Derivation and Validation of a 4-Level Clinical Pretest Probability Score for Suspected Pulmonary Embolism to Safely Decrease Imaging Testing

Pierre-Marie Roy, Emilie Friou, Boris Germeau, Delphine Douillet, Jeffrey Allen Kline, Marc Righini, Grégoire Le Gal, Thomas Moumneh, Andrea Penaloza, Pierre-Marie Roy, Emilie Friou, Boris Germeau, Delphine Douillet, Jeffrey Allen Kline, Marc Righini, Grégoire Le Gal, Thomas Moumneh, Andrea Penaloza

Abstract

Importance: In patients with suspected pulmonary embolism (PE), overuse of diagnostic imaging is an important point of concern.

Objective: To derive and validate a 4-level pretest probability rule (4-Level Pulmonary Embolism Clinical Probability Score [4PEPS]) that makes it possible to rule out PE solely on clinical criteria and optimized D-dimer measurement to safely decrease imaging testing for suspected PE.

Design, setting, and participants: This study included consecutive outpatients suspected of having PE from US and European emergency departments. Individual data from 3 merged management studies (n = 11 114; overall prevalence of PE, 11%) were used for the derivation cohort and internal validation cohort. The external validation cohorts were taken from 2 independent studies, the first with a high PE prevalence (n = 1548; prevalence, 21.5%) and the second with a moderate PE prevalence (n = 1669; prevalence, 11.7%). A prior definition of pretest probability target values to achieve a posttest probability less than 2% was used on the basis of the negative likelihood ratios of D-dimer. Data were collected from January 2003 to April 2016, and data were analyzed from June 2018 to August 2019.

Main outcomes and measures: The rate of PE diagnosed during the initial workup or during follow-up and the rate of imaging testing.

Results: Of the 5588 patients in the derivation cohort, 3441 (61.8%) were female, and the mean (SD) age was 52 (18.5) years. The 4PEPS comprises 13 clinical variables scored from -2 to 5. It results in the following strategy: (1) very low probability of PE if 4PEPS is less than 0: PE ruled out without testing; (2) low probability of PE if 4PEPS is 0 to 5: PE ruled out if D-dimer level is less than 1.0 μg/mL; (3) moderate probability of PE if 4PEPS is 6 to 12: PE ruled out if D-dimer level is less than the age-adjusted cutoff value; (4) high probability of PE if 4PEPS is greater than 12: PE ruled out by imaging without preceding D-dimer test. In the first and the second external validation cohorts, the area under the receiver operator characteristic curves were 0.79 (95% CI, 0.76 to 0.82) and 0.78 (95% CI, 0.74 to 0.81), respectively. The false-negative testing rates if the 4PEPS strategy had been applied were 0.71% (95% CI, 0.37 to 1.23) and 0.89% (95% CI, 0.53 to 1.49), respectively. The absolute reductions in imaging testing were -22% (95% CI, -26 to -19) and -19% (95% CI, -22 to -16) in the first and second external validation cohorts, respectively. The 4PEPS strategy compared favorably with all recent strategies in terms of imaging testing.

Conclusions and relevance: The 4PEPS strategy may lead to a substantial and safe reduction in imaging testing for patients with suspected PE. It should now be tested in a formal outcome study.

Conflict of interest statement

Conflict of Interest Disclosures: Dr Roy has received grants from the French Health Ministry as well as personal fees and nonfinancial support from Bayer Health Care, Boehringer Ingelheim France, Bristol Myers Squibb, Pfizer, Aspen, Daiichi Sankyo, and Sanofi Aventis France outside the submitted work. Dr Kline has received grants from the National Institutes of Health, Stago Diagnostica, Janssen/Johnson & Johnson, and Pfizer/Bristol Myers Squibb outside the submitted work. Dr Righini has received grants from the Swiss National Research Foundation. Dr Le Gal has received grants from the French Health Ministry, Portola Pharmaceuticals, Boehringer Ingelheim, Pfizer, Bristol Myers Squibb, LEO Pharma, Daiichi Sankyo, and Bayer as well as personal fees from Bayer, Pfizer, LEO Pharma, Sanofi, and bioMérieux. Dr Moumneh has received grants from the French Health Ministry, Société Française de Médecine d’Urgence, and CanVECTOR Network outside the submitted work. Dr Penaloza has received grants from Fondation Saint Luc and Bristol Myers Squibb; grants and personal fees from Bayer; and personal fees and nonfinancial support from Boehringer Ingelheim, Daiichi Sankyo, Sanofi, Stago Diagnostica, Bristol Myers Squibb, Aspen, and Roche outside the submitted work. No other disclosures were reported.

