Incorporating genetic and clinical data into the prediction of thromboembolism risk in patients with lymphoma

Thrombosis risk prediction in lymphoma patients: A multi-institutional, retrospective model development and validation study

Venous thromboembolism (VTE) poses a significant risk to cancer patients receiving systemic therapy. The generalizability of pan-cancer models to lymphomas is limited. Currently, there are no reliable risk prediction models for thrombosis in patients with lymphoma. Our objective was to create a risk assessment model (RAM) specifically for lymphomas. We performed a retrospective cohort study to develop Fine and Gray sub-distribution hazard model for VTE and pulmonary embolism (PE)/ lower extremity deep vein thrombosis (LE-DVT) respectively in adult lymphoma patients from the Veterans Affairs national healthcare system (VA). External validations were performed at the Harris Health System (HHS) and the MD Anderson Cancer Center (MDACC). Time-dependent c-statistic and calibration curves were used to assess discrimination and fit. There were 10,313 (VA), 854 (HHS), and 1858 (MDACC) patients in the derivation and validation cohorts with diverse baseline. At 6 months, the VTE incidence was 5.8% (VA), 8.2% (HHS), and 8.8% (MDACC), respectively. The corresponding estimates for PE/LE-DVT were 3.9% (VA), 4.5% (HHS), and 3.7% (MDACC), respectively. The variables in the final RAM included lymphoma histology, body mass index, therapy type, recent hospitalization, history of VTE, history of paralysis/immobilization, and time to treatment initiation. The RAM had c-statistics of 0.68 in the derivation and 0.69 and 0.72 in the two external validation cohorts. The two models achieved a clear differentiation in risk stratification in each cohort. Our findings suggest that easy-to-implement, clinical-based model could be used to predict personalized VTE risk for lymphoma patients.

Comprehensive evaluation of genetic and acquired thrombophilia markers for an individualized prediction of clinical thrombosis in patients with lymphoma and multiple myeloma

Patients diagnosed with lymphoma or multiple myeloma are at elevated risk of venous thromboembolism (VTE). Optimum risk stratification and effective thromboprophylaxis can only be achieved through the development of a multiple-specific risk score that successfully captures all aspects of the heterogeneous prothrombotic environment existing in these patients. Our aim was to identify risk factors for thrombosis and suggest an improved tool combining clinical data, thrombo-inflammatory biomarkers and genetic (Thrombo inCode® test) variables for predicting thrombotic risk in patients with lymphoma and multiple myeloma. A prospective longitudinal study was conducted on newly-diagnosed lymphoma and multiple myeloma patients who presented at our institution between February 2020 and January 2021. The study included 47 patients with lymphoma and 16 patients with multiple myeloma. We performed a follow-up of 1 year or until September 2021. The incidence of venous thrombosis and associated risk factors were analysed, including the genetic Thrombo inCode® test. Khorana and ThroLy scores for lymphoma patients and IMPEDE VTE score for myeloma patients were calculated. At a median follow-up of 9.1 months, VTE incidence was 9.5% (6/63), with 4 and 2 patients with lymphoma and myeloma who developed the events, respectively. Univariate analysis showed that the incidence of thrombosis was significantly higher in patients with ECOG ≥ 2 and prior immobility. Median factor VIII levels were significantly higher in patients with thrombosis (with increased values in all of them). Moreover, there was a trend in genetic variant rs5985 (factor XIII) as a protective factor, and a trend to higher thrombotic risk in patients with factor V Leiden, rs2232698 variant (serpinA10), low total protein S activity, elevated D-dimer, aggressive lymphoma and treatment with dexamethasone. The results of our study demonstrate promise for the potential use of widely accessible markers to increase precision in risk prediction for VTE in patients with lymphoma and multiple myeloma, particularly ECOG ≥ 2, immobility and higher factor VIII levels, as well as lymphoma aggressiveness, treatment with dexamethasone and the haemostatic biomarkers D-dimer and total protein S activity. Additionally, genetic variants factor V Leiden, serpinA10 rs2232698 and factor XIII-A Val34Leu warrant further investigation for use in the research setting.

Developing a risk assessment tool for cancer-related venous thrombosis in China: a modified Delphi-analytic hierarchy process study

OBJECTIVE

To develop a Risk Assessment Tool for Cancer-related Venous Thrombosis in China.

METHODS

A modified two-round Delphi method was employed to establish consensus within a field to reach an agreement via a questionnaire or by interviewing a multidisciplinary panel of experts by collecting their feedback to inform the next round, exchanging their knowledge, experience, and opinions anonymously, and resolving uncertainties. Furthermore, The AHP (Analytic Hierarchy Process) was used to determine the final quality indicators' relative importance.

RESULTS

The expert's positive coefficient was 85.19% in the first round and 82.61% in the second round, with authoritative coefficients of 0.89 and 0.92 in the respective surveys. The P-value of Kendall's W test was all less than 0.001 for each round, and the W-value for concordance at the end of the two rounds was 0.115. The final Risk Assessment Tool for Cancer-related Venous Thrombosis consisted of three domains, ten subdomains, and 39 indicators, with patient factors weighing 0.1976, disease factors weighing 0.4905, and therapeutic factors weighing 0.3119.

