The Lancet Regional Health: Western Pacific最新文献

{"title":"Trends in palliative care utilization among older adult decedents with and without cancer in Taiwan: a population-based comparative study","authors":"Yu-Tai Lo ,&nbsp;Tzu-Jung Chuang ,&nbsp;Yu-Tung Huang ,&nbsp;Yi-Lin Wu ,&nbsp;Yi-Ching Yang ,&nbsp;Chung-Yi Li","doi":"10.1016/j.lanwpc.2025.101479","DOIUrl":"10.1016/j.lanwpc.2025.101479","url":null,"abstract":"<div><h3>Background</h3><div>The leading causes of death among the older adults have shifted from cancer to non-cancer conditions such as ischemia heart diseases, stroke, and dementia, affecting end-of-life care needs. This study examined the difference in the proportion of palliative care utilization in relation to specific causes of death and compared the trends in palliative care utilization between older adult decedents with and without cancer in Taiwan from 2010 to 2020.</div></div><div><h3>Methods</h3><div>The study utilized data from the Health and Welfare Data Science Center in Taiwan, covering demographic and healthcare variables for 588,010 decedents aged 65+ years who died between 2010 and 2020. We used Poisson regression to investigate the temporal trends in palliative care utilization during the last six months of life. Multivariable logistic regression models were constructed to analyze cancer, and non-cancer causes of death associated with palliative care utilization.</div></div><div><h3>Findings</h3><div>The proportion of palliative utilization in cancer deaths started at 21.7% in 2010 and increased to 63.2% by 2020 with the beta coefficient of 0.09 (95% CI: 0.09–0.09). The proportion of palliative utilization in non-cancer deaths started at 0.8% in 2010 and increased to 23.5% by 2020, with the beta coefficient of 0.26 (95% CI: 0.26–0.26). Compared to deceased cancer patients, deceased non-cancer individuals were less likely to have received palliative care (OR = 0.12, 95% CI: 0.12–0.13).</div></div><div><h3>Interpretation</h3><div>Efforts to ensure equitable access to palliative care for non-cancer individuals should focus on expanding services, enhancing provider education, and promoting cultural sensitivity to meet the growing need for palliative care integration.</div></div><div><h3>Funding</h3><div>This study was supported in part by grants from the <span>National Cheng Kung University Hospital</span> (<span><span>NCKUH-11305001</span></span>, <span><span>NCKUH-V101-10</span></span>) and the <span>National Health Research Institutes</span> (<span><span>NHRI-13A1-CG-CO-04-2225-1</span></span>). The sponsors had no influence on the study.</div></div>","PeriodicalId":22792,"journal":{"name":"The Lancet Regional Health: Western Pacific","volume":"55 ","pages":"Article 101479"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of a multi-cancer risk identification model in 42,666 individuals: a population-based prospective study","authors":"Renjia Zhao ,&nbsp;Huangbo Yuan ,&nbsp;Yanfeng Jiang ,&nbsp;Zhenqiu Liu ,&nbsp;Ruilin Chen ,&nbsp;Shuo Wang ,&nbsp;Linyao Lu ,&nbsp;Ziyu Yuan ,&nbsp;Zhixi Su ,&nbsp;Qiye He ,&nbsp;Kelin Xu ,&nbsp;Tiejun Zhang ,&nbsp;Li Jin ,&nbsp;Ming Lu ,&nbsp;Weimin Ye ,&nbsp;Rui Liu ,&nbsp;Chen Suo ,&nbsp;Xingdong Chen","doi":"10.1016/j.lanwpc.2024.101291","DOIUrl":"10.1016/j.lanwpc.2024.101291","url":null,"abstract":"<div><h3>Background</h3><div>Identifying high-risk individuals is crucial for effective cancer screening. However, developing a practical risk prediction model with proper validation for multiple cancer types presents significant challenges.</div></div><div><h3>Methods</h3><div>We initialized the FuSion cohort study by recruiting 42,666 participants from Taizhou, China, between 2011 and 2021. Among these participants, 16,340 were recruited from 2011 to 2014 and were designated as the discovery cohort, while 26,308 participants enrolled between 2018 and 2021 were utilized as the validation cohort. In the discovery phase, we developed a multi-cancer risk prediction model for five common cancers, including lung, esophageal, liver, gastric, and colorectal cancer, using a comprehensive variable selection framework based on five machine learning methods. The predictors were selected from 74 epidemiological risk factors and blood biomarkers. The participants from the validation cohort were classified into high-, intermediate-, and low-risk groups based on the established model. We followed up the different risk groups and conducted clinical medical examinations, such as CT scans and endoscopic examinations, to evaluate the model's effectiveness in predicting cancer risk.