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arXiv 2025年

作者： Yang, Zhenwei Rizopoulos, Dimitris Newcomb, Lisa F. Erler, Nicole S. Department of Epidemiology and Biostatistics Erasmus Medical Center Rotterdam Netherlands Fred Hutchinson Cancer Center Cancer Prevention Program Public Health Sciences SeattleWA United States Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht University Netherlands

Evaluating the performance of a prediction model is a common task in medical statistics. Standard accuracy metrics require the observation of the true outcomes. This is typically not possible in the setting with time-to-event outcomes due to censoring. Interval censoring, the presence of time-varying covariates, and competing risks present additional challenges in obtaining those accuracy metrics. In this study, we propose two methods to deal with interval censoring in a time-varying competing risk setting: a model-based approach and the inverse probability of censoring weighting (IPCW) approach, focusing on three key time-dependent metrics: area under the receiver-operating characteristic curve (AUC), Brier score, and expected predictive cross-entropy (EPCE). The evaluation is conducted over a medically relevant time interval of interest, [t,∆t). The model-based approach includes all subjects in the risk set, using their predicted risks to contribute to the accuracy metrics. In contrast, the IPCW approach only considers the subset of subjects who are known to be event-free or experience the event within the interval of interest. we performed a simulation study to compare the performance of the two approaches with regard to the three metrics. © 2025, CC BY-NC-ND.

关键词： Prediction models

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Novel Genetic Loci Associated with PhenoAge Acceleration——Changzhou City, Jiangsu Province, China, 2012-2019

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China CDC weekly 2024年第49期6卷 1294-1298,I0004-I0006页

作者： Yifan Wang Yue Jiang Hui Wang Shuang Liang Muhammed Lamin Sambou Mei Wang Meiqi Yang Yakubu Salimata Feifei Xu Chenjie Li Xiao Wang Junpeng Yang Meng Zhu Cheng Wang Guangfu Jin Hongxia Ma Honggang Yi Hongbing Shen Juncheng Dai Department of Epidemiology Center for Global HealthSchool of Public HealthNanjing Medical UniversityNanjing CityJiangsu ProvinceChina State Key Laboratory of Reproductive Medicine Nanjing Medical UniversityNanjing CityJiangsu ProvinceChina China International Cooperation Center for Environment and Human Health Nanjing Medical UniversityNanjing CityJiangsu ProvinceChina State Key Lab of Cancer Biomarkers Prevention and TreatmentCollaborative Innovation Center for Cancer Personalized MedicineNanjing Medical UniversityNanjing CityJiangsu ProvinceChina The First School of Clinical Medicine Nanjing Medical UniversityNanjingChina Department of Bioinformatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing CityJiangsu ProvinceChina Department of Biostatistics School of Public HealthNanjing Medical UniversityNanjing CityJiangsu ProvinceChina The Chinese Center for Disease Control and Prevention BeijingChina Jiangsu Life and Health Industry Academician Collaborative Innovation Center Nanjing CityJiangsu ProvinceChina

What is already known about this topic?China is rapidly encountering population aging,yet studies on aging are limited by the traditional aging measure:chronological age,particularly in the field of *** promising agin... 详细信息

关键词： measures evaluation Jiangsu

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From pixels to patients: the evolution and future of deep learning in cancer diagnostics

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Trends in molecular medicine 2024年第6期31卷 548-558页

作者： Yichen Yang Hongru Shen Kexin Chen Xiangchun Li Tianjin Cancer Institute Tianjin's Clinical Research Center for Cancer National Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy of Tianjin Tianjin Medical University Cancer Institute and Hospital Tianjin Medical University Tianjin China. Department of Epidemiology and Biostatistics Key Laboratory of Molecular Cancer Epidemiology of Tianjin Key Laboratory of Prevention and Control of Human Major Diseases in Ministry of Education Tianjin's Clinical Research Center for Cancer National Clinical Research Center for Cancer Tianjin Medical University Cancer Institute and Hospital Tianjin Medical University Tianjin China. Electronic address: chenkexin@***. Tianjin Cancer Institute Tianjin's Clinical Research Center for Cancer National Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy of Tianjin Tianjin Medical University Cancer Institute and Hospital Tianjin Medical University Tianjin China. Electronic address: lixiangchun@***.

