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Population-Based Prognostic Models for Head and Neck Cancers Using National Cancer Registry Data from Taiwan

Journal of Epidemiology and Global Health 2024年第2期14卷 433-443页

作者： Tsai, Yu-Lun Kang, Yi-Ting Chan, Han-Ching Chattopadhyay, Amrita Chiang, Chun-Ju Lee, Wen-Chung Cheng, Skye Hung-Chun Lu, Tzu-Pin Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Department of Radiation Oncology Cathay General Hospital Taipei Taiwan Bioinformatics and Biostatistics Core Center of Genomic and Precision Medicine National Taiwan University Taipei Taiwan Taiwan Cancer Registry Taipei Taiwan Institute of Health Data Analytics and Statistics College of Public Health National Taiwan University Taipei Taiwan Department of Radiation Oncology Koo Foundation Sun Yat-Sen Cancer Center Taipei Taiwan Taitung Christian Hospital Taitung Taiwan

Purpose: This study aims to raise awareness of the disparities in survival predictions among races in head and neck cancer (HNC) patients by developing and validating population-based prognostic models specifically tailored for Taiwanese and Asian populations. Methods: A total of 49,137 patients diagnosed with HNCs were included from the Taiwan Cancer Registry (TCR). Six prognostic models, divided into three categories based on surgical status, were developed to predict both overall survival (OS) and cancer-specific survival using the registered demographic and clinicopathological characteristics in the Cox proportional hazards model. The prognostic models underwent internal evaluation through a tenfold cross-validation among the TCR Taiwanese datasets and external validation across three primary racial populations using the Surveillance, Epidemiology, and End Results database. Predictive performance was assessed using discrimination analysis employing Harrell’s c-index and calibration analysis with proportion tests. Results: The TCR training and testing datasets demonstrated stable and favorable predictive performance, with all Harrell’s c-index values ≥ 0.7 and almost all differences in proportion between the predicted and observed mortality being < 5%. In external validation, Asians exhibited the best performance compared with white and black populations, particularly in predicting OS, with all Harrell’s c-index values > 0.7. Conclusions: Survival predictive disparities exist among different racial groups in HNCs. We have developed population-based prognostic models for Asians that can enhance clinical practice and treatment plans. © The Author(s) 2024.

关键词： Asian Head and neck cancer Prognostic model Taiwan Cancer Registry

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Prognostic factors for clinical outcomes of patients with central nervous system leukemia

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Hematology/ Oncology and Stem Cell Therapy 2021年第3期14卷 240-245页

作者： Bharucha, Jinai Cao, Qing Sachs, Zohar Smith, Angela Williams, Sarah Amin, Khalid Bachanova, Veronika Warlick, Erica Brunstein, Claudio Weisdorf, Daniel Bejanyan, Nelli University of Minnesota Medical School Minneapolis MN United States Biostatistics and Bioinformatics Core Masonic Cancer Center University of Minnesota Minneapolis MN United States Division of Hematology Oncology and Transplantation Department of Medicine University of Minnesota Minneapolis MN United States Division of Blood and Marrow Transplantation Department of Pediatrics University of Minnesota Minneapolis MN United States Department of Laboratory Medicine and Pathology University of Minnesota Minneapolis MN United States Department of Blood and Marrow Transplant and Cellular Immunotherapy Moffitt Cancer Center Tampa FL United States

Prognostic factors associated with clinical outcomes of acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) patients with central nervous system (CNS) involvement are unknown. We retrospectively studied the characteristics and outcomes of 66 (18 pediatric and 48 adult) patients with CNS leukemia with ALL (n = 41) or AML (n = 25). The median age of patients at diagnosis of CNS leukemia was 30 (range, 1–69) years. Nearly two-third patients had CNS involvement at the initial diagnosis of leukemia. Complete remission of CNS leukemia was attained in 58 (88%) patients, and probability of overall survival at 36 months after the diagnosis of CNS leukemia was 43% for the entire cohort. We identified that achieving remission of systemic leukemia and having CNS leukemia diagnosed and treated before allogeneic transplantation were the factors associated with CNS leukemia remission. Prognostic factors associated with better overall survival in patients with CNS leukemia included pediatric age, diagnosis of CNS leukemia before receiving allogenic transplantation, achieving clearance of systemic or CNS leukemia, receiving no cranial radiation in conjunction with intrathecal chemotherapy (IT), and receiving IT consolidation after achieving remission of CNS leukemia. Our findings show that patients with CNS leukemia are at considerable risk of mortality. Awareness of modifiable prognostic factors such as avoidance of cranial radiation whenever possible and use of IT consolidation can result in improved outcomes in subset of patients with CNS leukemia. © 2020 King Faisal Specialist Hospital & Research Centre