</div></div><div><h3>Findings</h3><div>In the discovery phase, we developed a multi-cancer risk prediction model based on four biomarkers, AFP, CEA, CYFRA-211 and HBsAg, as well as age, sex, and smoking intensity. The model exhibited an AUROC of 0.767 (95%CI: 0.723-0.814) for five-year incidence prediction of multiple cancers, and the high-risk group exhibited a 15.19-fold (95%CI: 5.97-38.64) and 4.13-fold (95%CI: 2.67-6.39) increased risk compared to the low-risk population and intermediate-risk population, respectively. Among 17.19% of participants in the validation cohort that were identified as high risk, 50.41% of all new cancer cases were expected. In the face-to-face follow-up of 2,941 high-risk individuals, 9.64% were newly diagnosed with cancer or precancerous lesions. It was 5.02 times and 1.74 times as high as that in the low- and intermediate-risk group, respectively. In particular, the incidence of esophageal cancers in the high-risk group was 16.84 times as high as that in the low-risk group.</div></div><div><h3>Interpretation</h3><div>This is the first population-based multi-cancer risk prediction study conducted on a large Chinese cohort. The effective risk stratification model developed in this study would facilitate targeted prevention strategies and enhance early screening efforts for high-risk populations, ultimately optimizing healthcare resources.</div></div>","PeriodicalId":22792,"journal":{"name":"The Lancet Regional Health: Western Pacific","volume":"55 ","pages":"Article 101291"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of an intelligent endoscopic assistant device for detecting gastric neoplasms and its application conditions: a multi-center, randomized, controlled trial","authors":"Zehua Dong ,&nbsp;Lianlian Wu ,&nbsp;Hongliu Du ,&nbsp;Xiao Tao ,&nbsp;Junxiao Wang ,&nbsp;Xiaoquan Zeng ,&nbsp;Yijie Zhu ,&nbsp;Shuzhe Tan ,&nbsp;Jiamin Wang ,&nbsp;Mei Deng ,&nbsp;Ting Yang ,&nbsp;Lilei Yu ,&nbsp;Honggang Yu","doi":"10.1016/j.lanwpc.2024.101308","DOIUrl":"10.1016/j.lanwpc.2024.101308","url":null,"abstract":"<div><div>Evidence about the effect of AI systems on upper endoscopy in multi-center, randomized controlled trials is lacking. We aimed to explore whether AI can enhance gastric neoplasm detection and how AI can be applied better in real clinics.</div><div>Patients from 24 hospitals were allocated to receive AI-assisted esophagogastroduodenoscopy (EGD) or non-assisted EGD from December 21, 2021, to November 11, 2023 (pre-registered, ChiCTR2100054449). Primary outcome was detection rate of gastric neoplasms. Secondary outcomes included detection rate of early gastric cancer and precancerous conditions, biopsy rate, number of blind spots, and procedure/inspection time. We did modified intention-to-treat (m-ITT), per-protocol (PP) analysis, and an exploratory subgroup analysis.</div><div>A total of 30,540 patients were enrolled. In m-ITT cohort, the detection rate of gastric neoplasms under assistance was higher (RR 1·13, 1·00-1·28; 4·00 vs. 3·52%, p=0·04) with consistent results in the PP cohort. While after a pre-specified pathology review, numerically more gastric neoplasms were detected (RR 1·12, 0·92-1·38; 1·41 vs. 1·26%, p=0·28) with no statistical significance, and the result in PP analysis was consistent. Moreover, the system reduced the number of blind spots from 2·52 to 1·07 and increased the procedure/inspection time significantly. In exploratory subgroup analysis, potential benefits of AI in less experienced endoscopists and fatigue periods were detected. In the experimental group, the AI diagnosed the gastric adenocarcinoma with a sensitivity of 100%.