Reporting of Bayesian analysis in epidemiologic research should become more transparent.

Objectives: The objective of this systematic review is to investigate the use of Bayesian data analysis in epidemiology in the past decade and particularly to evaluate the quality of research papers reporting the results of these analyses.

Study Design And Setting: Complete volumes of five major epidemiological journals in the period 2005-2015 were searched via PubMed. In addition, we performed an extensive within-manuscript search using a specialized Java application.

Diagnostic accuracy of conventional or age adjusted D-dimer cut-off values in older patients with suspected venous thromboembolism: systematic review and meta-analysis.

Objective: To review the diagnostic accuracy of D-dimer testing in older patients (>50 years) with suspected venous thromboembolism, using conventional or age adjusted D-dimer cut-off values.

Design: Systematic review and bivariate random effects meta-analysis.

Data Sources: We searched Medline and Embase for studies published before 21 June 2012 and we contacted the authors of primary studies.

Accuracy of symptoms, signs, and C-reactive protein for early chronic obstructive pulmonary disease.

Background: Guidelines recommend detection of early chronic obstructive pulmonary disease (COPD), but evidence on the diagnostic work-up for COPD only concerns advanced and established COPD.

Aim: To quantify the accuracy of symptoms and signs for early COPD, and the added value of C-reactive protein (CRP), in primary care patients presenting with cough.

Design And Setting: Cross-sectional diagnostic study of 73 primary care practices in the Netherlands.

Validation of two age dependent D-dimer cut-off values for exclusion of deep vein thrombosis in suspected elderly patients in primary care: retrospective, cross sectional, diagnostic analysis.

Objective: To determine whether the use of age adapted D-dimer cut-off values can be translated to primary care patients who are suspected of deep vein thrombosis.

Design: Retrospective, cross sectional diagnostic study.

Setting: 110 primary care doctors affiliated with three hospitals in the Netherlands.

A simple adaptation method improved the interpretability of prediction models for composite end points.

Objective: The pros and cons of composite end points in prognostic research are discussed, and an adaptation method, designed to accurately adjust absolute risks for a composite end point to risks for the individual component outcomes, is presented.

Study Design And Setting: An example prediction model for recurrent cardiovascular events (composite end point) was used to evaluate the performance regarding the individual component outcomes (cardiovascular death, myocardial infarction, and stroke) before and after the adaptation method.

Results: Discrimination for the individual component outcomes (concordance index for myocardial infarction, 0.

Adjusting for partial verification or workup bias in meta-analyses of diagnostic accuracy studies.

A key requirement in the design of diagnostic accuracy studies is that all study participants receive both the test under evaluation and the reference standard test. For a variety of practical and ethical reasons, sometimes only a proportion of patients receive the reference standard, which can bias the accuracy estimates. Numerous methods have been described for correcting this partial verification bias or workup bias in individual studies.

Development and validation of clinical prediction models: marginal differences between logistic regression, penalized maximum likelihood estimation, and genetic programming.

Objective: Many prediction models are developed by multivariable logistic regression. However, there are several alternative methods to develop prediction models. We compared the accuracy of a model that predicts the presence of deep venous thrombosis (DVT) when developed by four different methods.

Incorporation of historical data in the analysis of randomized therapeutic trials.

Historical studies provide a valuable source of information for the motivation and design of later trials. Bayesian techniques offer possibilities for the quantitative inclusion of prior knowledge within the analysis of current trial data. Combining information from previous studies into an informative prior distribution is, however, a delicate case.

A model for preconceptional prediction of recurrent early-onset preeclampsia: derivation and internal validation.

Objective: To develop a model to identify women at very low risk of recurrent early-onset preeclampsia.

Methods: We enrolled 407 women who had experienced early-onset preeclampsia in their first pregnancy, resulting in a delivery before 34 weeks' gestation. Preeclampsia was defined as hypertension (systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg) after 20 weeks' gestation with de novo proteinuria (≥300 mg urinary protein excretion/day).

Adjusting for differential-verification bias in diagnostic-accuracy studies: a Bayesian approach.

In studies of diagnostic accuracy, the performance of an index test is assessed by verifying its results against those of a reference standard. If verification of index-test results by the preferred reference standard can be performed only in a subset of subjects, an alternative reference test could be given to the remainder. The drawback of this so-called differential-verification design is that the second reference test is often of lesser quality, or defines the target condition in a different way.

