Meta-Analysis: The Value of Clinical Assessment in the Diagnosis of Deep Venous Thrombosis

Context Which clinical findings most affect the probability of deep venous thrombosis (DVT)? Contribution This systematic review of 54 cohort studies found that previous DVT and malignant disease modestly increased the probability of DVT (positive likelihood ratios, 2.25 and 2.71), followed by recent immobilization, difference in calf diameter, and recent surgery (positive likelihood ratios, 1.75 to 1.98). Wells scores, based on 9 items, stratified patients' probability of proximal DVT much better than did individual findings, particularly in younger patients and in patients without previous DVT. Implications Estimating the probability of DVT is best accomplished by assessing and scoring multiple findings. The Editors Suspected deep venous thrombosis (DVT) is a common cause of emergency hospitalization (1). Many technologies can be used to diagnose DVT, varying from the cheap and simple but inaccurate (d-dimer testing) to the accurate but expensive and technically challenging (venography). Clinical assessment can be used to select patients for an appropriate diagnostic test. This may involve using individual clinical features to estimate the likelihood of DVT or using standardized clinical assessment to derive a pretest probability based on a clinical score. The Wells clinical score is a widely used instrument that categorizes patients into high, intermediate, and low risk for DVT (2). It is increasingly being recognized that clinical diagnosis should be based on systematic evaluation of the scientific evidence (3). Investigations of the clinical diagnosis of DVT have been published over more than 4 decades (4, 5). We aimed to systematically review the literature to determine whether physicians' empirical judgments, clinical findings, and risk scores affect the likelihood of detecting thrombosis with venography, ultrasonography, or plethysmography in adults with suspected DVT. Methods We sought to identify all diagnostic cohort studies of patients with suspected DVT that recorded physicians' empirical judgments, clinical findings, or a clinical score and then undertook diagnostic testing for DVT. We searched the following electronic sources (1966 to January 2005): MEDLINE, EMBASE, CINAHL, Web of Science, Cochrane Database of Systematic Reviews, Cochrane Controlled Trials Register, Database of Reviews of Effectiveness, and ACP Journal Club. We scanned the bibliographies of all retrieved articles for potentially relevant articles that were not identified by the original search. Two reviewers screened the titles and abstracts of all articles identified by the search strategy and independently determined whether the article could potentially be reporting a cohort study that measured the diagnostic performance of physicians' empirical judgments, clinical findings, or a clinical score compared with a reference standard test (venography, ultrasonography, or plethysmography). Full copies of all selected articles were retrieved. The same 2 reviewers then independently reviewed the full articles to determine whether they did meet the criteria outlined earlier. A score was calculated for agreement between the 2 reviewers at both stages of the selection process, and disagreements were resolved by discussion. We specifically excluded the following: studies that measured the risk for developing DVT after recording clinical characteristics rather than measuring the probability that DVT was present at the time of assessment; casecontrol studies, in which patients were selected on the basis or having or not having DVT; and studies with fewer than 10 patients. We included studies published in English, French, Spanish, or Italian and excluded studies published in other languages. If a study was published as an abstract, we contacted the authors to ask for full details of the data. If we could not extract the necessary data from the published report, we contacted the authors for clarification, provided the study was published in the past 10 years. We assessed study quality by determining whether the reference standard was applied independently of the findings of the clinical assessment, whether observers blinded to the reference standard result undertook clinical assessment, and whether observers blinded to the results of clinical assessment interpreted the reference standard. Empirical evidence suggests that failure to meet these criteria is associated with overestimation of diagnostic accuracy (6). We extracted the following data from each article: the setting for recruitment; groups excluded from the study; population characteristics (mean or median age, sex balance); prevalence of DVT (proximal/above knee and distal/below knee); whether clinical data were extracted from clinical notes or collected on a standardized form by the clinician; the person who recorded the clinical data; the reference standard used; the number of true-positive results (proximal and distal DVT), true-negative