Reviews16 August 2016
A Systematic Review and Individual-Patient Data Meta-analysis
    Author, Article, and Disclosure Information



    The performance of different diagnostic strategies for pulmonary embolism (PE) in patient subgroups is unclear.


    To evaluate and compare the efficiency and safety of the Wells rule with fixed or age-adjusted d-dimer testing overall and in inpatients and persons with cancer, chronic obstructive pulmonary disease, previous venous thromboembolism, delayed presentation, and age 75 years or older.

    Data Sources:

    MEDLINE and EMBASE from 1 January 1988 to 13 February 2016.

    Study Selection:

    6 prospective studies in which the diagnostic management of PE was guided by the dichotomized Wells rule and quantitative d-dimer testing.

    Data Extraction:

    Individual data of 7268 patients; risk of bias assessed by 2 investigators with the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) tool.

    Data Synthesis:

    The proportion of patients in whom imaging could be withheld based on a “PE-unlikely” Wells score and a negative d-dimer test result (efficiency) was estimated using fixed (≤500 µg/L) and age-adjusted (age × 10 µg/L in patients aged >50 years) d-dimer thresholds; their 3-month incidence of symptomatic venous thromboembolism (failure rate) was also estimated. Overall, efficiency increased from 28% to 33% when the age-adjusted (instead of the fixed) d-dimer threshold was applied. This increase was more prominent in elderly patients (12%) but less so in inpatients (2.6%). The failure rate of age-adjusted d-dimer testing was less than 3% in all examined subgroups.


    Post hoc analysis, between-study differences in patient characteristics, use of various d-dimer assays, and limited statistical power to assess failure rate.


    Age-adjusted d-dimer testing is associated with a 5% absolute increase in the proportion of patients with suspected PE in whom imaging can be safely withheld compared with fixed d-dimer testing. This strategy seems safe across different high-risk subgroups, but its efficiency varies.

    Primary Funding Source:



