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Risk prediction of recurrent venous thromboembolism: a multiple genetic risk model.

ABSTRACT: A single genetic biomarker is unable to accurately predict the risk for venous thromboembolism (VTE) recurrence. We aimed to: (a) develop a multiple single nucleotide polymorphisms (SNPs) model to predict the risk of VTE recurrence and (b) validate a previously described genetic risk score (GRS) and compare its performance with the model developed in this study. Twenty-two SNPs, including established and putative SNPs associated with VTE risk, were genotyped in the Malmö thrombophilia study cohort (MATS; n?=?1465, follow-up ~?10 years) by using TaqMan PCR. Out of 22-SNPs, 12 had an association with the risk of VTE recurrence and were included for calculating GRSs. The risk of VTE recurrence was calculated by stratifying patients according to number of risk alleles. In 12-SNP GRS, patients with ??7 risk alleles were associated with higher risk of VTE recurrence compared to patients having???6 risk alleles. In a simplified model (8-SNP GRS), the discriminative power of 8-SNP GRS was similar to that of 12-SNP GRS based on post-test probabilities (PP). Furthermore, 8-SNP GRS further improved the risk prediction of VTE recurrence in unprovoked VTE and male patients (PP%?=?15.4 vs 8.3, 17.1 vs 7.2 and 19.0 vs 7.1 for high risk groups vs low risk groups in whole population, males and unprovoked VTE patients respectively). In addition, we also validated previously described 5-SNP GRS in our cohort and found that the 8-SNP GRS performed better than the 5-SNP GRS in terms of higher PP. Our results show that a multiple SNP GRS consisting of 8-SNPs may be an effective model for prediction of VTE recurrence, particularly in unprovoked VTE and male patients.

SUBMITTER: Ahmad A

PROVIDER: S-EPMC6394443 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Risk prediction of recurrent venous thromboembolism: a multiple genetic risk model.

Ahmad Abrar A Sundquist Kristina K Palmér Karolina K Svensson Peter J PJ Sundquist Jan J Memon Ashfaque A AA

Journal of thrombosis and thrombolysis 20190201 2

A single genetic biomarker is unable to accurately predict the risk for venous thromboembolism (VTE) recurrence. We aimed to: (a) develop a multiple single nucleotide polymorphisms (SNPs) model to predict the risk of VTE recurrence and (b) validate a previously described genetic risk score (GRS) and compare its performance with the model developed in this study. Twenty-two SNPs, including established and putative SNPs associated with VTE risk, were genotyped in the Malmö thrombophilia study coho ...[more]

PMID: 30368761

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Project description:ImportanceThe size of the risk of recurrent venous thromboembolism (VTE) after surgery in patients with a history of VTE is not well known.ObjectivesTo estimate the risk of and to identify the factors associated with recurrent VTE in patients undergoing surgery who have a history of VTE.Design, setting, and participantsThis population-based, follow-up cohort study includes patients with VTE who participated in the Multiple Environment and Genetic Assessment (MEGA) study. Original data were collected from March 1999 to April 2010. Data analysis began in June 1999 and ended in April 2010.ExposuresSurgery following a first VTE.Main outcomes and measurementsKaplan-Meier analyses were used to estimate cumulative incidences of recurrent VTE. Cox regression with a time-dependent covariate (surgery) was used to calculate the hazard ratio (HR) for developing recurrent VTE after surgery compared with no surgery.ResultsOverall, 3741 patients (mean [SD] age, 48.4 [12.8] years; 2020 [54.0%] women) with a history of VTE were included in the analysis, amounting to 18 899 person-years, with a median (interquartile range) follow-up of 5.7 (3.0-7.2) years. Of the 3741 patients, 580 (15.5%) underwent surgery and 601 (16.1%) developed a recurrent thrombotic event. The 1-month cumulative incidence of recurrent VTE for all surgery types was 2.1% (95% CI, 1.2%-3.6%), which increased to 3.3% (95% CI, 2.1%-5.1%) at 3 months and 4.6% (95% CI, 3.1%-6.6%) at 6 months. At 6 months, risk of recurrent VTE ranged from 2.3% to 9.3%, depending on surgery type. In addition to surgery type, factor V Leiden mutation (HR, 3.4; 95% CI, 1.6-7.4) and male sex (HR, 2.7; 95% CI, 1.3-5.8) were associated with increased risk of recurrent VTE.Conclusions and relevanceSurgery was associated with an increased risk of recurrent VTE in patients with a history of VTE; risk remained high for up to 6 months after the procedure. This study suggests that high-risk individuals may be identified based on surgery type, sex, and the presence of factor V Leiden mutation. These findings stress the need for revision of the current thromboprophylactic approach to prevent recurrence in these patients.

