Efficacy and Toxicity of Folfoxiri for Patients with Metastatic Colorectal Cancer

BACKGROUND: In recent times, scientists have found new treatments for colorectal cancer patients. AIM: The study is to evaluate the efficacy and toxicity of triplet combination chemotherapy of 5-fluorouracil/leucovorin, oxaliplatin, and irinotecan (FOLFOXIRI) for patients with metastatic colorectal cancer in stage IV. METHODS: Uncontrolled clinical trial carried on 39 stage IV colorectal cancer patients. RESULTS: The overall response rate of the treatment was 79.4%. The average progression-free survival was 13.4 ± 9 months. The overall survival rate at 12th month and 24th month were 90% and 76%, respectively. The proportion of granulocytopenia was 48.9%, no grade 3 or 4. Side effect beyond hematology was most seen in hepatic toxicity with 52.5%, mainly at grade 1. Vomiting was 18.3%, all at grade 1. Other adverse event was very low at percentage. CONCLUSIONS: The triplet combination FOLFOXIRI chemotherapy improves the outcome of patients with metastatic colorectal cancer regarding rate of response, overall survival rate and progression-free survival, and the level of toxicity was acceptable

Economic burden of venous thromboembolism in surgical patients: A propensity score analysis from the national claims database in Vietnam.

BACKGROUND:Venous thromboembolism (VTE) associated with surgery can cause serious comorbidities or death and imposes a substantial economic burden to society. The study examined VTE cases after surgery to determined how this condition imposed an economic burden on patients based on the national health insurance reimbursement database. Methods: This retrospective analysis adopted the public payer's perspective. The direct medical cost was estimated using data from the national claims database of Vietnam from Jan 1, 2017 to Sep 31, 2018. Adult patients who underwent surgeries were recruited for the study. Patients with a diagnostic code of up to 90 days after surgery were considered VTE cases with the outcome measure being the surgery-related costs within 90 days. RESULTS:The 90-day cost of VTE patients was found to be US$2,939. The rate of readmission increased by 5.4 times, the rate of outpatient visits increased by 1.8 times and total costs over 90 days in patients with VTE undergoing surgery increased by 2.2 times. Estimation using propensity score matching method showed that an increase of US$1,019 in the 90-day cost of VTE patients. CONCLUSION:The VTE-related costs can be used to assess the potential economic benefit and cost-savings from prevention efforts

Convolutional Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening for Vietnamese patients

Nowadays, breast cancer is one of the leading cancers in Vietnam, and it causes approximately 6000 deaths every year. The rate of breast cancer patients was calculated as 26.4/100000 persons in 2018. There are 21,555 new cases reported in 2020. However, these figures can be reduced with early detection and diagnosis of breast cancer disease in women through mammographic imaging. In many hospitals in Vietnam, there is a lack of experienced breast cancer radiologists. Therefore, it is helpful to develop an intelligent system to improve radiologists’ performance in breast cancer screening for Vietnamese patients. Our research aims to develop a convolutional neural network-based system for classifying breast cancer X-Ray images into three classes of BI-RADS categories as BI-RADS 1 (“normal”), BI-RADS 23 (“benign”) and BI-RADS 045 (“incomplete and malignance”). This classification system is developed based on the convolutional neural network with ResNet 50. The system is trained and tested on a breast cancer image dataset of Vietnamese patients containing 7912 images provided by Hanoi Medical University Hospital radiologists. The system accuracy uses the testing set achieved a macAUC (a macro average of the three AUCs) of 0.754. To validate our model, we performed a reader study with the breast cancer radiologists of the Hanoi Medical University Hospital, reading about 500 random images of the test set. We confirmed the efficacy of our model, which achieved performance comparable to a committee of two radiologists when presented with the same data. Additionally, the system takes only 6 seconds to interpret a breast cancer X-Ray image instead of 450 seconds interpreted by a Vietnamese radiologist. Therefore, our system can be considered as a “second radiologist,” which can improve radiologists’ performance in breast cancer screening for Vietnamese patients