Deep learning has revolutionized cancer diagnostics, shifting from pixel-based image analysis to more comprehensive, patient-centric care. This opinion article explores recent advancements in neural network architectures, highlighting their evolution in biomedical research and their impact on medical imaging interpretation and multimodal data integration. We emphasize the need for domain-specific artificial intelligence (AI) systems capable of handling complex clinical tasks, advocating for the development of multimodal large language models that can integrate diverse data sources. These models have the potential to significantly enhance the precision and efficiency of cancer diagnostics, transforming AI from a supplementary tool into a core component of clinical decision-making, ultimately improving patient outcomes and advancing cancer care.

关键词： artificial intelligence cancer diagnosis deep learning multimodal large language model visual-language model

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Disparities in trends and drivers of the burden of tracheal,bronchus,and lung cancer among Chinese population during 1990-2021:a systematic analysis for the global burden of disease study 2021

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Science Bulletin 2025年第4期70卷 496-499页

作者： Huixin Liu Jinlei Qi Wenhui Ren Zifang Zhou Xiangyu Guo Peng Yin Lijun Wang Fanshu Yan Xiaohui Xu Jun Wang Maigeng Zhou Kezhong Chen Thoracic Oncology Institute&Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer Chinese Academy of Medical Sciences2021RU002Peking University People’s HospitalBeijing 100044China Department of Clinical Epidemiology and Biostatistics Peking University People’s HospitalBeijing 100044China National Center for Chronic and Noncommunicable Disease Control and Prevention Chinese Center for Disease Control and PreventionBeijing 100050China Department of Neuro-Oncology Cancer CenterBeijing Tiantan HospitalCapital Medical UniversityBeijing 100070China Department of Thoracic Surgery Peking University People’s HospitalBeijing 100044China Institute of Advanced Clinical Medicine Peking UniversityBeijing 100191China

Globally,lung cancer is the most prevalent cancer(11.4%of all cancers)and the leading cause of cancer deaths(18%of all cancers)[1],[2].With one-fifth of the global population,China is a top contributor to the lung cancer burden,accounting for 37%of new cases and 30%of deaths worldwide[2].Several studies have estimated the tracheal,bronchus,and lung cancer(TBLC)burden at the global and national levels[3],[4],[5].However,the drivers and patterns of TBLC burden in China are different from those in other *** China’s vast territory,uneven economic development,and disparities in medical resources of China,a detailed description and analysis of the current and temporal trends in TBLC and its attributable risks across different Chinese populations would help to identify priority populations that require attention and targeted strategies to reduce the TBLC burden.

关键词： lung tracheal TBL

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Disparities in stage at diagnosis for liver cancer in China

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Journal of the National cancer Center 2023年第1期3卷 7-13页

作者： Tianhao Shan Xianhui Ran Huizhang Li Guoshuang Feng Siwei Zhang Xuehong Zhang Lei Zhang Lingeng Lu Lan An Ruiying Fu Kexin Sun Shaoming Wang Ru Chen Li Li Wanqing Chen Wenqiang Wei Hongmei Zeng Jie He National Central Cancer Registry National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina Cancer Hospital of University of Chinese Academy of Sciences/Zhejiang Cancer Hospital Department of Cancer PreventionInstitute of Cancer Research and Basic Medical SciencesChinese Academy of SciencesHangzhouChina Big Data Center Beijing Children’s HospitalCapital Medical UniversityNational Center for Children’s HealthBeijingChina Channing Division of Network Medicine Department of MedicineBrigham and Women’s Hospital and Harvard Medical SchoolBostonUSA Department of Nutrition T.H.Chan School of Public HealthHarvard UniversityBostonUSA China-Australia Joint Research Center for Infectious Diseases School of Public HealthXi’an Jiaotong University Health Science CenterXi’anChina Artificial Intelligence and Modelling in Epidemiology Program Melbourne Sexual Health CentreAlfred HealthMelbourneAustralia Central Clinical School Faculty of MedicineMonash UniversityMelbourneAustralia Department of Epidemiology and Biostatistics College of Public HealthZhengzhou UniversityZhengzhouChina Department of Chronic Disease Epidemiology Yale School of Public HealthYale Cancer CenterNew HavenUSA Department of Thoracic Surgery National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina

Background:The stage at diagnosis is a major factor in making treatment strategies and cancer control ***,the stage distribution for liver cancer in China was not well *** this multi-center hospital-based study,we aimed to identify the distribution and factors associated with stage at diagnosis for liver cancer in ***:We included patients diagnosed with primary liver cancer in 13 hospitals of 10 provinces covering various geographic and socioeconomic populations during 2016-2017 in *** stage distribution overall,and by sex and age at diagnosis were *** used logistic regression to identify the factors associated with stage Ⅲ-Ⅳ *** further compared these estimates with data from the ***:We included 2,991 patients with known stage at diagnosis in *** proportion of patients diagnosed with stageⅠ,Ⅱ,Ⅲ,and Ⅳ was 17.5%,25.6%,29.3%,and 27.6%,*** proportion of stage Ⅲ-Ⅳ cases was higher in women[65.1%vs 54.9%,adjusted odds ratio(OR)=1.5,95%CI:1.2,1.8]and those≥60 years(61.6%vs 52.8%,OR=1.4,95%CI:1.2,1.6).We found an increased risk of stage Ⅲ-Ⅳ among drinkers and those without a family history of *** to the USA,our study population had a substantially higher proportion of stage Ⅲ-Ⅳ cases(56.9%vs 45.6%).Conclusion:The disparities in liver cancer stage at diagnosis among different populations within China,and between China and the USA,imply the necessity for improving cancer awareness and early detection for liver cancer in China.

关键词： Liver cancer Stage at diagnosis Disparity China USA

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Development and validation of an infectious disease control competency scale for public health professionals

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Global Health Research and Policy 2024年第1期9卷 171-189页

作者： Yiguo Zhou Wan‑Xue Zhang Shan‑Shan Zhang Ning‑Hua Huang Jing Zeng Han Yang Qin‑Yi Ma Le Ao Ya‑Qiong Liu Juan Du Xiao‑Ling Tian Qing‑Bin Lu Fuqiang Cui Department of Health Policy and Management School of Public HealthPeking UniversityBeijingChina Department of Epidemiology and Biostatistics School of Public HealthPeking UniversityBeijingChina Centre for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group Peking UniversityBeijingChina Department of Laboratorial Science and Technology and Vaccine Research Centre School of Public HealthPeking UniversityNo.38 Xue‑Yuan RoadHaidian DistrictBeijing 100191China Institute for Immunization Program Inner Mongolia Centre for Disease Control and Prevention(The Academy of Preventive Medicine Sciences In Inner Mongolia)South Yongping RoadXincheng DistrictHohhot 010080China Key Laboratory of Epidemiology of Major Diseases(Peking University) Ministry of EducationBeijingChina

Background Infectious diseases persistently pose global threats,and it is imperative to accelerate the profession-alization of public health *** study aimed to develop and validate the infectious disease control compe-tency scale(IDCCS)for public health professionals to fill a theoretical gap and elevate practical capabilities by inform-ing public health professionals’development *** The initial item pool was generated through a literature review,and categorized into three dimensions(knowledge,practical skills,and leadership)based on the competency iceberg model and public health leadership framework.A two-round Delphi process was conducted to determine indicators within the scale.A pilot survey was utilized for item analysis and exploratory factor analysis(EFA).A formal survey was employed for confirmatory fac-tor analysis(CFA).The weight value of each indicator was calculated using the analytic hierarchy *** An initial scale with three primary items,14 secondary items,and 81 tertiary items was *** experts participated in the two rounds of the Delphi *** coefficients exceeded 0.9 in both ***’s W was 0.29 and 0.19,respectively(both P<0.001).Item analysis presented a Cronbach’s Alpha of 0.98,with corrected item-total correlation coefficients ranging from 0.33 to *** demonstrated that cumulative vari-ance explanations for the four primary dimensions(knowledge,practical skills,leadership,and personal quality)were 77.463%,73.976%,81.174%,and 68.654%,*** indicated that all composite reliability values and aver-age variance extracted surpassed 0.8 and 0.5,*** standardized factor loadings of the items ranged from 0.630 to *** the seven model fit indices,each of the four dimensions satisfied at least five criteria.A final three-level scale comprising four primary items,14 secondary items,and 64 tertiary items was *** weight values for the four primary it

关键词： Public health professionals Infectious diseases Competency Delphi Exploratory factor analysis

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Opportunities, challenges, and future directions for simulation modeling the effects of structural racism on cancer mortality in the United States: a scoping review

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Journal of the National cancer Institute - Monographs 2023年第62期2023卷 231-245页

