Field Synopsis of Sex in Clinical Prediction Models for Cardiovascular Disease

Overview

Journal Circ Cardiovasc Qual Outcomes

Specialty Cardiology & Vascular Diseases

Date 2016 Feb 25

PMID 26908865

Citations 7

Authors

Jessica K Paulus

Benjamin S Wessler

Christine Lundquist

Lana L Y Lai

Gowri Raman

Jennifer S Lutz

David M Kent

Affiliations

Soon will be listed here.

Abstract

Background: Several widely used risk scores for cardiovascular disease (CVD) incorporate sex effects, yet there has been no systematic summary of the role of sex in clinical prediction models (CPMs). To better understand the potential of these models to support sex-specific care, we conducted a field synopsis of sex effects in CPMs for CVD.

Methods And Results: We identified CPMs in the Tufts Predictive Analytics and Comparative Effectiveness CPM Registry, a comprehensive database of CVD CPMs published from January 1990 to May 2012. We report the proportion of models including sex effects on CVD incidence or prognosis, summarize the directionality of the predictive effects of sex, and explore factors influencing the inclusion of sex. Of 592 CVD-related CPMs, 193 (33%) included sex as a predictor or presented sex-stratified models. Sex effects were included in 78% (53/68) of models predicting incidence of CVD in a general population, versus only 35% (59/171), 21% (12/58), and 17% (12/72) of models predicting outcomes in patients with coronary artery disease, stroke, and heart failure, respectively. Among sex-including CPMs, women with heart failure were at lower mortality risk in 8 of 8 models; women undergoing revascularization for coronary artery disease were at higher mortality risk in 10 of 12 models. Factors associated with the inclusion of sex effects included the number of outcome events and using cohorts at-risk for CVD (rather than with established CVD).

Conclusions: Although CPMs hold promise for supporting sex-specific decision making in CVD clinical care, sex effects are included in only one third of published CPMs.

Citing Articles

Cardiovascular Disease Risk Modeling for Astronauts: Making the Leap From Earth to Space.

Huff J, Plante I, Blattnig S, Norman R, Little M, Khera A Front Cardiovasc Med. 2022; 9:873597.

PMID: 35665268 PMC: 9161032. DOI: 10.3389/fcvm.2022.873597.

Tufts PACE Clinical Predictive Model Registry: update 1990 through 2015.

Wessler B, Paulus J, Lundquist C, Ajlan M, Natto Z, Janes W Diagn Progn Res. 2019; 1:20.

PMID: 31093549 PMC: 6460840. DOI: 10.1186/s41512-017-0021-2.

Racial and Ethnic Differences in Graft Loss Among Female Liver Transplant Recipients.

Dave S, Dodge J, Terrault N, Sarkar M Transplant Proc. 2018; 50(5):1413-1423.

PMID: 29880364 PMC: 6545290. DOI: 10.1016/j.transproceed.2018.02.059.

Investigation of Gender Differences and Exclusive Criteria in a Diabetic Acute Ischemic Stroke Population Treated with Recombinant Tissue-Type Plasminogen Activator (rtPA).

Wapshott T, Blum B, Kelsey W, Nathaniel T J Vasc Interv Neurol. 2018; 9(6):26-32.

PMID: 29445435 PMC: 5805905.

Acetaminophen-induced Acute Liver Failure Is More Common and More Severe in Women.

Rubin J, Hameed B, Gottfried M, Lee W, Sarkar M Clin Gastroenterol Hepatol. 2017; 16(6):936-946.

PMID: 29199145 PMC: 5962381. DOI: 10.1016/j.cgh.2017.11.042.

References

Lempereur M, Magne J, Cornelis K, Hanet C, Taeymans Y, Vrolix M . Impact of gender difference in hospital outcomes following percutaneous coronary intervention. Results of the Belgian Working Group on Interventional Cardiology (BWGIC) registry. EuroIntervention. 2014; 12(2):e216-23. DOI: 10.4244/EIJY14M12_11. View

Vaccarino V . Ischemic heart disease in women: many questions, few facts. Circ Cardiovasc Qual Outcomes. 2010; 3(2):111-5. PMC: 3012351. DOI: 10.1161/CIRCOUTCOMES.109.925313. View

Antman E, Cohen M, Bernink P, McCabe C, Horacek T, Papuchis G . The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making. JAMA. 2000; 284(7):835-42. DOI: 10.1001/jama.284.7.835. View

