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

Background Recurrent 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 findings Data 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 (Tromso 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 Tromso 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. Conclusions The 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. Author summaryWhy was this study done? Patients who suffered from a deep vein thrombosis or pulmonary embolism for the first time have an average risk of 3%-5% per year of having a second event. Such a recurrence can be prevented with anticoagulant treatment, but this should be continued indefinitely, which will lead to a substantial risk of bleeding. The risks of both recurrent thrombosis and bleeding differ substantially between individuals. The choice of continuation on the one hand (with a decreased thrombosis risk but an increased bleeding risk) and discontinuation on the other hand (with an increased thrombosis risk but a decreased bleeding risk) is currently difficult to make for both clinicians and patients. Individual differences in risks are hardly taken into account. What did the researchers do and find? Data were used from two population-based cohorts of patients with first venous thrombosis from the Netherlands (Multiple Environment and Genetic Assessment of Risk Factors for Venous Thrombosis [MEGA] study; = 3,750) and from Norway (Tromso study; = 663). Four versions of a venous thromboembolism (VTE) recurrence risk prediction model were developed in the MEGA data, differing in number and type of included predictors, of which two were validated in the Tromso study. During 19,201 person-years of follow-up, 507 recurrences occurred. The predictive capability varied between the models. A substantial proportion of patients with a first venous thrombosis are currently misclassified with respect to duration of anticoagulant treatment. What do these findings mean? The prediction model we propose applies to all patients, allows refined risk stratification, and is easily usable. A limitation of both cohorts is that laboratory measurements were missing in a substantial proportion of patients, which were imputed. For optimal individualized treatment, a management study is necessary in which bleeding risks are also taken into account.