作者： Jayasekera, Jinani El Kefi, Safa Fernandez, Jessica R. Wojcik, Kaitlyn M. Woo, Jennifer M.P. Ezeani, Adaora Ish, Jennifer L. Bhattacharya, Manami Ogunsina, Kemi Chang, Che-Jung Cohen, Camryn M. Ponce, Stephanie Kamil, Dalya Zhang, Julia Le, Randy Ramanathan, Amrita L. Butera, Gisela Chapman, Christina Grant, Shakira J. Lewis-Thames, Marquita W. Dash, Chiranjeev Bethea, Traci N. Forde, Allana T. Division of Intramural Research at the National Institute on Minority Health and Health Disparities National Institutes of Health Bethesda MD United States NYU Langone Health New York University New York NY USA Epidemiology Branch at the National Institute of Environmental Health Sciences at the National Institutes of Health Bethesda MD United States Health Behaviors Research Branch of the Behavioral Research Program Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD United States Cancer Prevention Fellowship Program Division of Cancer Prevention the Surveillance Research Program Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD United States Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health Rockville MD United States Sophomore at Williams College Williamstown MA United States Diabetes Endocrinology Obesity Branch National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD United States Office of Research Services National Institutes of Health Library Bethesda MD United States Department of Radiation Oncology Baylor College of Medicine the Center for Innovations in Quality Safety in the Department of Medicine Baylor College of Medicine and the Houston Veterans Affairs Houston TX United States Department of Medicine Division of Hematology University of North Carolina Chapel Hill NC United States Department of Medical Social Science Center for Community Health at Northwestern University Feinberg School of Medicine Chicago IL United States Office of Minority Health and Health Disparities Research at the Georgetown-Lombardi Comprehensive Cancer Center WA United States

Purpose: Structural racism could contribute to racial and ethnic disparities in cancer mortality via its broad effects on housing, economic opportunities, and health care. However, there has been limited focus on incorporating structural racism into simulation models designed to identify practice and policy strategies to support health equity. We reviewed studies evaluating structural racism and cancer mortality disparities to highlight opportunities, challenges, and future directions to capture this broad concept in simulation modeling research. Methods: We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review Extension guidelines. Articles published between 2018 and 2023 were searched including terms related to race, ethnicity, cancer-specific and all-cause mortality, and structural racism. We included studies evaluating the effects of structural racism on racial and ethnic disparities in cancer mortality in the United States. Results: A total of 8345 articles were identified, and 183 articles were included. Studies used different measures, data sources, and methods. For example, in 20 studies, racial residential segregation, one component of structural racism, was measured by indices of dissimilarity, concentration at the extremes, redlining, or isolation. Data sources included cancer registries, claims, or institutional data linked to area-level metrics from the US census or historical mortgage data. Segregation was associated with worse survival. Nine studies were location specific, and the segregation measures were developed for Black, Hispanic, and White residents. Conclusions: A range of measures and data sources are available to capture the effects of structural racism. We provide a set of recommendations for best practices for modelers to consider when incorporating the effects of structural racism into simulation models. © 2023 Oxford University Press. All rights reserved.

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An exploration for quantification of overdiagnosis and its effect for breast cancer screening

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Chinese Journal of cancer Research 2020年第1期32卷 26-35页

作者： Lei Yang Shengfeng Wang Yubei Huang Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Beijing Office for Cancer Prevention and ControlPeking University Cancer Hospital&InstituteBeijing 100142China Department of Epidemiology&Biostatistics School of Public HealthPeking UniversityBeijing 100191China Department of Epidemiology and Biostatistics Key Laboratory of Cancer Prevention and TherapyTianjinKey Laboratory of Breast Cancer Prevention and TherapyMinistry of EducationNational Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin 300060China

Objective: To redefine overdiagnosis and reestimate the proportion of overdiagnosis of breast cancer caused by screening based on the Surveillance, epidemiology, and End Results(SEER, 1973-2015) program ***: The breast cancer diagnosed before 1977 was defined as the no-screening cohort since America had initiated breast cancer screening from 1977. The breast cancer diagnosed in 1999 was defined as the screening cohort due to no increases in both the proportion of early-stage breast cancer until 1999 and the overall survival of early-stage breast cancer diagnosed over the three years since 1999. The magnitude of overdiagnosis was calculated as the difference in the proportions of early-stage breast cancer patients with long-time(15-year) survival to all breast cancer patients between two ***: Over 23 years before and after widespread screening in America, the proportion of early-stage breast cancer patients increased from 52.1%(16,891/32,443) to 72.7%(16,021/22,025)(P<0.001). The 15-year survival rate of early-stage breast cancer patients increased from 51.1% to 61.5%(P<0.001), while the proportions of earlystage breast cancer patients with long-time survival to all breast cancer patients increased from 26.6%(52.1%×51.1%) to 44.7%(72.7%×61.5%). Assuming no improvements in cancer screening technology and treatment technology, 18.1%(44.7%-26.6%) of breast cancer patients were overdiagnosed associated with screening. The age-specific overdiagnosis rates were 18.9%, 24.7%, 24.5%, 20.5%, and 8.3% for breast cancer patients aged 40-49, 50-59, 60-69, 70-74, and ≥75 years old, ***: Overdiagnosis caused by mammographic screening is probably overestimated in current screening practices. Further trials with more sophisticated designs and analyses are needed to validate our findings in the future.

