of Bologna ; Viale Berti Pichat 5 ; 40127 ; Bologna ; Italy
12. School of Human Welfare Studies ; Kwansei Gakuin University ; 1-1-155 ; Uegahara ; Nishinomiya ; Hyogo ; 662-8501 ; Japan
13. Department of Cardiology ; Queen Elizabeth Hospital ; Edgbaston ; Birmingham ; B15 2TH ; West Midlands ; UK
14. Department of Health Care Policy ; Harvard Medical School ; 180 Longwood Avenue ; Boston ; Massachusetts ; 02115 ; USA - 关键词：All ; cause mortality ; Interactions ; Myocardial infarction ; Prediction ; Risk factors ; Sex
- 刊名：BMC Medicine
- 出版年：2014
- 出版时间：December 2014
- 年：2014
- 卷：12
- 期：1
- 全文大小：512 KB
- 参考文献：1. Yeh, RW, Sidney, S, Chandra, M, Sorel, M, Selby, JV, Go, AS (2010) Population trends in the incidence and outcomes of acute myocardial infarction. N Engl J Med 362: pp. 2155-2165 CrossRef
2. Nauta, ST, Deckers, JW, Domburg, RT, Akkerhuis, KM (2012) Sex-related trends in mortality in hospitalized men and women after myocardial infarction between 1985 and 2008: equal benefit for women and men. Circulation 126: pp. 2184-2189 CrossRef
3. Antman, EM, Cohen, M, Bernink, PJ, McCabe, CH, Horacek, T, Papuchis, G, Mautner, B, Corbalan, R, Radley, D, Braunwald, E (2000) The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making. JAMA 284: pp. 835-842 CrossRef
4. Morrow, DA, Antman, EM, Charlesworth, A, Cairns, R, Murphy, SA, Lemos, JA, Giugliano, RP, McCabe, CH, Braunwald, E (2000) TIMI risk score for ST-elevation myocardial infarction: a convenient, bedside, clinical score for risk assessment at presentation: an intravenous nPA for treatment of infarcting myocardium early II trial substudy. Circulation 102: pp. 2031-2037 CrossRef
5. Granger, CB, Goldberg, RJ, Dabbous, O, Pieper, KS, Eagle, KA, Cannon, CP, Werf, F, Avezum, A, Goodman, SG, Flather, MD, Fox, KA (2003) Predictors of hospital mortality in the global registry of acute coronary events. Arch Intern Med 163: pp. 2345-2353 CrossRef
6. Vaccarino, V, Parsons, L, Every, NR, Barron, HV, Krumholz, HM (1999) Sex-based differences in early mortality after myocardial infarction. National Registry of Myocardial Infarction 2 Participants. N Engl J Med 341: pp. 217-225 CrossRef
7. Berger, JS, Brown, DL (2006) Gender-age interaction in early mortality following primary angioplasty for acute myocardial infarction. Am J Cardiol 98: pp. 1140-1143 CrossRef
8. Frasure-Smith, N, Lesperance, F, Juneau, M, Talajic, M, Bourassa, MG (1999) Gender, depression, and one-year prognosis after myocardial infarction. Psychosom Med 61: pp. 26-37 CrossRef
9. Tibshirani, R (1996) Regression Shrinkage and Selection via the Lasso. J Royal Stat Soc Series B (Methodology) 58: pp. 267-288
10. James, G, Witten, D, Hastie, T, Tibshirani, R (2013) An Introduction to Statistical Learning with Applications in R. Springer, New York CrossRef
11. Meijer, A, Conradi, HJ, Bos, EH, Anselmino, M, Carney, RM, Denollet, J, Doyle, F, Freedland, KE, Grace, SL, Hosseini, SH, Lane, DA, Pilote, L, Parakh, K, Rafanelli, C, Sato, H, Steeds, RP, Welin, C, Jonge, P (2013) Adjusted prognostic association of depression following myocardial infarction with mortality and cardiovascular events: individual patient data meta-analysis. Br J Psych 203: pp. 90-102 CrossRef
12. Lichtman, JH, Froelicher, ES, Blumenthal, JA, Carney, RM, Doering, LV, Frasure-Smith, N, Freedland, KE, Jaffe, AS, Leifheit-Limson, EC, Sheps, DS, Vaccarino, V, Wulsin, L (2014) Depression as a risk factor for poor prognosis among patients with acute coronary syndrome: systematic review and recommendations: a scientific statement from the American Heart Association. Circulation 129: pp. 1350-1369 CrossRef
13. Bucholz, EM, Rathore, SS, Reid, KJ, Jones, PG, Chan, PS, Rich, MW, Spertus, JA, Krumholz, HM (2012) Body mass index and mortality in acute myocardial infarction patients. Am J Med 125: pp. 796-803 CrossRef
14. Buuren, S, Groothuis-Oudshoorn, K (2011) mice: Multivariate imputation by chained equations in R. J Stat Software 45: pp. 1-67
