Ralph B. D'Agostino

Prediction of Coronary Heart Disease Using Risk Factor Categories

BACKGROUND The objective of this study was to examine the association of Joint National Committee (JNC-V) blood pressure and National Cholesterol Education Program (NCEP) cholesterol categories with coronary heart disease (CHD) risk, to incorporate them into coronary prediction algorithms, and to compare the discrimination properties of this approach with other noncategorical prediction functions. METHODS AND RESULTS This work was designed as a prospective, single-center study in the setting of a community-based cohort. The patients were 2489 men and 2856 women 30 to 74 years old at baseline with 12 years of follow-up. During the 12 years of follow-up, a total of 383 men and 227 women developed CHD, which was significantly associated with categories of blood pressure, total cholesterol, LDL cholesterol, and HDL cholesterol (all P<.001). Sex-specific prediction equations were formulated to predict CHD risk according to age, diabetes, smoking, JNC-V blood pressure categories, and NCEP total cholesterol and LDL cholesterol categories. The accuracy of this categorical approach was found to be comparable to CHD prediction when the continuous variables themselves were used. After adjustment for other factors, approximately 28% of CHD events in men and 29% in women were attributable to blood pressure levels that exceeded high normal (> or =130/85). The corresponding multivariable-adjusted attributable risk percent associated with elevated total cholesterol (> or =200 mg/dL) was 27% in men and 34% in women. CONCLUSIONS Recommended guidelines of blood pressure, total cholesterol, and LDL cholesterol effectively predict CHD risk in a middle-aged white population sample. A simple coronary disease prediction algorithm was developed using categorical variables, which allows physicians to predict multivariate CHD risk in patients without overt CHD.

Propensity score methods for bias reduction in the comparison of a treatment to a non‐randomized control group

In observational studies, investigators have no control over the treatment assignment. The treated and non-treated (that is, control) groups may have large differences on their observed covariates, and these differences can lead to biased estimates of treatment effects. Even traditional covariance analysis adjustments may be inadequate to eliminate this bias. The propensity score, defined as the conditional probability of being treated given the covariates, can be used to balance the covariates in the two groups, and therefore reduce this bias. In order to estimate the propensity score, one must model the distribution of the treatment indicator variable given the observed covariates. Once estimated the propensity score can be used to reduce bias through matching, stratification (subclassification), regression adjustment, or some combination of all three. In this tutorial we discuss the uses of propensity score methods for bias reduction, give references to the literature and illustrate the uses through applied examples.

THE FEMALE SEXUAL FUNCTION INDEX (FSFI): A MULTIDIMENSIONAL SELF-REPORT INSTRUMENT FOR THE ASSESSMENT OF FEMALE SEXUAL FUNCTION

This article presents the development of a brief, self-report measure of female sexual function. Initial face validity testing of questionnaire items, identified by an expert panel, was followed by a study aimed at further refining the questionnaire. It was administered to 131 normal controls and 128 age-matched subjects with female sexual arousal disorder (FSAD) at five research centers. Based on clinical interpretations of a principal components analysis, a 6- domain structure was identified, which included desire, subjective arousal, lubrication, orgasm, satisfaction, and pain. Overall test-retest reliability coefficients were high for each of the individual domains (r=0.79 to 0.86) and a high degree of internal consistency was observed (Cronbach’s alpha values of 0.82 and higher) Good construct validity was demonstrated by highly significant mean difference scores between the FSAD and control groups for each of the domains (p<0.001). Additionally, divergent validity with a scale of marital satisfaction was observed. These results support the reliability and psychometric(as well as clinical) validity of the Female Sexual Function Index (FSFI) in the assessment of key dimensions of female sexual function in clinical and nonclinical samples. Our findings also suggest important gender differences in the patterning of female sexual function in comparison with similar questionnaire studies in males.This article presents the development of a brief, self-report measure of female sexual function. Initial face validity testing of questionnaire items, identified by an expert panel, was followed by a study aimed at further refining the questionnaire. It was administered to 131 normal controls and 128 age-matched subjects with female sexual arousal disorder (FSAD) at five research centers. Based on clinical interpretations of a principal components analysis, a 6-domain structure was identified, which included desire, subjective arousal, lubrication, orgasm, satisfaction, and pain. Overall test-retest reliability coefficients were high for each of the individual domains (r = 0.79 to 0.86) and a high degree of internal consistency was observed (Cronbachs alpha values of 0.82 and higher) Good construct validity was demonstrated by highly significant mean difference scores between the FSAD and control groups for each of the domains (p < or = 0.001). Additionally, divergent validity with a scale of marital satisfaction was observed. These results support the reliability and psychometric (as well as clinical) validity of the Female Sexual Function Index (FSFI) in the assessment of key dimensions of female sexual function in clinical and nonclinical samples. Our findings also suggest important gender differences in the patterning of female sexual function in comparison with similar questionnaire studies in males.

