Integrating Genotype With Clinical Indicators Improves Venous Thromboembolism Risk Prediction in Cancer Patients: A Retrospective Cohort Study From Xinjiang
Abstract
Objective To develop and validate a venous thromboembolism (VTE) risk prediction model integrating genetic polymorphisms and routine clinical indicators in a cohort of cancer patients from Xinjiang, China. Methods A retrospective study was conducted on 1135 cancer patients (179 with VTE, 956 without) at Affiliated Cancer Hospital of Xinjiang Medical University between March 2024 and May 2025. Six gene polymorphisms ( SERPINE1 , SERPINC1 , PROC , MTHFR , F5 , F2 ) and clinical predictors were assessed. Chi-square tests and logistic regression identified independent predictors for model construction. Model performance was evaluated using ROC analysis, and three clinically optimized cut-off values were defined. Results The SERPINE1 4G allele was identified as a strong genetic risk factor for VTE (4G/4G genotype: OR=2.330, 95%CI: 1.378-3.942; 4G/5G genotype: OR=2.399, 95%CI: 1.411-4.078). No significant associations were found for the other five genes. Age (OR=1.022, 95%CI: 1.008-1.037), D-dimer level (OR=1.288, 95%CI: 1.186-1.399), and hemoglobin level (OR=0.987, 95%CI: 0.979-0.995) were independent clinical predictors ( P <0.01). The combined model achieved an area under the ROC curve (AUC) of 0.769 (95%CI: 0.731-0.807). Three optimized cut-off values were derived for different clinical contexts: high-sensitivity (90.5%), balanced (Youden index 0.434), and high-specificity (90.1%). Conclusion The SERPINE1 4G allele independently predicts VTE risk in this cohort of cancer patients from Xinjiang. A prediction model integrating this genetic marker with age, D-dimer, and hemoglobin demonstrates good discriminatory performance. The three derived cut-off values may facilitate risk-stratified thromboprophylaxis in clinical practice; however, these findings are based on a retrospective, single-center cohort and internally validated only by ROC analysis.
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BibTeX
@article{guo2026integrating,
title = {{Integrating Genotype With Clinical Indicators Improves Venous Thromboembolism Risk Prediction in Cancer Patients: A Retrospective Cohort Study From Xinjiang}},
author = {Fan Guo and Yiliminuer Keremu and Gang Zhao and Huiting Hu and Yufei Wu and Xiaolu Yu and Chongxiao Hao and Weina Kong and Xiumin Ma},
journal = {Clinical and Applied Thrombosis/Hemostasis},
year = {2026},
month = oct,
doi = {10.1177/10760296261503703},
url = {https://doi.org/10.1177/10760296261503703},
note = {CC BY},
}
RIS
TY - JOUR
TI - Integrating Genotype With Clinical Indicators Improves Venous Thromboembolism Risk Prediction in Cancer Patients: A Retrospective Cohort Study From Xinjiang
AU - Fan Guo
AU - Yiliminuer Keremu
AU - Gang Zhao
AU - Huiting Hu
AU - Yufei Wu
AU - Xiaolu Yu
AU - Chongxiao Hao
AU - Weina Kong
AU - Xiumin Ma
PY - 2026
DA - 2026/10/01
JO - Clinical and Applied Thrombosis/Hemostasis
DO - 10.1177/10760296261503703
UR - https://doi.org/10.1177/10760296261503703
AB - Objective To develop and validate a venous thromboembolism (VTE) risk prediction model integrating genetic polymorphisms and routine clinical indicators in a cohort of cancer patients from Xinjiang, China. Methods A retrospective study was conducted on 1135 cancer patients (179 with VTE, 956 without) at Affiliated Cancer Hospital of Xinjiang Medical University between March 2024 and May 2025. Six gene polymorphisms ( SERPINE1 , SERPINC1 , PROC , MTHFR , F5 , F2 ) and clinical predictors were assessed. Chi-square tests and logistic regression identified independent predictors for model construction. Model performance was evaluated using ROC analysis, and three clinically optimized cut-off values were defined. Results The SERPINE1 4G allele was identified as a strong genetic risk factor for VTE (4G/4G genotype: OR=2.330, 95%CI: 1.378-3.942; 4G/5G genotype: OR=2.399, 95%CI: 1.411-4.078). No significant associations were found for the other five genes. Age (OR=1.022, 95%CI: 1.008-1.037), D-dimer level (OR=1.288, 95%CI: 1.186-1.399), and hemoglobin level (OR=0.987, 95%CI: 0.979-0.995) were independent clinical predictors ( P <0.01). The combined model achieved an area under the ROC curve (AUC) of 0.769 (95%CI: 0.731-0.807). Three optimized cut-off values were derived for different clinical contexts: high-sensitivity (90.5%), balanced (Youden index 0.434), and high-specificity (90.1%). Conclusion The SERPINE1 4G allele independently predicts VTE risk in this cohort of cancer patients from Xinjiang. A prediction model integrating this genetic marker with age, D-dimer, and hemoglobin demonstrates good discriminatory performance. The three derived cut-off values may facilitate risk-stratified thromboprophylaxis in clinical practice; however, these findings are based on a retrospective, single-center cohort and internally validated only by ROC analysis.
SN - 1938-2723
SN - 1076-0296
ER -