d-Dimer for the Exclusion of Acute Venous Thrombosis and Pulmonary Embolism

Context Clinicians may not know which d-dimer assay is best for diagnosing deep venous thrombosis (DVT) or pulmonary embolism (PE). Contribution This meta-analysis summarizes data from 78 prospective studies that compared results of different d-dimer assays with findings of objective tests (for example, compression ultrasonography, venography, lung scanning) in patients with suspected DVT or PE. Enzyme-linked immunosorbent assays (ELISAs) had the best sensitivity (about 95%) and negative likelihood ratios (about 0.1) for excluding DVT and PE. None of the assays had positive likelihood values that greatly increased the certainty of diagnosis. Implications Negative ELISA results are strong evidence against DVT or PE. The Editors Tests for d-dimer to exclude venous thromboembolic disease have been available since the 1980s (1). Hundreds of original studies, reviews, commentaries, and technical notes related to d-dimer as a diagnostic aid have been published. Even with this extensive literature, the role of d-dimer in the diagnosis of deep venous thrombosis (DVT) or pulmonary embolism (PE) remains unclear. This lack of clarity is due in part to the multiple d-dimer assays that are available (Appendix Table 1), availability of central laboratory and point-of-care testing, and concerns about differing sensitivities and variability of the assays (1). In 1998, the American College of Chest Physicians Consensus Panel on Pulmonary Embolism called for more evaluation of the utility of d-dimer (2). In 1999, a Clinical Practice Guideline of the American Thoracic Society also called for additional outcome studies to further define the role of rapid bedside assays of d-dimer (3). As recently as 2000, investigators argued that the whole-blood agglutination test with d-dimer is not validated for clinical use for the exclusion of DVT (4). Although several useful reviews of the topic exist (1, 3, 5), none in recent years have comprehensively reviewed the world literature in an effort to summarize the accumulated published experience with d-dimer testing. Given continuing uncertainty about d-dimer testing, we performed a systematic review of the literature to assess the sensitivity and specificity of the d-dimer assays and the variability of those measures among studies for diagnosing DVT and PE. The comparative findings among the differing d-dimer assays provide both the laboratory pathologist and clinician with a practical pathway for translating clinical research into practice. Methods We used several sources to guide our review processes, including recommendations by Lijmer and colleagues concerning avoidance of bias in studies of diagnostic tests (6), the Standards for Reporting Diagnostic Accuracy (STARD) statement (7, 8), and guidelines for meta-analyses of observational studies in epidemiology (9). Study Identification We attempted to identify all published trials in all languages that used d-dimer to exclude PE or DVT on the basis of objective diagnostic tests. Studies were identified by searching PubMed from 1983 to January 2003 and EMBASE from 1988 to January 2003. All searches used the key words d -dimer, PE, and DVT. We augmented our searches by manually reviewing the reference lists of all original articles and all review articles. This was done by 2 of the authors working together. Abstracts were excluded. Study Eligibility At least 2 authors evaluated each study for inclusion. Any disagreements were resolved by discussion. Authors were not blinded to journal, author, or institution. Studies were included if they met all of the following criteria: 1) A specific statement was made about whether PE or DVT (not the inclusive term thromboembolic disease) was being diagnosed; 2) the diagnosis of PE or DVT was based on objective tests; 3) studies were performed prospectively; 4) participants were recruited consecutively; 5) the population studied included a broad spectrum of patients; 6) results of d-dimer and the diagnostic tests for PE and DVT were interpreted independently; 7) the participants studied were suspected of having PE or DVT, and all studies included patients with and without disease; 8) the decision to perform the reference diagnostic test was made independently of the d-dimer result; 9) test descriptions were sufficiently detailed to permit replication; 10) the cutoff value for a negative d-dimer test result was stated unless qualitative tests were used; and 11) sensitivity and specificity or the raw data for these calculations were presented. We labeled studies that did not meet the third, fourth, or tenth inclusion criteria as tier 3 studies and included them in sensitivity analyses. We categorized studies that met all inclusion criteria into 2 tiers. Tier 1 included studies that compared an enzyme-linked immunosorbent assay (ELISA) and at least one other d-dimer assay. Tier 2 included the tier 1 studies and all other studies that met all inclusion criteria. Data