</div><div>In conclusion, the ENDOANGEL-GC reliably contributed to the homogenization and standardization of endoscopic quality. The detection of gastric neoplasms was numerically improved without statistical significance. Our exploratory analysis seeking the optimal application condition of ENDOANGEL-GC found that AI might play a promising role among less experienced endoscopists and in labor-intensive areas, provides preliminary evidence for future researches.</div></div>","PeriodicalId":22792,"journal":{"name":"The Lancet Regional Health: Western Pacific","volume":"55 ","pages":"Article 101308"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Results and exploratory biomarker analyses of a phase II study CHANGEABLE: combination of HX008 and niraparib in GErm-line-mutAted metastatic breast cancer","authors":"Yizi Jin ,&nbsp;Yiqun Du ,&nbsp;Yanchun Meng ,&nbsp;Xuchen Shao ,&nbsp;Xiaojun Liu ,&nbsp;Yuxin Mu ,&nbsp;Yun Liu ,&nbsp;Zhen Hu ,&nbsp;Jian Zhang","doi":"10.1016/j.lanwpc.2024.101309","DOIUrl":"10.1016/j.lanwpc.2024.101309","url":null,"abstract":"<div><h3>Background</h3><div>The combination of poly (ADP-ribose) polymerase inhibitors and immune-checkpoint inhibitors demonstrated synergistic antitumor activity in preclinical studies. We aim to investigate the efficacy, safety, and biomarker analyses of the combination of niraparib and PD-1 inhibitor HX008 in metastatic breast cancer (MBC) patients with germline DNA damage response (DDR) gene mutations in a phase II trial (CHANGEABLE).</div></div><div><h3>Methods</h3><div>Eligible patients had histologically confirmed MBC with at least one measurable disease and germline pathogenic/likely pathogenic mutations in DDR genes. Patients were enrolled into two cohorts: the main cohort (HER2-negative MBC patients with a germline mutation in BRCA1/2 or PALB2) and the exploration cohort (MBC patients with a germline mutation in other DDR genes or with brain metastases or HER2-postive MBC patients). Simon's Two-Stage design was used for recruiting patients in the main cohort. Patients with HER2-negative MBC received niraparib 200 mg orally once daily combined with HX008 200 mg intravenously every 3 weeks, while HER2-positive patients received additional pyrotinib 400mg orally once daily if having brain metastases, until disease progression. The primary endpoint was objective response rate (ORR). Next-generation sequencing (NGS) of tissue and circulating tumor DNA (ctDNA) were performed for exploratory biomarker analyses.</div></div><div><h3>Findings</h3><div>As of February 2023, 37 patients were enrolled. In the main cohort with germline BRCA1/2 mutations, ORR was 79% (22/28), with three patients having CR; the DCR was 96% (27/28); the median PFS was 7.4 months (95%CI 5.4 to 12). In the patients having brain metastases, ORR was 40% (2/5) and DCR was 80% (4/5). The most common treatment-related adverse events of grade 3 or higher were anemia (13 [35.1%]), thrombocytopenia (4 [10.8%]), and neutropenia (3 [8.1%]). No treatment-related deaths were reported. Somatic mutations in XPO1 showed significant correlation with response. Somatic mutations in TP53 were significantly correlated with shorter PFS, while those in ASXL1 were significantly correlated with longer PFS.</div></div><div><h3>Interpretation</h3><div>The combination of niraparib and HX008 demonstrated promising clinical benefits with a tolerable safety profile in MBC patients with germline DDR mutations, even in patients with brain metastases.</div></div>","PeriodicalId":22792,"journal":{"name":"The Lancet Regional Health: Western Pacific","volume":"55 ","pages":"Article 101309"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National age-specific mortality trends for breast cancer from 2009 to 2021 and the surge age in China","authors":"Menglong Li ,&nbsp;Jinlei Qi ,&nbsp;Wen Shu ,&nbsp;Huidi Xiao ,&nbsp;Lijun Wang ,&nbsp;Peng Yin ,&nbsp;Haoyan Guo ,&nbsp;Sten H. Vermund ,&nbsp;Maigeng Zhou ,&nbsp;Yifei Hu","doi":"10.1016/j.lanwpc.2024.101383","DOIUrl":"10.1016/j.lanwpc.2024.101383","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background&lt;/h3&gt;&lt;div&gt;The age-specific mortality temporal trends of breast cancer can compare differences across subgroups and determine the surge age of mortality rates. We aim to assess the surge of mortality by age for breast cancer in China.