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F E Harrell

Publications and source records attributed to F E Harrell.

131 records · Page 8Linked to original sources
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Psychosocial and physical predictors of anginal pain relief with medical management.

This study was undertaken to identify psychosocial and physical characteristics that independently predict anginal pain relief. The original study group comprised over 570 patients in whom the characteristics were identified at the time of coronary arteriography and who were followed up after 6 months of standard medical therapy. In the subset of 382 of these patients who were assessed as having NYHA Class III or IV angina at the time of angiography, a multivariable analysis of 101 baseline descriptors showed that higher scores on the MMPI hypochondriasis scale, unemployment, and more severe right coronary occlusion were significant independent predictors of failure to achieve two-class improvement at follow-up. These three characteristics also predicted continuing severe angina in a subsequent, independent sample of 91 new patients. These findings could help physicians select appropriate treatment by prospectively identifying patients who are unlikely to respond to standard medical treatment of angina.

Adrenergic beta-Antagonists↗
PubMedDate not supplied

Type A behavior and angiographically documented coronary atherosclerosis in a sample of 2,289 patients.

To determine the relationship between Type A behavior pattern and angiographically documented coronary atherosclerosis (CAD), we analyzed risk factor, behavioral, and angiographic data collected on 2,289 patients undergoing diagnostic coronary angiography at Duke University Medical Center between 1974 and 1980. Multivariable analyses using ordinal logistic regression techniques showed that Type A behavior as assessed by the structured interview (SI) is significantly associated with CAD severity after age, sex, hyperlipidemia, smoking, hypertension, and their various significant interactions were controlled for. This relationship, however, is dependent upon age. Among patients aged 45 or younger, Type A's had more severe CAD than did Type B's; among patients aged 46-54, CAD severity was similar between Type A's and B's; and among patients 55 and older, there was a trend toward more severe CAD among Type B's than among Type A's. These Type A-CAD relationships did not appear to be the result of various factors relating to the selection of patients for angiography. Type A behavior as assessed by the Jenkins Activity Survey was unrelated to CAD severity. These findings suggest that SI-determined Type A behavior is associated with more severe CAD among younger patients referred for diagnostic coronary angiography. The reversal of the Type A-CAD relationship among older patients may be due to survival effects. Inadequate sample sizes, use of assessment tools other than the SI, and failure to consider the Type A by age interaction could account for failures to find a Type A-CAD relationship in other studies. We conclude that the present findings are consistent with the hypothesis that Type A behavior is involved in the pathogenesis of CAD, but only in younger age groups. The Type A effect in the present data is small relative to that of both smoking and hyperlipidemia, however, and future research should focus more specifically on the hostility and anger components of Type A behavior, particularly in younger samples.

Adult↗
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Prognostic modeling with logistic regression analysis: in search of a sensible strategy in small data sets.

Clinical decision making often requires estimates of the likelihood of a dichotomous outcome in individual patients. When empirical data are available, these estimates may well be obtained from a logistic regression model. Several strategies may be followed in the development of such a model. In this study, the authors compare alternative strategies in 23 small subsamples from a large data set of patients with an acute myocardial infarction, where they developed predictive models for 30-day mortality. Evaluations were performed in an independent part of the data set. Specifically, the authors studied the effect of coding of covariables and stepwise selection on discriminative ability of the resulting model, and the effect of statistical "shrinkage" techniques on calibration. As expected, dichotomization of continuous covariables implied a loss of information. Remarkably, stepwise selection resulted in less discriminating models compared to full models including all available covariables, even when more than half of these were randomly associated with the outcome. Using qualitative information on the sign of the effect of predictors slightly improved the predictive ability. Calibration improved when shrinkage was applied on the standard maximum likelihood estimates of the regression coefficients. In conclusion, a sensible strategy in small data sets is to apply shrinkage methods in full models that include well-coded predictors that are selected based on external information.

Aged↗
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The covariance decomposition of the probability score and its use in evaluating prognostic estimates. SUPPORT Investigators.

The probability score (PS) or Brier score has been used in a large number of studies in which physician judgment performance was assessed. However, the covariance decomposition of the PS has not previously been used to evaluate medical judgment. The authors introduce the technique and demonstrate it by analyzing prognostic estimates of three groups: physicians, their patients, and the patients' decision-making surrogates. The major components of the covariance decomposition--bias, slope, and scatter--are displayed in covariance graphs for each of the three groups. The decomposition reveals that whereas the physicians have the best overall estimation performance, their bias and their scatter are not always superior to those of the other two groups. This is primarily due to two factors. First, the physicians' prognostic estimates are pessimistic. Second, the patients place the large majority of their estimates in the most optimistic category, thereby achieving low scatter. The authors suggest that the calculational simplicity of this decomposition, its informativeness, and the intuitive nature of its components make it a useful tool with which to analyze medical judgment.

Bias↗