All else being equal, men and women are still not the same: using risk models to understand gender disparities in care

Relationship between sexual differences and cardiovascular risk factors in the prevalence of asymptomatic coronary disease

BACKGROUND

This study investigated the sexual differences of coronary artery disease (CAD) prevalence and its association with cardiovascular risk factors in the asymptomatic population.

METHODS

In total 6434 asymptomatic participants without known CAD (1740 women and 4694 men) underwent coronary computed tomography angiography (CCTA). The prevalence of significant CAD (diameter stenosis ≥50%) and other CCTA findings were compared by sex, and its influence on CAD was investigated in groups stratified by the number of cardiovascular risk factors, including age (>55 years), hypertension, diabetes, dyslipidemia, and current smoking.

RESULTS

The prevalence of current smokers, hypertension, and diabetes were higher in men than women. The mean coronary artery calcium score was 13.1 ± 58.4 for women and 51.1 ± 158.2 for men; the coronary atherosclerosis burden indices were significantly higher in men than women. Significant CAD was identified in 65 women (3.7%) and 429 men (9.1%), showing a significant association (adjusted odds ratio [OR] 2.38, P < 0.001). The relatively higher risk for significant CAD in men was observed in patients with fewer risk factors, and the risk difference was not significant in patients with many risk factors (adjusted ORs: 7.69, 3.37, 1.71, 1.31, and 0.88 in patients with 0, 1, 2, 3, and 4-5 risk factors, respectively). The association between sex and risk factor groups was significant (P < 0.001).

CONCLUSIONS

In the asymptomatic population, a significantly higher CAD prevalence was noted in men than women. However, women with a high number of cardiovascular risk factors showed a CAD prevalence similar to that of men.

Impact of sex-specific differences in calculating the pretest probability of obstructive coronary artery disease in symptomatic patients: a coronary computed tomographic angiography study

Objectives

Little is known about the impact of sex-specific differences in calculating the pretest probability (PTP) of obstructive coronary artery disease. We sought to determine whether the calculation of PTP differ by sex in symptomatic patients referred to coronary computed tomographic angiography (CCTA).

Patients and methods

The characteristics of 5777 men and women who underwent CCTA were compared. For each patient, PTP was calculated according to the updated Diamond–Forrester method (UDFM) and the Duke clinical score (DCS), respectively. Follow-up clinical data were also recorded. Area under the receiver operating characteristic curve, integrated discrimination improvement, net reclassification improvement, and the Hosmer–Lemeshow goodness-of-fit statistic were used to assess the models’ performance.

Results

The area under the receiver operating characteristic curve of UDFM and DCS showed little difference in men (0.782 vs. 0.785, P=0.4708) and women (0.668 vs. 0.654, P=0.1255), and calibration of neither model was satisfactory. Compared with UDFM, DCS showed positive integrated discrimination improvement (10% in men, P<0.0001, and 8% in women, P<0.0001, respectively), net reclassification improvement (12.17% in men, P<0.0001, and 27.19% in women, P<0.0001, respectively), and obviously reduced unnecessary noninvasive testing for women with negative CCTA.

Conclusion

Although the performance of neither model was favorable, DCS offered a more accurate calculation of PTP than UDFM and application of DCS instead of UDFM would result in a significant decrease in inappropriate testing, especially in women.

Tufts PACE Clinical Predictive Model Registry: update 1990 through 2015

BACKGROUND

Clinical predictive models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision-making and individualize care. The Tufts Predictive Analytics and Comparative Effectiveness (PACE) CPM Registry is a comprehensive database of cardiovascular disease (CVD) CPMs. The Registry was last updated in 2012, and there continues to be substantial growth in the number of available CPMs.

METHODS

We updated a systematic review of CPMs for CVD to include articles published from January 1990 to March 2015. CVD includes coronary artery disease (CAD), congestive heart failure (CHF), arrhythmias, stroke, venous thromboembolism (VTE), and peripheral vascular disease (PVD). The updated Registry characterizes CPMs based on population under study, model performance, covariates, and predicted outcomes.

RESULTS

The Registry includes 747 articles presenting 1083 models, including both prognostic (n = 1060) and diagnostic (n = 23) CPMs representing 183 distinct index condition/outcome pairs. There was a threefold increase in the number of CPMs published between 2005 and 2014, compared to the prior 10-year interval from 1995 to 2004. The majority of CPMs were derived from either North American (n = 455, 42%) or European (n = 344, 32%) populations. The database contains 265 CPMs predicting outcomes for patients with coronary artery disease, 196 CPMs for population samples at risk for incident CVD, and 158 models for patients with stroke. Approximately two thirds (n = 701, 65%) of CPMs report a c-statistic, with a median reported c-statistic of 0.77 (IQR, 0.05). Of the CPMs reporting validations, only 333 (57%) report some measure of model calibration. Reporting of discrimination but not calibration is improving over time (p for trend < 0.0001 and 0.39 respectively).