Correcting for partial verification bias: a comparison of methods.

Purpose: A common problem in diagnostic research is that the reference standard has not been carried out in all patients. This partial verification may lead to biased accuracy measures of the test under study. The authors studied the performance of multiple imputation and the conventional correction method proposed by Begg and Greenes under a range of different situations of partial verification.

Optimisation of the diagnostic strategy for suspected deep-vein thrombosis in primary care.

Recently, a diagnostic score was developed to safely exclude deep-vein thrombosis (DVT) in primary care. A large prospective study, in which general practitioners used this diagnostic score to decide which patients needed referral, revealed that the number of referrals for ultrasound measurements was reduced by almost 50%, at the cost of an acceptably low risk (1.4%, 95% confidence interval [CI] 0.

Diagnostic accuracy and user-friendliness of 5 point-of-care D-dimer tests for the exclusion of deep vein thrombosis.

Background: Point-of-care D-dimer tests have recently been introduced to enable rapid exclusion of deep venous thrombosis (DVT) without the need to refer a patient for conventional laboratory-based D-dimer testing. Before implementation in practice, however, the diagnostic accuracy of each test should be validated.

Methods: We analyzed data of 577 prospectively identified consecutive primary care patients suspected to have DVT, who underwent 5 point-of-care D-dimer tests-4 quantitative (Vidas®, Pathfast™, Cardiac®, and Triage®) and 1 qualitative (Clearview Simplify®)-and ultrasonography as the reference method.

Unpredictable bias when using the missing indicator method or complete case analysis for missing confounder values: an empirical example.

Objective: Missing indicator method (MIM) and complete case analysis (CC) are frequently used to handle missing confounder data. Using empirical data, we demonstrated the degree and direction of bias in the effect estimate when using these methods compared with multiple imputation (MI).

Study Design And Setting: From a cohort study, we selected an exposure (marital status), outcome (depression), and confounders (age, sex, and income).

Missing covariate data in medical research: to impute is better than to ignore.

Objective: We compared popular methods to handle missing data with multiple imputation (a more sophisticated method that preserves data).

Study Design And Setting: We used data of 804 patients with a suspicion of deep venous thrombosis (DVT). We studied three covariates to predict the presence of DVT: d-dimer level, difference in calf circumference, and history of leg trauma.

Prediction model for hypertension in pregnancy in nulliparous women using information obtained at the first antenatal visit.

Objective: To develop a prediction model for the occurrence of hypertension in pregnancy using clinical variables obtained routinely at the antenatal booking visit prior to 16 weeks gestation.

Methods: We studied 2334 nulliparous pregnant women participating in two population-based prospective cohort studies. Potential predictors included maternal age, blood pressure, body weight, height, previous miscarriage and smoking history, assessed at the visit booking prior to 16 weeks gestation.

Dealing with missing predictor values when applying clinical prediction models.

Background: Prediction models combine patient characteristics and test results to predict the presence of a disease or the occurrence of an event in the future. In the event that test results (predictor) are unavailable, a strategy is needed to help users applying a prediction model to deal with such missing values. We evaluated 6 strategies to deal with missing values.

A simple method to adjust clinical prediction models to local circumstances.

Introduction: Clinical prediction models estimate the risk of having or developing a particular outcome or disease. Researchers often develop a new model when a previously developed model is validated and the performance is poor. However, the model can be adjusted (updated) using the new data.

The risk of severe postoperative pain: modification and validation of a clinical prediction rule.

Background: Recently, a prediction rule was developed to preoperatively predict the risk of severe pain in the first postoperative hour in surgical inpatients. We aimed to modify the rule to enhance its use in both surgical inpatients and outpatients (ambulatory patients). Subsequently, we prospectively tested the modified rule in patients who underwent surgery later in time and in another hospital (external validation).

The Glasgow Aneurysm Score as a tool to predict 30-day and 2-year mortality in the patients from the Dutch Randomized Endovascular Aneurysm Management trial.

Objective: Randomized trials have shown that endovascular repair (EVAR) of an abdominal aortic aneurysm (AAA) has a lower perioperative mortality than conventional open repair (OR). However, this initial survival advantage disappears after 1 year. To make EVAR cost-effective, patient selection should be improved.