Chronic Subclinical Inflammation as Part of the Insulin Resistance Syndrome: The Insulin Resistance Atherosclerosis Study (IRAS)

BACKGROUND Inflammation has been suggested as a risk factor for the development of atherosclerosis. Recently, some components of the insulin resistance syndrome (IRS) have been related to inflammatory markers. We hypothesized that insulin insensitivity, as directly measured, may be associated with inflammation in nondiabetic subjects. METHODS AND RESULTS We studied the relation of C-reactive protein (CRP), fibrinogen, and white cell count to components of IRS in the nondiabetic population of the Insulin Resistance Atherosclerosis Study (IRAS) (n=1008; age, 40 to 69 years; 33% with impaired glucose tolerance), a multicenter, population-based study. None of the subjects had clinical coronary artery disease. Insulin sensitivity (S(I)) was measured by a frequently sampled intravenous glucose tolerance test, and CRP was measured by a highly sensitive competitive immunoassay. All 3 inflammatory markers were correlated with several components of the IRS. Strong associations were found between CRP and measures of body fat (body mass index, waist circumference), S(I), and fasting insulin and proinsulin (all correlation coefficients >0.3, P<0.0001). The associations were consistent among the 3 ethnic groups of the IRAS. There was a linear increase in CRP levels with an increase in the number of metabolic disorders. Body mass index, systolic blood pressure, and S(I) were related to CRP levels in a multivariate linear regression model. CONCLUSIONS We suggest that chronic subclinical inflammation is part of IRS. CRP, a predictor of cardiovascular events in previous reports, was independently related to S(I). These findings suggest potential benefits of anti-inflammatory or insulin-sensitizing treatment strategies in healthy individuals with features of IRS.

Vitamin D Deficiency and Risk of Cardiovascular Disease

Background— Vitamin D receptors have a broad tissue distribution that includes vascular smooth muscle, endothelium, and cardiomyocytes. A growing body of evidence suggests that vitamin D deficiency may adversely affect the cardiovascular system, but data from longitudinal studies are lacking. Methods and Results— We studied 1739 Framingham Offspring Study participants (mean age 59 years; 55% women; all white) without prior cardiovascular disease. Vitamin D status was assessed by measuring 25-dihydroxyvitamin D (25-OH D) levels. Prespecified thresholds were used to characterize varying degrees of 25-OH D deficiency (<15 ng/mL, <10 ng/mL). Multivariable Cox regression models were adjusted for conventional risk factors. Overall, 28% of individuals had levels <15 ng/mL, and 9% had levels <10 ng/mL. During a mean follow-up of 5.4 years, 120 individuals developed a first cardiovascular event. Individuals with 25-OH D <15 ng/mL had a multivariable-adjusted hazard ratio of 1.62 (95% confidence interval 1.11 to 2.36, P=0.01) for incident cardiovascular events compared with those with 25-OH D ≥15 ng/mL. This effect was evident in participants with hypertension (hazard ratio 2.13, 95% confidence interval 1.30 to 3.48) but not in those without hypertension (hazard ratio 1.04, 95% confidence interval 0.55 to 1.96). There was a graded increase in cardiovascular risk across categories of 25-OH D, with multivariable-adjusted hazard ratios of 1.53 (95% confidence interval 1.00 to 2.36) for levels 10 to <15 ng/mL and 1.80 (95% confidence interval 1.05 to 3.08) for levels <10 ng/mL (P for linear trend=0.01). Further adjustment for C-reactive protein, physical activity, or vitamin use did not affect the findings. Conclusions— Vitamin D deficiency is associated with incident cardiovascular disease. Further clinical and experimental studies may be warranted to determine whether correction of vitamin D deficiency could contribute to the prevention of cardiovascular disease.

Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers

Appropriate quantification of added usefulness offered by new markers included in risk prediction algorithms is a problem of active research and debate. Standard methods, including statistical significance and c statistic are useful but not sufficient. Net reclassification improvement (NRI) offers a simple intuitive way of quantifying improvement offered by new markers and has been gaining popularity among researchers. However, several aspects of the NRI have not been studied in sufficient detail. In this paper we propose a prospective formulation for the NRI which offers immediate application to survival and competing risk data as well as allows for easy weighting with observed or perceived costs. We address the issue of the number and choice of categories and their impact on NRI. We contrast category-based NRI with one which is category-free and conclude that NRIs cannot be compared across studies unless they are defined in the same manner. We discuss the impact of differing event rates when models are applied to different samples or definitions of events and durations of follow-up vary between studies. We also show how NRI can be applied to case-control data. The concepts presented in the paper are illustrated in a Framingham Heart Study example. In conclusion, NRI can be readily calculated for survival, competing risk, and case-control data, is more objective and comparable across studies using the category-free version, and can include relative costs for classifications. We recommend that researchers clearly define and justify the choices they make when choosing NRI for their application.

National Institutes of Health Consensus Development Conference Statement: Geriatric Assessment Methods for Clinical Decision‐making

he population of elderly persons in the developed nations is growing with extraordinary rapidity. Although the majority enjoy good T health, many older people suffer from multiple illnesses and significant disability. Comprehensive assessment methodologies, while not solely applicable to frail elderly persons, are believed to be particularly suited to their situation. These individuals tend to exhibit great medical complexity and vulnerability; have illnesses with atypical and obscure presentations; suffer major cognitive, affective, and functional problems; are especially vulnerable to iatrogenesis; are often socially isolated and economically deprived; and are at high risk for premature or inappropriate institutionalization. To deal with the exceedingly difficult health care issues posed by frail elderly persons, health professionals need to collect, organize, and use a vast array of clinically relevant information. This process, compre-

Ankle brachial index combined with Framingham risk score to predict cardiovascular events and mortality - A meta-analysis

CONTEXT Prediction models to identify healthy individuals at high risk of cardiovascular disease have limited accuracy. A low ankle brachial index (ABI) is an indicator of atherosclerosis and has the potential to improve prediction. OBJECTIVE To determine if the ABI provides information on the risk of cardiovascular events and mortality independently of the Framingham risk score (FRS) and can improve risk prediction. DATA SOURCES Relevant studies were identified. A search of MEDLINE (1950 to February 2008) and EMBASE (1980 to February 2008) was conducted using common text words for the term ankle brachial index combined with text words and Medical Subject Headings to capture prospective cohort designs. Review of reference lists and conference proceedings, and correspondence with experts was conducted to identify additional published and unpublished studies. STUDY SELECTION Studies were included if participants were derived from a general population, ABI was measured at baseline, and individuals were followed up to detect total and cardiovascular mortality. DATA EXTRACTION Prespecified data on individuals in each selected study were extracted into a combined data set and an individual participant data meta-analysis was conducted on individuals who had no previous history of coronary heart disease. RESULTS Sixteen population cohort studies fulfilling the inclusion criteria were included. During 480,325 person-years of follow-up of 24,955 men and 23,339 women, the risk of death by ABI had a reverse J-shaped distribution with a normal (low risk) ABI of 1.11 to 1.40. The 10-year cardiovascular mortality in men with a low ABI (< or = 0.90) was 18.7% (95% confidence interval [CI], 13.3%-24.1%) and with normal ABI (1.11-1.40) was 4.4% (95% CI, 3.2%-5.7%) (hazard ratio [HR], 4.2; 95% CI, 3.3-5.4). Corresponding mortalities in women were 12.6% (95% CI, 6.2%-19.0%) and 4.1% (95% CI, 2.2%-6.1%) (HR, 3.5; 95% CI, 2.4-5.1). The HRs remained elevated after adjusting for FRS (2.9 [95% CI, 2.3-3.7] for men vs 3.0 [95% CI, 2.0-4.4] for women). A low ABI (< or = 0.90) was associated with approximately twice the 10-year total mortality, cardiovascular mortality, and major coronary event rate compared with the overall rate in each FRS category. Inclusion of the ABI in cardiovascular risk stratification using the FRS would result in reclassification of the risk category and modification of treatment recommendations in approximately 19% of men and 36% of women. CONCLUSION Measurement of the ABI may improve the accuracy of cardiovascular risk prediction beyond the FRS.

