Immune activation and inflammatory biomarkers as predictors of venous thromboembolism in lymphoma patients

Systemic immune-inflammation index as a potential biomarker for predicting acute pulmonary embolism: A systematic review

BACKGROUND

Acute pulmonary embolism (APE) is a life-threatening condition with a high mortality rate. The pathophysiology involves various complex processes. The systemic immune-inflammatory index (SII) is a well-known biomarker that reflects the intricate balance between pro-inflammatory and anti-inflammatory immune components. In this systematic review, we aim to determine the significance of SII as a potential biomarker for APE.

METHOD

We utilized PubMed, ProQuest, EBSCOHost, and Google Scholar to search for articles. We assessed bias risk using the Newcastle Ottawa Scale (NOS). The outcomes we examined included in-hospital and long-term mortality, the severity of APE, and the sensitivity and specificity of the SII in predicting APE.

RESULTS

Four studies, involving 2,038 patients, were included for analysis. These studies discuss the use of SII in predicting APE severity, APE mortality, high-risk APE, and the occurrence of APE. SII demonstrates significant results in predicting each of these variables. Furthermore, each study establishes different SII cut-off values. Specifically, a cut-off of 1161 predicts massive APE events with a sensitivity of 91% and a specificity of 90%. A cut-off of >1235.35 differentiates high-risk APE with a sensitivity of 87.32% and a specificity of 68.85%. A cut-off of >1111x109 predicts overall mortality with a sensitivity of 72% and a specificity of 51%. Finally, a cut-off at 1839.91 predicts APE events with a sensitivity of 75.8% and a specificity of 61.9%.

CONCLUSION

The SII can be employed as a potential new biomarker to predict outcomes in APE patients, particularly the occurrence, severity, and mortality of APE.

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.

Circulating Blood Biomarkers and Risk of Venous Thromboembolism in Cancer Patients: A Systematic Review and Meta-Analysis

BACKGROUND

 Cancer patients have an increased risk of venous thromboembolism (VTE). Currently, the availability of highly discriminatory prediction models for VTE in cancer patients is limited. The implementation of biomarkers in prediction models might lead to refined VTE risk prediction. In this systematic review and meta-analysis, we aimed to evaluate candidate biomarkers and their association with cancer-associated VTE.

METHODS

 We searched Medline, EMBASE, and Cochrane Central for studies that evaluated biomarkers in adult cancer patients from inception to September 2022. We included studies reporting on VTE after a cancer diagnosis with biomarker measurements performed at a defined time point. Median/mean differences (for continuous measures) and odds ratios (for dichotomous measures) with 95% confidence intervals were estimated and pooled using random-effects models.

RESULTS

 We included 113 studies in the systematic review. Of these, 50 studies were included in the meta-analysis. We identified two biomarkers at cancer diagnosis (factor VIII and time to peak thrombin), three biomarkers pre-chemotherapy (D-dimer, fibrinogen, and mean platelet volume), and one biomarker preoperatively (platelet count) that had significant median or mean differences. Additionally, we found that hemoglobin <100 g/L and white blood count >11 × 109/L were significantly associated with future VTE risk only when measured at cancer diagnosis. Pre-chemotherapy neutrophil-to-lymphocyte ratio ≥3 and preoperative platelet count ≥400 × 109/L were also found to be associated with future VTE risk.

CONCLUSION

 In conclusion, this study identified nine candidate blood biomarkers that may help in optimizing VTE prediction in cancer patients that should be further explored in future studies.

