Dynamic assessment of venous thromboembolism risk in patients with cancer by longitudinal D-Dimer analysis: A prospective study

Multi-factor early monitoring method based on D-dimer for iliac crest flap loss

BACKGROUND

In recent years, the utilization of autogenous vascularized iliac crest flap for repairing jaw defects has seen a significant rise. However, the visual monitoring of iliac bone flaps present challenges, frequently leading to delayed detection of flap loss. Consequently, there's a urgent need to develop effective indicators for monitoring postoperative complications in iliac crest flaps.

METHODS

A retrospective analysis was conducted on 160 patients who underwent vascularized iliac crest flap transplantation for jawbone reconstruction from January 2020 to December 2022. We investigated the changes in D-dimer levels among patients with or without postoperative complications. Additionally, multivariable logistic regression analysis was performed to explore potential individual risk factors, including surgical duration, age, pathology type, absolute and relative D-dimer levels, and gender, culminating in the development of a nomogram.

RESULTS

On the first day following surgery, patients who experienced thrombosis exhibited a substantial increase in plasma D-dimer levels, reaching 3.75 mg/L, 13.84 times higher than the baseline. This difference was statistically significant (P < 0.05) compared to patients without postoperative complications. Furthermore, the nomogram we have developed and validated effectively predicts venous thrombosis, assigning individual risk scores to patients. This predictive tool was assessed in both training and validation cohorts, achieving areas under the curve (AUC) of 0.630 and 0.600, with the 95% confidence intervals of 0.452-0.807 and 0.243-0.957, respectively.

CONCLUSIONS

Our study illustrates that postoperative plasma D-dimer levels can serve as a sensitive biomarker for monitoring thrombosis-induced flap loss. Moreover, we have developed a novel prediction model that integrates multiple factors, thereby enhancing the accuracy of early identification of patients at risk of thrombosis-associated flap loss. This advancement contributes to improving the overall management and outcomes of such procedures.

Cancer progression and tumor hypercoagulability: a platelet perspective

Venous thromboembolism, which is common in cancer patients and accompanies or even precedes malignant tumors, is known as cancer-related thrombosis and is an important cause of cancer- associated death. At present, the exact etiology of the elevated incidence of venous thrombosis in cancer patients remains elusive. Platelets play a crucial role in blood coagulation, which is intimately linked to the development of arterial thrombosis. Additionally, platelets contribute to tumor progression and facilitate immune evasion by tumors. Tumor cells can interact with the coagulation system through various mechanisms, such as producing hemostatic proteins, activating platelets, and directly adhering to normal cells. The relationship between platelets and malignant tumors is also significant. In this review article, we will explore these connections.

Deep Learning-Based Dynamic Risk Prediction of Venous Thromboembolism for Patients With Ovarian Cancer in Real-World Settings From Electronic Health Records

PURPOSE

Patients with epithelial ovarian cancer (EOC) have an elevated risk for venous thromboembolism (VTE). To assess the risk of VTE, models were developed by statistical or machine learning algorithms. However, few models have accommodated deep learning (DL) algorithms in realistic clinical settings. We aimed to develop a predictive DL model, exploiting rich information from electronic health records (EHRs), including dynamic clinical features and the presence of competing risks.

METHODS

We extracted EHRs of 1,268 patients diagnosed with EOC from January 2007 through December 2017 at the National Cancer Center, Korea. DL survival networks using fully connected layers, temporal attention, and recurrent neural networks were adopted and compared with multi-perceptron-based classification models. Prediction accuracy was independently validated in the data set of 423 patients newly diagnosed with EOC from January 2018 to December 2019. Personalized risk plots displaying the individual interval risk were developed.

RESULTS

DL-based survival networks achieved a superior area under the receiver operating characteristic curve (AUROC) between 0.95 and 0.98 while the AUROC of classification models was between 0.85 and 0.90. As clinical information benefits the prediction accuracy, the proposed dynamic survival network outperformed other survival networks for the test and validation data set with the highest time-dependent concordance index (0.974, 0.975) and lowest Brier score (0.051, 0.049) at 6 months after a cancer diagnosis. Our visualization showed that the interval risk fluctuating along with the changes in longitudinal clinical features.

CONCLUSION

Adaption of dynamic patient clinical features and accounting for competing risks from EHRs into the DL algorithms demonstrated VTE risk prediction with high accuracy. Our results show that this novel dynamic survival network can provide personalized risk prediction with the potential to assist risk-based clinical intervention to prevent VTE among patients with EOC.

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.

Identifying novel biomarkers using proteomics to predict cancer-associated thrombosis

Comprehensive protein analyses of plasma are made possible by high-throughput proteomic screens, which may help find new therapeutic targets and diagnostic biomarkers. Patients with cancer are frequently affected by venous thromboembolism (VTE). The limited predictive accuracy of current VTE risk assessment tools highlights the need for new, more targeted biomarkers. Although coagulation biomarkers for the diagnosis, prognosis, and treatment of VTE have been investigated, none of them have the necessary clinical validation or diagnostic accuracy. Proteomics holds the potential to uncover new biomarkers and thrombotic pathways that impact the risk of thrombosis. This review explores the fundamental methods used in proteomics and focuses on particular biomarkers found in VTE and cancer-associated thrombosis.