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;We extracted mortality data of women aged 20-84 years by 5-year intervals and region (eastern, central and western) from 2009 to 2021 for breast cancer (ICD-10: C50) from China’s National Disease Surveillance Points (DSP) system. We assessed temporal trends in overall and age-specific mortality rates for breast cancer using log-linear Joinpoint models and estimated slope to determine the acceleration of mortality rate by age using linear Joinpoint models with three joinpoints to identify the mortality surge age range.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Findings&lt;/h3&gt;&lt;div&gt;From 2009 to 2021, the mortality rates of breast cancer were 9.95 per 100,000 women in 2009, 8.78 per 100,000 women in 2013, 10.11 per 100,000 women in 2017, 10.00 per 100,000 women in 2021 in China, presenting a stable trend (average annual percent change, AAPC: 0%, 95% confidence interval: −1.0% to 1.0%). The pooled mortality rate was 9.76 per 100,000 women from 2009-2021. Temporal trends showed that the years 2013 and 2017 were significant Joinpoints for stratified analysis by period with APCs of − 2.6% (95% CI − 4.4 to − 0.8, P = 0.015) during 2009–2013, 2.8% (95% CI − 0.2 to 5.9, P = 0.06) during 2013–2017, and − 0.2% (95% CI − 2.1 to 1.6, P = 0.75) during 2017–2021, respectively. Joinpoint regression shapes four segments for mortality rate trends by age group and we observed a difference in mortality velocity pattern. The accelerations of breast cancer mortality rates by segment were 4.31 per 100,000 women (segment 2, 35-39 to 50-54, ranks 1st), 2.16 per 100,000 women (segment 4, 65-69 to 80-84, ranks 2nd), 1.40 per 100,000 women (segment 3, 50-54 to 65-69, ranks 3rd), 0.94 per 100,000 women (segment 1, 20-24 to 35-39, ranks 4th). Stratifying by time-period and region, we found that the highest mortality acceleration for breast cancer mainly showed in segment 2, namely 35-39 to 50-54 years.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Interpretation&lt;/h3&gt;&lt;div&gt;This study investigates the temporal trends in overall and age-specific mortality rates of breast cancer from 2009 to 2021 in China. We propose that the mortality rates of breast cancer were stable in the past decade and the increasing trend of breast cancer mortality with age group can be divided into 4 segments, and the major mortality surge age is stable at 35-54 years across time-period and regions. Previous studies have demonstrated that national breast cancer screening programs can lead to a reduction in mortality rates after a period of implementation. This is attributed to the early detection and treatment of breast cancer, which enhances the chances of successful intervention and improves survival rates. Despite significant government investment in breast cancer scre","PeriodicalId":22792,"journal":{"name":"The Lancet Regional Health: Western Pacific","volume":"55 ","pages":"Article 101383"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Language model-based early detection of colorectal cancer occurrence from previous disease diagnosis trajectory data for primary care purpose","authors":"Zhiyao Luo ,&nbsp;Jiannan Yang ,&nbsp;Tingting Zhu ,&nbsp;William Chi Wai Wong ,&nbsp;Jiandong Zhou","doi":"10.1016/j.lanwpc.2024.101381","DOIUrl":"10.1016/j.lanwpc.2024.101381","url":null,"abstract":"&lt;div&gt;&lt;div&gt;The early prediction of colorectal cancer (CRC) in general patients is critical for improving outcomes through timely diagnosis and intervention. However, accurately predicting CRC is challenging due to the substantial variability in disease progression and the heterogeneity in patient presentations. In this study, we propose a non-invasive, accurate approach for predicting early-stage CRC using language models applied to longitudinal electronic health records (EHR) data.