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Thrombosis Rates and Genetic Thrombophilia Risk Among Patients With Advanced Germ Cell Tumors Treated With Chemotherapy.
Clinical Genitourinary Cancer 2024 March 29
INTRODUCTION: Men with advanced germ cell tumors (GCT) treated with chemotherapy are at high risk of venous thromboembolism (VTE). Predictors of VTE may identify patients who would benefit from prophylactic anticoagulation.
PATIENTS AND METHODS: Men with advanced GCT (Stage IS, II, III) treated with chemotherapy were identified at 2 centers. High genomic risk was defined from a 5 single nucleotide polymorphism (SNP) germline panel. Logistic regression was used to evaluate the impact of genomic risk on VTE within 6 months of chemotherapy initiation. Orthogonal Projection to Latent Structures Discriminant Analysis (OPLS-DA) was used to build models to predict VTE based on clinical variables and an 86 SNP panel.
RESULTS: This 123-patient cohort experienced a VTE rate of 26% with an incidence of high genomic risk of 21%. Men with high genomic risk did not have a significantly higher VTE rate (31%, 8/26) than men with low genomic risk (25%, 24/97), unadjusted OR 1.4 (95% CI 0.5-3.5, P = .54). Incorporation of clinical variables (Khorana score, N3 status and elevated LDH) resulted in adjusted OR 2.1 (95% CI 0.7-6.5, P = .18). A combined model using clinical variables and 86 SNPs performed similarly (AUC 0.77) compared to clinical variables alone (AUC 0.72).
CONCLUSIONS: A previously established 5-SNP panel was not associated with VTE among patients with GCT receiving chemotherapy. However, multivariable models based on clinical variables alone warrant further validation to inform prophylactic anticoagulation strategies.
PATIENTS AND METHODS: Men with advanced GCT (Stage IS, II, III) treated with chemotherapy were identified at 2 centers. High genomic risk was defined from a 5 single nucleotide polymorphism (SNP) germline panel. Logistic regression was used to evaluate the impact of genomic risk on VTE within 6 months of chemotherapy initiation. Orthogonal Projection to Latent Structures Discriminant Analysis (OPLS-DA) was used to build models to predict VTE based on clinical variables and an 86 SNP panel.
RESULTS: This 123-patient cohort experienced a VTE rate of 26% with an incidence of high genomic risk of 21%. Men with high genomic risk did not have a significantly higher VTE rate (31%, 8/26) than men with low genomic risk (25%, 24/97), unadjusted OR 1.4 (95% CI 0.5-3.5, P = .54). Incorporation of clinical variables (Khorana score, N3 status and elevated LDH) resulted in adjusted OR 2.1 (95% CI 0.7-6.5, P = .18). A combined model using clinical variables and 86 SNPs performed similarly (AUC 0.77) compared to clinical variables alone (AUC 0.72).
CONCLUSIONS: A previously established 5-SNP panel was not associated with VTE among patients with GCT receiving chemotherapy. However, multivariable models based on clinical variables alone warrant further validation to inform prophylactic anticoagulation strategies.
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