Tissue factor pathway inhibitor is associated with risk of venous thromboembolism and all-cause mortality in patients with cancer

Venous thromboembolism (VTE) is a common complication in patients with cancer. Data on the role of natural inhibitors of coagulation for occurrence of cancer-associated VTE are limited, thus, we investigated the association of tissue factor pathway inhibitor (TFPI) with risk of VTE and all-cause mortality in patients with cancer. Total TFPI antigen levels were measured with a commercially available enzyme-linked immunosorbant assay in patients included in the Vienna Cancer and Thrombosis Study, a prospective observational cohort study with the primary outcome VTE. Competing risk analysis and Cox regression analysis were performed to explore the association of TFPI levels with VTE and all-cause mortality. TFPI was analyzed in 898 patients (median age 62 years; interquartile range [IQR], 53-68; 407 (45%) women). Sixty-seven patients developed VTE and 387 died (24-month cumulative risk 7.5% and 42.1%, respectively). Patients had median TFPI levels at study inclusion of 56.4 ng/mL (IQR, 45.7-70.0), with highest levels in tumor types known to have a high risk of VTE (gastroesophageal, pancreatic and brain cancer: 62.0 ng/mL; IQR, 52.0-75.0). In multivariable analysis adjusting for age, sex, cancer type and stage, TFPI levels were associated with VTE risk (subdistribution hazard ratio per doubling =1.63, 95% confidence interval [CI]: 1.03-2.57). When patients with high and intermediate/low VTE risk were analyzed separately, the association remained independently associated in the high risk group only (subdistribution hazard ratio =2.63, 95% CI: 1.40-4.94). TFPI levels were independently associated with all-cause mortality (hazard ratio =2.36, 95% CI: 1.85-3.00). In cancer patients increased TFPI levels are associated with VTE risk, specifically in patients with high-risk tumor types, and with all-cause mortality.

Assessment of the association between D-dimer levels and clinicopathological characteristics of pancreatic cancer and its role in prognosis: A systematic review and meta-analysis

According to previous studies, D-dimer levels are associated with the prognosis of patients with pancreatic cancer (PC). However, the results of current studies are limited and controversial. Therefore, we performed this meta-analysis to assess the relationship between D-dimer levels and prognostic and pathological characteristics of PC patients. We first searched the databases of PubMed, Embase, The Cochrane Library, Web Of Science, CBM, VIP, CNKI and Wanfang to identify available studies. The relationship between pretreatment d-dimer levels and prognosis in PC patients was assessed using the combined hazard ratio (HR) and 95% confidence interval (CI). The combined odds ratio (OR) and 95% confidence interval (CI) were used in assessing the relationship between pathological characteristics and d-dimer levels in PC patients. Stata 12.0 software was used for all statistical analyses. In total, we included 13 studies involving 2777 patients. The results showed that elevated pre-treatment d -dimer levels were significantly associated with OS deterioration (HR = 1.46 95% CI: 1.34-1.59; p < 0.001). We also performed subgroup analyses based on sample size, d -dimer threshold, follow-up time, and HR source to further validate the prognostic value of pretreatment d -dimer levels in PC. In addition, according to the analysis, high pretreatment d -dimer levels in PC patients were associated with late tumor stage (OR = 4.78, 95% CI 1.73-13.20, p < 0. 005), larger tumor size (OR = 1.72, 95% CI 1.25-2.35, p < 0.005), and distant metastasis of tumor (OR = 5.06, 95% CI 2.45-10.43, p < 0.005) were significantly associated. In contrast, other clinicopathological factors, including age, gender and lymph node metastasis, were not associated with d-dimer levels. In conclusion, we found that high pre-treatment d-dimer levels were associated with a poor prognosis in PC patients, in relation to later tumor stage, larger tumor size and the development of distant metastases. Plasma d-dimer levels can be used as a biomarker of prognosis in PC patients.

Models for predicting venous thromboembolism in ambulatory patients with lung cancer: A systematic review and meta-analysis

AIMS

The incidence of venous thromboembolism (VTE) in patients with lung cancer is relatively high, and risk stratification models are vital for the targeted application of thromboprophylaxis. We aimed to review VTE risk prediction models that have been developed in patients with lung cancer and evaluated their performance.

METHODS AND RESULTS

Twenty-four eligible studies involving 123,493 patients were included. The pooled incidence of VTE within 12 months was 11 % (95 % CI 8 %-14 %). With the identified four VTE risk assessment tools, meta-analyses did not show a significant discriminatory capability of stratifying VTE risk for Khorana, PROTECHT and CONKO scores. The pooled sensitivity and specificity of the Khorana score were 24 % (95 % CI 11 %-44 %) and 84 % (95 % CI 73 %-91 %) at the 3-point cut-off, and 43 % (95 % CI 35 %-52 %) and 61 % (95 % CI 52 %-69 %) at the 2-point cut-off. However, a COMPASS-CAT score of ≥ 7 points indicated a significantly high VTE risk, with a RR of 4.68 (95 % CI 1.05-20.80).

CONCLUSIONS

The Khorana score lacked discriminatory capability in identifying patients with lung cancer at high VTE risk, regardless of the cut-off value. The COMPASS-CAT score had better performance, but further validation is needed. The results indicate the need for robust VTE risk assessment tools specifically designed and validated for lung cancer patients. Future research should include relevant biomarkers as important predictors and consider the combined use of risk tools. PROSPERO registration number: CRD42021245907.

Association between CT-based adipose variables, preoperative blood biochemical indicators and pathological T stage of clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is corelated with tumor-associated material (TAM), coagulation system and adipocyte tissue, but the relationships between them have been inconsistent. Our study aimed to explore the cut-off intervals of variables that are non-linearly related to ccRCC pathological T stage for providing clues to understand these discrepancies, and to effectively preoperative risk stratification.

Methods

This retrospective analysis included 218 ccRCC patients with a clear pathological T stage between January 1st, 2014, and November 30th, 2021. The patients were categorized into two cohorts based on their pathological T stage: low T stage (T1 and T2) and high T stage (T3 and T4). Abdominal and perirenal fat variables were measured based on preoperative CT images. Blood biochemical indexes from the last time before surgery were also collected. The generalized sum model was used to identify cut-off intervals for nonlinear variables.

