Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Given that low-dose computed tomography significantly amplifies image noise due to the mitigation of radiation exposure,which degrades image quality and lowers the precision of clinical diagnoses,a novel model incorporating convolutional neural network and Transformer is established,in which an intra-patch feature extraction module is used to effectively preserve tiny details in the image.A double attention Transformer is constructed by incorporating a multiple-input channel attention module into the self-attention for tackling the problem of incorrect restoration of texture details during denoising using Swin Transformer.AAPM dataset is used for testing,and the results demonstrate that the proposed algorithm not only surpasses the existing algorithms in denoising performance,but also excels in preserving tiny details in the image.

Background: Shared decision making using patient decision aids (PtDAs) was established over a decade ago, but few studies have evaluated its efficacy in Asian countries. We therefore evaluated the application of PtDAs in a decision conflict between two muscle relaxant reversal agents, neostigmine and sugammadex, and sequentially analyzed the regional differences and operating room turnover rates. Methods: This multicenter, outcome-assessor-blind, randomized controlled trial included 3,132 surgical patients from two medical centers admitted between March 2020 and August 2020. The patients were randomly divided into the classical and PtDA groups for pre-anesthesia consultations. Their clinicodemographic characteristics were analyzed to identify variables influencing the choice of reversal agent. On the day of the pre-anesthesia consultation, the patients completed the four SURE scale (sure of myself, understand information, risk-benefit ratio, encouragement) screening items. The operating turnover rates were also evaluated using anesthesia records. Results: Compared with the classical group, the PtDA group felt more confident about receiving sufficient medical information (P < 0.001), felt better informed about the advantages and disadvantages of the medications (P < 0.001), exhibited a superior understanding of the benefits and risks of their options (P < 0.001), and felt surer about their choice (P < 0.001). Moreover, the PtDA group had a significantly greater tendency to choose sugammadex over neostigmine (P < 0.001). Conclusions PtDA interventions in pre-anesthesia consultations provided surgical patients with clear knowledge and better support. PtDAs should be made available in other medical fields to enhance shared clinical decision-making.

Objective: The purpose of this study is to investigate the safety, tolerability and efficacy of titrating dose of rivastigmine oral solution in patients with mild to moderate Alzheimer’s disease (AD) in Taiwan. Methods: We recruited 108 mild to moderate AD patients with RivastⓇ (rivastigmine oral solution 2 mg/ml) treatment for 52 weeks. We recorded the demographic characteristics, initial cognition by mini-mental state examination (MMSE), initial global status by clinical dementia rating (CDR) with CDR-Sum of Boxes (CDR-SB), initial dose, and titrating dose at each visit. We investigated the adherence, proportion of possible side effects, optimal dose, and time to optimal dose. We demonstrated the proportion of cognitive decline and its possible risk factors. Results: During the course, 9 patients discontinued the rivastigmine oral solution due to poor compliance or preference. Twelve out of 99 patients (12.1%) reported possible side effects. Among 87 patients, the mean age was 77.2 ± 9.0 years ago with female predominant (65.2%). The optimal dose was 3.6 ± 1.4 ml in average and 4 ml (n = 31, 35.6%) in mode. The duration to optimal dose was 12.5 ± 10.2 weeks and 24 weeks (n = 35, 40.2%) in mode. It presented 25% with cognitive decline in MMSE, 27% with global function decline in CDR and 63% with global function decline in CDR-SB. Conclusion We demonstrated the clinical experience of rivastigmine oral solution in mild to moderate AD patients. It suggested rivastigmine oral solution 4ml is the optimal dose with 24 weeks to the optimal dose for at least one third of patients.

Objective: The purpose of this study is to investigate the safety, tolerability and efficacy of titrating dose of rivastigmine oral solution in patients with mild to moderate Alzheimer’s disease (AD) in Taiwan. Methods: We recruited 108 mild to moderate AD patients with RivastⓇ (rivastigmine oral solution 2 mg/ml) treatment for 52 weeks. We recorded the demographic characteristics, initial cognition by mini-mental state examination (MMSE), initial global status by clinical dementia rating (CDR) with CDR-Sum of Boxes (CDR-SB), initial dose, and titrating dose at each visit. We investigated the adherence, proportion of possible side effects, optimal dose, and time to optimal dose. We demonstrated the proportion of cognitive decline and its possible risk factors. Results: During the course, 9 patients discontinued the rivastigmine oral solution due to poor compliance or preference. Twelve out of 99 patients (12.1%) reported possible side effects. Among 87 patients, the mean age was 77.2 ± 9.0 years ago with female predominant (65.2%). The optimal dose was 3.6 ± 1.4 ml in average and 4 ml (n = 31, 35.6%) in mode. The duration to optimal dose was 12.5 ± 10.2 weeks and 24 weeks (n = 35, 40.2%) in mode. It presented 25% with cognitive decline in MMSE, 27% with global function decline in CDR and 63% with global function decline in CDR-SB. Conclusion We demonstrated the clinical experience of rivastigmine oral solution in mild to moderate AD patients. It suggested rivastigmine oral solution 4ml is the optimal dose with 24 weeks to the optimal dose for at least one third of patients.