关键词： ALL AML CNS Leukemia Prognosis

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Effects of a Workplace Well-being Program on Professional Quality of Life Among Healthcare Personnel

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The Joint Commission Journal on Quality and Patient Safety 2025年

作者： Nicholas A. Giordano Ingrid Duva Beth Ann Swan Theodore M Johnson Jeannie P. Cimiotti Dorian A. Lamis JoAnna Hillman Janelle Gowgiel Kristin Giordano Nikki Rider Lisa Muirhead Michelle Wallace Tim Cunningham Maureen Shelton Timothy Harrison LaTanya Holland Ammar A. Rashied Jennifer Mascaro Nell Hodgson Woodruff School of Nursing Emory University Atlanta Georgia US General Internal Medicine Emory University School of Medicine Atlanta Georgia US Birmingham/Atlanta VA Geriatrics Rehabilitation Education and Clinical Center Atlanta Veterans Affairs Healthcare System Atlanta Georgia US Division of Preventive Medicine Department of Family and Preventive Medicine Emory University School of Medicine Atlanta Georgia US Department of Psychiatry and Behavioral Sciences School of Medicine Emory University Atlanta Georgia US Hillman Associates LLC Pittsburgh Pennsylvania US The Southeast Permanente Medical Group Atlanta GA Emory Centers for Public Health Training and Technical Assistance Rollins School of Public Health Emory University Atlanta Georgia US Grady Memorial Hospital Atlanta Georgia US Emory Healthcare Atlanta Georgia US Spiritual Health Emory University Atlanta Georgia US Center for Contemplative Science and Compassion-Based Ethics Emory University Atlanta Georgia US Biostatistics Collaboration Core Department of Biostatistics and Bioinformatics Rollins School of Public Health Emory University Atlanta Georgia US

Introduction A healthy, competent, and compassionate healthcare workforce is critical to ensure health systems can deliver high-quality, safe patient care. Therefore, healthcare personnel need access to scalable, recurring, evidence-based training opportunities to bolster compassion, mitigate burnout, and enhance resiliency, ultimately improving their professional quality of life. This evaluation examined the reach, effectiveness, adoption, implementation, and maintenance of workplace-based well-being training opportunities offered by Atlanta’s Resiliency Resource for Frontline Workers (ARROW) program across two health systems. Methods ARROW formed through an academic practice partnership designed to introduce healthcare personnel to evidence-based mindfulness and compassion-based training opportunities: the Community Resiliency Model (CRM) and Cognitively Based Compassion Training (CBCT). Trainees provided evaluation feedback immediately before, two weeks after, and three months after attending a CRM or CBCT event. The Short Professional Quality of Life assessed compassion fatigue, burnout, and compassion satisfaction; the Connor-Davidson Resilience Scale assessed resiliency. Results ARROW hosted 59 training events that directly trained 761 healthcare personnel. Trainees’ compassion fatigue scores, a key component of professional quality of life, decreased up to 3 months after engaging in programming by 0.32 points ( p  = 0.005; d  = -0.14). Trainees who attended CBCT events were observed to have additional declines in compassion fatigue scores, by 0.45 points ( p  = 0.016; d  = -0.215). No differences in burnout, compassion satisfaction, or resiliency were observed. ARROW mentored 68 healthcare personnel to become either CRM- or CBCT-certified instructors using a train-the-trainer approach. New trainers continued to offer well-being training opportunities and reached an additional 772 colleagues. Conclusion The findings from this evaluation indicate the broad reac

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141P Preliminary results of a comprehensive genome profiling in patients treated with Cyclin-dependent Kinase 4/6 inhibitors (CDK4/6i) plus endocrine therapy (ET) as first-line treatment for advanced breast cancer (ABC)

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ESMO Open 2025年 10卷 104694-104694页

作者： Carbognin, L. Paris, I. Rossi, A. Minucci, A. Giacò, L. Piermattei, A. de bonis, M. Kulesco, M. Nero, C. Palazzo, A. Franceschini, G. D'Angelo, T. Marrazzo, M. Rotondaro, S. Mulè, A. Giannarelli, D. Tortora, G. Pasciuto, T. Scambia, G. Fabi, A. Precision Medicine Unit in Senology Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Gynecologic Oncology Department of Woman and Child Health and Public HealthWoman Health Area Fondazione Policlinico Universitario A.Gemelli IRCCS Rome Italy Molecular Diagnostic Genomic Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Bioinformatics Research Core Facility Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Unità di Ginecopatologia e Patologia Mammaria Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Department of Woman and Child Health and Public Health Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Scienze gastroenterologiche endocrino metaboliche e nefrourologiche Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Research Core Facility Data Collection G-STeP Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Facility of Epidemiology and Biostatistics Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy Universita Cattolica del Sacro Cuore Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy

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Genome-wide Association Study Reveals Multiple Nasopharyngeal Carcinoma-Associated Loci within the HLA Region at Chromosome 6p21.3

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American Journal of Human Genetics 2009年第2期85卷 194-203页

作者： Tse, Ka-Po Su, Wen-Hui Chang, Kai-Ping Tsang, Ngan-Ming Yu, Chia-Jung Tang, Petrus See, Lee-Chu Hsueh, Chuen Yang, Min-Lee Hao, Sheng-Po Li, Hong-Yi Wang, Ming-Hsi Liao, Li-Ping Chen, Lih-Chyang Lin, Sheue-Rong Jorgensen, Timothy J. Chang, Yu-Sun Shugart, Yin Yao Genomic Medicine Core Chang Gung Molecular Medicine Research Center Chang Gung University Taoyuan 333 Taiwan Molecular Epidemiology Core Chang Gung Molecular Medicine Research Center Chang Gung University Taoyuan 333 Taiwan Bioinformatics Core Chang Gung Molecular Medicine Research Center Chang Gung University Taoyuan 333 Taiwan Biostatistics Core Chang Gung Molecular Medicine Research Center Chang Gung University Taoyuan 333 Taiwan Pathology Core Chang Gung Molecular Medicine Research Center Chang Gung University Taoyuan 333 Taiwan Department of Otolaryngology Chang Gung Memorial Hospital at Lin-Kou Taoyuan 333 Taiwan Department of Radiation Oncology Chang Gung Memorial Hospital at Lin-Kou Taoyuan 333 Taiwan Department of Pathology Chang Gung Memorial Hospital at Lin-Kou Taoyuan 333 Taiwan Department of Biochemistry and Molecular and Cellular Biology Chang Gung University Taoyuan 333 Taiwan Department of Public Health Chang Gung University Taoyuan 333 Taiwan Department of Epidemiology Bloomberg School of Public Health Johns Hopkins University Baltimore MD 21205 United States Department of Biostatistics Bloomberg School of Public Health Johns Hopkins University Baltimore MD 21205 United States Health Bureau of Taoyuan County Taoyuan 33053 Taiwan Department of Radiation Medicine Lombardi Comprehensive Cancer Center Georgetown University Washington DC 20057 United States

Nasopharyngeal carcinoma (NPC) is a multifactorial malignancy closely associated with genetic factors and Epstein-Barr virus infection. To identify the common genetic variants linked to NPC susceptibility, we conducted a genome-wide association study (GWAS) in 277 NPC patients and 285 healthy controls within the Taiwanese population, analyzing 480,365 single-nucleotide polymorphisms (SNPs). Twelve statistically significant SNPs were identified and mapped to chromosome 6p21.3. Associations were replicated in two independent sets of case-control samples. Two of the most significant SNPs (rs2517713 and rs2975042;p_combined = 3.9 × 10^-20 and 1.6 × 10^-19, respectively) were located in the HLA-A gene. Moreover, we detected significant associations between NPC and two genes: specifically, gamma aminobutyric acid b receptor 1 (GABBR1) (rs29232;p_combined = 8.97 × 10^-17) and HLA-F (rs3129055 and rs9258122;p_combined = 7.36 × 10^-11 and 3.33 × 10^-10, respectively). Notably, the association of rs29232 remained significant (residual p < 5 × 10^-4) after adjustment for age, gender, and HLA-related SNPs. Furthermore, higher GABA_B receptor 1 expression levels can be found in the tumor cells in comparison to the adjacent epithelial cells (p < 0.001) in NPC biopsies, implying a biological role of GABBR1 in NPC carcinogenesis. To our knowledge, it is the first GWAS report of NPC showing that multiple loci (HLA-A, HLA-F, and GABBR1) within chromosome 6p21.3 are associated with NPC. Although some of these relationships may be attributed to linkage disequilibrium between the loci, the findings clearly provide a fresh direction for the study of NPC development. © 2009 The American Society of Human Genetics.

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Predicting Blood-Brain Barrier Penetration by Stochastic Discrimination

Predicting Blood-Brain Barrier Penetration by Stochastic Dis...

