Prof Gerotziafas is a specialist in thrombosis and hemostasis with a particular interest in cancer-associated thrombosis (CAT) and anti-thrombotic treatments in cancer patients. His group specializes in risk assessment model development, especially for CAT, and develops experimental models to study the interactions of cancer cells with the microenvironment and angiogenesis.
During the 10th ICTHIC, Prof. Gerotziafas gave an overview of risk assessment models for venous thromboembolism (VTE) in ambulatory patients with cancer. We had the opportunity to talk with him about this matter.
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VTE in cancer patients and risk factors
VTE is a major problem in patients with cancer; every year, 0.5% of cancer patients will experience thrombosis compared with a 0.1% incidence rate in the general population [1]. CAT causes approximately 544,000 deaths every year in Europe and is the second cause of mortality in cancer patients [2].
The majority of VTE events occur in not hospitalized patients, highlighting the importance of VTE risk prediction and awareness in cancer patients [3].
Despite its high incidence, CAT is underestimated in the oncologist community. A recent survey among oncology clinicians assessed the current practice patterns surrounding VTE. The survey results indicate that almost 30% of the oncologists rarely discuss VTE risk with their patients, and almost 60% of them never use validated VTE risk assessment scores in clinical practice. In addition, 67% reported no familiarity with the International Society on Thrombosis and Haemostasis (ISTH) recommendations [4].
The recent recommendations published by the American Society of Clinical Oncology (ASCO) urge oncologists and the oncology team members to educate patients regarding the risk of VTE, which can vary depending on patient-related, treatment-related and cancer-related factors [5].
Factors that can modify VTE risk are the type and stage of cancer, the time since the diagnosis, the type of anticancer therapies and supportive treatments. However, patient’s comorbidities, personal history of VTE or presence of thrombophilia and genetic polymorphisms can also modulate the risk of developing VTE. Risk assessment models have been developed to help evaluate VTE risk and identify patients eligible for pharmacological thromboprophylaxis [6].
The Khorana risk score
The Khorana risk score is the first risk assessment model proposed in 2008 [7]. Since then, it has been used and validated in several studies and two trials on the use of direct oral anticoagulants (DOACs) in outpatients. It is the only score recommended by the current guidelines to identify risk for CAT in patients initiating systemic therapy [8-10].
“One of the pros of the Khorana score is its simplicity; it is composed of predictors that are easily accessible during the discussion with the patient,” says Prof Gerotziafas.
The score relies on five simple clinical and laboratory variables: type of cancer, prechemotherapy platelet count (≥350 × 109/L), hemoglobin level (<10 mg/mL) or use of red cell growth factors, prechemotherapy leukocyte count (>11 × 109/L) and BMI (≥35 kg/m2). Patients with a score ≥3 are classified as at a high-risk level, although recently, it has been proposed to set the cutoff at 2 for both outpatients and hospitalized patients with cancer [8].
“The Khorana score simplicity is also its limitation,” says Prof. Gerotziafas.
The Khorana score performance varies across tumor types, “it has limited accuracy in the evaluation of VTE risk in patients with cancer of moderate risks, such as lung, breast or colon cancers,” continued Prof. Gerotziafas. “In addition, the patient parameters are absent. Patients with cancer can present other risk factors for VTE that can contribute. The stage, the time of diagnosis, and the anticancer treatment are also elements that have an important role in the overall risk calculation.”
New-generation scores
Starting from the idea that the cancer type is a determinant predictor of VTE risk, new scores were developed, such as Vienna, PROTECHT, ONKOTEV and Tic-Onco, Pabinger et al., IMPEDE, and SAVED, which include biomarkers specific for hypercoagulability [8].
These scores stratify cancer in very high-risk tumors and high-risk tumors, the first one comprising pancreatic and gastric cancer, and the second one including lung, gynecological, lymphoma, bladder and testicular cancer [6].
Pabinger et al., IMPEDE and SAVED are the only scores that have been validated to date, and the last two are specific for multiple myeloma [8].
The score developed by Pabinger et al. utilizes only two variables: the type of cancer and a continuous scale of D-dimer levels. The model is available for clinical use as a printed nomogram and as an online prediction tool. The model showed an improvement of 30% compared with the Khorana score, and it can be used for cancers that are excluded by the Khorana score, such as lung, breast and colon cancer [11].
