Abstract
Purpose
This study aims to develop a scoring system tailored for Asian populations through quantifying VTE risk in a cohort of hospitalized cancer patients receiving immune checkpoint inhibitors.
Methods
We retrospectively analyzed 1171 patients treated with PD-1/PD-L1 inhibitors at Zhongshan Hospital (Xiamen), Fudan University between January 2021 and December 2023. We gathered information on every patient from the electronic database of the hospital and follow-up.The collected data were statistically analyzed to obtain risk factors for for VTE and validation of the score. Finally, we validated the precision of the model in prediction.
Results
Based on these findings, we developed the L2HSDK score,that identified seven independent risk factors for VTE:liver cancer, smoking, diabetes mellitus, liver dysfunction, cardiovascular history, and a Khorana Risk Score ≥ 3. The patients were divided into low, moderate, and high VTE risk groups. Significant differences in VTE incidence were observed across these groups, with the high-risk group showing a markedly higher risk. The validation of the model demonstrates the precision of the L2HSDK score in prediction.
Conclusion
The L2HSDK score offers a more precise and tailored method for assessing VTE risk in cancer patients receiving PD-1/PD-L1 inhibitors therapy in mainland China, surpassing the widely used Khorana Risk Score by accounting for regional and treatment-specific factors.
Introduction
Cancer is globally recognized as a life-threatening disease, and VTE (venous thromboembolism) is one of the leading causes of death in cancer patients. There was a positive correlation between the occurrence of cancer, its treatment, and the incidence of VTE. The rate of VTE in cancer patients reached as high as 10%, with a relative risk of 4 to 7 compared to non-cancer patients.1,2 Currently, an increasing number of patients were receiving immunotherapy, especially those with lung cancer and melanoma, achieving durable tumor responses in some clinical trials.3,4 Although the related toxicities were generally manageable, life-threatening adverse events might still occur,5,6 such as immune-related thrombosis. The exact pathophysiological mechanisms of this condition remained unclear, and the characteristics of VTE incidence in patients undergoing immunotherapy had yet to be fully explored.
Venous thrombosis, which includes DVT (deep vein thrombosis) and PE (pulmonary embolism),7,8 is the most common manifestation of cancer-associated hypercoagulability. However, the risk of cancer-related thrombosis was multifactorial, involving factors such as the use of chemotherapy agents, anti-angiogenic drugs, and hormonal therapies.9–13 In addition, specific factors like advanced age, racial background, cancer stage, obesity, and comorbidities also contributed to the risk of thrombosis in cancer patients. Prediction models for thrombotic risk hold significant clinical value.
The most commonly used clinical tool for assessing VTE risk in patients with malignancies is the Khorana score. Developed in 2008 by Dr Alok A. Khorana and his colleagues, this score was designed to evaluate the risk of chemotherapy-associated VTE in outpatient settings and is now also applied to hospitalized oncology patients. However, it does not target patients using immune checkpoint inhibitors, and the use of PD-1/PD-L1 inhibitors will increase the risk of venous thromboembolism. Therefore, Jingyi Gong et al 14 conducted a study on immunosuppressant related thrombosis in tumor patients in 2023, and obtained 9 risk factors including age, hypertension and other factors, but did not score them. In addition, most of the included population were non-Asian people, and race had a great difference in the incidence of different diseases. Therefore, it was of great importance to establish a score model for predicting immune checkpoint inhibitor-related thrombus suitable for Asian people.The use of PD-1/PD-L1 inhibitors increases the risk of VTE, making it crucial to accurately predict the probability of VTE occurrence in this population.
This study retrospectively analyzed various test indices and the incidence of thrombosis among cancer patients who had received PD-1 inhibitors therapy in a certain hospital over the past three years. Through Multivariate analysis, risk factors were identified. Subsequently, scores were assigned based on the regression coefficients (B - values) of these risk factors. Ultimately, a risk - scoring system for venous thromboembolism (VTE) in Asian cancer patients receiving PD-1 inhibitors treatment was developed.