Cellular Components Contributing to the Development of Venous Thrombosis in Patients with Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive type of cancer and has a poor prognosis. Patients with PDAC are at high risk of developing thromboembolic events, which is a leading cause of morbidity and mortality following cancer progression. Plasma-derived coagulation is the most studied process in cancer-associated thrombosis. Other blood components, such as platelets, red blood cells, and white blood cells, have been gaining less attention. This narrative review addresses the literature on the role of cellular components in the development of venous thromboembolism (VTE) in patients with PDAC. Blood cells seem to play an important role in the development of VTE. Altered blood cell counts, i.e., leukocytosis, thrombocytosis, and anemia, have been found to associate with VTE risk. Tumor-related activation of leukocytes leads to the release of tissue factor-expressing microvesicles and the formation of neutrophil extracellular traps, initiating coagulation and forming a scaffold for thrombi. Tissue factor-expressing microvesicles are also thought to be released by PDAC cells. PDAC cells have been shown to stimulate platelet activation and aggregation, proposedly via the secretion of podoplanin and mucins. Hypofibrinolysis, partially explained by increased plasminogen activator inhibitor-1 activity, is observed in PDAC. In short, PDAC-associated hypercoagulability is a complex and multifactorial process. A better understanding of cellular contributions to hypercoagulability might lead to the improvement of diagnostic tests to identify PDAC patients at highest risk of VTE.

Derivation, validation and assessment of a novel nomogram-based risk assessment model for venous thromboembolism in hospitalized patients with lung cancer: A retrospective case control study

Purpose

This study aimed to develop and validate a specific risk-stratification nomogram model for the prediction of venous thromboembolism(VTE) in hospitalized patients with lung cancer using readily obtainable demographic, clinical and therapeutic characteristics, thus guiding the individualized decision-making on thromboprophylaxis on the basis of VTE risk levels.

Methods

We performed a retrospective case–control study among newly diagnosed lung cancer patients hospitalized between January 2016 and December 2021. Included in the cohort were 234 patients who developed PTE and 936 non-VTE patients. The patients were randomly divided into the derivation group (70%, 165 VTE patients and 654 non-VTE patients) and the validation group (30%, 69 VTE patients and 282 non-VTE patients). Cut off values were established using a Youden´s Index. Univariate and multivariate regression analyses were used to determine independent risk factors associated with VTE. Variance Inflation Factor(VIF) was used for collinearity diagnosis of the covariates in the model. The model was validated by the consistency index (C-index), receiver operating characteristic curves(ROC) and the calibration plot with the Hosmer-Lemeshow goodness-of-fit test. The clinical utility of the model was assessed through decision curve analysis(DCA). Further, the comparison of nomogram model with current models(Khorana, Caprini, Padua and COMPASS-CAT) was performed by comparing ROC curves using the DeLong’s test.

Results

The predictive nomogram modle comprised eleven variables: overweight(24-28) defined by body mass index (BMI): [odds ratio (OR): 1.90, 95% confidence interval (CI): 1.19-3.07], adenocarcinoma(OR:3.00, 95% CI: 1.88-4.87), stageIII-IV(OR:2.75, 95%CI: 1.58-4.96), Central venous catheters(CVCs) (OR:4.64, 95%CI: 2.86-7.62), D-dimer levels≥2.06mg/L(OR:5.58, 95%CI:3.54-8.94), PT levels≥11.45sec(OR:2.15, 95% CI:1.32-3.54), Fbg levels≥3.33 g/L(OR:1.76, 95%CI:1.12-2.78), TG levels≥1.37mmol/L (OR:1.88, 95%CI:1.19-2.99), ROS1 rearrangement(OR:2.87, 95%CI:1.74-4.75), chemotherapy history(OR:1.66, 95%CI:1.01-2.70) and radiotherapy history(OR:1.96, 95%CI:1.17-3.29). Collinearity analysis with demonstrated no collinearity among the variables. The resulting model showed good predictive performance in the derivation group (AUC 0.865, 95% CI: 0.832-0.897) and in the validation group(AUC 0.904,95%CI:0.869-0.939). The calibration curve and DCA showed that the risk-stratification nomogram had good consistency and clinical utility. Futher, the area under the ROC curve for the specific VTE risk-stratification nomogram model (0.904; 95% CI:0.869-0.939) was significantly higher than those of the KRS, Caprini, Padua and COMPASS-CAT models(Z=12.087, 11.851, 9.442, 5.340, all P<0.001, respectively).

