Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: Zinc finger protein 639 (ZNF639) is often found within the overlapping amplicon of PIK3CA, and previous studies suggest its involvement in the pathogenesis of esophageal and oral squamous cell carcinomas. However, its expression and significance in breast cancer remain uncharacterized. Methods: Immunohistochemical analysis of ZNF639 was performed using tissue microarrays.Functional studies, including colony formation, Transwell cell migration, and in vivo metastasis, were conducted on breast tumor cells with ZNF639 knockdown via small interfering RNA transfection. Results: Reduced ZNF639 immunoreactivity was observed in 82% of the breast cancer samples, independent of hormone receptor and human epidermal growth factor receptor 2 status. In multivariate Cox regression analyses, ZNF639 expression was associated with favorable survival outcomes, including recurrence-free survival (hazard ratio, 0.35; 95% confidence interval [CI], 0.14–0.89) and overall survival (hazard ratio, 0.41; 95% CI, 0.16– 1.05). ZNF639 knockdown increased clonogenicity, cell motility, and lung metastasis in NOD/ SCID mice. Following the ZNF639 knockdown, the expression of Snail1, vimentin, and C-C chemokine ligand 20 (CCL20) was upregulated, and the changes in cell phenotype mediated by ZNF639 were reversed by the subsequent knockdown of CCL20. Conclusion Low ZNF639 expression is a novel prognostic factor for recurrence-free survival in patients with breast cancer.

Purpose: Zinc finger protein 639 (ZNF639) is often found within the overlapping amplicon of PIK3CA, and previous studies suggest its involvement in the pathogenesis of esophageal and oral squamous cell carcinomas. However, its expression and significance in breast cancer remain uncharacterized. Methods: Immunohistochemical analysis of ZNF639 was performed using tissue microarrays.Functional studies, including colony formation, Transwell cell migration, and in vivo metastasis, were conducted on breast tumor cells with ZNF639 knockdown via small interfering RNA transfection. Results: Reduced ZNF639 immunoreactivity was observed in 82% of the breast cancer samples, independent of hormone receptor and human epidermal growth factor receptor 2 status. In multivariate Cox regression analyses, ZNF639 expression was associated with favorable survival outcomes, including recurrence-free survival (hazard ratio, 0.35; 95% confidence interval [CI], 0.14–0.89) and overall survival (hazard ratio, 0.41; 95% CI, 0.16– 1.05). ZNF639 knockdown increased clonogenicity, cell motility, and lung metastasis in NOD/ SCID mice. Following the ZNF639 knockdown, the expression of Snail1, vimentin, and C-C chemokine ligand 20 (CCL20) was upregulated, and the changes in cell phenotype mediated by ZNF639 were reversed by the subsequent knockdown of CCL20. Conclusion Low ZNF639 expression is a novel prognostic factor for recurrence-free survival in patients with breast cancer.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: Zinc finger protein 639 (ZNF639) is often found within the overlapping amplicon of PIK3CA, and previous studies suggest its involvement in the pathogenesis of esophageal and oral squamous cell carcinomas. However, its expression and significance in breast cancer remain uncharacterized. Methods: Immunohistochemical analysis of ZNF639 was performed using tissue microarrays.Functional studies, including colony formation, Transwell cell migration, and in vivo metastasis, were conducted on breast tumor cells with ZNF639 knockdown via small interfering RNA transfection. Results: Reduced ZNF639 immunoreactivity was observed in 82% of the breast cancer samples, independent of hormone receptor and human epidermal growth factor receptor 2 status. In multivariate Cox regression analyses, ZNF639 expression was associated with favorable survival outcomes, including recurrence-free survival (hazard ratio, 0.35; 95% confidence interval [CI], 0.14–0.89) and overall survival (hazard ratio, 0.41; 95% CI, 0.16– 1.05). ZNF639 knockdown increased clonogenicity, cell motility, and lung metastasis in NOD/ SCID mice. Following the ZNF639 knockdown, the expression of Snail1, vimentin, and C-C chemokine ligand 20 (CCL20) was upregulated, and the changes in cell phenotype mediated by ZNF639 were reversed by the subsequent knockdown of CCL20. Conclusion Low ZNF639 expression is a novel prognostic factor for recurrence-free survival in patients with breast cancer.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is an increasingly common liver disease worldwide. MAFLD is diagnosed based on the presence of steatosis on images, histological findings, or serum marker levels as well as the presence of at least one of the three metabolic features: overweight/obesity, type 2 diabetes mellitus, and metabolic risk factors. MAFLD is not only a liver disease but also a factor contributing to or related to cardiovascular diseases (CVD), which is the major etiology responsible for morbidity and mortality in patients with MAFLD. Hence, understanding the association between MAFLD and CVD, surveillance and risk stratification of MAFLD in patients with CVD, and assessment of the current status of MAFLD management are urgent requirements for both hepatologists and cardiologists. This Taiwan position statement reviews the literature and provides suggestions regarding the epidemiology, etiology, risk factors, risk stratification, nonpharmacological interventions, and potential drug treatments of MAFLD, focusing on its association with CVD.

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.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Ulcerative colitis (UC) is a chronic inflammation of the gastrointestinal tract and is characterized by alternating periods of inflammation and remission. Although UC incidence is lower in Taiwan than in Western countries, its impact remains considerable, demanding updated guidelines for addressing local healthcare challenges and patient needs. The revised guidelines employ international standards and recent research, emphasizing practical implementation within the Taiwanese healthcare system. Since the inception of the guidelines in 2017, the Taiwan Society of Inflammatory Bowel Disease has acknowledged the need for ongoing revisions to incorporate emerging therapeutic options and evolving disease management practices. This updated guideline aims to align UC management with local contexts, ensuring comprehensive and context-specific recommendations, thereby raising the standard of care for UC patients in Taiwan. By adapting and optimizing international protocols for local relevance, these efforts seek to enhance health outcomes for patients with UC.