Purpose: The optimal sequencing of targeted therapies and the role of primary tumor resection (PTR) in KRAS wild-type metastatic colorectal cancer (mCRC) remain unclear. This study compared survival outcomes in patients treated with first-line cetuximab plus FOLFIRI (folinic acid, 5-fluorouracil, and irinotecan) versus bevacizumab plus FOLFIRI, followed by second-line oxaliplatin-based chemotherapy and later-line trifluridine/tipiracil or regorafenib. Methods: This retrospective cohort study used Taiwan’s National Health Insurance Research Database and the Taiwan Cancer Registry. Patients diagnosed with mCRC between 2013 and 2019 were included if they received first-line cetuximab or bevacizumab plus FOLFIRI, followed by later-line trifluridine/tipiracil or regorafenib. Patients were stratified by PTR status. Primary endpoints were overall survival and survival during trifluridine/tipiracil or regorafenib treatment. Secondary endpoints included time to treatment discontinuation (TTD) and TTD during trifluridine/tipiracil or regorafenib therapy. Stabilized inverse probability of treatment weighting was used for adjustment. Results: Among 559 patients, 278 were assigned to the non-PTR group and 281 to the PTR group. In the non-PTR group, the cetuximab cohort demonstrated significantly longer survival during trifluridine/tipiracil or regorafenib therapy (6.2 months vs. 4.9 months; hazard ratio [HR], 0.72) and longer TTD1 (the interval between initiation of first-line therapy and the start of second-line chemotherapy; 11.8 months vs. 9.5 months; HR, 0.67) than the bevacizumab cohort. Survival differences between regimens were less pronounced among patients who underwent PTR. Conclusion First-line cetuximab plus FOLFIRI may confer a survival advantage over bevacizumab in patients with KRAS wild-type mCRC without PTR, including during later-line therapy with trifluridine/tipiracil or regorafenib, whereas bevacizumab appears to provide more consistent benefits in those with PTR.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

INTRODUCTION: We aimed to understand the awareness and attitudes of elderly Southeast Asians towards telehealth services during the coronavirus disease 2019 (COVID-19) pandemic in this study. METHODS: In this qualitative study, 78 individuals from Singapore (51.3% female, mean age 73.0 ± 7.6 years) were interviewed via telephone between 13 May 2020 and 9 June 2020 during Singapore's first COVID-19 'circuit breaker'. Participants were asked to describe their understanding of telehealth, their experience of and willingness to utilise these services, and the barriers and facilitators underlying their decision. Transcripts were analysed using thematic analysis, guided by the United Theory of Acceptance Use of Technology framework. RESULTS: Of the 78 participants, 24 (30.8%) were able to describe the range of telehealth services available and 15 (19.2%) had previously utilised these services. Conversely, 14 (17.9%) participants thought that telehealth comprised solely home medication delivery and 50 (51.3%) participants did not know about telehealth. Despite the advantages offered by telehealth services, participants preferred in-person consultations due to a perceived lack of human interaction and accuracy of diagnoses, poor digital literacy and a lack of access to telehealth-capable devices. CONCLUSION Our results showed poor overall awareness of the range of telehealth services available among elderly Asian individuals, with many harbouring erroneous views regarding their use. These data suggest that public health education campaigns are needed to improve awareness of and correct negative perceptions towards telehealth services in elderly Asians.
Humans ; COVID-19/epidemiology* ; Female ; Telemedicine ; Aged ; Male ; Singapore/epidemiology* ; Qualitative Research ; Health Knowledge, Attitudes, Practice ; SARS-CoV-2 ; Aged, 80 and over ; Middle Aged ; Pandemics ; Awareness ; Asian People ; Southeast Asian People

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: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC patients into distinct prognostic groups. Methods: The study retrospectively enrolled 1,411 consecutive treatment-naïve patients with the Barcelona Clinic Liver Cancer (BCLC) stage 0 to A HCC from 2012 to 2021. The patients were randomly divided into a training cohort (n=988) and validation cohort (n=423). Two risk scores (CATS-IF and CATS-INF) were developed to predict overall survival (OS) in the training cohort using the conventional methods (Cox proportional hazards model) and ML-based methods (LASSO Cox regression), respectively. They were then validated and compared in the validation cohort. Results: In the training cohort, factors for the CATS-IF score were selected by the conventional method, including age, curative treatment, single large HCC, serum creatinine and alpha-fetoprotein levels, fibrosis-4 score, lymphocyte-tomonocyte ratio, and albumin-bilirubin grade. The CATS-INF score, determined by ML-based methods, included the above factors and two additional ones (aspartate aminotransferase and prognostic nutritional index). In the validation cohort, both CATS-IF score and CATS-INF score outperformed other modern prognostic scores in predicting OS, with the CATSINF score having the lowest Akaike information criterion value. A calibration plot exhibited good correlation between predicted and observed outcomes for both scores. Conclusions Both the conventional Cox-based CATS-IF score and ML-based CATS-INF score effectively stratified patients with early-stage HCC into distinct prognostic groups, with the CATS-INF score showing slightly superior performance.

