Download PDF
Thromb Haemost 2018; 118(07): 1242-1249
DOI: 10.1055/s-0038-1655743
New Technologies, Diagnostic Tools and Drugs
Georg Thieme Verlag KG Stuttgart · New York

Development and Validation of a Practical Two-Step Prediction Model and Clinical Risk Score for Post-Thrombotic Syndrome

Elham E. Amin
1   Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands
2   Department of Clinical Epidemiology and Medical Technology Assessment, School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
,
Sander M. J. van Kuijk
2   Department of Clinical Epidemiology and Medical Technology Assessment, School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
,
Manuela A. Joore
2   Department of Clinical Epidemiology and Medical Technology Assessment, School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
,
Paolo Prandoni
3   Arianna Foundation on Anticoagulation, Bologna, Italy
,
Hugo ten Cate
1   Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands
4   Department of Biochemistry, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
,
Arina J. ten Cate-Hoek
1   Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands
4   Department of Biochemistry, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
› Author Affiliations Funding None.
Further Information

Publication History

24 January 2018

12 April 2018

Publication Date:
04 June 2018 (online)

    Permissions and Reprints

Abstract

Background Post-thrombotic syndrome (PTS) is a common chronic consequence of deep vein thrombosis that affects the quality of life and is associated with substantial costs. In clinical practice, it is not possible to predict the individual patient risk. We develop and validate a practical two-step prediction tool for PTS in the acute and sub-acute phase of deep vein thrombosis.

Methods Multivariable regression modelling with data from two prospective cohorts in which 479 (derivation) and 1,107 (validation) consecutive patients with objectively confirmed deep vein thrombosis of the leg, from thrombosis outpatient clinic of Maastricht University Medical Centre, the Netherlands (derivation) and Padua University hospital in Italy (validation), were included. PTS was defined as a Villalta score of ≥ 5 at least 6 months after acute thrombosis.

Results Variables in the baseline model in the acute phase were: age, body mass index, sex, varicose veins, history of venous thrombosis, smoking status, provoked thrombosis and thrombus location. For the secondary model, the additional variable was residual vein obstruction. Optimism-corrected area under the receiver operating characteristic curves (AUCs) were 0.71 for the baseline model and 0.60 for the secondary model. Calibration plots showed well-calibrated predictions. External validation of the derived clinical risk scores was successful: AUC, 0.66 (95% confidence interval [CI], 0.63–0.70) and 0.64 (95% CI, 0.60–0.69).

Conclusion Individual risk for PTS in the acute phase of deep vein thrombosis can be predicted based on readily accessible baseline clinical and demographic characteristics. The individual risk in the sub-acute phase can be predicted with limited additional clinical characteristics.

Keywords

post-thrombotic syndrome - clinical risk score - prediction model - deep vein thrombosis - validation

Ethical Approval

For this study, no separate ethical approval was needed or acquired, but data from the clinical care pathway in MUMC+ was used. For data collection in this pathway, approval was obtained by Maastricht University Medical Centre Ethics Committee (reference METC 15–4-256). No informed consent from participants was required.


Supplementary Material

 