Results

In specific intervals, fibrinogen levels (FIB) (2.63-4.06 g/L) and platelet (PLT) counts (>200.34 × 109/L) were significantly positively correlated with T stage, while PLT counts (<200.34 × 109/L) were significantly negatively correlated with T stage. Additionally, tumor-associated material exhibited varying degrees of positive correlation with T stage at different cut-off intervals (cut-off value: 90.556 U/mL).

Conclusion

Preoperative PLT, FIB and TAM are nonlinearly related to pathological T stage. This study is the first to provide specific cut-off intervals for preoperative variables that are nonlinearly related to ccRCC T stage. These intervals can aid in the risk stratification of ccRCC patients before surgery, allowing for developing a more personalized treatment planning.

D-dimer predicts venous thromboembolism in multiple myeloma: a nested case-control study

Background

Clinical risk assessment scores, such as IMPEDE VTE, can identify patients with multiple myeloma (MM) at high-risk of venous thromboembolism (VTE). Refinement of these scores, by including 1 or more biomarkers, could improve risk assessment.

Objectives

We sought to determine the association between soluble P-selectin (sP-selectin) and D-dimer with VTE in MM.

Methods

We identified 545 patients with newly diagnosed MM. Using a nested case-control design, we identified 38 cases of VTE within 6-months of MM treatment and 137 randomly selected controls. Using logistic regression, we examined the association between D-dimer and sP-selectin with VTE. We also analyzed the association after adjusting for IMPEDE VTE.

Results

Each 1-point increase in IMPEDE VTE score was associated with a 27% increase in odds of VTE (odds ratio 1.27; 95% CI 1.08-1.51; c-statistic 0.61; 95% CI 0.51-0.71). There was no association between sP-selectin and VTE. Each one increase in natural log of D-dimer was associated with a 44% increase in odds of VTE, so we assigned points (ranging from -2 to +2) to D-dimer values and incorporated them into IMPEDE VTE, forming IMPEDED VTE. There was a 30% increase in odds of VTE per each 1-point increase in IMPEDED VTE (OR 1.30; 95% CI 1.12-1.52; c-statistic 0.65; 95% CI 0.55-0.75).

Conclusion

Among patients with newly diagnosed MM starting chemotherapy, D-dimer was associated with increased odds of developing VTE within the subsequent 6-months. The addition of D-dimer to IMPEDE VTE-IMPEDED VTE-could improve prediction of VTE among patients with MM.

Contact system and intrinsic pathway activation in patients with advanced pancreatic cancer: a prospective cohort study

BACKGROUND

Despite high risk of venous thromboembolism (VTE) in patients with pancreatic cancer, there are little data on contact system activation in these patients.

OBJECTIVES

To quantify contact system and intrinsic pathway activation and subsequent VTE risk in patients with pancreatic cancer.

METHODS

Patients with advanced pancreatic cancer were compared with controls. Blood was drawn at baseline and patients were followed for 6 months. Complexes of proteases with their natural inhibitors, C1-esterase inhibitor (C1-INH), antithrombin (AT), or alpha-1 antitrypsin (α1at), were measured for complexes containing kallikrein (PKa:C1-INH), factor (F)XIIa (FXIIa:C1-INH), and FXIa (FXIa:C1-INH, FXIa:AT, FXIa:α1at). The association of cancer with complex levels was assessed in a linear regression model, adjusted for age, sex, and body mass index. In a competing risk regression model, we assessed associations between complex levels and VTE.

RESULTS

One hundred nine patients with pancreatic cancer and 22 controls were included. The mean age was 66 years (SD, 8.4) in the cancer cohort and 52 years (SD, 10.1) in controls. In the cancer cohort, 18 (16.7%) patients developed VTE during follow-up. In the multivariable regression model, pancreatic cancer was associated with increased complexes of PKa:C1-INH (P < .001), FXIa:C1-INH (P < .001), and FXIa:AT (P < .001). High FXIa:α1at (subdistribution hazard ratio, 1.48 per log increase; 95% CI, 1.02-2.16) and FXIa:AT (subdistribution hazard ratio, 2.78 highest vs lower quartiles; 95% CI, 1.10-7.00) were associated with VTE.

CONCLUSION

Complexes of proteases with their natural inhibitors were elevated in patients with cancer. These data suggest that the contact system and intrinsic pathway activation are increased in patients with pancreatic cancer.

Simple yet (more?) effective. Venous thromboembolism risk assessment model for germ cell tumour patients receiving first-line chemotherapy

BACKGROUND

Germ cell tumours (GCT) are highly curable malignancies. Venous thromboembolism (VTE) is a serious complication, needing better risk assessment models (RAM).

AIM

Identification of VTE incidence and risk factors in metastatic GCT patients starting first-line chemotherapy. Developing a RAM and comparing it to Khorana risk score (KRS) and Padua Prediction Score (PPS).

MATERIAL AND METHODS

We retrospectively analysed GCT patients staged IS-IIIC. VTE risk factors were identified with logistic regression. Area under curve of receiver operating characteristic (AUC-ROC), Akaike and Bayesian Information Criteria (AIC, BIC) were calculated for the developed RAM, KRS and PPS.

