ABSTRACT

The implantation of a totally implantable central venous(CV)access port is considered a risk factor for venous thromboembolism( VTE). In the treatment of catheter-related thrombosis(CRT), both European and American guidelines recommend anticoagulation therapy with catheters in place. We experienced 2 cases of upper extremity deep vein thrombosis (UEDVT)after the implantation of CV access ports through the left subclavian vein for adjuvant chemotherapy in patients with resected breast cancer. Both patients were successfully treated with direct oral anticoagulants(DOAC) while the port remained in place with a careful follow-up that included monitoring of serum D-dimer levels. The administration of DOAC to CRT that develops in patients undergoing postoperative adjuvant chemotherapy for breast cancer may be relatively safe, with a low potential for adverse events such as bleeding.

PMID:37800295

22:20

PubMed articles on: Cancer & VTE/PE

Artificial intelligence in the prediction of venous thromboembolism: A systematic review and pooled analysis

Eur J Haematol. 2023 Oct 4. doi: 10.1111/ejh.14110. Online ahead of print.

ABSTRACT

BACKGROUND: Accurate diagnostic and prognostic predictions of venous thromboembolism (VTE) are crucial for VTE management. Artificial intelligence (AI) enables autonomous identification of the most predictive patterns from large complex data. Although evidence regarding its performance in VTE prediction is emerging, a comprehensive analysis of performance is lacking.

AIMS: To systematically review the performance of AI in the diagnosis and prediction of VTE and compare it to clinical risk assessment models (RAMs) or logistic regression models.

METHODS: A systematic literature search was performed using PubMed, MEDLINE, EMBASE, and Web of Science from inception to April 20, 2021. Search terms included "artificial intelligence" and "venous thromboembolism." Eligible criteria were original studies evaluating AI in the prediction of VTE in adults and reporting one of the following outcomes: sensitivity, specificity, positive predictive value, negative predictive value, or area under receiver operating curve (AUC). Risks of bias were assessed using the PROBAST tool. Unpaired t-test was performed to compare the mean AUC from AI versus conventional methods (RAMs or logistic regression models).

RESULTS: A total of 20 studies were included. Number of participants ranged from 31 to 111 888. The AI-based models included artificial neural network (six studies), support vector machines (four studies), Bayesian methods (one study), super learner ensemble (one study), genetic programming (one study), unspecified machine learning models (two studies), and multiple machine learning models (five studies). Twelve studies (60%) had both training and testing cohorts. Among 14 studies (70%) where AUCs were reported, the mean AUC for AI versus conventional methods were 0.79 (95% CI: 0.74-0.85) versus 0.61 (95% CI: 0.54-0.68), respectively (p < .001). However, the good to excellent discriminative performance of AI methods is unlikely to be replicated when used in clinical practice, because most studies had high risk of bias due to missing data handling and outcome determination.

CONCLUSION: The use of AI appears to improve the accuracy of diagnostic and prognostic prediction of VTE over conventional risk models; however, there was a high risk of bias observed across studies. Future studies should focus on transparent reporting, external validation, and clinical application of these models.

PMID:37794526 | DOI:10.1111/ejh.14110

22:20

PubMed articles on: Cancer & VTE/PE

Development and validation of a new risk assessment model for immunomodulatory drug-associated venous thrombosis among Chinese patients with multiple myeloma

Thromb J. 2023 Oct 4;21(1):105. doi: 10.1186/s12959-023-00534-y.

ABSTRACT

BACKGROUND: Individuals with multiple myeloma (MM) receiving immunomodulatory drugs (IMiDs) are at risk of developing venous thromboembolism (VTE), a serious complication. There is no established clinical model for predicting VTE in the Chinese population. We develop a new risk assessment model (RAM) for IMiD-associated VTE in Chinese MM patients.

METHODS: We retrospectively selected 1334 consecutive MM patients receiving IMiDs from 16 medical centers in China and classified them randomly into the derivation and validation cohorts. A multivariate Cox regression model was used for analysis.

