Background/Aims: Chronic constipation is prevalent yet under-diagnosed across Asia, compromising quality of life and burdening healthcare systems. Cultural stigma, varied diets, and limited access to standardized diagnostic tools delay timely care. Methods: The Bali Chronic Constipation Roundtable in November 2024, brought together experts from 11 Asian countries. The group reviewed epidemiological data, analyzed multinational questionnaire on clinical practice pattern, and conducted structured discussions to identify key barriers and propose region-specific recommendations. Results: Chronic constipation prevalence varies across Asia, ranging from 1.8% in India to 16.6% in Japan, with women and the elderly disproportionately affected. Under-reporting persists owing to cultural taboos and widespread self treatment with laxatives and traditional medications. Although the Rome IV criteria remains the global standard, they may not fully reflect Asian symptom profiles, and diagnosis is limited by scarce motility laboratories. First line therapies such as dietary-fiber optimization and osmotic laxatives are widely available, but newer pharmacotherapies (prucalopride, linaclotide, lubiprostone, and elobixibat) remain costly and unevenly accessible. Biofeedback for dyssynergic defecation is underutilized due to limited availability. Experts recommend expanded regional research on to refine diagnostic criteria, coupled with enhanced physician education and public awareness. They advocate accessibility to second-line and novel therapies that incorporate culturally attuned regional guidelines, and improved access to gastrointestinal motility testing. Conclusions The Bali Chronic Constipation Roundtable highlighted Asia’s need for region specific diagnostics and management. Addressing diagnostic and treatment gaps will improve outcomes, while ongoing researcher clinician policy collaboration must standardize guidelines, advance research, and ensure equitable care across Asia.

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.

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.

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.

Objective: This post-hoc analysis of the AtTEnd trial explored differences in the prognostic characteristics and in the efficacy of atezolizumab between Asians and non-Asians. Methods: The role of Asian race was evaluated on progression-free survival (PFS) using Cox-models and on time to appearance of new lesions using Fine and Gray models. Results: From October 2018 to February 2022, 549 patients were randomized, of whom, 20.4% were Asian. Asians showed a better prognostic profile in terms of age, body mass index, Eastern Cooperative Oncology Group performance status, disease status and previous treatments. The prognostic impact of Asian race on PFS was confirmed in the placebo arm (adjusted hazard ratio [HR]=0.41; 95% confidence interval [CI]=0.24–0.70). In proficient mismatch repair (pMMR) tumors, the HRs for PFS comparing atezolizumab versus placebo were 0.82 (95% CI=0.63–1.05) in non-Asians, and 1.42 (95% CI=0.80–2.50) in Asians. In the pMMR population randomized to atezolizumab, the subdistribution HRs comparing Asians to non-Asians were 0.68 (95% CI=0.43–1.09) for progression with new lesions and 1.21 (95% CI=0.73–2.03) for progression without new lesions. Asians showed a higher occurrence of severe adverse events in atezolizumab compared to placebo arm (Asians: 82.1% vs. 64.3%, p=0.036; non-Asian: 63.3% vs. 63.6%, p=0.949). Conclusion Race seems to affect the safety of the addition of atezolizumab and, in pMMR tumors, also its efficacy. In the atezolizumab arm, Asian patients seem to have a lower cumulative incidence of new lesions when primary tumor regrowth was considered a competing risk, and a higher cumulative incidence of primary tumor regrowth when new lesions appearance was the competing risk.

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.

Background: Ovarian cancer is the most lethal gynecological cancer, causing over 200,000 deaths worldwide in 2020. Initial standard treatment for primary ovarian cancer is optimal cytoreductive surgery (CRS) preceded and/or followed by intravenous platinum-based chemotherapy. However, most women develop recurrence within the peritoneal cavity and die of disease. Results of the OVIHIPEC 1 trial (2018) showed improved survival of 34% when hyperthermic intraperitoneal chemotherapy (HIPEC) was given immediately following interval-CRS in women with stage III disease. However, it is unknown if the effect of HIPEC is due to hyperthermia, one extra cycle of intraperitoneal (IP) chemotherapy, or other factors. There is also concern that hyperthermia might be associated with an increase in adverse events (AEs) due to a heightened systemic inflammatory response. HyNOVA is a seamless, multi-stage randomized study that attempts to answer these questions by comparing HIPEC to normothermic intraperitoneal chemotherapy (NIPEC), focusing on safety (stage 1), then assessing activity (stage 2) and effectiveness (stage 3). In this initial study, we hypothesize that NIPEC will result in a lower rate of severe AEs compared to HIPEC. Methods This initial stage of HyNOVA is a phase II study of 80 women with International Federation of Gynaecology and Obstetrics stage III epithelial ovarian cancer, with at least stable disease following 3–4 cycles of neoadjuvant chemotherapy, achieving interval-CRS to <2.5 mm residual disease. Participants are randomized 1:1 to receive IP cisplatin 100 mg/m2 for 90 minutes either as HIPEC, heated to 42°C (41.5°C–42.5°C), or NIPEC, at 37°C (36.5°C–37.5°C). The primary outcome is the proportion of AEs ≥ grade 3 occurring within 90 days. Secondary outcomes are AE of interest, surgical morbidity, patient reported outcomes, resource allocation, feasibility, progression-free survival and overall survival. AEs are measured using both CTCAE v5.0 and Clavien-Dindo classification, particularly infection, pain, bowel dysfunction, and anemia. Tertiary outcomes are potential predictive biomarkers measured before and after HIPEC/NIPEC including circulating cell-free tumor DNA, tissue factors, and systemic inflammatory markers. There are 4 participating Australian sites with experience in CRS and HIPEC for peritoneal malignancy. HyNOVA is funded by an MRFF grant (APP1199155).