关键词： Breast cancer screening overdiagnosis

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Reporting tumor genomic test results to SEER registries via linkages

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Journal of the National cancer Institute - Monographs 2024年第65期2024卷 168-179页

作者： Petkov, Valentina I. Byun, Jung S. Ward, Kevin C. Schussler, Nicola C. Archer, Natalie P. Bentler, Suzanne Doherty, Jennifer A. Durbin, Eric B. Gershman, Susan T. Cheng, Iona Insaf, Tabassum Gonsalves, Lou Hernandez, Brenda Y. Koch, Lori Liu, Lihua Monnereau, Alain Morawski, Bozena M. Schwartz, Stephen M. Stroup, Antoinette Wiggins, Charles Wu, Xiao-Cheng Bonds, Sarah Negoita, Serban Penberthy, Lynne Surveillance Research Program Division of Cancer Control and Population Sciences National Cancer Institute Bethesda MD United States Emory University Atlanta GA United States Information Management Services Inc Calverton MD United States Cancer Epidemiology and Surveillance Branch Texas Department of State Health Services Austin TX United States Iowa Cancer Registry The University of Iowa Iowa City IA United States Hunstman Cancer Institute University of Utah Salt Lake City UT United States Department of Population Health Sciences University of Utah Salt Lake City UT United States Cancer Research Informatics Shared Resource Facility Markey Cancer Center Kentucky Cancer Registry University of Kentucky Lexington KY United States Massachusetts Cancer Registry Boston MA United States Department of Epidemiology and Biostatistics University of California San Francisco San Francisco CA United States New York State Department of Health New York State Cancer Registry Albany NY United States Connecticut Department of Public Health Connecticut Tumor Registry Hartford CT United States University of Hawaii Cancer Center Honolulu HI United States Illinois State Cancer Registry Springfield IL United States Department of Population and Public Health Sciences Keck School of Medicine University of Southern California Los Angeles CA United States Public Health Institute Cancer Registry of Greater California Sacramento CA United States Cancer Data Registry of Idaho Boise ID United States Division of Public Health Sciences Fred Hutchinson Cancer Center Seattle WA United States New Jersey State Cancer Registry Trenton NJ United States Department of Internal Medicine University of New Mexico Albuquerque NM United States School of Medicine Louisiana State University New Orleans LA United States

Background: Precision medicine has become a mainstay of cancer care in recent years. The National cancer Institute (NCI) Surveillance, epidemiology, and End Results (SEER) program has been an authoritative source of cancer statistics and data since 1973. However, tumor genomic information has not been adequately captured in the cancer surveillance data, which impedes population-based research on molecular subtypes. To address this, the SEER program has developed and implemented a centralized process to link SEER registries' tumor cases with genomic test results that are provided by molecular laboratories to the registries. Methods: Data linkages were carried out following operating procedures for centralized linkages established by the SEER program. The linkages used Match∗Pro, a probabilistic linkage software, and were facilitated by the registries' trusted third party (an honest broker). The SEER registries provide to NCI limited datasets that undergo preliminary evaluation prior to their release to the research community. Results: Recently conducted genomic linkages included OncotypeDX Breast Recurrence Score, OncotypeDX Breast Ductal Carcinoma in Situ, OncotypeDX Genomic Prostate Score, Decipher Prostate Genomic Classifier, DecisionDX Uveal Melanoma, DecisionDX Preferentially Expressed Antigen in Melanoma, DecisionDX Melanoma, and germline tests results in Georgia and California SEER registries. Conclusions: The linkages of cancer cases from SEER registries with genomic test results obtained from molecular laboratories offer an effective approach for data collection in cancer surveillance. By providing de-identified data to the research community, the NCI's SEER program enables scientists to investigate numerous research inquiries. © 2024 The Author(s). Published by Oxford University Press. All rights reserved.