    • 1. Pollack CVSchreiber DGoldhaber SZSlattery DFanikos JO'Neil BJet alClinical characteristics, management, and outcomes of patients diagnosed with acute pulmonary embolism in the emergency department: initial report of EMPEROR (Multicenter Emergency Medicine Pulmonary Embolism in the Real World Registry). J Am Coll Cardiol2011;57:700-6. [PMID: 21292129] doi:10.1016/j.jacc.2010.05.071 CrossrefMedlineGoogle Scholar
    • 2. Konstantinides SVTorbicki AAgnelli GDanchin NFitzmaurice DGaliè Net alTask Force for the Diagnosis and Management of Acute Pulmonary Embolism of the European Society of Cardiology (ESC)2014 ESC guidelines on the diagnosis and management of acute pulmonary embolism. Eur Heart J2014;35:3033-69, 3069a-3069k. [PMID: 25173341] doi:10.1093/eurheartj/ehu283 CrossrefMedlineGoogle Scholar
    • 3. Lucassen WGeersing GJErkens PMReitsma JBMoons KGBüller Het alClinical decision rules for excluding pulmonary embolism: a meta-analysis. Ann Intern Med2011;155:448-60. [PMID: 21969343]. doi:10.7326/0003-4819-155-7-201110040-00007 LinkGoogle Scholar
    • 4. Wells PSAnderson DRRodger MGinsberg JSKearon CGent Met alDerivation of a simple clinical model to categorize patients probability of pulmonary embolism: increasing the models utility with the SimpliRED d-dimer. Thromb Haemost2000;83:416-20. [PMID: 10744147] CrossrefMedlineGoogle Scholar
    • 5. van Belle ABüller HRHuisman MVHuisman PMKaasjager KKamphuisen PWet alChristopher Study InvestigatorsEffectiveness of managing suspected pulmonary embolism using an algorithm combining clinical probability, d-dimer testing, and computed tomography. JAMA2006;295:172-9. [PMID: 16403929] CrossrefMedlineGoogle Scholar
    • 6. Righini MVan Es JDen Exter PLRoy PMVerschuren FGhuysen Aet alAge-adjusted d-dimer cutoff levels to rule out pulmonary embolism: the ADJUST-PE study. JAMA2014;311:1117-24. [PMID: 24643601] doi:10.1001/jama.2014.2135 CrossrefMedlineGoogle Scholar
    • 7. Stewart LAClarke MRovers MRiley RDSimmonds MStewart Get alPRISMA-IPD Development GroupPreferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data: the PRISMA-IPD Statement. JAMA2015;313:1657-65. [PMID: 25919529] doi:10.1001/jama.2015.3656 CrossrefMedlineGoogle Scholar
    • 8. Wells PSGinsberg JSAnderson DRKearon CGent MTurpie AGet alUse of a clinical model for safe management of patients with suspected pulmonary embolism. Ann Intern Med1998;129:997-1005. [PMID: 9867786] LinkGoogle Scholar
    • 9. Geersing GJBouwmeester WZuithoff PSpijker RLeeflang MMoons KGet alSearch filters for finding prognostic and diagnostic prediction studies in MEDLINE to enhance systematic reviews. PLoS One2012;7:e32844. [PMID: 22393453] doi:10.1371/journal.pone.0032844 CrossrefMedlineGoogle Scholar
    • 10. Whiting PFRutjes AWWestwood MEMallett SDeeks JJReitsma JBet alQUADAS-2 GroupQUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med2011;155:529-36. [PMID: 22007046]. doi:10.7326/0003-4819-155-8-201110180-00009 LinkGoogle Scholar
    • 11. van der Heijden GJDonders ARStijnen TMoons KGImputation of missing values is superior to complete case analysis and the missing-indicator method in multivariable diagnostic research: a clinical example. J Clin Epidemiol2006;59:1102-9. [PMID: 16980151] CrossrefMedlineGoogle Scholar
    • 12. Rubin DBInference and missing data. Biometrika1976;63:581-92. CrossrefGoogle Scholar
    • 13. Debray TPMoons KGAbo-Zaid GMKoffijberg HRiley RDIndividual participant data meta-analysis for a binary outcome: one-stage or two-stage? PLoS One2013;8:e60650. [PMID: 23585842] doi:10.1371/journal.pone.0060650 CrossrefMedlineGoogle Scholar
    • 14. Stewart GBAltman DGAskie LMDuley LSimmonds MCStewart LAStatistical analysis of individual participant data meta-analyses: a comparison of methods and recommendations for practice. PLoS One2012;7:e46042. [PMID: 23056232] doi:10.1371/journal.pone.0046042 CrossrefMedlineGoogle Scholar