RESULTS: The overall incidence of IMiD-related VTE in Chinese MM patients was 6.1%. Independent predictive factors of VTE (diabetes, ECOG performance status, erythropoietin-stimulating agent use, dexamethasone use, and VTE history or family history of thrombosis) were identified and merged to develop the RAM. The model identified approximately 30% of the patients in each cohort at high risk for VTE. The hazard ratios (HRs) were 6.08 (P < 0.001) and 6.23 (P < 0.001) for the high-risk subcohort and the low-risk subcohort, respectively, within both the derivation and validation cohorts. The RAM achieved satisfactory discrimination with a C statistic of 0.64. The stratification approach of the IMWG guidelines yielded respective HRs of 1.77 (P = 0.053) and 1.81 (P = 0.063). The stratification approach of the SAVED score resulted in HRs of 3.23 (P = 0.248) and 1.65 (P = 0.622), respectively. The IMWG guideline and the SAVED score-based method yielded C statistics of 0.58 and 0.51, respectively.

CONCLUSIONS: The new RAM outperformed the IMWG guidelines and the SAVED score and could potentially guide the VTE prophylaxis strategy for Chinese MM patients.

PMID:37794471 | PMC:PMC10552366 | DOI:10.1186/s12959-023-00534-y

22:20

PubMed articles on: Cancer & VTE/PE

Ruptured Baker's cyst presenting with a palpable popliteal mass and crescent sign

BMJ Case Rep. 2023 Oct 4;16(10):e257869. doi: 10.1136/bcr-2023-257869.

NO ABSTRACT

PMID:37793850 | PMC:PMC10551967 | DOI:10.1136/bcr-2023-257869

22:20

PubMed articles on: Cancer & VTE/PE

Monocyte recruitment in venous pulmonary embolism at time of cancer diagnosis in upper gastrointestinal cancer patients

J Thromb Thrombolysis. 2023 Oct 4. doi: 10.1007/s11239-023-02897-5. Online ahead of print.

ABSTRACT

Upper gastrointestinal cancer is frequently complicated by venous thromboembolisms (VTE), especially pulmonary embolisms (PE) increase the mortality rate. Monocytes are a part of the innate immune system and up-regulation may indicate an ongoing inflammatory response or infectious disease and has lately been associated with a moderate risk of suffering from VTE. This prospectively study aims to compare the incidence of pulmonary embolism with markers of coagulation and compare it to the absolute monocyte count. A consecutive cohort of 250 patients with biopsy proven upper gastrointestinal cancer (i.e. pancreas, biliary tract, esophagus and gastric cancer) where included at the time of cancer diagnosis and before treatment. All patients underwent bilateral compression ultrasonography for detection of deep vein thrombosis (DVT). Of these 143 had an additionally pulmonary angiografi (CTPA) with the staging computer tomography. 13 of 250 patients (5.2%) had a DVT and 11 of 143 (7.7%) had CTPA proven PE. PE was significantly more common among patients with elevated D-dimer (OR 11.62, 95%CI: 1.13-119, P = 0.039) and elevated absolute monocyte count (OR 7.59, 95%CI: 1.37-41.98, P = 0.020). Only patients with pancreatic cancer had a significantly higher risk of DVT (OR 11.03, 95%CI: 1.25-97.43, P = 0.031). The sensitivity of absolute monocyte count was 63.6 (95%CI: 30.8-89.1) and specificity 80.3 (95%CI: 72.5-86.7), with a negative predictive value of 96.4 (95%CI: 91-99) in PE. An increased absolute monocyte count was detected in patients suffering from PE but not DVT, suggesting a possible interaction with the innate immune system.

PMID:37792208 | DOI:10.1007/s11239-023-02897-5

22:20

PubMed articles on: Cancer & VTE/PE

Machine-Learning-Assisted Procoagulant Extracellular Vesicle Barcode Assay toward High-Performance Evaluation of Thrombosis-Induced Death Risk in Cancer Patients

ACS Nano. 2023 Oct 4. doi: 10.1021/acsnano.3c04615. Online ahead of print.