Current risk assessment models to predict the risk of recurrent venous thromboembolism (VTE) in an individual patient (i.e Vienna Pedicitive Model, DASH score) include clinical and biochemical parameters and have showed discrimination values ranging from 0.64 to 0.68. Genetic variants associated to thrombophilia have showed to play a relevant role in predicting primary VTE. Combination of those genetic variables together with clinical parameters may improve the predictive capacity of current models for predicting recurrent VTE.


To analyze the predictive capacity of a new clinic-genetic score for predicting recurrence of VTE, Thrombo inCode-Recurrent (TiC-Reccurent).


A population of 55 patients with a first VTE and none or one or more recurrent VTE (21 males, 34 females; 47.8±14.7 years old) and 39 controls with only the first VTE event (13 males, 26 females; 40.2±13.2 years old) and the same follow-up was used.

A regression model was constructed including clinical variants (age, gender, diabetes status, pregnancy status, contraceptive hormonal therapy, smoker status and family history of VTE) and genetic variants (F5 rs6025/rs118203906/rs118203905, F2 rs1799963, F12 rs1801020, F13 rs5985, SERPINC1 rs121909548, and SERPINA10rs2232698 plus the A1 blood group (rs8176719, rs7853989, rs8176743, rs8176750).

The predictive capacity was assessed by calculating the c-statistic (AUC-ROC); sensitivity, specificity Positive and Negative Likehoood ratios and odds ratio of a positive test result.

Informed consent was obtained and the study was approved by the Institution Ethics Committee. This study complies with the guiding principles for experimental procedures found in the Declaration of Helsinkiof the World Medical Association.


In an univariate analysis, none of the clinic or genetic variables showed a significant difference between the patient with or without recurrences. TiC-Recurrent score showed a predictive capacity for recurrent VTE measures as AUC-ROC: 0.738, p<0,0001. For TiC-Recurrent the clinical sensitivity was 81.82 and the specificity was 33.33. The predictive capacity measures as LR+, LR- were 1.23 and 0.55, respectively. The odds ratio for TiC-recurrent was 2.7.


TIC-Recurrent score showed a good predictive capacity to identify subject at high risk of suffering a recurrence of VTE. Although a direct comparison to current scores for predicting the risk for a recurrence of VTE was not possible in the present study if the observed predictive capability for TiC-recurrent is confirmed it will improve the capacity of current scores. Our study suggests that the use of a clinical-genetic algorithm could be an aid in the treatment of patient with a first VTE and contribute to the prevention of VTE recurrences.


No relevant conflicts of interest to declare.

Author notes


Asterisk with author names denotes non-ASH members.

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