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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Dechang Chen Jianwen Fang Jiawei Yu Division of Epidemiology and Biostatistics Department of Preventive Medicine and Biometrics Uniformed Services University of Health Sciences Bethesda MD USA Bioinformatics Core Facility and Information and Telecommunication Technology Center University of Kansas Lawrence KS Department of Computer Science George Washington University WA USA

The importance of optimizing the ability to penetrate blood-brain barrier of potential drug candidates is now widely recognized. Accurate computational prediction of such a properly will significantly enhance the speed of the blood-brain barrier penetration analysis and reduce the cost of drug discovery. In this paper, we present some results of our predictive model built on the stochastic discrimination, a pattern classification method that has been shown to be a useful in the literature.

关键词： Stochastic processes Drugs Predictive models Costs Pattern recognition Biomedical engineering Biomedical informatics Biometrics Bridges bioinformatics

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Outcomes Following Allogeneic Hematopoietic Stem Cell Transplantation For Metachromatic Leukodystrophy

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BLOOD 2013年第21期122卷 714-714页

作者： Boucher, Alexander A. Raymond, Gerald V. Shanley, Ryan Orchard, Paul J. Miller, Weston P. Department of Internal Medicine and Pediatrics University of Minnesota Minneapolis MN USA Department of Neurology University of Minnesota Minneapolis MN USA Biostatistics and Bioinformatics Core University of Minnesota Masonic Cancer Center Minneapolis MN USA Department of Pediatrics Division of Blood and Marrow Transplantation University of Minnesota Minneapolis MN USA

714

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The largest genome-wide association study for breast cancer in Taiwanese Han population

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Breast Cancer Research and Treatment 2024年第2期203卷 291-306页

作者： Hsu, Yu-Ching Chen, Hung-Lin Cheng, Chi-Fung Chattopadhyay, Amrita Chen, Pei-Shan Lin, Che-Chen Chiang, Hsiu-Yin Liu, Ting-Yuan Huang, Chi-Hao Kuo, Chin-Chi Chuang, Eric Y. Lu, Tzu-Pin Tsai, Fuu-Jen Bioinformatics Program Taiwan International Graduate Program National Taiwan University Taipei Taiwan Bioinformatics Program Institute of Statistical Science Taiwan International Graduate Program Academia Sinica Taipei Taiwan Institute of Health Data Analytics and Statistics Department of Public Health College of Public Health National Taiwan University Taipei Taiwan Big Data Center China Medical University Hospital Taichung Taiwan Center for Translational Genomic Research Department of Medical Research China Medical University Hospital Taichung Taiwan Million-Person Precision Medicine Initiative Department of Medical Research China Medical University Hospital Taichung Taiwan Division of Breast Surgery Department of Surgery China Medical University Hospital Taichung Taiwan Division of Nephrology Department of Internal Medicine China Medical University Hospital Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Bioinformatics and Biostatistics Core Center of Genomic and Precision Medicine National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Biomedical Technology and Device Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Genetic Center Department of Medical Research China Medical University Hospital Taichung Taiwan

Purpose: Breast cancer is a molecularly heterogeneous disease, and multiple genetic variants contribute to its development and prognosis. Most of previous genome-wide association studies (GWASs) and polygenic risk scores (PRSs) analyses focused on studying breast cancers of Caucasian populations, which may not be applicable to other population. Therefore, we conducted the largest breast cancer cohort of Taiwanese population to fill in the knowledge gap. Methods: A total of 152,534 Participants recruited by China Medical University Hospital between 2003 and 2019 were filtered by several patient selection criteria and GWAS quality control steps, resulting in the inclusion of 2496 cases and 9984 controls for this study. We then conducted GWAS for all breast cancers and PRS analyses for all breast cancers and the four breast cancer subtypes, including luminal A, luminal B, basal-like, and HER2-enriched. Results: The GWAS analyses identified 113 SNPs, 50 of which were novel. The PRS models for all breast cancers and the luminal A subtype showed positively correlated trends between the PRS and the risk of developing breast cancer. The odds ratios (95% confidence intervals) for the groups with the highest PRS in all breast cancers and the luminal A subtype were 5.33 (3.79–7.66) and 3.55 (2.13–6.14), respectively. Conclusion: In summary, we explored the association of genetic variants with breast cancer in the largest Taiwanese cohort and developed two PRS models that can predict the risk of developing any breast cancer and the luminal A subtype in Taiwanese women. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Breast cancer Genome-wide association study Polygenic risk score Taiwanese population