RESULTS

Among 495 eligible patients, VTE occurred in 69 (13.9%), including 40 prior to chemotherapy. Vein compression (OR: 8.96; 95% CI: 2.85-28.13; p < 0.001), clinical stage IIIB-IIIC (OR: 5.68; 95% CI: 1.82-17.70; p = 0.003) and haemoglobin concentration (OR for 1 g/dL decrease: 1.32; 95% CI: 1.03-1.67; p = 0.026) were significant in our RAM. KRS ≥ 3 (OR: 3.31; 95% CI: 1.77-6.20; p < 0.001), PPS 4-5 (OR: 3.06; 95% CI: 1.49-6.29; p = 0.002) and PPS > 5 (OR 8.05; 95% CI 3.79-17.13; p < 0.001) correlated with VTE risk. Diagnostic criteria (AUC-ROC, AIC, BIC) for the developed RAM, KRS and PPS were (0.885; 0.567; -1641), (0.588; 0.839; -1576) and (0.700; 0.799; -1585), respectively. In the numerical score, the optimal cut-off point for high-risk was ≥9, with sensitivity, specificity, positive and negative predictive value of 0.78, 0.77, 0.35 and 0.96, respectively.

CONCLUSIONS

Our RAM, based on vein compression, clinical stage and haemoglobin concentration proved superior to both KRS and PPS. VTE is frequent in GCT patients.

External validation and longitudinal application of the DO-GAP index to individualise survival prediction in idiopathic pulmonary fibrosis

Background

The Distance-Oxygen-Gender-Age-Physiology (DO-GAP) index has been shown to improve prognostication in idiopathic pulmonary fibrosis (IPF) compared to the Gender-Age-Physiology (GAP) score. We sought to externally validate the DO-GAP index compared to the GAP index for baseline risk assessment in patients with IPF. Additionally, we evaluated the utility of serial change in the DO-GAP index in predicting survival.

Methods

We performed an analysis of patients with IPF from the Pulmonary Fibrosis Foundation-Patient Registry (PFF-PR). Discrimination and calibration of the two models were assessed to predict transplant-free survival and IPF-related mortality. Joint longitudinal time-to-event modelling was utilised to individualise survival prediction based on DO-GAP index trajectory.

Results

There were 516 patients with IPF from the PFF-PR with available demographics, pulmonary function tests, 6-min walk test data and outcomes included in this analysis. The DO-GAP index (C-statistic: 0.73) demonstrated improved discrimination in discerning transplant-free survival compared to the GAP index (C-statistic: 0.67). DO-GAP index calibration was adequate, and the model retained predictive accuracy to identify IPF-related mortality (C-statistic: 0.74). The DO-GAP index was similarly accurate in the subset of patients taking antifibrotic medications. Serial change in the DO-GAP index improved model discrimination (cross-validated area under the curve: 0.83) enabling the personalised prediction of disease trajectory in individual patients.

Conclusion

The DO-GAP index is a simple, validated, multidimensional score that accurately predicts transplant-free survival in patients with IPF and can be adapted longitudinally in individual patients. The DO-GAP may also find use in studies of IPF to risk stratify patients and possibly as a clinical trial end-point.

Left ventricular ejection fraction and cardiac biomarkers for dynamic prediction of cardiotoxicity in early breast cancer

Background/Purpose

This study aims to quantify the utility of monitoring LVEF, hs-cTnT, and NT-proBNP for dynamic cardiotoxicity risk assessment in women with HER2+ early breast cancer undergoing neoadjuvant/adjuvant trastuzumab-based therapy.

Materials and methods

We used joint models of longitudinal and time-to-event data to analyze 1,136 echocardiography reports and 326 hs-cTnT and NT-proBNP measurements from 185 women. Cardiotoxicity was defined as a 10% decline in LVEF below 50% and/or clinically overt heart failure.

Results

Median pre-treatment LVEF was 64%, and 19 patients (10%) experienced cardiotoxicity (asymptomatic n = 12, during treatment n = 19). The pre-treatment LVEF strongly predicted for cardiotoxicity (subdistribution hazard ratio per 5% increase in pre-treatment LVEF = 0.68, 95%CI: 0.48–0.95, p = 0.026). In contrast, pre-treatment hs-cTnT and NT-proBNP were not consistently associated with cardiotoxicity. During treatment, the longitudinal LVEF trajectory dynamically identified women at high risk of developing cardiotoxicity (hazard ratio per 5% LVEF increase at any time of follow-up = 0.36, 95% CI: 0.2–0.65, p = 0.005). Thirty-four patients (18%) developed an LVEF decline ≥ 5% from pre-treatment to first follow-up (“early LVEF decline”). One-year cardiotoxicity risk was 6.8% in those without early LVEF decline and pre-treatment LVEF ≥ 60% (n = 117), 15.9% in those with early LVEF decline or pre-treatment LVEF < 60% (n = 65), and 66.7% in those with early LVEF decline and pre-treatment LVEF < 60% (n = 3), (Gray’s test p < 0.0001).

Conclusion

Cardiotoxicity risk is low in two thirds of women with HER2+ early breast cancer who have pre-treatment LVEF ≥ 60% and no early LVEF decline > 5% during trastuzumab-based therapy. The longitudinal LVEF trajectory but not hs-cTnT or NT-proBNP allows for a dynamic assessment of cardiotoxicity risk in this setting.

Unanswered questions in cancer-associated thrombosis

Cancer-associated venous thromboembolism (VTE) is a leading cause of morbidity and mortality in patients with cancer. Treatment of cancer-associated VTE comes with a heightened risk of anticoagulant-related bleeding that differs by choice of anticoagulant as well as by patient- and disease-specific risk factors. Available data from randomized controlled trials and observational studies in cancer-associated VTE suggest that direct oral anticoagulants are effective, continuing anticoagulation beyond six months is indicated in those with active cancer and that patients who develop 'breakthrough' thrombotic events can be effectively treated. We review the evidence that addresses these key clinical questions and offer pragmatic approaches in individualizing care. While significant investigative efforts over the past decade have made impactful advances, future research is needed to better define the factors that contribute to anticoagulant-related bleeding and VTE recurrence, in order to aid clinical decision-making that improves the care of patients with cancer-associated VTE.