Identification of Asthma Phenotypes Using Cluster Analysis in the Severe Asthma Research Program

RATIONALE The Severe Asthma Research Program cohort includes subjects with persistent asthma who have undergone detailed phenotypic characterization. Previous univariate methods compared features of mild, moderate, and severe asthma. OBJECTIVES To identify novel asthma phenotypes using an unsupervised hierarchical cluster analysis. METHODS Reduction of the initial 628 variables to 34 core variables was achieved by elimination of redundant data and transformation of categorical variables into ranked ordinal composite variables. Cluster analysis was performed on 726 subjects. MEASUREMENTS AND MAIN RESULTS Five groups were identified. Subjects in Cluster 1 (n = 110) have early onset atopic asthma with normal lung function treated with two or fewer controller medications (82%) and minimal health care utilization. Cluster 2 (n = 321) consists of subjects with early-onset atopic asthma and preserved lung function but increased medication requirements (29% on three or more medications) and health care utilization. Cluster 3 (n = 59) is a unique group of mostly older obese women with late-onset nonatopic asthma, moderate reductions in FEV(1), and frequent oral corticosteroid use to manage exacerbations. Subjects in Clusters 4 (n = 120) and 5 (n = 116) have severe airflow obstruction with bronchodilator responsiveness but differ in to their ability to attain normal lung function, age of asthma onset, atopic status, and use of oral corticosteroids. CONCLUSIONS Five distinct clinical phenotypes of asthma have been identified using unsupervised hierarchical cluster analysis. All clusters contain subjects who meet the American Thoracic Society definition of severe asthma, which supports clinical heterogeneity in asthma and the need for new approaches for the classification of disease severity in asthma.

Low Serum Thyrotropin Concentrations as a Risk Factor for Atrial Fibrillation in Older Persons

BACKGROUND Low serum thyrotropin concentrations are a sensitive indicator of hyperthyroidism but can also occur in persons who have no clinical manifestations of the disorder. We studied whether low serum thyrotropin concentrations in clinically euthyroid older persons are a risk factor for subsequent atrial fibrillation. METHODS We studied 2007 persons (814 men and 1193 women) 60 years of age or older who did not have atrial fibrillation in order to determine the frequency of this arrhythmia during a 10-year follow-up period. The subjects were classified according to their serum thyrotropin concentrations: those with low values (< or = 0.1 mU per liter; 61 subjects); those with slightly low values (> 0.1 to 0.4 mU per liter; 187 subjects); those with normal values (> 0.4 to 5.0 mU per liter; 1576 subjects); and those with high values (> 5.0 mU per liter; 183 subjects). RESULTS During the 10-year follow-up period, atrial fibrillation occurred in 13 persons with low initial values for serum thyrotropin, 23 with slightly low values, 133 with normal values, and 23 with high values. The cumulative incidence of atrial fibrillation at 10 years was 28 percent among the subjects with low serum thyrotropin values (< or = 0.1 mU per liter), as compared with 11 percent among those with normal values; the age-adjusted incidence of atrial fibrillation was 28 per 1000 person-years among those with low values and 10 per 1000 person-years among those with normal values (P = 0.005). After adjustment for other known risk factors, the relative risk of atrial fibrillation in elderly subjects with low serum thyrotropin concentrations, as compared with those with normal concentrations, was 3.1 (95 percent confidence interval, 1.7 to 5.5; P < 0.001). The 10-year incidence of atrial fibrillation in the groups with slightly low and high serum thyrotropin values was not significantly different from that in the group with normal values. CONCLUSIONS Among people 60 years of age or older, a low serum thyrotropin concentration is associated with a threefold higher risk that atrial fibrillation will develop in the subsequent decade.