&lt;/div&gt;&lt;div&gt;Our study evaluates the effectiveness of multiple language models, including Transformer, Recurrent Neural Network (RNN), and Multi-Layer Perceptron (MLP), in predicting CRC occurrence. The models were trained using a two-stage process of pretraining and finetuning. For model development, we used a dataset comprising the diagnostic history of 136,801 patients (45.6% male, median age 65.8 years [IQR: 52.5-76.0]) admitted between January 1, 2000, and December 31, 2003, with follow-up data through December 31, 2023. A five-fold cross-validation approach was employed, with 80% of the data used for model training and 20% reserved for evaluation. This training process was repeated five times to mitigate potential overfitting. To gain insights into the model’s interpretability, we applied the GradientSHAP method to identify key disease features along the CRC risk trajectory. We further validated the model on an independent cohort of 1 million family medicine patients (46.9% male, median age at recruitment 63.8 years [IQR: 54.8-77.5]), enrolled between January 1, 2008, and December 31, 2009, with follow-up until May 31, 2024. This cohort included 4, 301 patients diagnosed with CRC (63.0% male, median age at diagnosis 66.6 years [IQR: 56.3-76.3]), alongside matched controls. Notably, none of these patients were included in the model training set. For the sensitivity analysis, we employed a bootstrapping statistical test with 1,000 iterations to assess metrics such as AUROC and AUPRC for significance.&lt;/div&gt;&lt;div&gt;Among the evaluated models (i.e., Transformer, RNN, and MLP model with variants of using only diagnosis trajectory, both demographics and diagnosis trajectory, all demographics, diagnosis trajectory and medication histories as model input), RNN demonstrated superior performance in predicting CRC when incorporating patient demographics, disease history, and medication data. The RNN achieved an area under the receiver operating characteristic (AUROC) score of 0.887 (95% CI: 0.886-0.889) on the holdout validation cohort and 0.903 (95% CI: 0.882-0.902) on the independent validation cohort. This performance surpassed that of the Transformer and MLP models. The GradientSHAP analysis revealed that the RNN model’s predictions aligned well with clinical observations. Specifically, the model identified histories of “Crohn’s disease” (ICD-9: 555.x), “Ulcerative colitis” (ICD-9: 556.x), “Overweight and obesity” (ICD-9: 278), and “Diabetes” (ICD-9: 250.x) as the top predicto","PeriodicalId":22792,"journal":{"name":"The Lancet Regional Health: Western Pacific","volume":"55 ","pages":"Article 101381"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term effect of berberine in preventing recurrence of colorectal adenomas and neoplasms after endoscopic resection: 6-year-follow-up in a randomized, placebo-controlled, multicenter clinical study","authors":"Yongjie Tan ,&nbsp;Jingyuan Fang ,&nbsp;Tianhui Zou ,&nbsp;Ke Yu ,&nbsp;Jian-Qiu Sheng ,&nbsp;Peng Jin ,&nbsp;Ming-Jie Zhang ,&nbsp;Xiao-Ping Zou ,&nbsp;Xiao-Tan Dou ,&nbsp;Si-De Liu ,&nbsp;Shao-Hui Huang ,&nbsp;Jian-Lin Ren ,&nbsp;Xiao-Ning Yang ,&nbsp;Zhan-Ju Liu ,&nbsp;Xiao-Min Sun ,&nbsp;Bang-Mao Wang ,&nbsp;Hai-Long Cao ,&nbsp;Qin-Yan Gao ,&nbsp;Hui-Min Chen ,&nbsp;Yun Cui ,&nbsp;Ying-Xuan Chen","doi":"10.1016/j.lanwpc.2024.101408","DOIUrl":"10.1016/j.lanwpc.2024.101408","url":null,"abstract":"<div><div>Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide and in recent years its incidence is increasing rapidly in China, which constitutes a major public health burden. Almost 90% of CRC cases develop from precursor adenomatous polyps, through a series of genetic changes known as adenoma-carcinoma sequence during at least 10 years. Detection and removal of colorectal adenoma (CRA) could reduce CRC mortality risk by colonoscopy, but the recurrence rate is high. Our previous RCT study (NCT02226185) found that oral Berberine (BBR), a natural isoquinoline alkaloid extracted from the Chinese herb Coptis chinensis for 2 years significantly reduced recurrence after endoscopic removal of CRA (RR 0.77, 95% CI 0.66-0.91; p=0.001). The study recruited 895 participants who had undergone complete polypectomy within 6 months in seven hospital centers across six provinces in China between Nov 14, 2014, and Dec 30, 2016. Participants were randomly assigned (1:1) to receive BBR (0·3 g twice daily) or placebo tablets via block randomization for 2 years. After the end of randomized treatment, we continued this Follow-up Study to track adenoma recurrence