ABO blood group type and risk of venous thromboembolism in patients with cancer

Venous thromboembolism (VTE) is common in patients with cancer. Although in the general population blood type non-O is associated with increased VTE risk, the impact of ABO blood type on risk of cancer-associated VTE has not been clarified. To determine the influence of ABO blood type on cancer-associated VTE risk, we conducted an analysis within the Vienna Cancer and Thrombosis Study, a prospective cohort study including patients with newly diagnosed or recurrent cancer observed for the primary outcome VTE. Restricted cubic spline analysis was performed and specific time-restricted subdistribution hazard ratios (SHR) were calculated to investigate the association between non-O blood type and VTE over time. One thousand, seven hundred and eight patients were included in the analysis (median follow-up time: 24 months; interquartile range: 10-24), and 151 patients developed VTE (8.8%). During the first 3 months of follow-up, there was no association between non-O blood type and VTE risk (SHR: 1.00; 95% confidence interval [CI]: 0.60-1.67). Thereafter, non-O blood type was associated with a higher VTE risk (SHR: 1.79; 95% CI: 1.12-2.85). Furthermore, non-O blood type was associated with increased VTE risk in patients with intermediate and low thrombotic risk tumor types (SHR: 1.73; 95% CI: 1.09-2.73) but not in very high-risk types (pancreatic, gastroesophageal, and brain cancer; SHR: 0.94; 95% CI: 0.55-1.61). This association was weakened after adjustment for factor VIII. Non-O blood type is a time-dependent predictor of VTE in patients with cancer. It is associated with increased VTE risk beyond 3 months of follow-up and in patients with intermediate- and low-risk tumor types.

Patterns of Thromboembolism in Patients with Advanced Pancreatic Cancer Undergoing First-Line Chemotherapy with FOLFIRINOX or Gemcitabine/nab-Paclitaxel

INTRODUCTION

Recent advances in prophylactic anticoagulation and antineoplastic treatment for advanced pancreatic cancer (aPC) warrant an updated reassessment of thromboembolic risk in this population. This multicenter retrospective cohort study aims to comprehensively characterize incidence, risk factors, and outcomes of venous (VTE) and arterial thromboembolism (ATE) in homogenously treated patients with aPC.

METHODS

Four hundred and fifty-five patients with aPC undergoing palliative first-line chemotherapy (Gemcitabine/nab-Paclitaxel (GN) or FOLIRINOX) were included. Primary outcomes were objectively confirmed VTE and/or ATE.

RESULTS

Over a median follow-up of 26 months, 86 VTE (cumulative incidence: 20.0%; 95% confidence interval [CI]: 16.3-24.0) and 11 ATE events (cumulative incidence: 2.8%; 95% CI: 1.5-4.9) were observed. VTE diagnosis was associated with increased mortality (transition hazard ratio [THR]: 1.59 [95% CI: 1.21-2.09]) and increased risk of cancer progression (THR: 1.47 [95% CI: 1.08-2.01]), while the impact of ATE on mortality was numerically but not statistically significant (THR: 1.85 [95% CI: 0.87-3.94]). The strongest predictor of increased VTE risk was history of cancer-associated VTE (subdistribution hazard ratio [SHR]: 3.29 [95% CI: 2.09-5.18]), while the Khorana score (SHR: 0.78 [0.57-1.06]) failed to predict VTE risk. A history of cerebrovascular disease was associated with markedly increased ATE risk (SHR: 22.05 [95% CI: 6.83-71.22], p < 0.001), especially ischemic stroke. Risk of VTE/ATE did not significantly differ according to type of first-line chemotherapy.

CONCLUSION

Patients with aPC undergoing palliative first-line chemotherapy with FOLFIRINOX or GN face a high risk for VTE/ATE and its diagnosis is linked to worse clinical outcomes. VTE-risk prediction models have limited ability to sub-stratify thrombotic events in this high-risk scenario.

Coagulome and the tumor microenvironment: an actionable interplay

Human tumors often trigger a hypercoagulable state that promotes hemostatic complications, including venous thromboembolism. The recent application of systems biology to the study of the coagulome highlighted its link to shaping the tumor microenvironment (TME), both within and outside of the vascular space. Addressing this link provides the opportunity to revisit the significance of biomarkers of hemostasis and assess the communication between vasculature and tumor parenchyma, an important topic considering the advent of immune checkpoint inhibitors and vascular normalization strategies. Understanding how the coagulome and TME influence each other offers exciting new prospects for predicting hemostatic complications and boosting the effectiveness of cancer treatment.

F. L. de Vos F, ten Tije AJ, Beerepoot LV, Tjan‐Heijnen VCG, van Laarhoven HWM, Hamberg P, Vulink AJE, Los M, Zwinderman AH, Ferwerda B, Lolkema MPJK, Steeghs N, Büller HR, Kamphuisen PW, van Es N. Evaluation of the Khorana, PROTECHT, and 5-SNP scores for prediction of venous thromboembolism in patients with cancer

BACKGROUND

The Khorana score is a validated tool to identify cancer patients at higher risk of venous thromboembolism (VTE).

OBJECTIVE

We compared its predictive performance to that of the clinical PROTECHT and the polygenic 5-SNP scores in patients who participated in the Dutch CPCT-02 study.