    • 15. Mos ICDouma RAErkens PMKruip MJHovens MMvan Houten AAet alPrometheus Study GroupDiagnostic outcome management study in patients with clinically suspected recurrent acute pulmonary embolism with a structured algorithm. Thromb Res2014;133:1039-44. [PMID: 24735976] doi:10.1016/j.thromres.2014.03.050 CrossrefMedlineGoogle Scholar
    • 16. Douma RAMos ICErkens PMNizet TADurian MFHovens MMet alPrometheus Study GroupPerformance of 4 clinical decision rules in the diagnostic management of acute pulmonary embolism: a prospective cohort study. Ann Intern Med2011;154:709-18. [PMID: 21646554]. doi:10.7326/0003-4819-154-11-201106070-00002 LinkGoogle Scholar
    • 17. Goekoop RJSteeghs NNiessen RWJonkers GJDik HCastel Aet alSimple and safe exclusion of pulmonary embolism in outpatients using quantitative d-dimer and Wells' simplified decision rule. Thromb Haemost2007;97:146-50. [PMID: 17200782] CrossrefMedlineGoogle Scholar
    • 18. Galipienzo JGarcia de Tena JFlores JAlvarez CGarcia-Avello AArribas IEffectiveness of a diagnostic algorithm combining clinical probability, d-dimer testing, and computed tomography in patients with suspected pulmonary embolism in an emergency department. Rom J Intern Med2012;50:195-202. [PMID: 23330286] MedlineGoogle Scholar
    • 19. Qaseem ASnow VBarry PHornbake ERRodnick JETobolic Tet alJoint American Academy of Family Physicians/American College of Physicians Panel on Deep Venous Thrombosis/Pulmonary EmbolismCurrent diagnosis of venous thromboembolism in primary care: a clinical practice guideline from the American Academy of Family Physicians and the American College of Physicians. Ann Fam Med2007;5:57-62. [PMID: 17261865] CrossrefMedlineGoogle Scholar
    • 20. Carrier MRighini MWells PSPerrier AAnderson DRRodger MAet alSubsegmental pulmonary embolism diagnosed by computed tomography: incidence and clinical implications. A systematic review and meta-analysis of the management outcome studies. J Thromb Haemost2010;8:1716-22. [PMID: 20546118] doi:10.1111/j.1538-7836.2010.03938.x CrossrefMedlineGoogle Scholar
    • 21. Anderson DRKahn SRRodger MAKovacs MJMorris THirsch Aet alComputed tomographic pulmonary angiography vs ventilation-perfusion lung scanning in patients with suspected pulmonary embolism: a randomized controlled trial. JAMA2007;298:2743-53. [PMID: 18165667] doi:10.1001/jama.298.23.2743 CrossrefMedlineGoogle Scholar
    • 22. Wells PSAnderson DRRodger MStiell IDreyer JFBarnes Det alExcluding pulmonary embolism at the bedside without diagnostic imaging: management of patients with suspected pulmonary embolism presenting to the emergency department by using a simple clinical model and d-dimer. Ann Intern Med2001;135:98-107. [PMID: 11453709] LinkGoogle Scholar
    • 23. Kline JARunyon MSWebb WBJones AEMitchell AMProspective study of the diagnostic accuracy of the simplify d-dimer assay for pulmonary embolism in emergency department patients. Chest2006;129:1417-23. [PMID: 16778257] CrossrefMedlineGoogle Scholar
    • 24. Di Nisio MSquizzato ARutjes AWBüller HRZwinderman AHBossuyt PMDiagnostic accuracy of d-dimer test for exclusion of venous thromboembolism: a systematic review. J Thromb Haemost2007;5:296-304. [PMID: 17155963] CrossrefMedlineGoogle Scholar
    • 25. Schouten HJGeersing GJKoek HLZuithoff NPJanssen KJDouma RAet alDiagnostic accuracy of conventional or age adjusted d-dimer cut-off values in older patients with suspected venous thromboembolism: systematic review and meta-analysis. BMJ2013;346:f2492. [PMID: 23645857] doi:10.1136/bmj.f2492 CrossrefMedlineGoogle Scholar
    • 26. Douma RAle Gal GSöhne MRighini MKamphuisen PWPerrier Aet alPotential of an age adjusted d-dimer cut-off value to improve the exclusion of pulmonary embolism in older patients: a retrospective analysis of three large cohorts. BMJ2010;340:c1475. [PMID: 20354012] doi:10.1136/bmj.c1475 CrossrefMedlineGoogle Scholar