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Age at menarche by birth cohort: A pooled analysis of half a million women in Asia

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Public Health 2024年 237卷 130-134页

作者： Abe, Sarah K. Nishio, Marisa Huang, Hsi-Lan Leung, Chi Yan Islam, Md Rashedul Rahman, Md Shafiur Saito, Eiko Shin, Aesun Merritt, Melissa A. Choi, Ji-Yeob Katagiri, Ryoko Mohammadi, Zahra Shu, Xiao-Ou Wakai, Kenji Sawada, Norie Ideno, Yuki Tamakoshi, Akiko Seow, Wei Jie Koh, Woon-Puay Sakata, Ritsu Hozawa, Atsushi Kim, Jeongseon Nagata, Chisato Sugawara, Yumi Park, Sue K. Kweon, Sun-Seog Azizi, Fereidoun Malekzadeh, Reza Moy, Foong-Ming Pourfarzi, Farhad Gao, Yu-Tang Kubo, Yoko Hirabayashi, Mayo Nagai, Kazue Kimura, Takashi Yuan, Jian-Min Kanemura, Seiki Wada, Keiko Kang, Daehee Shin, Min-Ho Khalili, Davood Poustchi, Hossein Rezaianzadeh, Abbas Mansour-Ghanaei, Fariborz Najafi, Farid Mohebbi, Iraj Boffetta, Paolo Lee, Jung Eun Matsuo, Keitaro Rothman, Nathaniel Qiao, You-Lin Zheng, Wei Inoue, Manami Division of Prevention National Cancer Center Institute for Cancer Control Japan Hitotsubashi Institute for Advanced Study Hitotsubashi University Japan Research Center for Child Mental Development Hamamatsu University School of Medicine Japan Sustainable Society Design Center Graduate School of Frontier Sciences the University of Tokyo Japan Department of Preventive Medicine Seoul National University College of Medicine Seoul South Korea Cancer Research Institute Seoul National University Seoul South Korea The Daffodil Centre The University of Sydney a joint venture with Cancer Council NSW Sydney NSW Australia Department of Biomedical Sciences Seoul National University Graduate School Seoul South Korea Graduate School of Informatics Faculty of Informatics Chiba University Japan Liver and Pancreatobiliary Diseases Research Center Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Division of Epidemiology Department of Medicine Vanderbilt Epidemiology Center Vanderbilt-Ingram Cancer Center Vanderbilt University Medical Center Nashville TN United States Department of Preventive Medicine Nagoya University School of Medicine Nagoya Japan Division of Cohort Research National Cancer Center Institute for Cancer Control Japan Gunma University Center for Food Science and Wellness Maebashi Japan Department of Public Health Hokkaido University Faculty of Medicine Sapporo Japan Saw Swee Hock School of Public Health and Department of Medicine National University of Singapore and National University Health System Singapore Healthy Longevity Translational Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore Institute for Clinical Sciences Agency for Science Technology and Research (A∗STAR) Singapore Department of Epidemiology Radiation Effects Research Foundation Hiroshima Japan Division of Epidemiology Department of Public Health and Forensic Medicine Tohoku University Graduate School

Objectives: To evaluate changes in the age at menarche in Asian populations. Study design: Retrospective cohort study. Methods: We included 548,830 women from six countries in Asia. The data were sourced from 20 cohorts participating in the Asia Cohort Consortium (ACC) and two additional cohort studies: Japan Multi-institutional Collaborative Cohorts (J-MICC), and Japan Nurse Health Study (JNHS) with data on age at menarche. Joinpoint regression was used to evaluate changes in age at menarche by birth year and by country. Results: The study includes data from cohorts in six Asian countries namely, China, Iran, Japan, Korea, Malaysia and Singapore. Birth cohorts ranged from 1873 to 1995. The mean age of menarche was 14.0 years with a standard deviation (SD) of 1.4 years, ranged from 12.6 to 15.5 years. Over 100 years age at menarche showed an overall decrease in all six countries. China showed a mixed pattern of decrease, increase, and subsequent decrease from 1926 to 1960. Iran and Malaysia experienced a sharp decline between about 1985 and 1990, with APC values of −4.48 and −1.24, respectively, while Japan, South Korea, and Singapore exhibited a nearly linear decline since the 1980s, notably with an APC of −3.41 in Singapore from 1993 to 1995. Conclusions: Overall, we observed a declining age at menarche, while the pace of the change differed by country. Additional long-term observation is needed to examine the contributing factors of differences in trend across Asian countries. The study could serve as a tool to strengthen global health campaigns. © 2024 The Royal Society for Public Health

关键词： Age Asia Birth cohort Menarche

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