With obesity rate consistently increasing,a strong relationship between obesity and fatty liver disease has been discovered.More than 90％of bariatric surgery patients also have non-alcoholic fatty liver diseases(NAFLDs).NAFLD and non-alcoholic steatohepatitis(NASH),which are the hepatic manifesta-tions of metabolic syndrome,can lead to liver carcinogenesis.Unfortunately,there is no effective medicine that can be used to treat NASH or liver cancer.Thus,it is critically important to understand the mechanism underlying the development of these diseases.Extensive evidence suggests that microRNA 22(miR-22)can be a diagnostic marker for liver diseases as well as a treatment target.This review paper focuses on the roles of miR-22 in metabolism,steatosis,and liver carcinogenesis.Literature search is limited based on the publications included in the PubMed database in the recent 10 years.

Hepatocellular carcinoma(HCC)is one of the most common malignant tumors with a low survival rate.The identification of mechanisms underlying the development of HCC helps uncover cellular and mo-lecular targets for the diagnosis,prevention,and treatment of HCC.Golgi protein 73(GP73)level is up-regulated in HCC patients and potentially can be a therapeutic target.Despite many studies devoted to GP73 as a marker for HCC early diagnosis,there is little discussion about the function of GP73 in HCC tumorigenesis.Given the poor response to currently available HCC therapies,a better understanding of the role of GP73 in HCC may provide a new therapeutic target for HCC.The current paper summarizes the role of GP73 as a diagnostic marker as well as its roles in liver carcinogenesis.Its roles in other types of cancer are also discussed.

Hepatocellular carcinoma(HCC)is a malignant tumor with a fairly poor prognosis(5-year survival of less than 50％).Using sorafenib,the only food and drug administration(FDA)-approved drug,HCC cannot be effectively treated;it can only be controlled at most for a couple of months.There is a great need to develop efficacious treatment against this debilitating disease.Glypican-3(GPC3),a member of the glypican family that attaches to the cell surface by a glycosylphosphatidylinositol anchor,is overex-pressed in HCC cases and is elevated in the serum of a large proportion of patients with HCC.GPC3 expression contributes to HCC growth and metastasis.Furthermore,several different types of antibodies targeting GPC3 have been developed.The aim of this review is to summarize the current literatures on the GPC3 expression in human HCC,molecular mechanisms of GPC3 regulation and antibodies targeting GPC3.

PURPOSE: Renal cell carcinoma (RCC) and melanoma have been considered ‘radioresistant’ due to the fact that they do not respond to conventionally fractionated radiation therapy. Stereotactic radiosurgery (SRS) provides high-dose radiation to a defined target volume and a limited number of studies have suggested the potential effectiveness of SRS in radioresistant histologies. We sought to determine the effectiveness of SRS for the treatment of patients with radioresistant brain metastases.MATERIALS AND METHODS: We performed a retrospective review of our institutional database to identify patients with RCC or melanoma brain metastases treated with SRS. Treatment response were determined in accordance with the Response Evaluation Criteria in Solid Tumors.RESULTS: We identified 53 radioresistant brain metastases (28% RCC and 72% melanoma) treated in 18 patients. The mean target volume and coverage was 6.2 ± 9.5 mL and 95.5% ± 2.9%, respectively. The mean prescription dose was 20 ± 4.9 Gy. Forty lesions (75%) demonstrated a complete/partial response and 13 lesions (24%) with progressive/stable disease. Smaller target volume (p < 0.001), larger SRS dose (p < 0.001), and coverage (p = 0.008) were found to be positive predictors of complete response to SRS.CONCLUSION: SRS is an effective management option with up to 75% response rate for radioresistant brain metastases. Tumor volume and radiation dose are predictors of response and can be used to guide the decision-making for patients with radioresistant brain metastases.
Brain ; Carcinoma, Renal Cell ; Humans ; Melanoma ; Neoplasm Metastasis ; Prescriptions ; Radiosurgery ; Response Evaluation Criteria in Solid Tumors ; Retrospective Studies ; Tumor Burden