    • 27. Penaloza ARoy PMKline JVerschuren FLEGal GQuentin-Georget Set alPerformance of age-adjusted d-dimer cut-off to rule out pulmonary embolism. J Thromb Haemost2012;10:1291-6. [PMID: 22568451] doi:10.1111/j.1538-7836.2012.04769.x CrossrefMedlineGoogle Scholar
    • 28. Douma RAvan Sluis GLKamphuisen PWSöhne MLeebeek FWBossuyt PMet alClinical decision rule and d-dimer have lower clinical utility to exclude pulmonary embolism in cancer patients. Explanations and potential ameliorations. Thromb Haemost2010;104:831-6. [PMID: 20664894] doi:10.1160/TH10-02-0093 CrossrefMedlineGoogle Scholar
    • 29. Righini MParis SLe Gal GLaroche JPPerrier ABounameaux HClinical relevance of distal deep vein thrombosis. Review of literature data. Thromb Haemost2006;95:56-64. [PMID: 16543962] CrossrefMedlineGoogle Scholar
    • 30. Sohne MKruip MJNijkeuter MTick LKwakkel HHalkes SJet alChristoper Study GroupAccuracy of clinical decision rule, d-dimer and spiral computed tomography in patients with malignancy, previous venous thromboembolism, COPD or heart failure and in older patients with suspected pulmonary embolism. J Thromb Haemost2006;4:1042-6. [PMID: 16689757] CrossrefMedlineGoogle Scholar
    • 31. Söhne MKamphuisen PWvan Mierlo PJBüller HRDiagnostic strategy using a modified clinical decision rule and d-dimer test to rule out pulmonary embolism in elderly in- and outpatients. Thromb Haemost2005;94:206-10. [PMID: 16113805] CrossrefMedlineGoogle Scholar
    • 32. Le Gal GRighini MRoy PMSanchez OAujesky DPerrier Aet alValue of d-dimer testing for the exclusion of pulmonary embolism in patients with previous venous thromboembolism. Arch Intern Med2006;166:176-80. [PMID: 16432085] CrossrefMedlineGoogle Scholar
    • 33. Nijkeuter MKwakkel-van Erp HSöhne MTick LWKruip MJUllmann EFet alChristopher Study InvestigatorsClinically suspected acute recurrent pulmonary embolism: a diagnostic challenge. Thromb Haemost2007;97:944-8. [PMID: 17549296] CrossrefMedlineGoogle Scholar
    • 34. den Exter PLvan Es JErkens PMvan Roosmalen MJvan den Hoven PHovens MMet alImpact of delay in clinical presentation on the diagnostic management and prognosis of patients with suspected pulmonary embolism. Am J Respir Crit Care Med2013;187:1369-73. [PMID: 23590273] doi:10.1164/rccm.201212-2219OC CrossrefMedlineGoogle Scholar
    • 35. van der Hulle TdenExter PLMos ICKamphuisen PWHovens MMKruip MJet alOptimization of the diagnostic management of clinically suspected pulmonary embolism in hospitalized patients. Br J Haematol2014;167:681-6. [PMID: 25146098] doi:10.1111/bjh.13090 CrossrefMedlineGoogle Scholar
    • 36. van Beek EJBrouwerst EMSong BStein PDOudkerk MClinical validity of a normal pulmonary angiogram in patients with suspected pulmonary embolism—a critical review. Clin Radiol2001;56:838-42. [PMID: 11895301] CrossrefMedlineGoogle Scholar
    • 37. Donders ARvan der Heijden GJStijnen TMoons KGReview: a gentle introduction to imputation of missing values. J Clin Epidemiol2006;59:1087-91. [PMID: 16980149] CrossrefMedlineGoogle Scholar
    • 38. van Buuren SGroothuis-Oudshoorn KMice: multivariate imputation by chained equations in R. J Stat Softw2011;45. MedlineGoogle Scholar
    • 39. van Buuren SBrand JPLGroothuis-Oudshoorn CGMRubin DBFully conditional specification in multivariate imputation. J Stat Comput Simul2006;76:1049-64. CrossrefGoogle Scholar
    • 40. Moons KGDonders RAStijnen THarrell FEUsing the outcome for imputation of missing predictor values was preferred. J Clin Epidemiol2006;59:1092-101. [PMID: 16980150] CrossrefMedlineGoogle Scholar
    • 41. Bates DMächler MBolker BWalker SFitting linear mixed-effects models using lme4. J Stat Softw2015;67. CrossrefGoogle Scholar
    • 42. Skrondal ARabe-Hesketh SPrediction in multilevel generalized linear models. J R Stat Soc Ser A2009;172:659-87. CrossrefGoogle Scholar
    • 43. Baddeley ATurner RSpatstat: an R package for analyzing spatial point patterns. J Stat Softw2005;12:1-42. CrossrefGoogle Scholar