
Assessment of risk prediction scores for venous thromboembolism in ambulatory cancer patients with solid tumors receiving chemotherapy: A comparative analysis
Hamsaveni Muthukumar, Wesley Mannirathil Jose, Nikhil Krishna Haridas, Anjali Sajikumar Nair, Keechilat Pavithran
Malignancy Spectrum ›› 2024, Vol. 1 ›› Issue (4) : 332-338.
Assessment of risk prediction scores for venous thromboembolism in ambulatory cancer patients with solid tumors receiving chemotherapy: A comparative analysis
Objective: Cancer patients have a 4–7-fold increased risk of thrombotic complications due to cancer as well as chemotherapy-induced hypercoagulable state. This study compared the different risk assessment models (Khorana, PROTECHT, CONKO, and COMPASS-CAT scores) that help predict venous thromboembolism (VTE) in ambulatory cancer patients. Early identification of high-risk patients would benefit from thromboprophylaxis, thereby improving the mortality and morbidity due to thrombotic events.
Methods: This is a single-center, prospective, cross-sectional study on ambulatory patients with solid malignancy. The study was conducted over six months, from March 2022 to August 2022. Data on VTE predictors were gathered from 230 ambulatory cancer patients undergoing chemotherapy.
Results: Among the 230 patients receiving chemotherapy, 20 were diagnosed with VTE, with the majority of this population being either diagnosed with gynecological cancer or lung cancer, constituting 25% of VTE-diagnosed patients. The Khorana score, with a VTE accuracy of 83.04%, was found to be the highest, followed by the CONKO (80.00%), PROTECHT (69.57%), COMPASS-CAT Ⅱ (54.35%), and COMPASS-CAT Ⅰ (38.26%) scores. The cumulative incidence of VTE among high-risk patients showed that the PROTECHT score had the highest cumulative incidence (CI = 14.28), and the CONKO score had the lowest (CI = 9.40).
Conclusion: The Khorana score was the most accurate, followed by the CONKO, PROTECHT, and COMPASS-CAT Ⅱ scores, while the COMPASS-CAT Ⅰ score was the least accurate. Hence, the Khorana scoring is essential for diagnosing VTE in patients with ambulatory cancer treated with chemotherapy.
venous thromboembolism / VTE predictors / ambulatory cancer patients receiving chemotherapy / risk assessment model
[1] |
Khorana AA, Francis CW, Culakova E, Lyman GH. Risk factors for chemotherapy-associated venous thromboembolism in a prospective observational study. Cancer. 2005;104(12):2822-2829.
CrossRef
Google scholar
|
[2] |
Lyman GH, Eckert L, Wang Y, Wang H, Cohen A. Venous thromboembolism risk in patients with cancer receiving chemotherapy: a real-world analysis. Oncologist. 2013;18(12):1321-1329.
CrossRef
Google scholar
|
[3] |
Stone J, Hangge P, Albadawi H, et al. Deep vein thrombosis: pathogenesis, diagnosis, and medical management. Cardiovasc Diagn Ther. 2017;(suppl 3):S276-S284.
CrossRef
Google scholar
|
[4] |
O’donnell M, Weitz JI. Thromboprophylaxis in surgical patients. Can J Surg. 2003;46(2):129-135.
|
[5] |
Blom JW. Malignancies, prothrombotic mutations, and the risk of venous thrombosis. JAMA. 2005;293(6):715.
CrossRef
Google scholar
|
[6] |
Laryea J, Champagne B. Venous thromboembolism prophylaxis. Clin Colon Rectal Surg. 2013;26(3):153-159.
CrossRef
Google scholar
|
[7] |
Abdol Razak N, Jones G, Bhandari M, Berndt M, Metharom P. Cancer-associated thrombosis: an overview of mechanisms, risk factors, and treatment. Cancers (Basel). 2018;10(10):380.
CrossRef
Google scholar
|
[8] |
Hamza MS, Mousa SA. Cancer-associated thrombosis: risk factors, molecular mechanisms, future management. Clin Appl Thromb Hemost. 2020;26:1076029620954282.
CrossRef
Google scholar
|
[9] |
Key NS, Khorana AA, Kuderer NM, et al. Venous thromboembolism prophylaxis and treatment in patients with cancer: ASCO clinical practice guideline update. J Clin Oncol. 2020;38(5):496-520.
CrossRef
Google scholar
|
[10] |
Gervaso L, Dave H, Khorana AA. Venous and arterial thromboembolism in patients with cancer. JACC CardioOncol. 2021;3(2):173-190.
CrossRef
Google scholar
|
[11] |
Sultan AA, West J, Grainge MJ, et al. Development and validation of risk prediction model for venous thromboembolism in postpartum women: multinational cohort study. BMJ. 2016;355: i6253.
CrossRef
Google scholar
|
[12] |
Xiong W, Zhao Y, Du H, Wang Y, Xu M, Guo X. Optimal authoritative risk assessment score of cancer-associated venous thromboembolism for hospitalized medical patients with lung cancer. Thromb J. 2021;19(1):95.
CrossRef
Google scholar
|
[13] |
van Es N, Di Nisio M, Cesarman G, et al. Comparison of risk prediction scores for venous thromboembolism in cancer patients: a prospective cohort study. Haematologica. 2017;102(9):1494-1501.
CrossRef
Google scholar
|
[14] |
Aleidan FA. The cumulative incidence and risk factors of recurrent venous thromboembolism in the elderly. Vasc Health Risk Manag. 2020;16:437-443.
CrossRef
Google scholar
|
[15] |
Darzi AJ, Repp AB, Spencer FA, et al. Risk-assessment models for VTE and bleeding in hospitalized medical patients: an overview of systematic reviews. Blood Adv. 2020;4(19):4929-4944.
CrossRef
Google scholar
|
[16] |
Mulder FI, Candeloro M, Kamphuisen PW, et al. The Khorana score for prediction of venous thromboembolism in cancer patients: a systematic review and meta-analysis. Haematologica. 2019;104(6):1277-1287.
CrossRef
Google scholar
|
[17] |
Guman NAM, van Geffen RJ, Mulder FI, et al. Evaluation of the Khorana, PROTECHT, and 5-SNP scores for prediction of venous thromboembolism in patients with cancer. J Thromb Haemostasis. 2021;19(12):2974-2983.
CrossRef
Google scholar
|
[18] |
Moik F, Englisch C, Pabinger I, Ay C. Risk assessment models of cancer-associated thrombosis -potentials and perspectives. Thrombosis Update. 2021;5:100075.
CrossRef
Google scholar
|
/
〈 |
|
〉 |