ABSTRACT

PURPOSE: Therapy for cancer-associated venous thromboembolism (VTE) includes long-term anticoagulation, which may have substantial impact on the health-related quality of life (HRQL) of patients. We assessed patient-reported outcomes to characterize the HRQL associated with VTE treatment and to begin to examine those HRQL elements impacting anticoagulation adherence (AA).

METHODS: Participants were adult cancer patients with confirmed symptomatic acute lower extremity deep venous thrombosis. Patients were excluded if there was an indication for anticoagulation other than VTE, ECOG performance status >3, or life expectancy < 3 months. Participants were assessed with a self-reported adherence tool. HRQL was measured with a 6-domain questionnaire using a seven-point Likert scale. Evaluations were performed at 30 days and 3 months after enrollment. For the primary objective, an overall adherence rate was calculated at each time point of evaluation. For the HRQL domains, non-parametric testing was used to compare results between subgroups.

RESULTS: Seventy-four patients were enrolled. AA and HRQL at 30 days and 3 months were assessed in 50 and 36 participants, respectively. At 30 days the AA rate was 90%, and at 3 months it was 83%. In regard to HRQL, patients suffered frequent and moderate-severe distress in the domains of emotional and physical symptoms, sleep disturbance, and limitations to physical activity. An association between emotional or physical distress and AA was observed.

CONCLUSION: Patients with VTE suffer a substantial impairment of their HRQL. Increased emotional distress correlated with better long-term AA. These results can be used to inform additional research aimed at developing novel strategies to improve AA.

PMID:37801086 | DOI:10.1007/s00520-023-08073-y

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PubMed articles on: Cancer & VTE/PE

Two Cases of Catheter-Related Venous Thrombosis Treated with Direct Oral Anticoagulants(DOAC)

Gan To Kagaku Ryoho. 2023 Sep;50(9):993-996.

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

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PubMed articles on: Cancer & VTE/PE

Computer image analysis with artificial intelligence: a practical introduction to convolutional neural networks for medical professionals

Postgrad Med J. 2023 Oct 4:qgad095. doi: 10.1093/postmj/qgad095. Online ahead of print.

ABSTRACT

Artificial intelligence tools, particularly convolutional neural networks (CNNs), are transforming healthcare by enhancing predictive, diagnostic, and decision-making capabilities. This review provides an accessible and practical explanation of CNNs for clinicians and highlights their relevance in medical image analysis. CNNs have shown themselves to be exceptionally useful in computer vision, a field that enables machines to 'see' and interpret visual data. Understanding how these models work can help clinicians leverage their full potential, especially as artificial intelligence continues to evolve and integrate into healthcare. CNNs have already demonstrated their efficacy in diverse medical fields, including radiology, histopathology, and medical photography. In radiology, CNNs have been used to automate the assessment of conditions such as pneumonia, pulmonary embolism, and rectal cancer. In histopathology, CNNs have been used to assess and classify colorectal polyps, gastric epithelial tumours, as well as assist in the assessment of multiple malignancies. In medical photography, CNNs have been used to assess retinal diseases and skin conditions, and to detect gastric and colorectal polyps during endoscopic procedures. In surgical laparoscopy, they may provide intraoperative assistance to surgeons, helping interpret surgical anatomy and demonstrate safe dissection zones. The integration of CNNs into medical image analysis promises to enhance diagnostic accuracy, streamline workflow efficiency, and expand access to expert-level image analysis, contributing to the ultimate goal of delivering further improvements in patient and healthcare outcomes.

PMID:37794609 | DOI:10.1093/postmj/qgad095

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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

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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

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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.