A Digital Twin Strategy Combined with a Monte Carlo Simulation Framework to Predict Outcomes in Patients with Unusual-Site Venous Thrombosis Treated with Direct Oral Anticoagulants Versus Vitamin K Antagonists Using Data from Real-World Populations

<b>Background/Objectives:</b> Unusual-site venous thrombosis (USVT) lacks robust evidence guiding anticoagulant selection between vitamin K antagonists (VKAs) and direct oral anticoagulants (DOACs). This study aimed to evaluate recanalization, recurrence, and major bleeding outcomes in real-world USVT patients and to replicate these findings through a validated digital twin model with Monte Carlo simulation. <b>Methods:</b> We conducted a retrospective study of 90 USVT patients (72% VKAs, 28% DOACs). A conditional generative adversarial network was used to generate digital twins matched on age, sex, thrombosis site, and malignancy. Logistic regression was applied to estimate treatment-specific outcome probabilities for recanalization, recurrence, and major bleeding. A nested stochastic simulation framework simulated 500 iterations across clinical scenarios, including increased DOAC use, cancer prevalence, cerebral vein thrombosis proportion, and optimized VKA control. <b>Results:</b> The mean age was 67.5 years, and 54.4% were female. 61.1% of splanchnic vein thrombosis, 36.7% of upper extremity deep vein thrombosis, and 2.2% of cerebral vein thrombosis were included. In the real cohort, complete recanalization occurred in 40.0% of patients with DOACs and 36.0% with VKAs. Recurrence was 8.0% with DOACs and 7.7% with VKAs, and major bleeding occurred in 8.0% and 10.8% of cases, respectively. All-cause mortality was 20% in DOAC-treated patients and 60% in those receiving VKAs. Digital Twin-based predictions replicated these results (recanalization 40.3% versus 38.0%; recurrence 10.9% versus 8.6%; bleeding 7.6% versus 9.1%). Simulated scenarios preserved the directionality effect, with the most significant differences observed in high-cerebral vein thrombosis and cancer-enriched patients. <b>Conclusions:</b> DOACs showed comparable efficacy and slightly lower bleeding risk than VKAs in USVT. Digital twin and Monte Carlo modeling provided robust, reproducible simulations of treatment effects under varying clinical conditions. Separating empirical and simulation-based findings, the digital twin supported the internal consistency of real-world observations and demonstrated the potential of in silico modeling as a complementary tool in rare thrombotic diseases.

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Journal
Clinics and Practice
Published
2025-12-17
DOI
https://doi.org/10.3390/clinpract15120237
Primary Topic
Venous Thromboembolism Diagnosis and Management
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article
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article

A Digital Twin Strategy Combined with a Monte Carlo Simulation Framework to Predict Outcomes in Patients with Unusual-Site Venous Thrombosis Treated with Direct Oral Anticoagulants Versus Vitamin K Antagonists Using Data from Real-World Populations

Anabel Franco‐Moreno, A. Rivas, Paz Arranz-García, Luis Escobar-Curbelo et al.
Clinics and Practice
Venous Thromboembolism Diagnosis and Management
article

A Digital Twin Strategy Combined with a Monte Carlo Simulation Framework to Predict Outcomes in Patients with Unusual-Site Venous Thrombosis Treated with Direct Oral Anticoagulants Versus Vitamin K Antagonists Using Data from Real-World Populations

Anabel Franco‐Moreno, A. Rivas, Paz Arranz-García, Luis Escobar-Curbelo, Cristina de Ancos Aracil, Miguel Ángel Casado-Suela, Juan Torres-Macho, Ana Martínez de la Casa-Muñoz, Ana Bustamante- Fermosel
article en

Abstract

<b>Background/Objectives:</b> Unusual-site venous thrombosis (USVT) lacks robust evidence guiding anticoagulant selection between vitamin K antagonists (VKAs) and direct oral anticoagulants (DOACs). This study aimed to evaluate recanalization, recurrence, and major bleeding outcomes in real-world USVT patients and to replicate these findings through a validated digital twin model with Monte Carlo simulation. <b>Methods:</b> We conducted a retrospective study of 90 USVT patients (72% VKAs, 28% DOACs). A conditional generative adversarial network was used to generate digital twins matched on age, sex, thrombosis site, and malignancy. Logistic regression was applied to estimate treatment-specific outcome probabilities for recanalization, recurrence, and major bleeding. A nested stochastic simulation framework simulated 500 iterations across clinical scenarios, including increased DOAC use, cancer prevalence, cerebral vein thrombosis proportion, and optimized VKA control. <b>Results:</b> The mean age was 67.5 years, and 54.4% were female. 61.1% of splanchnic vein thrombosis, 36.7% of upper extremity deep vein thrombosis, and 2.2% of cerebral vein thrombosis were included. In the real cohort, complete recanalization occurred in 40.0% of patients with DOACs and 36.0% with VKAs. Recurrence was 8.0% with DOACs and 7.7% with VKAs, and major bleeding occurred in 8.0% and 10.8% of cases, respectively. All-cause mortality was 20% in DOAC-treated patients and 60% in those receiving VKAs. Digital Twin-based predictions replicated these results (recanalization 40.3% versus 38.0%; recurrence 10.9% versus 8.6%; bleeding 7.6% versus 9.1%). Simulated scenarios preserved the directionality effect, with the most significant differences observed in high-cerebral vein thrombosis and cancer-enriched patients. <b>Conclusions:</b> DOACs showed comparable efficacy and slightly lower bleeding risk than VKAs in USVT. Digital twin and Monte Carlo modeling provided robust, reproducible simulations of treatment effects under varying clinical conditions. Separating empirical and simulation-based findings, the digital twin supported the internal consistency of real-world observations and demonstrated the potential of in silico modeling as a complementary tool in rare thrombotic diseases.

Clinics and PracticeVol. 15(12)
Universidad Complutense de Madrid (ES), Hospital General Universitario Gregorio Marañón (ES), Artificial Intelligence Research Institute (ES), Hospital Universitario de Fuenlabrada (ES), Hospital Universitario Infanta Leonor (ES)
Openalex Percentile: Top 38%
Venous Thromboembolism Diagnosis and Management
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