The aim of this study was to quantify the VTE risk in a cohort of hospitalized patients receiving immune checkpoint inhibitors, explore its clinical impact, and investigate potential clinical risk factors. The ultimate goal is to establish a scoring system tailored to Asian cancer patients undergoing immunotherapy. This system would assess the risk of VTE in these patients and provide a basis for corresponding clinical treatment and care.
Methods
Study Design and Population
We retrospectively analyzed the data of patients treated with immune checkpoint inhibitors at Zhongshan Hospital (Xiamen), Fudan University, from January 2022 to June 2024. Data were retrieved from the inpatient medical records system. During hospitalization, we obtained informed consent from patients through thorough communication, followed by data collection via internet or telephone follow-up. (Figure 1).
Flowchart of Patient Screening.
Inclusion criteria included: (1) Tumor patients undergoing treatment with immune checkpoint inhibitors (2) Patients aged ≥18 years and <90 years.
Exclusion criteria included: (1) age <18 years; (2) insufficient data for subsequent analysis; (3) no follow-up or follow-up duration <12 months.
The pilot program have received approval from the Ethics Committee of Zhongshan Hospital (Xiamen), Fudan University (Ethics B2024-007). Through telephone follow-up, all study participants have provided their informed consent.
Data Collection
We collected patient data from the hospital's electronic database. Information was systematically organized and recorded by trained physicians and nurses, including demographic details (eg, age, sex), comorbidities (eg, hypertension, diabetes, chronic kidney or liver disease, history of cardiovascular events), immune checkpoint inhibitor type (eg, Tislelizumab,Sintilimab,Camrelizumab), and cancer types (eg, non-small cell lung cancer, gastrointestinal cancers). Cardiovascular event history and Khorana Risk Score were defined according to prior studies. Specifically, cardiovascular event history was defined as a composite of myocardial infarction, coronary revascularization, and ischemic stroke. Liver dysfunction was defined as aspartate aminotransferase (AST), alanine aminotransferase (ALT), or total bilirubin (TB) exceeding 1.5 times the upper limit of normal (ULN). The Khorana Risk Score is based on five variables, with cancer types associated with a higher risk of VTE (eg, stomach and pancreatic cancer) assigned 2 points, and others (eg, lung, lymphoma, gynecologic, bladder, testicular cancers) assigned 1 point. Pre-treatment platelet counts ≥350 × 10⁹/L, hemoglobin <10 g/dL, pre-treatment leukocyte count >11 × 10⁹/L, and BMI ≥ 35 kg/m² each contribute 1 point.
Endpoints and Follow-Up
Patients were followed for approximately 12 months through clinic visits and telephone contact. Most patients were required to attend monthly outpatient follow-ups to monitor symptoms and clinical signs. The primary outcome was the occurrence of VTE, defined as a composite of deep venous thrombosis or pulmonary embolism confirmed by standardized radiographic findings.
Statistical Analysis
Statistical analysis was conducted using SPSS 25.0 (IBM Corp., Armonk, NY, United States). Continuous variables are presented as mean ± standard deviation or median, while categorical variables are presented as percentages. Pearson's χ² test or Fisher's exact test was used for univariate analysis of categorical variables, as appropriate. Variables with p < 0.20 in the univariate analysis were included in a logistic regression to identify independent predictors of VTE. Variables with p < 0.05 were retained in the final model to develop a risk score. The weight of each predictor was determined based on the regression coefficients. Model calibration was assessed using the Hosmer–Lemeshow test.
Results
Patient Characteristics
A total of 1171 patients were enrolled in the study,204 of whom were used for validation of the score. Table 1 and Table 2 provides an overview of the baseline characteristics of patients treated with immune checkpoint inhibitors, including demographic information (eg, age, height, weight), type of immune checkpoint inhibitor (eg, Tislelizumab, Sintilimab, Camrelizumab), and cancer types (eg, non-small cell lung cancer, gastrointestinal cancers).
Baseline Clinical Characteristics of Patients.
SD, standard deviation; BMI, body mass index.
Baseline Clinical Characteristics of Patients (Validation Group).
SD, standard deviation; BMI, body mass index.