15. Carpenter, JR, Kenward, MG (2013) Multiple Imputation and its Application. Wiley, Chichester CrossRef
16. R Core Team: R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2012.
17. Wu, TT, Chen, YF, Hastie, T, Sobel, E, Lange, K (2009) Genome-wide association analysis by lasso penalized logistic regression. Bioinformatics 25: pp. 714-721 CrossRef
18. Friedman, J, Hastie, T, Tibshirani, R (2010) Regularization paths for generalized linear models via coordinate descent. J Stat Software 33: pp. 1-22
19. Simon, N, Friedman, J, Hastie, T, Tibshirani, R (2011) Regularization paths for Cox鈥檚 proportional hazards model via coordinate descent. J Stat Software 39: pp. 1-13
20. Thernau T: coxme: Mixed Effects Cox Models. R package version 2.2-3. Vienna: R Foundation for Statistical Computing; 2012.
21. Cooper, H, Patall, EA (2009) The relative benefits of meta-analysis conducted with individual participant data versus aggregated data. Psychol Methods 14: pp. 165-176 CrossRef
22. Borenstein, M, Hadges, LV, Higgins, JPT, Rothstein, HR (2009) Introduction to Meta-Analysis. Wiley, Chichester CrossRef
23. Heagerty PJ, Saha-Chaudhuri P: survivalROC: Time-Dependent ROC Curve Estimation from Censored Survival Data. R package version 1.0.3. Vienna: R Foundation for Statistical Computing; 2013
24. Canty A, Ripley B: boot: Bootstrap R (S-Plus) Functions. R package version 1.3-11. Vienna: R Foundation for Statistical Computing; 2014.
25. Gore, MO, Patel, MJ, Kosiborod, M, Parsons, LS, Khera, A, Lemos, JA, Rogers, WJ, Peterson, ED, Canto, JC, McGuire, DK (2012) Diabetes mellitus and trends in hospital survival after myocardial infarction, 1994 to 2006: data from the national registry of myocardial infarction. Circ Cardiovasc Qual Outcomes 5: pp. 791-797 CrossRef
26. Fokkema, ML, James, SK, Albertsson, P, Akerblom, A, Calais, F, Eriksson, P, Jensen, J, Nilsson, T, Smet, BJ, Sjogren, I, Thorvinger, B, Lagerqvist, B (2013) Population trends in percutaneous coronary intervention: 20-year results from the SCAAR (Swedish Coronary Angiography and Angioplasty Registry). J Am Coll Cardiol 61: pp. 1222-1230 CrossRef
27. Chang, WC, Kaul, P, Westerhout, CM, Graham, MM, Armstrong, PW (2007) Effects of socioeconomic status on mortality after acute myocardial infarction. Am J Med 120: pp. 33-39 CrossRef
28. Zeller, M, Steg, PG, Ravisy, J, Lorgis, L, Laurent, Y, Sicard, P, Janin-Manificat, L, Beer, JC, Makki, H, Lagrost, AC, Rochette, L, Cottin, Y (2008) Relation between body mass index, waist circumference, and death after acute myocardial infarction. Circulation 118: pp. 482-490 CrossRef
29. Vaccarino, V, Horwitz, RI, Meehan, TP, Petrillo, MK, Radford, MJ, Krumholz, HM (1998) Sex differences in mortality after myocardial infarction: evidence for a sex-age interaction. Arch Intern Med 158: pp. 2054-2062 CrossRef
30. Martinez-Selles, M, Garcia Robles, JA, Prieto, L, Dominguez Munoa, M, Frades, E, Diaz-Castro, O, Almendral, J (2003) Systolic dysfunction is a predictor of long term mortality in men but not in women with heart failure. Eur Heart J 24: pp. 2046-2053 CrossRef
31. Frasure-Smith, N, Lesperance, F (2008) Depression and anxiety as predictors of 2-year cardiac events in patients with stable coronary artery disease. Arch Gen Psychiatry 65: pp. 62-71 CrossRef
32. Emery, M, Lopez-Sendon, J, Steg, PG, Anderson, FA, Dabbous, OH, Scheuble, A, Eagle, KA (2006) Patterns of use and potential impact of early beta-blocker therapy in non-ST-elevation myocardial infarction with and without heart failure: the Global Registry of Acute Coronary Events. Am Heart J 152: pp. 1015-1021 CrossRef