results, and false-positive and false-negative results (proximal and distal DVT) for each clinical feature; and the number of case-patients with and without DVT for each clinical score (either as reported or calculated from the reported data). Statistical Analysis We used a random-effects model, as implemented by MetaDiSc statistical software (7), to estimate pooled likelihood ratios for the presence and absence of each clinical feature (8). A chi-square test for heterogeneity is reported for each clinical feature. Although considerable heterogeneity existed for a proportion of the outcomes, we did not undertake meta-regression of individual clinical features because of the relatively small numbers of studies available for most meta-analyses (9). Clinical scores are usually reported as the prevalence of DVT in each risk category. This is similar to reporting the predictive values of a diagnostic test and will vary according to the population prevalence of DVT. We therefore analyzed the data by examining how the scores categorized patients with and without DVT. This approach is similar to analyzing and reporting sensitivity and specificity. Meta-analyses of the Wells score and empirical estimates were necessarily more complex since individuals were categorized into 3 groups (high, intermediate, and low risk for DVT). We carried out ordinal logistic regression, including a random study effect coefficient, using the software WinBUGS (MRC Biostatistics Unit, Cambridge, United Kingdom) (10) to estimate the probability of being categorized as having high, intermediate, and low risk; we used separate models for persons with any DVT, those with proximal DVT, those with distal DVT, and those without DVT. From this analysis, we could estimate sensitivity and specificity for 2 possible decision thresholds for all cases of DVT: high versus intermediate and low, and high and intermediate versus low. We estimated pooled likelihood ratios for high and low categories using the random-effects model implemented by MetaDiSc statistical software. We used meta-regression to explore the influence of study-level covariates on diagnostic performance of the Wells score and potentially explain a proportion of the between-study heterogeneity. To do this, we extended the ordinal regression model to fit a fixed-effects summary receiver-operating characteristic (ROC) curve through the data and to explore the influence of adding covariates into the model on the shape of the curve (11). Results are reported along with an indication of which covariates were statistically significant at the 5% level. The NLMIXED procedure in SAS (SAS Institute, Inc., Cary, North Carolina) (12) was used for the analysis. The Appendix further describes the details of this analysis. Role of the Funding Source The United Kingdom Health Technology Assessment R&D Programme funded this project (reference no. 02/03/01). The funding source had no role in the design, conduct, and reporting of the study or in the decision to submit the report for publication. Data Synthesis Figure 1 outlines the flow of articles considered for the review. The 51 articles included in the meta-analysis reported data from 54 cohorts: 29 cohorts evaluated individual clinical features, 25 cohorts evaluated the Wells clinical score, 7 cohorts developed or evaluated other scores, and 8 cohorts evaluated physicians' empirical judgments. Appendix Table 1 describes the characteristics of the cohorts. In most studies, the reference standard was applied independently of the results of clinical assessment. The exceptions were studies that augmented an ultrasonography reference standard with further testing based on clinical probability. Reporting of blinding of clinical assessment and the reference standard was generally poor; in most studies, it was unclear whether assessments were blinded or not. Figure 1. Flow diagram of studies considered for the review. We undertook meta-analyses of 13 different clinical features, 1 clinical score (the Wells score), and 2 approaches to physicians' empirical judgments. Table 1 summarizes the characteristics of the studies included in each meta-analysis. Studies included in meta-analyses of individual clinical features were more likely to use venography as the reference standard, whereas studies included in the meta-analysis of the Wells score were more likely to use ultrasonography. More studies in the meta-analysis of the Wells score used a reference standard that depended on the results of clinical assessment. Table 1. Summaries of Characteristics of Cohorts Included in Each Meta-Analysis Individual Clinical Features Each study of clinical features reported only a selection of the 13 features evaluated. Table 2 shows which cohorts studied which clinical features and outlines the likelihood ratios from these studies. In most cases, when a particular feature was not reported it was unclear whether it had been examined but not reported or simply not examined. A few studies reported clinical features