Literature DB >> 25660555

Risk of recurrence after a first unprovoked venous thromboembolism: external validation of the Vienna Prediction Model with pooled individual patient data.

M Marcucci1, A Iorio, J D Douketis, S Eichinger, A Tosetto, T Baglin, M Cushman, G Palareti, D Poli, R C Tait, P A Kyrle.   

Abstract

BACKGROUND: In order to stratify patients with a first unprovoked venous thromboembolism (VTE) according to their recurrence risk and to identify those who would actually benefit from indefinite anticoagulation, three prediction models have been developed so far; none of them has been yet externally validated.
OBJECTIVE: To externally validate the Vienna Prediction Model (VPM), a prediction guide for estimating the recurrence risk after a first unprovoked VTE developed through Cox modeling and including sex, D-dimer and index VTE site as predictors. PATIENTS/
METHODS: Nine hundred and four patients pooled from five prospective studies evaluating the prognostic value of D-dimer for VTE recurrence served as the validation cohort. The validity of the VPM in stratifying patients according to their relative recurrence risk (discrimination) and in predicting the absolute recurrence risk (calibration) was tested with survival analysis methods.
RESULTS: The ability of the VPM to distinguish patients' risk for recurrent VTE in the validation cohort was at least as good as in the original cohort, with a calibration slope of 1.17 (95% confidence interval 0.71-1.64; P = 0.456 for the hypothesis of a significant difference from 1), and a c-statistic of 0.626 (vs. 0.651 in the original derivation cohort). The VPM absolute predictions in terms of cumulative rates tended to underestimate the observed recurrence rates at 12 months.
CONCLUSIONS: By using a pooled individual patient database as a validation cohort, we confirmed the ability of the VPM to stratify patients with a first unprovoked VTE according to their risk of recurrence.
© 2015 International Society on Thrombosis and Haemostasis.

Entities:  

Keywords:  decision support technique; pulmonary embolism; recurrence; venous thromboembolism; venous thrombosis

Mesh:

Year:  2015        PMID: 25660555     DOI: 10.1111/jth.12871

Source DB:  PubMed          Journal:  J Thromb Haemost        ISSN: 1538-7836            Impact factor:   5.824


  8 in total

Review 1.  Assessing the risk of recurrent venous thromboembolism--a practical approach.

Authors:  Jennifer Fahrni; Marc Husmann; Silvia B Gretener; Hong H Keo
Journal:  Vasc Health Risk Manag       Date:  2015-08-17

Review 2.  Systematic review of prognostic models for recurrent venous thromboembolism (VTE) post-treatment of first unprovoked VTE.

Authors:  Joie Ensor; Richard D Riley; David Moore; Kym I E Snell; Susan Bayliss; David Fitzmaurice
Journal:  BMJ Open       Date:  2016-05-06       Impact factor: 2.692

3.  Effect of tailoring anticoagulant treatment duration by applying a recurrence risk prediction model in patients with venous thromboembolism compared to usual care: A randomized controlled trial.

Authors:  Geert-Jan Geersing; Janneke M T Hendriksen; Nicolaas P A Zuithoff; Kit C Roes; Ruud Oudega; Toshihiko Takada; Roger E G Schutgens; Karel G M Moons
Journal:  PLoS Med       Date:  2020-06-26       Impact factor: 11.069

4.  Data Rich, Information Poor: Can We Use Electronic Health Records to Create a Learning Healthcare System for Pharmaceuticals?

Authors:  Hans-Georg Eichler; Brigitte Bloechl-Daum; Karl Broich; Paul Alexander Kyrle; Jillian Oderkirk; Guido Rasi; Rui Santos Ivo; Ad Schuurman; Thomas Senderovitz; Luke Slawomirski; Martin Wenzl; Valerie Paris
Journal:  Clin Pharmacol Ther       Date:  2018-10-14       Impact factor: 6.875

5.  Bootstrapping complex time-to-event data without individual patient data, with a view toward time-dependent exposures.

Authors:  Tobias Bluhmki; Hein Putter; Arthur Allignol; Jan Beyersmann
Journal:  Stat Med       Date:  2019-06-04       Impact factor: 2.373

6.  Prediction of recurrent venous thrombosis in all patients with a first venous thrombotic event: The Leiden Thrombosis Recurrence Risk Prediction model (L-TRRiP).

Authors:  Jasmijn F Timp; Sigrid K Braekkan; Willem M Lijfering; Astrid van Hylckama Vlieg; John-Bjarne Hansen; Frits R Rosendaal; Saskia le Cessie; Suzanne C Cannegieter
Journal:  PLoS Med       Date:  2019-10-11       Impact factor: 11.069

7.  Risk prediction of recurrent venous thrombosis; where are we now and what can we add?

Authors:  Jasmijn F Timp; Willem M Lijfering; Frits R Rosendaal; Saskia le Cessie; Suzanne C Cannegieter
Journal:  J Thromb Haemost       Date:  2019-07-04       Impact factor: 5.824

8.  Risk factors of thrombotic recurrence and major bleeding in patients with intermediate-risk for recurrence of venous thromboembolism.

Authors:  Yugo Yamashita; Hidewo Amano; Takeshi Morimoto; Kazushige Kadota; Reo Hata; Kazuki Matsushita; Kohei Osakada; Arata Sano; Toru Takase; Seiichi Hiramori; Kitae Kim; Maki Oi; Masaharu Akao; Yohei Kobayashi; Mamoru Toyofuku; Moriaki Inoko; Tomohisa Tada; Po-Min Chen; Koichiro Murata; Yoshiaki Tsuyuki; Yuji Nishimoto; Tomoki Sasa; Jiro Sakamoto; Minako Kinoshita; Kiyonori Togi; Hiroshi Mabuchi; Kensuke Takabayashi; Takao Kato; Koh Ono; Takeshi Kimura
Journal:  J Thromb Thrombolysis       Date:  2021-07-06       Impact factor: 2.300

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.