Risk Factors for VTE and Establishment and Evaluation of the Risk-Scoring Model
Univariate analysis identified several factors significantly associated with VTE risk, including smoking (p = 0.003), liver dysfunction (p < 0.001), diabetes mellitus (p < 0.001), history of cardiovascular events (p = 0.016), lung cancer (p = 0.002), liver cancer (p < 0.001), esophageal carcinoma (p < 0.001), renal insufficiency (p = 0.048), use of sintilimab (p = 0.019) and Khorana Risk Score ≥3 (p < 0.001). Multivariate analysis identified seven independent risk factors for VTE in cancer patients treated with PD-1/PD-L1 inhibitors: liver cancer, smoking, diabetes mellitus, liver dysfunction, history of cardiovascular events and Khorana Risk Score ≥3. Based on the regression coefficients of the final model, we developed the L2HSDK score, assigning 3 points to Khorana Risk Score ≥3, 2 point to liver cancer and diabetes mellitus, 1 point to smoking, liver dysfunction, and history of cardiovascular events (Table 3).
VTE Risk with a Univariate Analysis.
History of any cardiovascular event: a composite of myocardial infarction, coronary revascularization, and ischemic stroke; Liver dysfunction: Aspartate aminotransferase (AST), alanine aminotransferase (ALT), or total bilirubin (TB) exceeding 1.5 times the upper limit of normal (ULN).
We categorized patients into three risk groups: low risk (score ≤2), moderate risk (score 3–5), and high risk (score ≥6). After a 12-month follow-up, significant differences in VTE incidence were observed between the groups (P < 0.05), with the high-risk group having approximately 15 times the VTE risk compared to the low-risk group (Figure 2).
Time to Thrombosis (TTT) in Immune Checkpoint Inhibitors Treated Patients, Stratified into Three Subgroups (Low Risk Group, Moderate Risk Group, High Risk Group) According to the L2HSDK Scores. “ aReferred as the Comparison Between Low Risk Group and Moderate Risk Group. bReferred as the Comparison Between Moderate Risk Group and High Risk Group. “ cReferred as the Comparison Between Low Risk Group and High Risk Group.
Validated Model
Extra information of 210 patients was brought into L2HSDK score, and ROC (Receiver Operating Characteristic) analysis was performed. AUC (area under the curve) of L2HSDK score was 0.818 (95% CI 0.686–0.950; p < 0.001) (Figure 3). These results indicated that the L2HSDK score exhibited a high level of precision in its predictions.
The ROC Curve of the L2HSDK Score was Verified. (AUC 0.818 95% CI 0.686–0.950; p < 0.001).
Discussion
The imbalance of procoagulant factors in patients with hepatocellular carcinoma (HCC) leads to an acquired hypercoagulable state,15,16 and thus, in our L2HSDK score, liver cancer is assigned 2 points for its association with VTE. At the same time, published data supports a direct link between biomarkers of liver dysfunction and a hypercoagulable state.17,18 The aforementioned studies indicate an association between elevated bilirubin concentrations and hypercoagulability, with bilirubin levels identified as a risk factor for heightened thrombotic risk in patients with acute myocardial infarction. Additionally, AST and ALT are established circulating biomarkers for evaluating liver injury. Research by Zhen Wang demonstrated that elevated ALT levels may serve as potential risk factors for venous thromboembolism (VTE) in non-small cell lung cancer patients, potentially attributable to metabolic dysregulation. 19 Furthermore, Yin ZJ's investigation revealed that an elevated AST/ALT ratio not only increases blood viscosity but also reflects underlying inflammatory processes, thereby linking these parameters to an elevated risk of VTE. 20 Therefore, assigning liver dysfunction 1 point in the L2HSDK score is justifiable. In our scoring system, Diabetes mellitus account for 2 points. Diabetes mellitus has long been considered a risk factor for increased VTE incidence. Studies suggest that diabetes-associated coagulation and endothelial function abnormalities are significant, with glycosylation of coagulation factors altering their activity or affecting gene transcription.21,22 Additionally, hyperinsulinemia associated with diabetes has been shown to have prothrombotic effects.23,24 Furthermore, patients with cancer who are at extremely high risk of VTE (Khorana Risk Score ≥ 3) require mechanical or pharmacological prophylaxis, and such patients are assigned 3 points in the L2HSDK score. Through univariate regression analysis, it was determined that a Khorana Risk Score ≤ 2 holds no significant value in the L2HSDK score.