  • References

  • 1 Brandjes DP, Büller HR, Heijboer H. , et al. Randomised trial of effect of compression stockings in patients with symptomatic proximal-vein thrombosis. Lancet 1997; 349 (9054): 759-762
    CrossrefPubMedGoogle Scholar
  • 2 Prandoni P, Lensing AW, Cogo A. , et al. The long-term clinical course of acute deep venous thrombosis. Ann Intern Med 1996; 125 (01) 1-7
    CrossrefPubMedGoogle Scholar
  • 3 Kahn SR, Shrier I, Julian JA. , et al. Determinants and time course of the postthrombotic syndrome after acute deep venous thrombosis. Ann Intern Med 2008; 149 (10) 698-707
    CrossrefPubMedGoogle Scholar
  • 4 Guanella R, Ducruet T, Johri M. , et al. Economic burden and cost determinants of deep vein thrombosis during 2 years following diagnosis: a prospective evaluation. J Thromb Haemost 2011; 9 (12) 2397-2405
    CrossrefPubMedGoogle Scholar
  • 5 Prandoni P, Lensing AW, Prins MH. , et al. Below-knee elastic compression stockings to prevent the post-thrombotic syndrome: a randomized, controlled trial. Ann Intern Med 2004; 141 (04) 249-256
    CrossrefPubMedGoogle Scholar
  • 6 van Dongen CJ, Prandoni P, Frulla M, Marchiori A, Prins MH, Hutten BA. Relation between quality of anticoagulant treatment and the development of the postthrombotic syndrome. J Thromb Haemost 2005; 3 (05) 939-942
    CrossrefPubMedGoogle Scholar
  • 7 Chitsike RS, Rodger MA, Kovacs MJ. , et al. Risk of post-thrombotic syndrome after subtherapeutic warfarin anticoagulation for a first unprovoked deep vein thrombosis: results from the REVERSE study. J Thromb Haemost 2012; 10 (10) 2039-2044
    CrossrefPubMedGoogle Scholar
  • 8 Stain M, Schönauer V, Minar E. , et al. The post-thrombotic syndrome: risk factors and impact on the course of thrombotic disease. J Thromb Haemost 2005; 3 (12) 2671-2676
    CrossrefPubMedGoogle Scholar
  • 9 Tick LW, Kramer MH, Rosendaal FR, Faber WR, Doggen CJ. Risk factors for post-thrombotic syndrome in patients with a first deep venous thrombosis. J Thromb Haemost 2008; 6 (12) 2075-2081
    CrossrefPubMedGoogle Scholar
  • 10 Ageno W, Piantanida E, Dentali F. , et al. Body mass index is associated with the development of the post-thrombotic syndrome. Thromb Haemost 2003; 89 (02) 305-309
    Article in Thieme ConnectPubMedGoogle Scholar
  • 11 Ten Cate-Hoek AJ, Ten Cate H, Tordoir J, Hamulyák K, Prins MH. Individually tailored duration of elastic compression therapy in relation to incidence of the postthrombotic syndrome. J Vasc Surg 2010; 52 (01) 132-138
    CrossrefPubMedGoogle Scholar
  • 12 Prandoni P, Frulla M, Sartor D, Concolato A, Girolami A. Vein abnormalities and the post-thrombotic syndrome. J Thromb Haemost 2005; 3 (02) 401-402
    CrossrefPubMedGoogle Scholar
  • 13 Latella J, Desmarais S, Miron MJ. , et al. Relation between D-dimer level, venous valvular reflux and the development of post-thrombotic syndrome after deep vein thrombosis. J Thromb Haemost 2010; 8 (10) 2169-2175
    CrossrefPubMedGoogle Scholar
  • 14 Bouman AC, Smits JJ, Ten Cate H, Ten Cate-Hoek AJ. Markers of coagulation, fibrinolysis and inflammation in relation to post-thrombotic syndrome. J Thromb Haemost 2012; 10 (08) 1532-1538
    CrossrefPubMedGoogle Scholar
  • 15 Rabinovich A, Cohen JM, Cushman M. , et al. Inflammation markers and their trajectories after deep vein thrombosis in relation to risk of post-thrombotic syndrome. J Thromb Haemost 2015; 13 (03) 398-408
    CrossrefPubMedGoogle Scholar
  • 16 Ziegler S, Schillinger M, Maca TH, Minar E. Post-thrombotic syndrome after primary event of deep venous thrombosis 10 to 20 years ago. Thromb Res 2001; 101 (02) 23-33
    CrossrefPubMedGoogle Scholar
  • 17 Villalta S, Bagatella P, Piccioli A, Lensing A, Prins MH, Prandoni P. Assessment of validity and reproducibility of a clinical scale for the post-thrombotic syndrome. Haemostasis 1994;24(158a)
    PubMedGoogle Scholar