Project description:ImportanceThe assessment of the risk of venous thromboembolism (VTE) among outpatients with cancer represents an unsolved topic. Current international guidelines recommend primary prophylaxis for patients at intermediate to high risk of VTE, indicated by a Khorana score of 2 or more. A previous prospective study developed the ONKOTEV score, a 4-variable risk assessment model (RAM) consisting of a Khorana score of more than 2, metastatic disease, vascular or lymphatic compression, and previous VTE event.ObjectiveTo validate the ONKOTEV score as a novel RAM to assess the risk of VTE among outpatients with cancer.Design, setting, and participantsONKOTEV-2 is a noninterventional prognostic study conducted in 3 European centers located in Italy, Germany, and the United Kingdom among a prospective cohort of 425 ambulatory patients with a histologically confirmed diagnosis of a solid tumor who were receiving active treatments. The total study duration was 52 months, with an accrual period of 28 months (from May 1, 2015, to September 30, 2017) and an overall follow up-period of 24 months (data were censored September 30, 2019). Statistical analysis was performed in October 2019.ExposuresThe ONKOTEV score was calculated for each patient at baseline by collecting clinical, laboratory, and imaging data from tests performed for routine practice. Each patient was then observed to detect any thromboembolic event throughout the study period.Main outcomes and measuresThe primary outcome of the study was the incidence of VTE, including deep vein thrombosis and pulmonary embolism.ResultsA total of 425 patients (242 women [56.9%]; median age, 61 years [range, 20-92 years]) were included in the validation cohort of the study. The cumulative incidences for the risk of developing VTE at 6 months were 2.6% (95% CI, 0.7%-6.9%), 9.1% (95% CI, 5.8%-13.2%), 32.3% (95% CI, 21.0%-44.1%), and 19.3% (95% CI, 2.5%-48.0%), respectively, among 425 patients with an ONKOTEV score of 0, 1, 2, and greater than 2 (P < .001). The time-dependent area under the curve at 3, 6, and 12 months was 70.1% (95% CI, 62.1%-78.7%), 72.9% (95% CI, 65.6%-79.1%), and 72.2% (95% CI, 65.2%-77.3%), respectively.Conclusions and relevanceThis study suggests that, because the ONKOTEV score has been validated in this independent study population as a novel predictive RAM for cancer-associated thrombosis, it can be adopted into practice and into clinical interventional trials as a decision-making tool for primary prophylaxis.

Project description:BackgroundVenous thromboembolism (VTE) increases the risk of death or adverse outcomes in patients with lung cancer. Therefore, early identification and treatment of high-risk groups of VTE have been the research focus. In this systematic review, the risk assessment tools of VTE in patients with lung cancer were systematically analyzed and evaluated to provide a reference for VTE management.MethodsRelevant studies were retrieved from major English databases (The Cochrane Library, Embase, Web of Science, PubMed, Scopus, Medline) and Chinese databases (China National Knowledge Infrastructure [CNKI] and WanFang Data) until July 2023 and extracted by two researchers. This systematic review was registered at PROSPERO (no. CRD42023409748).ResultsFinally, two prospective cohort studies and four retrospective cohort studies were included from 2019. There was a high risk of bias in all included studies according to the Prediction Model Risk of Bias Assessment tool (PROBAST). In the included studies, Cox and logistic regression were used to construct models. The area under the receiver operating characteristic curve (AUC) of the model ranged from 0.670 to 0.904, and the number of predictors ranged from 4 to 11. The D-dimer index was included in five studies, but significant differences existed in optimal cutoff values from 0.0005 mg/L to 2.06 mg/L. Then, three studies validated the model externally, two studies only validated the model internally, and only one study validated the model using a combination of internal and external validation.ConclusionVTE risk prediction models for patients with lung cancer have received attention for no more than 5 years. The included model shows a good predictive effect and may help identify the risk population of VTE at an early stage. In the future, it is necessary to improve data modeling and statistical analysis methods, develop predictive models with good performance and low risk of bias, and focus on external validation and recalibration of models.

Dataset Information

Risk prediction of recurrent venous thromboembolism: a multiple genetic risk model.

Publications

Risk prediction of recurrent venous thromboembolism: a multiple genetic risk model.

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