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Practice-, Provider-, and Patient-level interventions to improve preventive care: Development of the P3 Model

Preventive Medicine Reports 2018年 11卷 131-138页

作者： Bednarczyk, Robert A. Chamberlain, Allison Mathewson, Kara Salmon, Daniel A. Omer, Saad B. Hubert Department of Global Health Rollins School of Public Health Emory University Atlanta GA United States Department of Epidemiology Rollins School of Public Health Emory University Atlanta GA United States Cancer Prevention and Control Program Winship Cancer Institute Emory University Atlanta GA United States Emory Vaccine Center Emory University Atlanta GA United States Institute for Vaccine Safety Bloomberg School of Public Health Johns Hopkins University Baltimore MD United States Department of Pediatrics School of Medicine Emory University Atlanta GA United States

For adequate provision of preventive services, there is an interplay between activities at the healthcare practice, healthcare provider, and patient levels of the clinical encounter. Commonly used health promotion and behavior theoretical models address some of these three levels, but none fully account for all three. Building off of key components of many existing theoretical models, including the Health Belief Model, Theory of Planned Behavior/Theory of Reasoned Action, Social Cognitive Theory, Social Ecological Model, and the Systems Model of Clinical Preventive Care, we describe the development of the P3 (Practice-, Provider-, and Patient-level) Model for preventive care interventions. The P3 Model accounts for all three levels of the clinical encounter, and the factors that impact these levels, concurrently. This yields a model for preventive care that is applicable and adaptable to different settings, and that provides a framework for the development, implementation, and evaluation of preventive care promotion interventions. The applicability of the P3 Model is shown through two exemplar preventive care programs – immunization and colorectal cancer screening. The P3 Model allows interventions to be developed and evaluated in a modular approach, to allow more practical refinement and optimization of the intervention. © 2018 The Authors

关键词： Behavior change Behavior change theory cancer prevention and control Health promotion Immunization

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Correction: Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes

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Leukemia 2023年第10期37卷 2142页

作者： Sonja I Berndt Joseph Vijai Yolanda Benavente Nicola J Camp Alexandra Nieters Zhaoming Wang Karin E Smedby Geffen Kleinstern Henrik Hjalgrim Caroline Besson Christine F Skibola Lindsay M Morton Angela R Brooks-Wilson Lauren R Teras Charles Breeze Joshua Arias Hans-Olov Adami Demetrius Albanes Kenneth C Anderson Stephen M Ansell Bryan Bassig Nikolaus Becker Parveen Bhatti Brenda M Birmann Paolo Boffetta Paige M Bracci Paul Brennan Elizabeth E Brown Laurie Burdett Lisa A Cannon-Albright Ellen T Chang Brian C H Chiu Charles C Chung Jacqueline Clavel Pierluigi Cocco Graham Colditz Lucia Conde David V Conti David G Cox Karen Curtin Delphine Casabonne Immaculata De Vivo Arjan Diepstra W Ryan Diver Ahmet Dogan Christopher K Edlund Lenka Foretova Joseph F Fraumeni Attilio Gabbas Hervé Ghesquières Graham G Giles Sally Glaser Martha Glenn Bengt Glimelius Jian Gu Thomas M Habermann Christopher A Haiman Corinne Haioun Jonathan N Hofmann Theodore R Holford Elizabeth A Holly Amy Hutchinson Aalin Izhar Rebecca D Jackson Ruth F Jarrett Rudolph Kaaks Eleanor Kane Laurence N Kolonel Yinfei Kong Peter Kraft Anne Kricker Annette Lake Qing Lan Charles Lawrence Dalin Li Mark Liebow Brian K Link Corrado Magnani Marc Maynadie James McKay Mads Melbye Lucia Miligi Roger L Milne Thierry J Molina Alain Monnereau Rebecca Montalvan Kari E North Anne J Novak Kenan Onel Mark P Purdue Kristin A Rand Elio Riboli Jacques Riby Eve Roman Gilles Salles Douglas W Sborov Richard K Severson Tait D Shanafelt Martyn T Smith Alexandra Smith Kevin W Song Lei Song Melissa C Southey John J Spinelli Anthony Staines Deborah Stephens Heather J Sutherland Kaitlyn Tkachuk Carrie A Thompson Hervé Tilly Lesley F Tinker Ruth C Travis Jenny Turner Celine M Vachon Claire M Vajdic Anke Van Den Berg David J Van Den Berg Roel C H Vermeulen Paolo Vineis Sophia S Wang Elisabete Weiderpass George J Weiner Stephanie Weinstein Nicole Wong Doo Yuanqing Ye Meredith Yeager Kai Yu Anne Zeleniuch-Jacquotte Yawei Zhang Tongzhang Zheng Elad Ziv Joshua Sampson Nilanjan Chatterjee Kenn Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda Md USA. berndts@mail.nih.gov. Department of Medicine Memorial Sloan Kettering Cancer Center New York NY USA. Cancer Epidemiology Research Programme Catalan Institute of Oncology-IDIBELL L'Hospitalet de Llobregat Barcelona Spain. CIBER de Epidemiología y Salud Pública (CIBERESP) Barcelona Spain. Department of Internal Medicine and Huntsman Cancer Institute University of Utah School of Medicine Salt Lake City UT USA. Institute for Immunodeficiency University Medical Center Freiburg Freiburg Germany. Department of Epidemiology and Cancer Control St. Jude Children's Research Hospital Memphis TN USA. Laboratory of Translational Genomics Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda MD USA. Department of Medicine Solna Karolinska Institutet Stockholm Sweden. Hematology Center Karolinska University Hospital Stockholm Sweden. School of Public Health University of Haifa Haifa Israel. Department of Epidemiology Research Division of Health Surveillance and Research Statens Serum Institut Copenhagen Denmark. Department of Clinical Medicine University of Copenhagen Copenhagen Denmark. Department of Haematology Rigshospitalet Copenhagen Denmark. Danish Cancer Society Research Center Danish Cancer Society Copenhagen Denmark. Centre Hospitalier de Versailles Le Chesnay France. Université Paris-Saclay UVSQ Inserm Équipe "Exposome et Hérédité" CESP Villejuif France. Department of Hematology and Medical Oncology Emory University School of Medicine Atlanta GA USA. Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda Md USA. Genome Sciences Centre BC Cancer Agency Vancouver BC Canada. Department of Biomedical Physiology and Kinesiology Simon Fraser University Burnaby BC Canada. Department of Population Science American Cancer Society Atlanta GA USA. Department of Medical Epidemiology and Biostatistics Karolinska In

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Dietary Inflammatory Index (DII®) and Lung Function in Adults from Ten European Countries – Evidence from the GA2LEN Follow-Up Survey

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Current Developments in Nutrition 2020年第SUPPL 2期4卷 4141393-4141393页

作者： de Castro Mendes, Francisca Thawer, Sumaiyya Shivappa, Nitin Hebert, James R. Burney, Peter GJ Garcia-Larsen, Vanessa Visiting Scholar The Johns Hopkins Bloomberg of Public Health PhD Student Serviço de Imunologia Básica e Clínica Departamento de Patologia Faculdade de Medicina da Universidade do Porto EPI Unit - Instituto de Saúde Pública Universidade do Porto Swiss Tropical Institute of Public Health University of Basel Basel Switzerland Cancer Prevention and Control Program University of South Carolina Department of Epidemiology and Biostatistics Arnold School of Public Health University of South Carolina Connecting Health Innovations LLC Director Cancer Prevention and Control Program University of South Carolina Health Sciences Distinguished Professor Department of Epidemiology and Biostatistics Arnold School of Public Health University of South Carolina President and Scientific Director Connecting Health Innovations LLC National Heart and Lung Institute Imperial College London UK Program in Human Nutrition Department of International Health The Johns Hopkins Bloomberg School of Public Health