Figures

Figure.. Pulmonary Embolism Prevalence by 4-Level Pulmonary…
Figure.. Pulmonary Embolism Prevalence by 4-Level Pulmonary Embolism Clinical Probability Score (4PEPS) in the Derivation and Validation Cohorts

References

    1. Konstantinides SV, Meyer G, Becattini C, et al. ; ESC Scientific Document Group . 2019 ESC guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS). Eur Heart J. 2020;41(4):543-603. doi:10.1093/eurheartj/ehz405
    1. Kline JA, Garrett JS, Sarmiento EJ, Strachan CC, Courtney DM. Over-testing for suspected pulmonary embolism in American emergency departments: the continuing epidemic. Circ Cardiovasc Qual Outcomes. 2020;13(1):e005753. doi:10.1161/CIRCOUTCOMES.119.005753
    1. Wang RC, Miglioretti DL, Marlow EC, et al. . Trends in imaging for suspected pulmonary embolism across US health care systems, 2004 to 2016. JAMA Netw Open. 2020;3(11):e2026930. doi:10.1001/jamanetworkopen.2020.26930
    1. Dobler CC. Overdiagnosis of pulmonary embolism: definition, causes and implications. Breathe (Sheff). 2019;15(1):46-53. doi:10.1183/20734735.0339-2018
    1. Wiener RS, Schwartz LM, Woloshin S. Time trends in pulmonary embolism in the United States: evidence of overdiagnosis. Arch Intern Med. 2011;171(9):831-837. doi:10.1001/archinternmed.2011.178
    1. Mitchell AM, Jones AE, Tumlin JA, Kline JA. Prospective study of the incidence of contrast-induced nephropathy among patients evaluated for pulmonary embolism by contrast-enhanced computed tomography. Acad Emerg Med. 2012;19(6):618-625. doi:10.1111/j.1553-2712.2012.01374.x
    1. Niemann T, Zbinden I, Roser HW, Bremerich J, Remy-Jardin M, Bongartz G. Computed tomography for pulmonary embolism: assessment of a 1-year cohort and estimated cancer risk associated with diagnostic irradiation. Acta Radiol. 2013;54(7):778-784. doi:10.1177/0284185113485069
    1. Le Gal G, Righini M, Roy P-M, et al. . Prediction of pulmonary embolism in the emergency department: the revised Geneva score. Ann Intern Med. 2006;144(3):165-171. doi:10.7326/0003-4819-144-3-200602070-00004
    1. Kearon C, Ginsberg JS, Douketis J, et al. ; Canadian Pulmonary Embolism Diagnosis Study (CANPEDS) Group . An evaluation of D-dimer in the diagnosis of pulmonary embolism: a randomized trial. Ann Intern Med. 2006;144(11):812-821. doi:10.7326/0003-4819-144-11-200606060-00007
    1. Kline JA, Mitchell AM, Kabrhel C, Richman PB, Courtney DM. Clinical criteria to prevent unnecessary diagnostic testing in emergency department patients with suspected pulmonary embolism. J Thromb Haemost. 2004;2(8):1247-1255. doi:10.1111/j.1538-7836.2004.00790.x
    1. Righini M, Van Es J, Den Exter PL, et al. . Age-adjusted D-dimer cutoff levels to rule out pulmonary embolism: the ADJUST-PE study. JAMA. 2014;311(11):1117-1124. doi:10.1001/jama.2014.2135
    1. van der Hulle T, Cheung WY, Kooij S, et al. ; YEARS study group . Simplified diagnostic management of suspected pulmonary embolism (the YEARS study): a prospective, multicentre, cohort study. Lancet. 2017;390(10091):289-297. doi:10.1016/S0140-6736(17)30885-1
    1. Kearon C, de Wit K, Parpia S, et al. ; PEGeD Study Investigators . Diagnosis of pulmonary embolism with D-dimer adjusted to clinical probability. N Engl J Med. 2019;381(22):2125-2134. doi:10.1056/NEJMoa1909159
    1. Singh B, Mommer SK, Erwin PJ, Mascarenhas SS, Parsaik AK. Pulmonary Embolism Rule-out Criteria (PERC) in pulmonary embolism—revisited: a systematic review and meta-analysis. Emerg Med J. 2013;30(9):701-706. doi:10.1136/emermed-2012-201730
    1. Kline JA, Courtney DM, Kabrhel C, et al. . Prospective multicenter evaluation of the Pulmonary Embolism Rule-out Criteria. J Thromb Haemost. 2008;6(5):772-780. doi:10.1111/j.1538-7836.2008.02944.x
    1. Dronkers CEA, van der Hulle T, Le Gal G, et al. ; Subcommittee on Predictive and Diagnostic Variables in Thrombotic Disease . Towards a tailored diagnostic standard for future diagnostic studies in pulmonary embolism: communication from the SSC of the ISTH. J Thromb Haemost. 2017;15(5):1040-1043. doi:10.1111/jth.13654