Extraction Two authors collected data on the following study-level factors: 1) the d-dimer assay used in the study, 2) the cutoff value below which disease was considered to be absent, and 3) whether d-dimer was used to exclude PE or DVT. At least 2 authors confirmed the values for sensitivity and specificity. Statistical Analysis Sensitivities reflect the proportion of patients with disease who had a positive d-dimer result, while specificities reflect the proportion of patients without disease who had a negative d-dimer result, depending on cutoff level. Values for the likelihood ratio (the multiplicative factor for converting pretest to post-test disease probabilities) associated with positive test results were obtained by the following formula: sensitivity/(1 corresponding specificity). This formula provided likelihood ratios arising from negative test results. Primary analysis was restricted to the 500-ng/mL cutoff because that was the most commonly used value. On the basis of the varying array of assays examined in individual studies and our anticipation of important between-study heterogeneity, we applied a linear mixed-model approach (10) to jointly analyze the proportions of positive test results in the disease and nondisease samples (that is, true-positive and false-positive rates). Similar models have been applied to Bayesian meta-analysis of receiver-operating characteristic curves (11). The main explanatory term in the model was a fixed effect reflecting distinct positive response rates for each combination of assay and population. To allow for variability in assay performance that might arise from idiosyncratic features of patient samples, such as spectrum of disease severity, and other aspects of study context, such as laboratory procedure, we incorporated 3 random-effects terms corresponding to assay nested within patient group (disease/nondisease) nested within study. Residual variances were assumed to follow the standard binomial form depending on underlying proportion and sample size. Applying restricted maximum likelihood, we obtained population average estimates for sensitivity and specificity, which were later combined to provided estimated likelihood ratios. Overall, the estimates did not differ substantially from conventional sample-size weighted averages, although the associated standard errors were increased, reflecting underlying between-study heterogeneity. The joint statistical significance of overall differences was assessed by using likelihood-based Wald tests. Pairwise differences between estimates were assessed on the basis of the model-based standard errors without adjustment for multiple comparisons. Significant pairwise differences should be interpreted with caution when the Wald test is not significant. Confidence limits are derived from asymptotic standard errors; asymmetric intervals for likelihood ratios reflect the application of likelihood theory to logarithmically transformed estimates. Values for the sensitivity and specificity for the different studies and test types were examined graphically by use of boxplots. The range between the upper and lower quartiles of the values for each assay provides a measure of between-study variability associated with the assay. Sensitivity analyses were conducted by adding the 30 studies that did not meet one or more of the 3 inclusion criteria previously mentioned (tier 3 analysis) and by analyzing sensitivity and specificity at the 250-ng/mL and 1000-ng/mL cutoffs. All analyses were conducted by using S-PLUS, version 6.1. 2, 2002 (Insightful Corp., Seattle, Washington) (12). Data Synthesis Figure 1 summarizes our search. We initially identified 513 potentially relevant reports. Thirty-one studies (13-43) were included; they met a priori inclusion criteria and compared 2 or more assays, including an ELISA (tier 1 analysis). An additional 47 studies (44-90) were also included; they did not have a comparative ELISA but met the a priori inclusion criteria evaluating a d-dimer assay. The 47 studies combined with the 31 studies provided a study sample of 78 studies (tier 2 analysis). Thirty additional studies (91-120) that did not meet one or more inclusion criteria were included in the sensitivity, or tier 3, analysis, which also included the 78 studies in the tier 2 analysis. Figure 1. Reports evaluated for inclusion in the review. Appendix Tables 2 and 3 list the d-dimer assays that were evaluated, patient characteristics, and the objective diagnostic reference test that was used for patients with clinically suspected DVT (49 studies) and clinically suspected PE (31 studies). All studies met the 11 criteria for inclusion listed in the Methods section. There was a total of 78 studies (2 studies [60, 71] gave data for patients with PE and DVT separately in the same article). In the various studies, prevalence of DVT ranged from 20% to 78% (overall prevalence, 36%), and the prevalence of PE ranged from 8% to 62% (overall prevalence, 25%). Sixteen studies of DVT used comp