33. Vaccarino, V, Parsons, L, Peterson, ED, Rogers, WJ, Kiefe, CI, Canto, J (2009) Sex differences in mortality after acute myocardial infarction: changes from 1994 to 2006. Arch Intern Med 169: pp. 1767-1774
34. Velders, MA, Boden, H, Boven, AJ, Hoeven, BL, Heestermans, AA, Cannegieter, SC, Umans, VA, Jukema, JW, Hofma, SH, Schalij, MJ (2013) Influence of gender on ischemic times and outcomes after ST-elevation myocardial infarction. Am J Cardiol 111: pp. 312-318 CrossRef
35. Poon, S, Goodman, SG, Yan, RT, Bugiardini, R, Bierman, AS, Eagle, KA, Johnston, N, Huynh, T, Grondin, FR, Schenck-Gustafsson, K, Yan, AT (2012) Bridging the gender gap: Insights from a contemporary analysis of sex-related differences in the treatment and outcomes of patients with acute coronary syndromes. Am Heart J 163: pp. 66-73 CrossRef
36. Bot, M, Pouwer, F, Zuidersma, M, Melle, JP, Jonge, P (2012) Association of coexisting diabetes and depression with mortality after myocardial infarction. Diabetes Care 35: pp. 503-509 CrossRef
37. Parakh, K, Thombs, BD, Bhat, U, Fauerbach, JA, Bush, DE, Ziegelstein, RC (2008) Long-term significance of Killip class and left ventricular systolic dysfunction. Am J Med 121: pp. 1015-1018 CrossRef
38. Leander, K, Hallqvist, J, Reuterwall, C, Ahlbom, A, Faire, U (2001) Family history of coronary heart disease, a strong risk factor for myocardial infarction interacting with other cardiovascular risk factors: results from the Stockholm Heart Epidemiology Program (SHEEP). Epidemiology 12: pp. 215-221 CrossRef
39. Roest, AM, Zuidersma, M, Jonge, P (2012) Myocardial infarction and generalised anxiety disorder: 10-year follow-up. Br J Psychiatry 200: pp. 324-329 CrossRef
40. Melle, JP, Jonge, P, Ormel, J, Crijns, HJ, Veldhuisen, DJ, Honig, A, Schene, AH, Berg, MP (2005) Relationship between left ventricular dysfunction and depression following myocardial infarction: data from the MIND-IT. Eur Heart J 26: pp. 2650-2656 CrossRef - 刊物主题：Medicine/Public Health, general; Biomedicine general;
- 出版者：BioMed Central
- ISSN：1741-7015
文摘
Background Although a number of risk factors are known to predict mortality within the first years after myocardial infarction, little is known about interactions between risk factors, whereas these could contribute to accurate differentiation of patients with higher and lower risk for mortality. This study explored the effect of interactions of risk factors on all-cause mortality in patients with myocardial infarction based on individual patient data meta-analysis. Methods Prospective data for 10,512 patients hospitalized for myocardial infarction were derived from 16 observational studies (MINDMAPS). Baseline measures included a broad set of risk factors for mortality such as age, sex, heart failure, diabetes, depression, and smoking. All two-way and three-way interactions of these risk factors were included in Lasso regression analyses to predict time-to-event related all-cause mortality. The effect of selected interactions was investigated with multilevel Cox regression models. Results Lasso regression selected five two-way interactions, of which four included sex. The addition of these interactions to multilevel Cox models suggested differential risk patterns for males and females. Younger women (age Conclusions Interactions of well-known risk factors for all-cause mortality after myocardial infarction suggested important sex differences. This study gives rise to a further exploration of prediction models to improve risk assessment for men and women after myocardial infarction.