PATIENTS/METHODS

Data on VTE and its risk factors were retrospectively collected for 2729 patients with advanced stage solid tumors planned for systemic cancer treatment. Patients were followed for 6 months. Overall discriminatory performance of the scores was evaluated by time-dependent c-indices. The scores were additionally evaluated dichotomously in competing risk models.

RESULTS

A total of 160 (5.9%) patients developed VTE during follow-up. Time-dependent c-indices at 6 months for the Khorana, PROTECHT, and 5-SNP scores were 0.57 (95% confidence interval [CI]: 0.55-0.60), 0.60 (95% CI: 0.57-0.62), and 0.54 (95% CI: 0.51-0.57), respectively. The dichotomous scores classified 9.6%, 16.8%, and 9.5% as high-risk, respectively. VTE risk was about 2-fold higher among high-risk patients than low-risk patients for the Khorana (subdistribution hazard ratio [SHR] 1.9, 95% CI: 1.3-3.0), PROTECHT (SHR 2.1, 95% CI: 1.5-3.0), and 5-SNP scores (SHR 1.7, 95% CI: 1.03-2.8). The sensitivity at 6 months was 16.6% (95% CI: 10.5-22.7), 28.9% (95% CI: 21.5-36.3), and 14.9% (95% CI: 8.5-21.2), respectively.

CONCLUSIONS

Performance of the PROTECHT or 5-SNP score was not superior to that of the Khorana score. The majority of cancer patients who developed VTE during 6-month follow-up were not identified by these scores. Future directions for studies on cancer-associated VTE prediction may include combined clinical-genetic scores.

Longitudinal tumor fraction trajectories predict risk of progression in metastatic HR+ breast cancer patients undergoing CDK4/6 treatment

Despite improved clinical outcomes, intrinsic or acquired resistance to CDK4/6 inhibitor treatment has limited the success of this treatment in HR+ HER2- metastatic breast cancer patients. Biomarkers are urgently needed, and longitudinal biomarker measurements may harbor more dynamic predictive and prognostic information compared to single time point measurements. The aim of this study was to explore the longitudinal evolution of circulating tumor fractions within cell-free DNA assessed by an untargeted sequencing approach during CDK4/6 therapy and to quantify the potential association between longitudinal z-score measurements and clinical outcome by using joint models. Forty-nine HR+ HER2- metastatic breast cancer patients were enrolled, and z-score levels were measured at baseline and during 132 follow-up visits (median number of measurements per patient = 3, 25th -75th percentile: 3-5, range: 1-8). We observed higher baseline z-score levels (estimated difference 0.57, 95% CI: 0.147-0.983, P-value = 0.008) and a constant increase of z-score levels over follow-up time (overall P-value for difference in log z-score over time = 0.024) in patients who developed progressive disease. Importantly, the joint model revealed that elevated z-score trajectories were significantly associated with higher progression risk (HR of log z-score at any time of follow-up = 3.3, 95% CI, 1.44-7.55, P = 0.005). In contrast, single z-score measurement at CDK4/6 inhibitor treatment start did not predict risk of progression. In this prospective study, we demonstrate proof-of-concept that longitudinal z-score trajectories rather than single time point measurements may harbor important dynamic information on the development of disease progression in HR+ HER2- breast cancer patients undergoing CDK4/6 inhibitor treatment.

Risk Assessment Models for Thrombosis and Anticoagulant-Related Bleeding in Ambulatory Cancer Patients

Cancer patients have a high risk of developing venous thromboembolism and arterial thrombosis, along with an increased risk of anticoagulant-related bleeding with primary and secondary prophylaxis of cancer-associated thrombosis. Decisions on initiation, dosing, and duration of anticoagulant therapy for prevention and treatment of cancer-associated thrombosis are challenging, as clinicians have to balance patients' individual risk of (recurrent) thrombosis against the risk of bleeding complications. For this purpose, several dedicated risk assessment models for venous thromboembolism in cancer patients have been suggested. However, most of these scores perform poorly and have received limited to no validation. For bleeding and arterial thrombosis, no risk scores have been developed specifically for cancer patients, and treatment decisions remain based on clinical gestalt and rough and unstructured estimation of the risks. The aims of this review are to summarize the characteristics and performance of risk assessment scores for (recurrent) venous thromboembolism and discuss available data on risk assessment for bleeding and arterial thrombosis in the cancer population. This summary can help clinicians in daily practice to make a balanced decision when considering the use of risk assessment models for cancer-associated venous thromboembolism. Future research attempts should aim at improving risk assessment for arterial thrombosis and anticoagulant-related bleeding in cancer patients.

Contrasts in Glioblastoma-Venous Thromboembolism versus Bleeding Risk

Glioblastoma is among the tumor entities with an extreme thrombogenic potential and patients are at very high risk of developing a venous thromboembolism (VTE) over the course of the disease, with an incidence of up to 30% per year. Major efforts are currently being made to understand and gain novel insights into the underlying pathomechanisms of the development of VTE in patients with glioblastoma and to find appropriate biomarkers. Yet, patients with glioblastoma not only face a high thromboembolic risk but are also at risk of bleeding events. In the case of VTE, a therapeutic anticoagulation with low molecular weight heparin or, in the case of low bleeding risk, treatment with a direct oral anticoagulant, is recommended, according to recently published guidelines. With respect to an elevated bleeding risk in glioblastoma patients, therapeutic anticoagulation remains challenging in this patient group and prospective data for this vulnerable patient group are scarce, particularly with regard to direct oral anticoagulants.