Conclusion

A high-performance nomogram model incorporated available clinical parameters, genetic and therapeutic factors was established, which can accurately predict the risk of VTE in hospitalized patients with lung cancer and to guide individualized decision-making on thromboprophylaxis. Notably, the novel nomogram model was significantly more effective than the existing well-accepted models in routine clinical practice in stratifying the risk of VTE in those patients. Future community-based prospective studies and studies from multiple clinical centers are required for external validation.

The Diagnostic Value of the Systemic Immune-Inflammation Index for Venous Thromboembolism in Lung Cancer Patients: A Retrospective Study

Background

Venous thromboembolism (VTE) is considered a common complication in lung cancer patients. Despite its widespread use, the Khorana score performed moderately in predicting VTE risk. This study aimed to determine the diagnostic utility of the Systemic Immunoinflammatory Index (SII) and to create a novel nomogram for predicting VTE in patients with pulmonary carcinoma.

Materials and Methods

The data, like clinical features and laboratory indicators, of inpatients diagnosed with lung cancer from March 2019 to March 2020 were collected and analyzed. Univariate and multivariate logistic analyses were performed to confirm the risk factors and then construct a nomogram model. The calibration curve and clinical decision curve analysis (DCA) were used to assess the model's fitting performance. The receiver-operating characteristic (ROC) curve and the area under the ROC curve (AUC) were used to evaluate the diagnostic value of SII and the nomogram.

Results

This study enrolled 369 lung patients with a VTE morbidity rate of 23.33%. The patients with VTE had higher SII levels than the non-VTE group (1441.47 ± 146.28 vs. 626.76 ± 26.04, P < 0.001). SII is the stronger correlator for VTE among inflammatory markers, of which the optimal cut-off value was 851.51. Univariate and multivariate analysis revealed that the age, metastasis, antitumor treatment, hemoglobin<100 g/L, SII>851.51 × 10⁹/L, and D-dimer>2 folds were independent risk factors for lung cancer-related VTE, and a new prediction nomogram model was constructed based on them. ROC curve analysis showed the AUC of the new model and Khorana score were 0.708 (0.643-0.772) and 0.600 (0.531-0.699).

Conclusion

The SII was a simple and valuable biomarker for VTE, and the new nomogram model based on it can accurately forecast the occurrence of VTE. They can be utilized in clinical practice to identify those at high risk of VTE in lung cancer patients.

Cellular Indices and Outcome in Patients with Acute Venous Thromboembolism

Background

Cellular indices provide integrative information about systemic inflammation status which is readily available from routine laboratory parameters. This study aimed to evaluate the prognostic role of three cellular indices in patients with venous thromboembolism (VTE).

Methods

The RIETE registry database was used to determine the association between the baseline neutrophil-to-lymphocyte-ratio (NLR), platelet-to-lymphocyte-ratio (PLR) and systemic-immune-inflammation-index (SII) for 90-day adverse outcomes in patients with acute VTE.

Results

From January 2020 to April 2021, 4487 patients with acute VTE were recruited in the RIETE registry. Of these, 2683 presented with symptomatic pulmonary embolism (PE); 283 with incidental PE; 1129 with lower-limb deep vein thrombosis (DVT); 175 with upper-limb DVT; 69 with splanchnic vein thrombosis; 142 with superficial vein thrombosis and 20 with retinal vein thrombosis. Mean values were: NLR 5.9 ± 7.1, PLR 190 ± 158 and SII 1459 ± 2028. During the first 90-days, 38 patients (0.8%) developed recurrent DVT, 45 (1.0%) had recurrent PE, 152 (3.4%) suffered major bleeding, and 484 (11%) died. On multivariable analysis, patients with NLR >4.41 were at an increased risk for major bleeding and patients with NLR >4.96 were at the risk of death, while those with SII >1134.5 were at increased risk for death.

Conclusions

This study reports the results of a large cohort to date which evaluate the prognostic value of three cellular indices simultaneously in patients with acute VTE. Results support that none of the three baseline cellular indices were sufficient for prediction of VTE recurrences in acute VTE patients. The patients with higher baseline NLR values were at an increased risk of major bleeding or death, those with high SII values were only at an increased risk for mortality.