Objective: Treatment with N-acetylcysteine (NAC) is believed to reduce the clinical symptoms among individuals with substance abuse or dependence. We conducted a meta-analysis of randomized controlled trials to evaluate the effectiveness of NAC in treating substance abuse and dependence. Methods: PubMed, EMBASE, ClinicalTrials.gov registry, and the Cochrane Library were searched for trials published before June 2020. Results: A total of 16 trials were analyzed. The treatment effectiveness domains assessed in this study were craving and depressive symptoms, withdrawal syndrome, adverse events, and smoking frequency. Standardized mean difference (SMD), weighted mean difference (WMD), and odds ratio (OR) were used for evaluation where appropriate. A significant decrease in craving symptoms was observed in the NAC treatment group compared with the control group (SMD, −0.67; 95% confidence interval [CI], −1.21 to 0.21). When withdrawal and depressive symptoms were considered as a single domain, the NAC treatment group demonstrated a significantly higher overall improvement than the control group (SMD, −0.35; 95% CI, −0.64 to −0.06). No between-group differences in term of the OR of adverse events (OR, 1.18;95% CI, 0.68 to 2.06) and a non-significant trend toward reduction in smoking frequency was observed in the NAC treatment group compared with the control group (WMD, −3.09; 95% CI, −6.50 to 0.32). Conclusion NAC provides certain noticeable benefits in attenuating substance craving and might help alleviate depressive symptoms and withdrawal syndrome. Precautious measures should be considered when using NAC although no difference in adverse effects was found between NAC treatment and control group.

Objective: Treatment with N-acetylcysteine (NAC) is believed to reduce the clinical symptoms among individuals with substance abuse or dependence. We conducted a meta-analysis of randomized controlled trials to evaluate the effectiveness of NAC in treating substance abuse and dependence. Methods: PubMed, EMBASE, ClinicalTrials.gov registry, and the Cochrane Library were searched for trials published before June 2020. Results: A total of 16 trials were analyzed. The treatment effectiveness domains assessed in this study were craving and depressive symptoms, withdrawal syndrome, adverse events, and smoking frequency. Standardized mean difference (SMD), weighted mean difference (WMD), and odds ratio (OR) were used for evaluation where appropriate. A significant decrease in craving symptoms was observed in the NAC treatment group compared with the control group (SMD, −0.67; 95% confidence interval [CI], −1.21 to 0.21). When withdrawal and depressive symptoms were considered as a single domain, the NAC treatment group demonstrated a significantly higher overall improvement than the control group (SMD, −0.35; 95% CI, −0.64 to −0.06). No between-group differences in term of the OR of adverse events (OR, 1.18;95% CI, 0.68 to 2.06) and a non-significant trend toward reduction in smoking frequency was observed in the NAC treatment group compared with the control group (WMD, −3.09; 95% CI, −6.50 to 0.32). Conclusion NAC provides certain noticeable benefits in attenuating substance craving and might help alleviate depressive symptoms and withdrawal syndrome. Precautious measures should be considered when using NAC although no difference in adverse effects was found between NAC treatment and control group.

Triple-negative breast cancer (TNBC) remains difficult to treat and urgently needs new therapeutic options. Nintedanib, a multikinase inhibitor, has exhibited efficacy in early clinical trials for HER2-negative breast cancer. In this study, we examined a new molecular mechanism of nintedanib in TNBC. The results demonstrated that nintedanib enhanced TNBC cell apoptosis, which was accompanied by a reduction of p-STAT3 and its downstream proteins. STAT3 overexpression suppressed nintedanib-mediated apoptosis and further increased the activity of purified SHP-1 protein. Moreover, treatment with either a specific inhibitor of SHP-1 or SHP-1-targeted siRNA reduced the apoptotic effects of nintedanib, which validates the role of SHP-1 in nintedanib-mediated apoptosis. Furthermore, nintedanib-induced apoptosis was attenuated in TNBC cells expressing SHP-1 mutants with constantly open conformations, suggesting that the autoinhibitory mechanism of SHP-1 attenuated the effects of nintedanib. Importantly, nintedanib significantly inhibited tumor growth via the SHP-1/p-STAT3 pathway. Clinically, SHP-1 levels were downregulated, whereas p-STAT3 was upregulated in tumor tissues, and SHP-1 transcripts were associated with improved disease-free survival in TNBC patients. Our findings revealed that nintedanib induces TNBC apoptosis by acting as a SHP-1 agonist, suggesting that targeting STAT3 by enhancing SHP-1 expression could be a viable therapeutic strategy against TNBC.
Apoptosis* ; Breast Neoplasms ; Disease-Free Survival ; Humans ; Protein-Tyrosine Kinases* ; RNA, Small Interfering ; Triple Negative Breast Neoplasms* ; Tyrosine*