Our results suggest that the Diamond-Forrester model overestimates the probability of CAD especially in women. We updated the predictive effects of age, sex, type of chest pain, and hospital setting which improved model performance and we extended it to include patients of 70 years and older.

The aim of the study was to compare the diagnostic performance of endoscopic ultrasonography (EUS), computed tomography (CT), and 18 F-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) in staging of oesophageal cancer. PubMed was searched to identify English-language articles published before January 2006 and reporting on diagnostic performance of EUS, CT, and/or FDG-PET in oesophageal cancer patients. Articles were included if absolute numbers of true-positive, false-negative, falsepositive, and true-negative test results were available or derivable for regional, celiac, and abdominal lymph node metastases and/or distant metastases. Sensitivities and specificities were pooled using a random effects model. Summary receiver operating characteristic analysis was performed to study potential effects of study and patient characteristics. Random effects pooled sensitivities of EUS, CT, and FDG-PET for regional lymph node metastases were 0. .86 -0.96) for CT, respectively. Diagnostic performance of FDG-PET for distant metastases was significantly higher than that of CT, which was not significantly affected by study and patient characteristics. The results suggest that EUS, CT, and FDG-PET each play a distinctive role in the detection of metastases in oesophageal cancer patients. For the detection of regional lymph node metastases, EUS is most sensitive, whereas CT and FDG-PET are more specific tests. For the evaluation of distant metastases, FDG-PET has probably a higher sensitivity than CT. Its combined use could however be of clinical value, with FDG-PET detecting possible metastases and CT confirming or excluding their presence and precisely determining the location(s).

Objectives To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations.Design Retrospective pooled analysis of individual patient data.Setting 18 hospitals in Europe and the United States.Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary angiography or catheter based coronary angiography (indicated as low and high prevalence settings, respectively). Main outcome measuresObstructive coronary artery disease (≥50% diameter stenosis in at least one vessel found on catheter based coronary angiography). Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures. Predictive models included a basic model (age, sex, symptoms, and setting), clinical model (basic model factors and diabetes, hypertension, dyslipidaemia, and smoking), and extended model (clinical model factors and use of the CT based coronary calcium score). We assessed discrimination (c statistic), calibration, and continuous net reclassification improvement by cross validation for the four largest low prevalence datasets separately and the smaller remaining low prevalence datasets combined. ResultsWe included 5677 patients (3283 men, 2394 women), of whom 1634 had obstructive coronary artery disease found on catheter based coronary angiography. All potential predictors were significantly associated with the presence of disease in univariable and multivariable analyses. The clinical model improved the prediction, compared with the basic model (cross validated c statistic improvement from 0.77 to 0.79, net reclassification improvement 35%); the coronary calcium score in the extended model was a major predictor (0.79 to 0.88, 102%). Calibration for low prevalence datasets was satisfactory.Conclusions Updated prediction models including age, sex, symptoms, and cardiovascular risk factors allow for accurate estimation of the pretest probability of coronary artery disease in low prevalence populations. Addition of coronary calcium scores to the prediction models improves the estimates. IntroductionIn the United States, about 10.2 million people have chest pain complaints each year, 1 and more than 1.1 million diagnostic procedures of catheter based coronary angiography are performed on inpatients each year. 2 In a recent report based on the national cardiovascular data registry of the American College of Cardiology, 3 only 41% of patients undergoing elective procedures of catheter based coronary angiographies are diagnosed with obstructive coronary artery disease. The report's authors concluded that better risk stratification was needed, underlined by decision analyses showing that the choice of further diagnostic investigation in patients with chest pain depends primarily on the pretest probability of coronary artery disease. [4][5][6] The American College of Cardiology/American Heart Associatio...