Epithelial ovarian cancer (EOC) is among the top ten causes of cancer deaths worldwide, and is one of the most lethal gynecological malignancies in high income countries, with incidence and death rates expected to rise particularly in Asian countries where ovarian cancer is among the 5 most common cancers. Despite the plethora of randomised clinical trials investigating various systemic treatment options in EOC over the last few decades, both progression-free and overall survival have remained at approximately 16 and 40 months respectively. To date the greatest impact on treatment has been made by the use of poly (ADP-ribose) polymerase (PARP) inhibitors in women with advanced EOC and a BRCA1/2 mutation. Inhibition of PARP, the key enzyme in base excision repair, is based on synthetic lethality whereby alternative DNA repair pathways in tumor cells that are deficient in homologous recombination is blocked, rendering them unviable and leading to cell death. The Australia New Zealand Gynaecological Oncology Group (ANZGOG) is the national gynecological cancer clinical trials organization for Australia and New Zealand. ANZGOG's purpose is to improve outcomes and quality of life for women with gynecological cancer through cooperative clinical trials and undertaking multidisciplinary research into the causes, prevention and treatments of gynecological cancer. This review summarizes current ovarian cancer research and treatment approaches presented by Australian and New Zealand experts in the field at the 2020 ANZGOG webinar series entitled “Ovarian Cancer systems of Care”.

Background/Aims: Direct‐acting antivirals (DAAs) have been approved for hepatitis C virus (HCV) treatment in patients with end-stage renal disease (ESRD) on hemodialysis. Nevertheless, the complicated comedications and their potential drug-drug interactions (DDIs) with DAAs might limit clinical practice in this special population. Methods: The number, class, and characteristics of comedications and their potential DDIs with five DAA regimens were analyzed among HCV-viremic patients from 23 hemodialysis centers in Taiwan. Results: Of 2,015 hemodialysis patients screened in 2019, 169 patients seropositive for HCV RNA were enrolled (mean age, 65.6 years; median duration of hemodialysis, 5.8 years). All patients received at least one comedication (median number, 6; mean class number, 3.4). The most common comedication classes were ESRD-associated medications (94.1%), cardiovascular drugs (69.8%) and antidiabetic drugs (43.2%). ESRD-associated medications were excluded from DDI analysis. Sofosbuvir/velpatasvir/voxilaprevir had the highest frequency of potential contraindicated DDIs (red, 5.6%), followed by glecaprevir/pibrentasvir (4.0%), sofosbuvir/ledipasvir (1.3%), sofosbuvir/velpatasvir (1.3%), and elbasvir/grazoprevir (0.3%). For potentially significant DDIs (orange, requiring close monitoring or dose adjustments), sofosbuvir/velpatasvir/voxilaprevir had the highest frequency (19.9%), followed by sofosbuvir/ledipasvir (18.2%), glecaprevir/pibrentasvir (12.6%), sofosbuvir/velpatasvir (12.6%), and elbasvir/grazoprevir (7.3%). Overall, lipid-lowering agents were the most common comedication class with red-category DDIs to all DAA regimens (n=62), followed by cardiovascular agents (n=15), and central nervous system agents (n=10). Conclusions HCV-viremic patients on hemodialysis had a very high prevalence of comedications with a broad spectrum, which had varied DDIs with currently available DAA regimens. Elbasvir/grazoprevir had the fewest potential DDIs, and sofosbuvir/velpatasvir/voxilaprevir had the most potential DDIs.