AbstractObjectivesTo investigate the association between Dietary Inflammatory Index (DII®) and lung function in European adults. MethodsThe study sample was drawn from the Global Allergy and Asthma Network of Excellence (GA 2LEN) screening survey, in which 55,000 adults aged 15 to 75 years answered a postal questionnaire on respiratory symptoms. A stratified random sample was obtained for follow-up. A cross-sectional study was conducted in this sample ( n = 3241), which included ascertainment of dietary intake and measures of lung function. Participants completed the internationally validated GA 2LEN food frequency questionnaire (FFQ), which enquired about usual intake of 245 food items. The dietary inflammatory index (DII®) was derived to ascertain the inflammatory potential of the diet (minimum and maximum reference range –8.87 to 7.98; i.e., the higher the score the more pro-inflammatory the diet). Participants performed post-bronchodilator spirometry, from which forced vital capacity (FVC), the ratio between the forced exhaled volume in 1 second (FEV1) and FVC (FEV1/FVC), FVC below lower limit of normal (FVC < LLN; (restriction)) and FEV1/FVC < LLN (airway obstruction) were calculated. Exposures and lung function outcomes were weighted to obtain estimated population parameters. Potential confounders included age, sex, height, body mass index, smoking status, country, education and employment. Adjusted regressions were used to investigate the associations between DII and respiratory outcomes. ResultsThe mean age of participants was 48 years (SD ± 15.1), and the median DII was –1.53 (IQR difference 3.5). In the fully adjusted models, a one-unit increase in DII score was statistically significantly associated with a lower FEV 1/FVC (β-coefficient –0.46, 95% CI –0.80, –0.12; P-value = 0.008) and with airway obstruction (odds ratio [OR] 1.17, 95% CI 1.03, 1.34; P-value = 0.018]. There was no association with the other lung function outcomes. ConclusionsA more pro-inf

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Expenditure and financial burden for the diagnosis and treatment of colorectal cancer in China:a ***,multicenter,cross-sectional survey

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Chinese Journal of cancer 2017年第8期36卷 352-366页

作者： Hui-Yao Huang Ju-Fang Shi Lan-Wei Guo Ya-Na Bai Xian-Zhen Liao Guo-iangLiu A-Yan Mao Jian-Song Ren Xiao-Jie Sun Xin-Yu Zhu Le Wang Bing-Bing Song Ling-Bin Du Lin Zhu Ji-Yong Gong Qi Zhou Yu-Qin Liu Rong Cao Ling Mai Li Lan Xiao-Hua Sun Ying Ren Jin-Yi Zhou Yuan-Zheng Wang Xiao Qi Pei-An Lou Dian Shi Ni Li Kai Zhang Jie He Min Dai Program Office for Cancer Screening in Urban China National Cancer Center/Cancer HospitalChinese Academy of Medical SciencesPeking Union Medical College17 South Panjiayuan LaneChaoyang DistrictBeijing 100021P.R.China Department of Cancer Epidemiology Henan Cancer HospitalAffiliated Cancer Hospital of Zhengzhou UniversityZhengzhouHenan 450008P.R.China Institute of Epidemiology and Health Statistics Lanzhou UniversityLanzhouGansu 730000P.R.China Hunan Office for Cancer Control and Research Hunan Provincial Cancer HospitalChangshaHunan 410006P.R.China Department of Health Economics School of Health ManagementHarbin Medical UniversityHarbinHeilongjiang 150081P.R.China Public Health Information Research Office Institute of Medical InformationChinese Academy of Medical SciencesBeijing 100020P.R.China Center for Health Management and Policy Key Lab of Health Economics and PolicyShandong UniversityJinanShandong 250012P.R.China Heilongjiang Office for Cancer Control and Research Affiliated Cancer Hospital of Harbin Medical UniversityHarbinHeilongjiang 150081P.R.China Zhejiang Office for Cancer Control and Research Zhejiang Cancer HospitalHangzhouZhejiang 310022P.R.China Teaching and Research Department Affiliated Cancer Hospital of Xinjiang Medical UniversityürümqiXinjiang 830011P.R.China Science and Education Department of Public Health Division Shandong Tumor HospitalJinanShandong 250117P.R.China Chongqing Office for Cancer Control and Research Chongqing Cancer HospitalChongqing 400030P.R.China Cancer Epidemiology Research Center Gansu Provincial Cancer HospitalLanzhouGansu 730050P.R.China Department of Health Policy and Economic Research Guangdong Provincial Institute of Public HealthGuangzhouGuangdong 511430P.R.China Department of Institute of Tumor Research Henan Cancer HospitalAffiliated Cancer Hospital of Zhengzhou UniversityZhengzhouHenan 450008P.R.China Institute of Chronic Disease Prevention and Control Harbin Center for Disease Control and PreventionHarbinHei