CONCLUSION

The tool is significantly valid and reliable with a strong authority and coordination degree, and it can be used to assess the risk of cancer-related VTE and initiate appropriate thrombophylactic interventions in China.

Novel Insights in Venous Thromboembolism Risk Assessment Methods in Ambulatory Cancer Patients: From the Guidelines to Clinical Practice

Many cancer patients will experience venous thromboembolism (VTE) at some stage, with the highest rate in the initial period following diagnosis. Novel cancer therapies may further enhance the risk. VTE in a cancer setting is associated with poor prognostic, a decreased quality of life, and high healthcare costs. If thromboprophylaxis in hospitalized cancer patients and perioperative settings is widely accepted in clinical practice and supported by the guidelines, it is not the same situation in ambulatory cancer patient settings. The guidelines do not recommend primary thromboprophylaxis, except in high-risk cases. However, nowadays, risk stratification is still challenging, although many tools have been developed. The Khrorana score remains the most used method, but it has many limits. This narrative review aims to present the current relevant knowledge of VTE risk assessment in ambulatory cancer patients, starting from the guideline recommendations and continuing with the specific risk assessment methods and machine learning models approaches. Biomarkers, genetic, and clinical features were tested alone or in groups. Old and new models used in VTE risk assessment are exposed, underlining their clinical utility. Imaging and biomolecular approaches to VTE screening of outpatients with cancer are also presented, which could help clinical decisions.

A Clinical-Genetic Risk Score for Predicting Cancer-Associated Venous Thromboembolism: A Development and Validation Study Involving Two Independent Prospective Cohorts

PURPOSE

Venous thromboembolism (VTE) is a leading cause of death among patients with cancer. The Khorana score was developed for assessing the risk of VTE in outpatients with cancer receiving chemotherapy, but its accuracy in identifying patients at high risk has been questioned. The aim of this study was to develop and validate a clinical-genetic score that improves the assessment of VTE risk in oncology outpatients within 6 months of diagnosis.

METHODS

The new score was developed using the data of 364 outpatients belonging to the Spanish ONCOTHROMB 12-01 population. In this cohort, clinical data associated with the risk of VTE were collected at the time of diagnosis, including the Khorana score. These patients were also genotyped for the 51 genetic variants known to be associated with VTE. Multivariate logistic regression was performed to determine the weight of each genetic and clinical variable in relation to VTE risk, allowing a clinical-genetic risk score (the ONCOTHROMB score) to be developed. The Khorana and the ONCOTHROMB scores were then compared via the area under the receiver operating characteristic curve (AUC), calibration, and the number of patients needed to treat. The new score was then validated in a study of 263 patients in the Vienna Cancer and Thrombosis Study population.

RESULTS

Nine genetic variants, tumor site, TNM stage, and a body mass index of > 25 kg/m2 were found to be associated with VTE and were used to build the ONCOTHROMB score, which better predicted the overall risk of VTE than did the Khorana score (AUC, 0.781 v 0.580; P < .001). Similar AUC results were recorded in the validation study the Vienna Cancer and Thrombosis Study cohort involving patients with the same type of tumor (AUC for the ONCOTHROMB score v the Khorana score: 0.686 v 0.577; P < .001) and with all type of tumors (AUC for the ONCOTHROMB score v the Khorana score: 0.720 v 0.561; P < .0001).

CONCLUSION

The ONCOTHROMB score for VTE risk in outpatients with cancer, which takes into account both clinical and genetic variables, better identifies patients who might benefit from primary thromboprophylaxis than does the Khorana score.

Incorporating genetic and clinical data into the prediction of thromboembolism risk in patients with lymphoma

Background

The incorporation of genetic variables into risk scores for predicting venous thromboembolic events (VTE) could improve their capacity to identify those patients for whom thromboprophylaxis would be most beneficial. Proof‐of‐concept of this is provided by the TiC‐ONCO score for predicting the risk of VTE in patients with solid tumours. Our aim was to develop a similarly improved tool—the TiC‐LYMPHO score—for predicting VTE in patients with lymphoma.

Methods

In a retrospective observational study of 208 patients with lymphoma, 31 (14.9%) were found to have experienced an episode of VTE either at the time of diagnosis or over the next 6 months. Clinical variables associated with VTE, determined via logistic regression analysis, plus the same genetic variables included in the TiC‐ONCO score, were used to build the TiC‐LYMPHO score algorithm. The sensitivity, specificity, predictive values and AUC of the TiC‐LYMPHO, the Khorana and ThroLy scores were compared in the same population.

Results

The TiC‐LYMPHO score showed a significantly higher AUC, sensitivity and NPV (0.783, 95.35% and 97.98% respectively) than the other scores. The ThroLy score showed a significantly higher specificity (96.43% vs. 54.49%; p < 0.0001) and PPV (37.50% vs. 26.36%; p = 0.0147) than the TiC‐LYMPHO score, whereas its AUC, sensitivity and NPV were significantly lower (0.579, 19.35% and 86.48%, respectively).

Conclusion

These results show that by incorporating genetic and clinical data into VTE risk assessment, the TiC‐LYMPHO score can categorize patients with lymphoma better in terms of their risk of VTE and allow individualized thromboprophylaxis to be prescribed.