  • 18 Kearon C, Kahn SR, Agnelli G, Goldhaber S, Raskob GE, Comerota AJ. Antithrombotic therapy for venous thromboembolic disease: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th Edition). Chest 2008; 133 (6 Suppl): 454S-545S
    CrossrefPubMedGoogle Scholar
  • 19 Ginsberg JS, Hirsh J, Julian J. , et al. Prevention and treatment of postphlebitic syndrome: results of a 3-part study. Arch Intern Med 2001; 161 (17) 2105-2109
    CrossrefPubMedGoogle Scholar
  • 20 Appelen D, van Loo E, Prins MH, Neumann MH, Kolbach DN. Compression therapy for prevention of post-thrombotic syndrome. Cochrane Database Syst Rev 2017; 9: CD004174
    PubMedGoogle Scholar
  • 21 Padberg Jr FT, Johnston MV, Sisto SA. Structured exercise improves calf muscle pump function in chronic venous insufficiency: a randomized trial. J Vasc Surg 2004; 39 (01) 79-87
    CrossrefPubMedGoogle Scholar
  • 22 O'Donnell MJ, McRae S, Kahn SR. , et al. Evaluation of a venous-return assist device to treat severe post-thrombotic syndrome (VENOPTS). A randomized controlled trial. Thromb Haemost 2008; 99 (03) 623-629
    Article in Thieme ConnectPubMedGoogle Scholar
  • 23 Ippolito E, Belcaro G, Dugall M. , et al. Venoruton®: post thrombotic syndrome. Clinical improvement in venous insufficiency (signs and symptoms) with Venoruton®. A five-year, open-registry, efficacy study. Panminerva Med 2011; 53 (03) (Suppl. 01) 13-19
    PubMedGoogle Scholar
  • 24 Kahn SR, Shrier I, Shapiro S. , et al. Six-month exercise training program to treat post-thrombotic syndrome: a randomized controlled two-centre trial. CMAJ 2011; 183 (01) 37-44
    CrossrefPubMedGoogle Scholar
  • 25 Haig Y, Enden T, Grøtta O. , et al; CaVenT Study Group. Post-thrombotic syndrome after catheter-directed thrombolysis for deep vein thrombosis (CaVenT): 5-year follow-up results of an open-label, randomised controlled trial. Lancet Haematol 2016; 3 (02) e64-e71
    CrossrefPubMedGoogle Scholar
  • 26 Vedantham S, Goldhaber SZ, Julian JA. , et al; ATTRACT Trial Investigators. Pharmacomechanical catheter-directed thrombolysis for deep-vein thrombosis. N Engl J Med 2017; 377 (23) 2240-2252
    CrossrefPubMedGoogle Scholar
  • 27 Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 1996; 49 (12) 1373-1379
    CrossrefPubMedGoogle Scholar
  • 28 Kahn SR, Partsch H, Vedantham S, Prandoni P, Kearon C. ; Subcommittee on Control of Anticoagulation of the Scientific and Standardization Committee of the International Society on Thrombosis and Haemostasis. Definition of post-thrombotic syndrome of the leg for use in clinical investigations: a recommendation for standardization. J Thromb Haemost 2009; 7 (05) 879-883
    CrossrefPubMedGoogle Scholar
  • 29 van Kuijk SMJ, Viegtbauer W, Peeters LL, Smits L. Bias in regression coefficient estimates when assumptions for handling missing data are violated: a simulation study. Epidemiol Biostat Public Health 2016; 13 (01) e11598
    PubMedGoogle Scholar
  • 30 Steyerberg EW. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating. New York: Springer-Verlag; 2009
    Google Scholar
  • 31 Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ 2015; 350: g7594
    CrossrefPubMedGoogle Scholar
  • 32 Ten Cate-Hoek AJ, Henke PK, Wakefield TW. The post thrombotic syndrome: ignore it and it will come back to bite you. Blood Rev 2016; 30 (02) 131-137
    CrossrefPubMedGoogle Scholar
  • 33 Kahn SR, Shapiro S, Wells PS. , et al; SOX trial investigators. Compression stockings to prevent post-thrombotic syndrome: a randomised placebo-controlled trial. Lancet 2014; 383 (9920): 880-888
    CrossrefPubMedGoogle Scholar
  • 34 Rabinovich A, Ducruet T, Kahn SR. Development of a clinical prediction model for the postthrombotic syndrome in a prospective cohort of patients with proximal deep vein thrombosis. J Thromb Haemost 2018; 16 (02) 262-270
    CrossrefPubMedGoogle Scholar