Cost-Effective Machine Learning Based Clinical Pre-Test Probability Strategy for DVT Diagnosis in Neurological Intensive Care Unit

In order to overcome the shortage of the current costly DVT diagnosis and reduce the waste of valuable healthcare resources, we proposed a new diagnostic approach based on machine learning pre-test prediction models using EHRs. We examined the sociodemographic and clinical factors in the prediction of DVT with 518 NICU admitted patients, including 189 patients who eventually developed DVT. We used cross-validation on the training data to determine the optimal parameters, and finally, the applied ROC analysis is adopted to evaluate the predictive strength of each model. Two models (GLM and SVM) with the strongest ROC were selected for DVT prediction, based on which, we optimized the current intervention and diagnostic process of DVT and examined the performance of the proposed approach through simulations. The use of machine learning based pre-test prediction models can simplify and improve the intervention and diagnostic process of patients in NICU with suspected DVT, and reduce the valuable healthcare resource occupation/usage and medical costs.

Assessing the risk of venous thromboembolism (VTE) in ambulatory patients with cancer: Rationale and implementation of a pharmacist-led VTE risk assessment program in an ambulatory cancer centre

Objectives

The objectives of this paper were to identify and compare clinical prediction models used to assess the risk of venous thromboembolism (VTE) in ambulatory patients with cancer, as well as review the rationale and implementation of a pharmacist-led VTE screening program using the Khorana Risk Score model in an ambulatory oncology centre in Sault Ste. Marie, Ontario, Canada.

Data Sources

PubMed was used to identify clinical practice guidelines and review articles discussing risk prediction models used to assess VTE risk in ambulatory patients with cancer.

Data Summary

Three commonly used VTE risk prediction models in ambulatory patients with cancer: the Khorana Risk Score, Vienna Cancer and Thrombosis Study (CATS) and Protecht Score, were identified via literature review. After considering guideline recommendations, site-specific factors (i.e. laboratory costs, time pharmacists spent calculating VTE risk) and evidence from the CASSINI and AVERT trials, a novel pharmacist-led VTE risk assessment program using the Khorana Risk Score was developed during a fourth-year PharmD clinical rotation at the Algoma District Cancer Program (ADCP) [ambulatory cancer care centre]. ADCP patients with a Khorana Risk Score of ≥2 were referred to the hematologist for a full VTE workup. Considering limitations, inclusion and exclusion criteria of the CASSINI and AVERT trials, the hematologist and pharmacy team decided on appropriate initiation of thromboprophylaxis with a direct oral anticoagulant (DOAC).

Conclusions

The Khorana Risk Score was the chosen model used for the pharmacist-led VTE risk assessment program due to its user-friendly scoring algorithm, evidence from validation studies and clinical trials, as well as ease of integration into pharmacy workflow. More research is needed to determine if pharmacist-led VTE risk assessment programs will impact patient outcomes, such as morbidity and mortality, secondary to cancer-associated thrombosis.

Consensus statement of the Spanish Society of Internal Medicine and the Spanish Society of Medical Oncology on secondary thromboprophylaxis in patients with cancer

Up to 20% of cancer patients will develop some manifestation of venous thromboembolic disease (VTD) during their clinical course. VTD greatly impacts morbidity, mortality, quality of life and pharmaceutical expenditure. In addition, both thrombotic relapse and major haemorrhages derived from VTD treatment are more likely in oncological patients. To make the decision to establish secondary thromboprophylaxis as an indefinite treatment in these patients, it is important to review all the risk factors involved, whether related to the disease, the patient or the prior thrombotic event. The objectives of this consensus of the Spanish Society of Internal Medicine (Sociedad Española de Medicina Interna-SEMI) and the Spanish Society of Medical Oncology (Sociedad Española de Oncología Médica-SEOM) are to establish recommendations that help assess the risk of recurrence of VTD and haemorrhagic risk in patients with cancer, as well as to analyse the evidence that exists on the currently available drugs, which will allow the establishment of a protocol for shared decision-making with the informed patient.

C-Reactive Protein (CRP) Levels in Immune Checkpoint Inhibitor Response and Progression in Advanced Non-Small Cell Lung Cancer: A Bi-Center Study

Background: Biomarkers for predicting response to immune checkpoint inhibitors (ICI) are scarce and often lack external validation. This study provides a comprehensive investigation of pretreatment C-reactive protein (CRP) levels as well as its longitudinal trajectories as a marker of treatment response and disease outcome in patients with advanced non-small cell lung cancer (NSCLC) undergoing immunotherapy with anti PD-1 or anti PD-L1 agents. Methods: We performed a retrospective bi-center study to assess the association between baseline CRP levels and anti PD-(L)1 treatment outcomes in the discovery cohort (n = 90), confirm these findings in an external validation cohort (n = 101) and explore the longitudinal evolution of CRP during anti PD-(L)1 treatment and the potential impact of dynamic CRP changes on treatment response and disease outcome in the discovery cohort. Joint models were implemented to evaluate the association of longitudinal CRP trajectories and progression risk. Primary treatment outcomes were progression-free survival (PFS) and overall survival (OS), while the objective response rate (ORR) was a secondary outcome, respectively. Results: In the discovery cohort, elevated pretreatment CRP levels emerged as independent predictors of worse PFS (HR per doubling of baseline CRP = 1.37, 95% CI: 1.16–1.63, p < 0.0001), worse OS (HR per doubling of baseline CRP = 1.42, 95% CI: 1.18–1.71, p < 0.0001) and a lower ORR ((odds ratio (OR) of ORR per doubling of baseline CRP = 0.68, 95% CI: 0.51–0.92, p = 0.013)). In the validation cohort, pretreatment CRP could be fully confirmed as a predictor of PFS and OS, but not ORR. Elevated trajectories of CRP during anti PD-(L)1 treatment (adjusted HR per 10 mg/L increase in CRP = 1.22, 95% CI: 1.15–1.30, p < 0.0001), as well as a faster increases of CRP over time (HR per 10 mg/L/month faster increase in CRP levels = 13.26, 95% CI: 1.14–154.54, p = 0.039) were strong predictors of an elevated progression risk, whereas an early decline of CRP was significantly associated with a reduction in PFS risk (HR = 0.91, 95% CI: 0.83–0.99, p = 0.036), respectively. Conclusion: These findings support the concept that CRP should be further explored by future prospective studies as a simple non-invasive biomarker for assessing treatment benefit during anti PD-(L)1 treatment in advanced NSCLC.

