ABSTRACT

Arterial (ATE) and venous (VTE) thromboembolic complications are common causes of morbidity and mortality in BCR-ABL-negative myeloproliferative neoplasms (MPNs). However, there are few studies that include all MPN subtypes and focus on both MPN-associated ATE and VTE. In our single-center retrospective study of 832 MPN patients, a total of 180 first thromboembolic events occurred during a median follow-up of 6.6 years (range: 0-37.6 years), of which 105 were VTE and 75 were ATE. The probability of a vascular event at the end of the follow-up period was 36.2%, and the incidence rate for all first ATE/VTE was 2.43% patient/year. The most frequent VTE localizations were deep vein thrombosis with or without pulmonary embolism (incidence rate: 0.59% patient/year), while strokes were the most frequent ATE with an incidence rate of 0.32% patient/year. When comparing the group of patients with ATE/VTE (n = 180) and the group without such an event (n = 652) using multivariate Cox regression analyses, patients with polycythemia vera (hazard ratio [HR]: 1.660; [95% confidence interval [CI] 1.206, 2.286]) had a significantly higher risk of a thromboembolic event than the other MPN subtypes. In contrast, patients with a CALR mutation had a significantly lower risk of thromboembolism compared with JAK2-mutated MPN patients (HR: 0.346; [95% CI: 0.172, 0.699]). In summary, a high incidence of MPN-associated VTE and ATE was observed in our retrospective study. While PV patients or generally JAK2-mutated MPN patients had a significantly increased risk of such vascular events, this risk was reduced in CALR-mutated MPN patients.

PMID:37813367 | DOI:10.1055/a-2159-8767

19:08

PubMed articles on: Cancer & VTE/PE

Thrombin Generation Markers as Predictors of Cancer-Associated Venous Thromboembolism: A Systematic Review

Semin Thromb Hemost. 2023 Oct 9. doi: 10.1055/s-0043-1775856. Online ahead of print.

ABSTRACT

Venous thromboembolism (VTE) is a main contributor to morbidity and mortality in cancer patients. Biomarkers with the potential to predict cancer-associated VTE are continually sought. Of these, markers of thrombin generation present a likely option. The present systematic review examines the ability of three widely used biomarkers of thrombin generation: prothrombin fragment 1.2 (F1.2), thrombin-antithrombin complex (TAT), and ex vivo thrombin generation, to predict VTE in both solid and hematologic adult cancer patients. Relevant studies were identified in the PubMed and Embase databases, and the review conformed to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Each study was evaluated using the quality assessment tool from the National Heart, Lung, and Blood Institute. The review protocol was published on PROSPERO with identifier CRD42022362339. In total, 24 papers were included in the review: 11 reporting data on F1.2, 9 on TAT, and 12 on ex vivo thrombin generation. The quality ratings of the included studies varied from good (n = 13), fair (n = 8), to poor (n = 3) with a high heterogenicity. However, F1.2, TAT complex, and ex vivo thrombin generation were all found to be associated with the development of VTE. This association was most pronounced for F1.2. Furthermore, the determination of F1.2 was able to improve the precision of several established risk assessment scores. In conclusion, markers of thrombin generation were found to be elevated in cancer patients with VTE, and particularly, F1.2 was found to be a promising predictor of cancer-associated VTE.

PMID:37813372 | DOI:10.1055/s-0043-1775856

19:08

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

19:08

PubMed articles on: Cancer & VTE/PE

Complications of Central Venous Access Devices Used in Palliative Care Settings for Terminally Ill Cancer Patients: A Systematic Review and Meta-Analysis

Cancers (Basel). 2023 Sep 25;15(19):4712. doi: 10.3390/cancers15194712.