Third-generation scores (COMPASS-CAT and ThroLy scores)
Recently, a new class of risk scores was developed, which represents a new strategy for evaluating VTE in outpatients on chemotherapy. They combine predictors related to the cancer characteristics (stage and diagnosis), the type of the treatment, and the patient’s characteristics. They can be used for frequent types of cancers, such as breast, lung and colon or specific hematological malignancies.
The COMPASS-CAT score was validated in outpatients with breast, ovarian, lung and colorectal cancer who receive chemotherapy.
The ThroLy score is specific for lymphoma. It is composed of predictors related to the malignancy and the patients’ intrinsic risk factors for VTE, and it is applicable in outpatients after chemotherapy initiation [6].
The brain tumor gap
Despite the number of risk scores available and the fact that up to 20% of patients with brain tumors develop VTE, no risk model today was validated for brain tumors [12].
Clinical risk factors for VTE in this setting are glioblastoma subtype, paresis and surgery. Recently some biomarkers specific for brain cancer were identified, and two of them are in evaluation: mutations in the IDH1 gene and the glycoprotein podoplanin. Patients with an IDH1 mutation have a lower risk of developing VTE than those with IDH1 wild-type status. The expression of the glycoprotein podoplanin in brain tumors is associated with a high risk of VTE and intra-tumoral thrombi [12].
Clinically, brain tumor management is particularly challenging because anticoagulation therapy is associated with an increased risk of intracranial hemorrhage [12].
Incorporating these biomarkers in a tool for risk prediction could help risk assessment of CAT in patients with brain tumors.
How can we choose the best model?
“First of all, it is important to know that we have the tool to evaluate the risk, and some of them are validated. So, the point is not to choose the best tool, but the one that has been validated.” We also need to consider differences between the risk scores; some are predictive only for certain tumors or can be applied in a specific moment of the patient’s journey. “The Khorana score can be applied before the chemotherapy, while the COMPASS-CAT and the Pabinger er al. tools can be applied throughout the patient’s journey,” concluded Prof. Gerotziafas.
References
- Sud R, Khorana AA. Cancer-associated thrombosis: risk factors, candidate biomarkers and a risk model. Thromb Res. 2009;123 Suppl 4:S18-21.
- Heit, JA. Poster 68 presented at: American Society of Hematology, 47th Annual Meeting, Atlanta, GA, December 10-13, 2005
- Spencer FA, Lessard D, Emery C, Reed G, Goldberg RJ. Venous thromboembolism in the outpatient setting. Arch Intern Med. 2007;167(14):1471-1475.
- Martin KA, Molsberry R, Khan SS, Linder JA, Cameron KA, Benson A 3rd. Preventing venous thromboembolism in oncology practice: Use of risk assessment and anticoagulation prophylaxis. Res Pract Thromb Haemost. 2020;4(7):1211-1215.
- 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.
- Gerotziafas GT, Mahé I, Lefkou E, et al. Overview of risk assessment models for venous thromboembolism in ambulatory patients with cancer. Thromb Res. 2020;191 Suppl 1:S50-S57.
- Khorana AA, Kuderer NM, Culakova E, Lyman GH, Francis CW. Development and validation of a predictive model for chemotherapy-associated thrombosis. Blood. 2008;111(10):4902-4907.
- Khorana AA, DeSancho MT, Liebman H, Rosovsky R, Connors JM, Zwicker J. Prediction and Prevention of Cancer-Associated Thromboembolism. Oncologist. 2021;26(1):e2-e7.
- Khorana AA, Soff GA, Kakkar AK, et al. Rivaroxaban for Thromboprophylaxis in High-Risk Ambulatory Patients with Cancer. N Engl J Med. 2019;380(8):720-728.
- Carrier M, Abou-Nassar K, Mallick R, et al. Apixaban to Prevent Venous Thromboembolism in Patients with Cancer. N Engl J Med. 2019;380(8):711-719.
- Pabinger I, van Es N, Heinze G, et al. A clinical prediction model for cancer-associated venous thromboembolism: a development and validation study in two independent prospective cohorts. Lancet Haematol. 2018;5(7):e289-e298.
- Riedl J, Ay C. Venous Thromboembolism in Brain Tumors: Risk Factors, Molecular Mechanisms, and Clinical Challenges. Semin Thromb Hemost. 2019;45(4):334-341.