CONCLUSIONS

There is substantial redundancy of CPMs for a wide spectrum of CVD conditions. While the number of CPMs continues to increase, model performance is often inadequately reported and calibration is infrequently assessed. More work is needed to understand the potential impact of this literature.

Implicit Gender Bias and the Use of Cardiovascular Tests Among Cardiologists

Background

Physicians' gender bias may contribute to gender disparities in cardiovascular testing. We used the Implicit Association Test to examine the association of implicit gender biases with decisions to use cardiovascular tests.

Methods and Results

In 2014, cardiologists completed Implicit Association Tests and a clinical vignette with patient gender randomly assigned. The Implicit Association Tests measured implicit gender bias for the characteristics of strength and risk taking. The vignette represented an intermediate likelihood of coronary artery disease regardless of patient gender: chest pain (part 1) followed by an abnormal exercise treadmill test (part 2). Cardiologists rated the likelihood of coronary artery disease and the usefulness of stress testing and angiography for the assigned patient. Of the 503 respondents (9.3% of eligible; 87% male, median age of 45 years, 58% in private practice), the majority associated strength or risk taking implicitly with male more than female patients. The estimated likelihood of coronary artery disease for both parts of the vignette was similar by patient gender. The utility of secondary stress testing after an abnormal exercise treadmill test was rated as “high” more often for female than male patients (32.8% versus 24.3%, P=0.04); this difference did not vary with implicit bias. Angiography was more consistently rated as having “high” utility for male versus female patients (part 1: 19.7% versus 9.8%; part 2: 73.7% versus 64.3%; P<0.05 for both); this difference was larger for cardiologists with higher implicit gender bias on risk taking (P=0.01).

Conclusions

Cardiologists have varying degrees of implicit gender bias. This bias explained some, but not all, of the gender variability in simulated clinical decision‐making for suspected coronary artery disease.

Field Synopsis of the Role of Sex in Stroke Prediction Models

Background

Guidelines for stroke prevention recommend development of sex‐specific stroke risk scores. Incorporating sex in Clinical Prediction Models (CPMs) may support sex‐specific clinical decision making. To better understand their potential to guide sex‐specific care, we conducted a field synopsis of the role of sex in stroke‐related CPMs.

Methods and Results

We identified stroke‐related CPMs in the Tufts Predictive Analytics and Comparative Effectiveness CPM Database, a systematic summary of cardiovascular CPMs published from January 1990 to May 2012. We report the proportion of models including the effect of sex on stroke incidence or prognosis, summarize the directionality of the predictive effects of sex, and explore factors influencing the inclusion of sex. Of 92 stroke‐related CPMs, 30 (33%) contained a coefficient for sex or presented sex‐stratified models. Only 12/58 (21%) CPMs predicting outcomes in patients included sex, compared to 18/30 (60%) models predicting first stroke (P<0.0001). Sex was most commonly included in models predicting stroke among a general population (69%). Female sex was consistently associated with reduced mortality after ischemic stroke (n=4) and higher risk of stroke from arrhythmias or coronary revascularization (n=5). Models predicting first stroke versus outcomes among patients with stroke (odds ratio=5.75, 95% CI 2.18–15.14, P<0.001) and those developed from larger versus smaller sample sizes (odds ratio=4.58, 95% CI 1.73–12.13, P=0.002) were significantly more likely to include sex.

Conclusions

Sex is included in a minority of published CPMs, but more frequently in models predicting incidence of first stroke. The importance of sex‐specific care may be especially well established for primary prevention.

Field Synopsis of Sex in Clinical Prediction Models for Cardiovascular Disease

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.

Statin use prior to first myocardial infarction in contemporary patients: Inefficient and not gender equitable

OBJECTIVES

Guidelines recommend initiating primary prevention with statins to those at highest cardiovascular risk. We assessed the gender-specific implementation and effectiveness of this risk-guided approach.

METHODS

We identified 1399 consecutive patients without known cardiovascular disease or diabetes hospitalized with a first myocardial infarction (MI) in Denmark. Statin use before MI was assessed, and cardiovascular risk was calculated using SCORE (Systematic COronary Risk Evaluation).

RESULTS

Among patients with first MI, 36% were women. Compared with men, they were older (mean 72 vs. 65years) but had a lower estimated risk (median 3.4% vs. 6.7%, SCORE high-risk model in the statin-naïve patients). Statin therapy had been initiated in 12% of women and 10% of men prior to MI. After adding 1.5mmol/L to the total cholesterol concentration of those already on statins, the estimated pre-treatment risk was much lower in women than men (median 3.8% vs. 9.2%, SCORE high-risk model), and only 29% of women would have passed the risk-based treatment threshold defined by the European guidelines (SCORE ≥5%). Estimated risk and statin use correlated directly in men but not in women. Only ~5% of first MI are prevented by the current use of statins in people without diabetes.

CONCLUSION

In people destined for a first MI, statin therapy is uncommon and prevents few events. Lower-risk women receive as much statins as higher risk men. This gender disparity and inefficient targeting of statins to those at highest risk indicate that risk scoring is not widely used in routine clinical practice in Denmark.