Cargando…

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

BACKGROUND: Several models are available to predict recurrent venous thrombosis (VT) in patients with unprovoked first events. OBJECTIVES: To validate these prediction models externally. METHODS: Within the MEGA follow‐up study (n = 3750), we externally validated the Vienna and DASH score. These mod...

Descripción completa

Detalles Bibliográficos
Autores principales: Timp, Jasmijn F., Lijfering, Willem M., Rosendaal, Frits R., le Cessie, Saskia, Cannegieter, Suzanne C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851549/
https://www.ncbi.nlm.nih.gov/pubmed/31188515
http://dx.doi.org/10.1111/jth.14535
_version_ 1783469641459302400
author Timp, Jasmijn F.
Lijfering, Willem M.
Rosendaal, Frits R.
le Cessie, Saskia
Cannegieter, Suzanne C.
author_facet Timp, Jasmijn F.
Lijfering, Willem M.
Rosendaal, Frits R.
le Cessie, Saskia
Cannegieter, Suzanne C.
author_sort Timp, Jasmijn F.
collection PubMed
description BACKGROUND: Several models are available to predict recurrent venous thrombosis (VT) in patients with unprovoked first events. OBJECTIVES: To validate these prediction models externally. METHODS: Within the MEGA follow‐up study (n = 3750), we externally validated the Vienna and DASH score. These models were validated (a) by using the original study's criteria for patients with unprovoked VT and (b) by using our own criteria for unprovoked VT. In addition, absolute recurrence risks based on individual VT risk factors were calculated. RESULTS: The recurrence rate was 5.2 (95% CI, 4.6‐5.9) per 100 patient‐years in those who had a first unprovoked VT according to our definition. For the Vienna model it was 3.4 per 100 patient‐years and for DASH 3.8 per 100 patient‐years. The C‐statistic was 0.62 for Vienna and 0.65 for DASH. The C‐statistic declined to 0.58 for both Vienna and DASH when we used our own definition of “unprovoked VT.” Within the provoked group a strong gradient in risk was found dependent on the presence of traditional risk factors or biomarkers in a patient. CONCLUSIONS: The ability to distinguish patients’ recurrence risks is lower than proposed in the original prediction model studies and dependent on the definition that is used for an unprovoked first event. Furthermore, our results suggest that a more‐refined risk estimation is possible, also in patients with a provoked first event, who are currently all classified as low risk.
format Online
Article
Text
id pubmed-6851549
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-68515492019-11-18 Risk prediction of recurrent venous thrombosis; where are we now and what can we add? Timp, Jasmijn F. Lijfering, Willem M. Rosendaal, Frits R. le Cessie, Saskia Cannegieter, Suzanne C. J Thromb Haemost THROMBOSIS BACKGROUND: Several models are available to predict recurrent venous thrombosis (VT) in patients with unprovoked first events. OBJECTIVES: To validate these prediction models externally. METHODS: Within the MEGA follow‐up study (n = 3750), we externally validated the Vienna and DASH score. These models were validated (a) by using the original study's criteria for patients with unprovoked VT and (b) by using our own criteria for unprovoked VT. In addition, absolute recurrence risks based on individual VT risk factors were calculated. RESULTS: The recurrence rate was 5.2 (95% CI, 4.6‐5.9) per 100 patient‐years in those who had a first unprovoked VT according to our definition. For the Vienna model it was 3.4 per 100 patient‐years and for DASH 3.8 per 100 patient‐years. The C‐statistic was 0.62 for Vienna and 0.65 for DASH. The C‐statistic declined to 0.58 for both Vienna and DASH when we used our own definition of “unprovoked VT.” Within the provoked group a strong gradient in risk was found dependent on the presence of traditional risk factors or biomarkers in a patient. CONCLUSIONS: The ability to distinguish patients’ recurrence risks is lower than proposed in the original prediction model studies and dependent on the definition that is used for an unprovoked first event. Furthermore, our results suggest that a more‐refined risk estimation is possible, also in patients with a provoked first event, who are currently all classified as low risk. John Wiley and Sons Inc. 2019-07-04 2019-09 /pmc/articles/PMC6851549/ /pubmed/31188515 http://dx.doi.org/10.1111/jth.14535 Text en © 2019 The Authors. Journal of Thrombosis and Haemostasis published by Wiley Periodicals, Inc. on behalf of International Society on Thrombosis and Haemostasis This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle THROMBOSIS
Timp, Jasmijn F.
Lijfering, Willem M.
Rosendaal, Frits R.
le Cessie, Saskia
Cannegieter, Suzanne C.
Risk prediction of recurrent venous thrombosis; where are we now and what can we add?
title Risk prediction of recurrent venous thrombosis; where are we now and what can we add?
title_full Risk prediction of recurrent venous thrombosis; where are we now and what can we add?
title_fullStr Risk prediction of recurrent venous thrombosis; where are we now and what can we add?
title_full_unstemmed Risk prediction of recurrent venous thrombosis; where are we now and what can we add?
title_short Risk prediction of recurrent venous thrombosis; where are we now and what can we add?
title_sort risk prediction of recurrent venous thrombosis; where are we now and what can we add?
topic THROMBOSIS
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851549/
https://www.ncbi.nlm.nih.gov/pubmed/31188515
http://dx.doi.org/10.1111/jth.14535
work_keys_str_mv AT timpjasmijnf riskpredictionofrecurrentvenousthrombosiswherearewenowandwhatcanweadd
AT lijferingwillemm riskpredictionofrecurrentvenousthrombosiswherearewenowandwhatcanweadd
AT rosendaalfritsr riskpredictionofrecurrentvenousthrombosiswherearewenowandwhatcanweadd
AT lecessiesaskia riskpredictionofrecurrentvenousthrombosiswherearewenowandwhatcanweadd
AT cannegietersuzannec riskpredictionofrecurrentvenousthrombosiswherearewenowandwhatcanweadd