    1. Roy P-M, Meyer G, Vielle B, et al. ; EMDEPU Study Group . Appropriateness of diagnostic management and outcomes of suspected pulmonary embolism. Ann Intern Med. 2006;144(3):157-164. doi:10.7326/0003-4819-144-3-200602070-00003
    1. Roy PM, Durieux P, Gillaizeau F, et al. . A computerized handheld decision-support system to improve pulmonary embolism diagnosis: a randomized trial. Ann Intern Med. 2009;151(10):677-686. doi:10.7326/0003-4819-151-10-200911170-00003
    1. Righini M, Le Gal G, Aujesky D, et al. . Diagnosis of pulmonary embolism by multidetector CT alone or combined with venous ultrasonography of the leg: a randomised non-inferiority trial. Lancet. 2008;371(9621):1343-1352. doi:10.1016/S0140-6736(08)60594-2
    1. Penaloza A, Soulié C, Moumneh T, et al. . Pulmonary Embolism Rule-out Criteria (PERC) rule in European patients with low implicit clinical probability (PERCEPIC): a multicentre, prospective, observational study. Lancet Haematol. 2017;4(12):e615-e621. doi:10.1016/S2352-3026(17)30210-7
    1. West J, Goodacre S, Sampson F. The value of clinical features in the diagnosis of acute pulmonary embolism: systematic review and meta-analysis. QJM. 2007;100(12):763-769. doi:10.1093/qjmed/hcm113
    1. Wasson JH, Sox HC, Neff RK, Goldman L. Clinical prediction rules. applications and methodological standards. N Engl J Med. 1985;313(13):793-799. doi:10.1056/NEJM198509263131306
    1. Hosmer DW, Lemeshow S. Applied Logistic Regression. Wiley; 1989.
    1. Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15(4):361-387. doi:10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>;2-4
    1. Fagan TJ. Letter: nomogram for Bayes theorem. N Engl J Med. 1975;293(5):257. doi:10.1056/NEJM197507312930513
    1. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44(3):837-845. doi:10.2307/2531595
    1. Hutchinson BD, Navin P, Marom EM, Truong MT, Bruzzi JF. Overdiagnosis of pulmonary embolism by pulmonary CT angiography. AJR Am J Roentgenol. 2015;205(2):271-277. doi:10.2214/AJR.14.13938
    1. Penaloza A, Verschuren F, Dambrine S, Zech F, Thys F, Roy PM. Performance of the Pulmonary Embolism Rule-out Criteria (the PERC rule) combined with low clinical probability in high prevalence population. Thromb Res. 2012;129(5):e189-e193. doi:10.1016/j.thromres.2012.02.016
    1. Hugli O, Righini M, Le Gal G, et al. . The Pulmonary Embolism Rule-out Criteria (PERC) rule does not safely exclude pulmonary embolism. J Thromb Haemost. 2011;9(2):300-304. doi:10.1111/j.1538-7836.2010.04147.x
    1. Kline JA, Hogg MM, Courtney DM, Miller CD, Jones AE, Smithline HA. D-dimer threshold increase with pretest probability unlikely for pulmonary embolism to decrease unnecessary computerized tomographic pulmonary angiography. J Thromb Haemost. 2012;10(4):572-581. doi:10.1111/j.1538-7836.2012.04647.x
    1. Eddy M, Robert-Ebadi H, Richardson L, et al. . External validation of the YEARS diagnostic algorithm for suspected pulmonary embolism. J Thromb Haemost. 2020. doi:10.1111/jth.15083
    1. Kline JA, Richardson DM, Than MP, Penaloza A, Roy PM. Systematic review and meta-analysis of pregnant patients investigated for suspected pulmonary embolism in the emergency department. Acad Emerg Med. 2014;21(9):949-959. doi:10.1111/acem.12471
    1. Penaloza A, Verschuren F, Meyer G, et al. . Comparison of the unstructured clinician gestalt, the Wells score, and the revised Geneva score to estimate pretest probability for suspected pulmonary embolism. Ann Emerg Med. 2013;62(2):117-124.e2.
    1. Carpenter CR, Raja AS. Arming the bayesian physician to rule out pulmonary embolism: using evidence-based diagnostics to combat overtesting. Acad Emerg Med. 2014;21(9):1036-1038. doi:10.1111/acem.12450

Source: PubMed

3
구독하다