for an average of 6 years till Sep 30, 2024. Besides 114 participants lost to follow up, we obtained follow-up information for 781 participants, 648 of whom underwent at least one colonoscopy after the end of study treatment and were included in this analysis. Mantel-Haenszel test was used to compute relative risks (RRs) and 95% confidence intervals (CIs) for the effect of BBR on risk of adenoma recurrence. Cox proportional-hazards model and Andersen-Gill model were used to analyze multi-recurrence by time. The study is registered with <span><span>ClinicalTrials.gov</span><svg><path></path></svg></span>, number <span><span>NCT06629051</span><svg><path></path></svg></span>. During the average 6 years follow up, we found that participants in the BBR group still had a substantially and statistically significantly lower risk of CRA than those in the placebo group (34.7% versus 52.1%; adjusted RR = 0.639, 95% CI = 0.508 to 0.785, P&lt;0.001) and a reduction in risk of any neoplasm including inflammatory polyps, serrated lesions and colorectal cancer (adjusted RR = 0.874, 95% CI = 0.775 to 0.983, P = 0.022). Meanwhile the risk of non-advanced CRA in BBR group was lower than that in placebo group (adjusted RR = 0.634, 95% CI = 0.497 to 0.790, P&lt;0.001). The incidence of adenoma recurrence was significantly lower in participants receiving BBR (HR= 0.601; 95% CI = 0.473-0.765; P&lt;0.001). And in every year after treatment ended, the risk of adenoma recurrence in BBR group was lower than placebo group for all RRs&lt;1.0 but some of which were not statistically significant. Generally, the protective effect of berberine on risk of colorectal recurrence extends up to 6 years after cessation of active treatment, even in the absence of continued supplementation.</div></div>","PeriodicalId":22792,"journal":{"name":"The Lancet Regional Health: Western Pacific","volume":"55 ","pages":"Article 101408"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cost-effectiveness of combining AI and cfDNA with LDCT for lung cancer screening in China: a modelling study","authors":"Mingjun Rui ,&nbsp;Yingcheng Wang ,&nbsp;Zhengwei Huang ,&nbsp;Yunfei Li ,&nbsp;Hongchao Li","doi":"10.1016/j.lanwpc.2024.101293","DOIUrl":"10.1016/j.lanwpc.2024.101293","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background&lt;/h3&gt;&lt;div&gt;Lung cancer remains one of the leading causes of cancer-related mortality in China, where early detection through screening is critical for improving survival rates. Low-dose computed tomography (LDCT) has proven effective for early lung cancer screening, but its high false-positive rate increases the economic burden and psychological stress on patients. Previous studies have shown that combining artificial intelligence (AI) and cell-free DNA methylation (cfDNA) can potentially reduce the false-positive rates of LDCT. However, the cost-effectiveness of using AI and cfDNA in combination with LDCT for lung cancer screening in the Chinese population remains unclear. Furthermore, current guidelines vary in the risk factors and thresholds. The impact of them on the cost-effectiveness of screening strategies remains underexplored. This study aims to evaluate the cost-effectiveness of combining AI and cfDNA with LDCT for lung cancer screening in China. Additionally, we assess the impact of varying smoking exposure thresholds (20 pack-years vs. 30 pack-years) and environmental or occupational risks on screening outcomes.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;We simulated a cohort of 100,000 individuals aged 45-74, stratified by screening methods (LDCT alone, LDCT+AI+cfDNA, and no screening), risk factors (20 pack-years, 30 pack-years, and environmental/occupational exposures), and screening intervals (annual, biennial, and one-time screening). A Markov state transition model with a lifetime horizon was used to simulate lung cancer progression and related health outcomes. The model was validated against lung cancer-specific mortality data from the Global Burden of Disease study. Primary outcomes were incremental cost-effectiveness ratios (ICERs), life years (LYs), and quality-adjusted life years (QALYs). Sensitivity analyses were performed to test the robustness of results under different parameter assumptions. Value-based pricing analysis was performed to evaluate the maximum cost of AI+cfDNA at the current willingness-to-pay threshold.