Dhruva S, Redberg R . Variations between clinical trial participants and Medicare beneficiaries in evidence used for Medicare national coverage decisions. Arch Intern Med. 2008; 168(2):136-40. DOI: 10.1001/archinternmed.2007.56. View

Pieper K, Gore J, FitzGerald G, Granger C, Goldberg R, Steg G . Validity of a risk-prediction tool for hospital mortality: the Global Registry of Acute Coronary Events. Am Heart J. 2009; 157(6):1097-105. DOI: 10.1016/j.ahj.2009.04.004. View

Chyu J, Fonarow G, Tseng C, Horwich T . Four-variable risk model in men and women with heart failure. Circ Heart Fail. 2013; 7(1):88-95. DOI: 10.1161/CIRCHEARTFAILURE.113.000404. View

Onuma Y, Kukreja N, Daemen J, Garcia-Garcia H, Gonzalo N, Cheng J . Impact of sex on 3-year outcome after percutaneous coronary intervention using bare-metal and drug-eluting stents in previously untreated coronary artery disease: insights from the RESEARCH (Rapamycin-Eluting Stent Evaluated at Rotterdam Cardiology.... JACC Cardiovasc Interv. 2009; 2(7):603-10. DOI: 10.1016/j.jcin.2009.03.016. View

Lip G, Nieuwlaat R, Pisters R, Lane D, Crijns H . Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation. Chest. 2009; 137(2):263-72. DOI: 10.1378/chest.09-1584. View

Harvey R, Coffman K, Miller V . Women-specific factors to consider in risk, diagnosis and treatment of cardiovascular disease. Womens Health (Lond). 2015; 11(2):239-257. PMC: 4386625. DOI: 10.2217/whe.14.64. View

10.

Redberg R . Don't assume women are the same as men: include them in the trial. Arch Intern Med. 2012; 172(12):921. DOI: 10.1001/archinternmed.2012.2407. View

11.

Berger J, Roncaglioni M, Avanzini F, Pangrazzi I, Tognoni G, Brown D . Aspirin for the primary prevention of cardiovascular events in women and men: a sex-specific meta-analysis of randomized controlled trials. JAMA. 2006; 295(3):306-13. DOI: 10.1001/jama.295.3.306. View

12.

Heiat A, Gross C, Krumholz H . Representation of the elderly, women, and minorities in heart failure clinical trials. Arch Intern Med. 2002; 162(15):1682-8. DOI: 10.1001/archinte.162.15.1682. View

13.

DAgostino Sr R, Vasan R, Pencina M, Wolf P, Cobain M, Massaro J . General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008; 117(6):743-53. DOI: 10.1161/CIRCULATIONAHA.107.699579. View

14.

Collins F, Varmus H . A new initiative on precision medicine. N Engl J Med. 2015; 372(9):793-5. PMC: 5101938. DOI: 10.1056/NEJMp1500523. View

15.

Kent D, Hayward R . Limitations of applying summary results of clinical trials to individual patients: the need for risk stratification. JAMA. 2007; 298(10):1209-12. DOI: 10.1001/jama.298.10.1209. View

16.

Melloni C, Berger J, Wang T, Gunes F, Stebbins A, Pieper K . Representation of women in randomized clinical trials of cardiovascular disease prevention. Circ Cardiovasc Qual Outcomes. 2010; 3(2):135-42. DOI: 10.1161/CIRCOUTCOMES.110.868307. View

17.

Bushnell C . Stroke and the female brain. Nat Clin Pract Neurol. 2008; 4(1):22-33. DOI: 10.1038/ncpneuro0686. View

18.

Doull M, Runnels V, Tudiver S, Boscoe M . Appraising the evidence: applying sex- and gender-based analysis (SGBA) to Cochrane systematic reviews on cardiovascular diseases. J Womens Health (Larchmt). 2010; 19(5):997-1003. DOI: 10.1089/jwh.2009.1626. View

19.

Pocock S, Ariti C, McMurray J, Maggioni A, Kober L, Squire I . Predicting survival in heart failure: a risk score based on 39 372 patients from 30 studies. Eur Heart J. 2012; 34(19):1404-13. DOI: 10.1093/eurheartj/ehs337. View

20.

Lloyd-Jones D, Leip E, Larson M, DAgostino R, Beiser A, Wilson P . Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age. Circulation. 2006; 113(6):791-8. DOI: 10.1161/CIRCULATIONAHA.105.548206. View