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Twnbiome: a public database of the healthy Taiwanese gut microbiome

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BMC bioinformatics 2023年第1期24卷 1-13页

作者： Chattopadhyay, Amrita Lee, Chien-Yueh Lee, Ya-Chin Liu, Chiang-Lin Chen, Hsin-Kuang Li, Yung-Hua Lai, Liang-Chuan Tsai, Mong-Hsun Ni, Yen-Hsuan Chiu, Han-Mo Lu, Tzu-Pin Chuang, Eric Y. Bioinformatics and Biostatistics Core Centers of Genomic and Precision Medicine National Taiwan University Taipei Taiwan Department of Biomedical Engineering China Medical University Taichung Taiwan Department of Public Health Institute of Health Data Analytics and Statistics National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Center for Biotechnology National Taiwan University Taipei Taiwan Graduate Institute of Physiology National Taiwan University Taipei Taiwan Institute of Biotechnology National Taiwan University Taipei Taiwan College of Medicine National Taiwan University Taipei Taiwan Department of Internal Medicine National Taiwan University Hospital Taipei Taiwan Institute of Health Data Analytics and Statistics National Taiwan University Taipei Taiwan Biomedical Technology and Device Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Division Research and Development Center for Medical Devices National Taiwan University Taipei Taiwan

With new advances in next generation sequencing (NGS) technology at reduced costs, research on bacterial genomes in the environment has become affordable. Compared to traditional methods, NGS provides high-throughput sequencing reads and the ability to identify many species in the microbiome that were previously unknown. Numerous bioinformatics tools and algorithms have been developed to conduct such analyses. However, in order to obtain biologically meaningful results, the researcher must select the proper tools and combine them to construct an efficient pipeline. This complex procedure may include tens of tools, each of which require correct parameter settings. Furthermore, an NGS data analysis involves multiple series of command-line tools and requires extensive computational resources, which imposes a high barrier for biologists and clinicians to conduct NGS analysis and even interpret their own data. Therefore, we established a public gut microbiome database, which we call Twnbiome, created using healthy subjects from Taiwan, with the goal of enabling microbiota research for the Taiwanese population. Twnbiome provides users with a baseline gut microbiome panel from a healthy Taiwanese cohort, which can be utilized as a reference for conducting case-control studies for a variety of diseases. It is an interactive, informative, and user-friendly database. Twnbiome additionally offers an analysis pipeline, where users can upload their data and download analyzed results. Twnbiome offers an online database which non-bioinformatics users such as clinicians and doctors can not only utilize to access a control set of data, but also analyze raw data with a few easy clicks. All results are customizable with ready-made plots and easily downloadable tables. Database URL: http://***/ . © 2023, The Author(s).

关键词： Database systems

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Analyzing differential regulatory networks modulated by continuous-state genomic features in glioblastoma multiforme

Analyzing differential regulatory networks modulated by cont...

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IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Yu-Chiao Chiu Kai-Wen Liang Tzu-Hung Hsiao Yidong Chen Eric Y. Chuang Greehey Children's Cancer Research Institute University of Texas Health Science Center at San Antonio Texas United States of America Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Deoartment of Medical Research Taichung Veterans General Hospital Taichung Taiwan Department of Epidemiology and Biostatistics University of Texas Health Science Center at San Antonio United States of America Bioinformatics and Biostatistics Core Center of Genomic Medicine National Taiwan University Taipei Taiwan

Gene regulatory networks are a global representation of complex interactions between molecules that dictate cellular behavior. Study of a regulatory network modulated by single or multiple modulators' expression levels, including microRNAs (miRNAs) and transcription factors (TFs), in different conditions can further reveal the modulators' roles in diseases such as cancers. Existing computational methods for identifying such modulated regulatory networks are typically carried out by comparing groups of samples dichotomized with respect to the modulator status, ignoring the fact that most biological features are intrinsically continuous variables. Here we devised a sliding window-based regression scheme and proposed the Regression-based Inference of Modulation (RIM) algorithm to infer the dynamic gene regulation modulated by continuous-state modulators. We demonstrated the improvement in performance as well as computation efficiency achieved by RIM. Applying RIM to genome-wide expression profiles of 520 glioblastoma multiforme (GBM) tumors, we investigated miRNA- and TF-modulated gene regulatory networks and showed their association with dynamic cellular processes and brain-related functions in GBM. Overall, the proposed algorithm provides an efficient and robust scheme for comprehensively studying modulated gene regulatory networks.

关键词： Genomics bioinformatics Modulation Robustness MATLAB Mathematical model

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