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Findings&lt;/h3&gt;&lt;div&gt;For individuals aged 45-49, the one-time LDCT screening strategy was the most cost-effective, with an incremental cost-effectiveness ratio (ICER) of 5,458 USD/QALY. For those aged 50-74, annual LDCT screening for individuals with a smoking history of 20 pack-years and environmental or occupational exposures was the most cost-effective (ICER range: 4,382-33,204 USD/QALY). At current pricing, AI+cfDNA combined with LDCT was not cost-effective. The value-based pricing analysis revealed that AI+cfDNA combined with LDCT would become cost-effective if the AI+cfDNA cost was reduced to a range of $232-$340.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Interpretation&lt;/h3&gt;&lt;div&gt;Annual LDCT screening for individuals aged 50-74 with a smoking history of 20 pack-years and environmental or occupational risks is the most cost-effective strategy in China. For younger individuals (aged 45-49), a one","PeriodicalId":22792,"journal":{"name":"The Lancet Regional Health: Western Pacific","volume":"55 ","pages":"Article 101293"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing large multimodal models in pulmonary CT: the generative AI edge in lung cancer diagnostics","authors":"Lihaoyun Huang,&nbsp;Junyi Shen,&nbsp;Anqi Lin,&nbsp;Jian Zhang,&nbsp;Peng Luo,&nbsp;Ting Wei","doi":"10.1016/j.lanwpc.2024.101336","DOIUrl":"10.1016/j.lanwpc.2024.101336","url":null,"abstract":"<div><h3>Background</h3><div>Generative Artificial Intelligence (Gen-AI) has rapidly advanced in multimodal information processing, particularly in medical applications such as the refinement of instruments and interpretation of medical images. However, limited evidence exists on the diagnostic performance of Gen-AI models in tumor recognition, particularly using computed tomography (CT) images. This study aimed to evaluate the diagnostic capabilities of several prevelant Gen-AI models (GPT-4-turbo, Gemini-pro-vision, Claude-3-opus) in the context of lung CT image analysis.</div></div><div><h3>Methods</h3><div>This retrospective study analyzed chest CT scans from 404 patients with lung conditions with lung neoplasms (n=184) and non-malignancy (n=210). After standardizing CT images, the diagnostic performance and reliability of three Gen-AI (GPT-4-turbo, Gemini-pro-vision, and Claude-3-opus) were assessed using chi-square tests and Receiver Operating Characteristic (ROC) curves across various clinical scenarios. Likert scale scoring and response rate analysis were employed to evaluate internal diagnostic tendencies, while regression analyses were conducted for model optimization.</div></div><div><h3>Findings</h3><div>In a cueing environment limited to a single CT image, Gemini demonstrated the highest diagnostic accuracy (92.21%), followed by Claude (91.49%), while GPT exhibited the lowest performance (65.22%). As the complexity of the cueing environment increased, all models experienced a decline in diagnostic accuracy. Claude showed a marginal decrease, whereas Gemini's accuracy fluctuated significantly. Under simplified cueing conditions, the performance of all models improved notably (Gemini AUC = 0.76, Claude AUC = 0.69, GPT AUC = 0.73). Feature identification analysis revealed that Claude and GPT excelled in recognizing key features, particularly prioritizing “Morphology/Margins” when diagnosing primary malignancies, with “spiculated” and “irregular” serving as critical indicators. However, in cases of misdiagnosis or missed diagnoses, Gen-AI exhibited significant deviations across multiple feature dimensions—some even completely contradicted the actual findings. Following optimization through Lasso and stepwise regression, the diagnostic performance of the models was significantly enhanced (AUC = 0.896 and AUC = 0.894, respectively).