Evidence map›Paper›PMID 31603898›Full record

ArticlePLoS medicine2019

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

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

Erratum issuedAbstract read
In one paragraph

Article in PLoS medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 30 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  5. Review
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  13. Provoked vs minimally provoked vs unprovoked VTE: does it matter?Hematology. American Society of Hematology. Education Program · 2023
    Article
  14. The dos, don'ts, and nuances of thrombophilia testing.Hematology. American Society of Hematology. Education Program · 2023
    Article
  15. Article
  16. Article
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  19. Observational
  20. Incident thrombus location and predicting risk of recurrent venous thromboembolism.Research and practice in thrombosis and haemostasis · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Jasmijn F TimpDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
Sigrid K BraekkanK. G. Jebsen Thrombosis Research and Expertise Center (TREC), Department of Clinical Medicine, UiT-The Arctic University of Norway, Tromsø, Norway.
Willem M LijferingDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
Astrid van Hylckama VliegDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.ORCID 0000-0001-7386-1168
John-Bjarne HansenK. G. Jebsen Thrombosis Research and Expertise Center (TREC), Department of Clinical Medicine, UiT-The Arctic University of Norway, Tromsø, Norway.
Frits R RosendaalDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.ORCID 0000-0003-2558-7496
Saskia le CessieDepartment of Medical Statistics, Leiden University Medical Center, Leiden, the Netherlands.
Suzanne C CannegieterDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.ORCID 0000-0003-4707-2303

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecurrent venous thromboembolism (VTE) is common. Current guidelines suggest that patients with unprovoked VTE should continue anticoagulants unless they have a high bleeding risk, whereas all others can stop. Prediction models may refine this dichotomous distinction, but existing models apply only to patients with unprovoked first thrombosis. We aimed to develop a prediction model for all patients with first VTE, either provoked or unprovoked. METHODS AND

findingsData were used from two population-based cohorts of patients with first VTE from the Netherlands (Multiple Environment and Genetic Assessment of Risk Factors for Venous Thrombosis [MEGA] follow-up study, performed from 1994 to 2009; model derivation; n = 3,750) and from Norway (Tromsø study, performed from 1999 to 2016; model validation; n = 663). Four versions of a VTE prediction model were developed: model A (clinical, laboratory, and genetic variables), model B (clinical variables and fewer laboratory markers), model C (clinical and genetic factors), and model D (clinical variables only). The outcome measure was recurrent VTE. To determine the discriminatory power, Harrell's C-statistic was calculated. A prognostic score was assessed for each patient. Kaplan-Meier plots for the observed recurrence risks were created in quintiles of the prognostic scores. For each patient, the 2-year predicted recurrence risk was calculated. Models C and D were validated in the Tromsø study. During 19,201 person-years of follow-up (median duration 5.7 years) in the MEGA study, 507 recurrences occurred. Model A had the highest predictive capability, with a C-statistic of 0.73 (95% CI 0.71-0.76). The discriminative performance was somewhat lower in the other models, with C-statistics of 0.72 for model B, 0.70 for model C, and 0.69 for model D. Internal validation showed a minimal degree of optimism bias. Models C and D were externally validated, with C-statistics of 0.64 (95% CI 0.62-0.66) and 0.65 (95% CI 0.63-0.66), respectively. According to model C, in 2,592 patients with provoked first events, 367 (15%) patients had a predicted 2-year risk of >10%, whereas in 1,082 patients whose first event was unprovoked, 484 (45%) had a predicted 2-year risk of <10%. A limitation of both cohorts is that laboratory measurements were missing in a substantial proportion of patients, which therefore were imputed.

conclusionsThe prediction model we propose applies to patients with provoked or unprovoked first VTE-except for patients with (a history of) cancer-allows refined risk stratification, and is easily usable. For optimal individualized treatment, a management study in which bleeding risks are also taken into account is necessary.

Indexed as

AdolescentAdultAgedAlgorithmsAnticoagulantsCase-Control StudiesFemaleFollow-Up StudiesHemorrhageHumansKaplan-Meier EstimateMaleMiddle AgedNetherlandsNorwayPolymorphism, Single NucleotideAnticoagulants

Identifiers

PMID31603898
PMCPMC6788686

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.