Smoking and cardiovascular events each contribute 1 point in our scoring system. Smoking is a well-established risk factor for atherosclerotic disease, and a procoagulant state, decreased fibrinolysis, increased inflammation, and elevated blood viscosity may underlie the association between smoking and VTE risk.25–27 A history of cardiovascular events is defined as a composite of myocardial infarction, coronary revascularization, and ischemic stroke. Hemodynamic changes in patients with a history of cardiovascular events influence the development and progression of VTE.
The L2HSDK score is designed to assess VTE risk in cancer patients receiving PD-1/PD-L1 inhibitors therapy, with a relatively fixed application scope. Compared to the Khorana Risk Score, it is better suited to hospitalized patients in mainland China. While the Khorana Risk Score has utility in evaluating thrombotic risk in outpatient oncology patients undergoing chemotherapy, it has certain limitations when applied to Chinese patients, such as: 1. Geographical limitation: The Khorana Risk Score was developed based on U.S. patients, where the prevalence of obesity is higher. In contrast, in China, patients with a BMI ≥ 35 kg/m² are rare, reducing the effectiveness of this factor in the scoring model. 2. Therapeutic limitation: The model was constructed using patient data from 2002–2005 and excluded patients undergoing biological or immunotherapy, as well as those in acute inflammatory states. With the rapid development of cancer therapies, including targeted and immunotherapies, the proportion of patients receiving only chemotherapy has decreased, limiting the generalizability of the Khorana Risk Score. 3. Dynamic risk assessment limitation: The Khorana model assigns scores based on hemoglobin levels, white blood cell count, and platelet count before the first chemotherapy cycle. However, VTE risk evolves with disease stage, therapeutic interventions, and changes in patient condition, and the Khorana Risk Score cannot dynamically reflect these shifts. 4. Confounding factors: In clinical practice, the Khorana Risk Score may be confounded by comorbidities such as chronic kidney disease and cardiovascular disease, which could skew the risk assessment. Additionally, patients undergoing concurrent chemoradiotherapy often receive prophylactic granulocyte colony-stimulating factor to reduce the incidence of neutropenia, which may prevent treatment interruptions that could compromise efficacy.
Although the Khorana Risk Score provides some benefit in assessing VTE risk in cancer patients, its limitations suggest that clinicians should incorporate other clinical factors, individual characteristics, and emerging biomarkers for a more comprehensive evaluation of thrombotic risk.
Limitations: Although L2HSDK score system has undergone validation, its clinical application has not yet been fully established. And the specific prophylactic measures corresponding to its “low-risk,” “intermediate-risk,” and “high-risk” classifications have not been fully defined.
Conclusion
We established a risk scoring model (L2HSDK score) for PD-1/PD-L1 inhibitor-associated venous thromboembolism (VTE) in cancer patients. The L2HSDK score evaluates VTE risk through seven clinical parameters: liver cancer, smoking history, diabetes mellitus, liver dysfunction, history of cardiovascular events and Khorana Risk Score ≥3. This novel scoring system can help identify cancer patients at high risk of VTE, enabling timely preventive interventions and targeted treatments to reduce mortality.
Footnotes
Acknowledgements
We would like to thank all the patients who provided hospitalization information for the development of the L2HSDK score.
Ethics Approval
Ethical approval to report this case was obtained from the Ethics Committee of Zhongshan Hospital (Xiamen), Fudan University carried out in accordance with the principles of the Declaration of Helsinki. ((Ethics B2024-007)).
Informed Consent
Verbal informed consent was obtained from the patient(s) for their anonymized information to be published in this article.
Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by grants from Xiamen Government and Xiamen Medical and Health Guidance Project (3502Z20224ZD1087).
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.