</div></div><div><h3>Interpretation</h3><div>Gen-AI shows promising potential in pulmonary CT imaging, particularly in simplified diagnostic settings. However, their limitations in processing complex multi-modal information highlight significant challenges for clinical integration. Ongoing efforts to improve the robustness and reliability of these models are crucial for their successful adoption in healthcare.</div></div>","PeriodicalId":22792,"journal":{"name":"The Lancet Regional Health: Western Pacific","volume":"55 ","pages":"Article 101336"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations between sleep disturbance, treatment-related adverse events, and psychological distress in patients with breast cancer: a prospective cohort study","authors":"Yuqiu Li ,&nbsp;Fang Zhao ,&nbsp;Yanjun Zhou ,&nbsp;Enfeng Fu ,&nbsp;Shanshan Zhu ,&nbsp;Lulu Yu ,&nbsp;Hangcheng Xu ,&nbsp;Qing Li ,&nbsp;Qiao Li ,&nbsp;Pin Zhang ,&nbsp;Jiani Wang ,&nbsp;Hongnan Mo","doi":"10.1016/j.lanwpc.2024.101325","DOIUrl":"10.1016/j.lanwpc.2024.101325","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background&lt;/h3&gt;&lt;div&gt;This study aimed to explore the relationship between sleep disturbance, treatment-related adverse events, and psychological distress in Chinese patients with breast cancer.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;This prospective cohort study reported on 300 female patients with breast cancer recruited from two medical centers across China between January 1, 2023, and October 31, 2023. Sleep disturbance and psychological health were assessed before and after every cycle of treatment using the Pittsburgh Sleep Quality Index (PSQI) and the Symptom Checklist-90 questionnaire (SCL-90). Statistical tests including t-test, Mann–Whitney U test, Spearman’s rank correlation analysis and multivariate linear regression analysis were used. The study was approved by the ethics committee of the National Cancer Center and written informed consent was obtained from each participant (22/272-3474).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Findings&lt;/h3&gt;&lt;div&gt;Patients were dichotomized into two groups: those with normal sleep (control; N=168) vs. those with sleep disorder (N=132). The incidence of most treatment-related adverse events such as nausea and vomiting (P=0.04), fatigue (P&lt;0.001), numbness in the hands or feet (P=0.004), alopecia (P=0.02), memory deterioration (P=0.02), and photophobia (P=0.02) were significantly higher in the sleep disorder group at baseline compared to the normal sleep group. The baseline sleep quality of the patients was significantly correlated with the severity of adverse events (rs=0.16, P=0.007). Psychological health at baseline was also correlated with the adverse events score (rs=0.57, P&lt;0.001). Multivariate analysis showed that psychological health was independently associated with the occurrence of adverse events (β=0.19, P &lt;0.001). Besides, the pre-treatment total psychological health score in the baseline sleep disorder group was significantly higher than that in the normal sleep group (Z=-3.42, P=0.001). Furthermore, the severity of treatment-related adverse events (rs=0.32, P&lt;0.001) and baseline sleep quality (rs=0.20, P=0.001) were respectively associated with psychological health.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Interpretation&lt;/h3&gt;&lt;div&gt;Poor baseline sleep quality is correlated with increased occurrence and severity of treatment-related adverse events in breast cancer patients. Besides, baseline psychological health is correlated with the occurrence of adverse events in breast cancer patients. Both baseline sleep quality and the severity of treatment-related adverse events significantly affect the psychological health of patients after treatment for breast cancer. We fill the knowledge gap and provide new insights for the factors affecting adverse events in breast cancer patients, which could reduce the incidence and severity of treatment-related adverse events and improve quality of life in patients with breast cancer. Our limitations are that we recorded only recent treatment-related adverse events instead of long-ter","PeriodicalId":22792,"journal":{"name":"The Lancet Regional Health: Western Pacific","volume":"55 ","pages":"Article 101325"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}