Dynamics of D-dimer in non-small cell lung cancer patients receiving radical surgery and its association with postoperative venous thromboembolism

BACKGROUND

Venous thromboembolism (VTE) occurs at a high rate after lung cancer surgery and can be attributed to various clinical risk factors. Here, we aimed to determine whether early detection of perioperative D-dimer and risk-stratified cutoff values would improve the diagnostic efficacy of VTE.

METHODS

In this case-control study, D-dimer results were acquired from 171 non-small cell lung cancer (NSCLC) patients preoperatively and at the first, third, and fifth day after surgery. VTE was confirmed by Doppler ultrasonography and computer tomography pulmonary angiography (CTPA). Repeated measures ANOVA was used to analyze how D-dimer changed with time and the effects of risk factors on D-dimer levels. We then compared sensitivity, specificity and negative predictive value, using both adjusted and unadjusted cutoff values.

RESULTS

VTE occurred in 23 patients (13.5%) of the study population. D-dimer levels increased unsustainably after lung cancer surgery (P < 0.001) due to a trough on the third day, and patients who had undergone thoracotomy (P < 0.001) and those at a more advanced tumor stage (P = 0.037) had higher D-dimer levels. Area under the curve of D-dimer was greatest on the third day (0.762 [P < 0.001, 95% CI: 0.643-0.882]). Applying stratified cutoff values improved the specificity in the video-assisted thoracoscopy surgery (VATS) (P = 0.004) and thoracotomy groups (P < 0.001).

CONCLUSIONS

D-dimer levels elevated with fluctuation in NSCLC patients after surgery. Surgical options and tumor stages had an impact on D-dimer levels. With regard to VTE diagnosis, stratified cutoff values by these two factors showed better accuracy compared with a collective one..

KEY POINTS

SIGNIFICANT FINDINGS OF THE STUDY: The changing pattern of perioperative D-dimer levels in NSCLC patients who received surgical therapy in a major teaching hospital in Beijing, China was revealed.

WHAT THIS STUDY ADDS

Risk-stratified D-dimer cutoff values adjusted to surgical methods and disease stages would benefit the exclusion of postoperative venous thromboembolism.

Dynamic assessment of venous thromboembolism risk in patients with cancer by longitudinal D-Dimer analysis: A prospective study

BACKGROUND

Venous thromboembolism (VTE) is a frequent complication of cancer. Elevated D-dimer is associated with an increased risk of cancer-associated VTE. Whether changes in D-dimer over time harbor additional prognostic information that may be exploited clinically for dynamic prediction of VTE is unclear.

OBJECTIVES

To explore the potential role of longitudinal D-dimer trajectories for personalized prediction of cancer-associated VTE.

PATIENTS/METHODS

A total of 167 patients with active malignancy were prospectively enrolled (gastrointestinal: n = 59 [35%], lung: n = 56 [34%], brain: n = 50 [30%], others: n = 2 [1%]; metastatic disease: n = 74 [44%]). D-dimer (median = 0.8 µg/mL [25th-75th percentile: 0.4-2.0]) was measured at baseline and during 602 monthly follow-up visits. Joint models of longitudinal and time-to-event data were implemented to quantify the association between D-dimer trajectories and prospective risk of VTE.

RESULTS

VTE occurred in 20 patients (250-day VTE risk = 12.1%, 95% confidence interval [CI], 7.8-18.5). D-dimer increased by 34%/month (0.47 µg/mL/month, 95% CI, 0.22-0.72, P < .0001) in patients who developed VTE, but remained constant in patients who did not develop VTE (change/month = -0.06 µg/mL, 95% CI, -0.15 to 0.02, P = .121). In joint modeling, a doubling of the D-dimer trajectory was associated with a 2.8-fold increase in the risk of VTE (hazard ratio = 2.78, 95% CI, 1.69-4.58, P < .0001). This finding was independent of established VTE risk factors. Highly personalized, dynamic predictions of VTE conditional on individual patients' D-dimer trajectories could be obtained.

CONCLUSIONS

D-dimer increases before the onset of cancer-associated VTE, but remains constant over time in patients without VTE. This study represents proof-of-concept that longitudinal trajectories of D-Dimer may advance the personalized assessment of VTE risk in the oncologic setting.

Incidence, Therapy, and Bleeding Risk-Cancer- Associated Thrombosis in Patients with Glioblastoma

Cancer is an independent risk factor for the development of venous thromboembolism (VTE). Glioblastomas are amongst cancer types with the most thrombogenic potential and patients are at a particularly high risk of VTE with an incidence up to 20-30% per year. Currently, major efforts are underway to gain novel insights into risk factors and pathomechanisms to provide a better understanding of development of VTE in patients with primary brain tumors. Treatment of VTE requires therapeutic anticoagulation, which accordingly to recently-published guidelines should be performed using low molecular weight heparin or, in case of low bleeding risk, using a direct oral anticoagulant. However, this can be very challenging due to an increased risk of intracranial hemorrhage in this patient group. Furthermore, limited data are available on the subgroup of patients with primary brain tumors.