Background: The increasing prevalence of colorectal cancer(CRC) in China and the paucity of information about relevant expenditure highlight the necessity of better understanding the financial burden and effect of CRC diagnosis and treatment. We performed a survey to quantify the direct medical and non-medical expenditure as well as the resulting financial burden of CRC patients in ***: We conducted a multicenter, cross-sectional survey in 37 tertiary hospitals in 13 provinces across China between 2012 and 2014. Each enrolled patient was interviewed using a structured questionnaire. All expenditure data were inflated to the 2014 Chinese Yuan(CNY; 1 CNY = 0.163 USD). We quantified the overall expenditure and financial burden and by subgroup(hospital type, age at diagnosis, sex, education, occupation, insurance type, household income, clinical stage, pathologic type, and therapeutic regimen). We then performed generalized linear modeling to determine the factors associated with overall ***: A total of 2356 patients with a mean age of 57.4 years were included, 57.1 % of whom were men; 13.9% of patients had stage I cancer; and the average previous-year household income was 54,525 *** overall average direct expenditure per patient was estimated to be 67,408 CNY, and the expenditures for stage Ⅰ, Ⅱ, Ⅲ, and Ⅳ disease were 56,099 CNY, 59,952 CNY, 67,292 CNY, and 82,729 CNY, respectively. Non-medical expenditure accounted for 8.3%of the overall expenditure. The 1-year out-of-pocket expenditure of a newly diagnosed patient was 32,649 CNY, which accounted for 59.9% of their previous-year household income and caused 75.0% of families to suffer an unmanageable financial burden. Univariate analysis showed that financial burden and overall expenditure differed in almost all subgroups(P < 0.05), except for sex. Multivariate analysis showed that patients who were treated in specialized hospitals and those who were diagnosed with adenocarcinoma or diagno

关键词： Colorectal neoplasms Direct expenditure Financial burden China

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Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women

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Gynecologic oncology 2019年第2期153卷 343-355页

作者： Kate Lawrenson Fengju Song Dennis J Hazelett Siddhartha P Kar Jonathan Tyrer Catherine M Phelan Rosario I Corona Norma I Rodríguez-Malavé Ji-Hei Seo Emily Adler Simon G Coetzee Felipe Segato Marcos A S Fonseca Christopher I Amos Michael E Carney Georgia Chenevix-Trench Jiyeob Choi Jennifer A Doherty Weihua Jia Gang J Jin Byoung-Gie Kim Nhu D Le Juyeon Lee Lian Li Boon K Lim Noor A Adenan Mika Mizuno Boyoung Park Celeste L Pearce Kang Shan Yongyong Shi Xiao-Ou Shu Weiva Sieh Pamela J Thompson Lynne R Wilkens Qingyi Wei Yin L Woo Li Yan Beth Y Karlan Matthew L Freedman Houtan Noushmehr Ellen L Goode Andrew Berchuck Thomas A Sellers Soo-Hwang Teo Wei Zheng Keitaro Matsuo Sue Park Kexin Chen Paul D P Pharoah Simon A Gayther Marc T Goodman Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute Cedars-Sinai Medical Center 8700 Beverly Boulevard Suite 290W Los Angeles CA USA Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Electronic address: kate.lawrenson@***. National Clinical Research Center for Cancer Tianjin Medical University Cancer Institute and Hospital Tianjin China Department of Epidemiology and Biostatistics Key Laboratory of Cancer Prevention and Therapy Tianjin China. Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Department of Oncology Centre for Cancer Genetic Epidemiology University of Cambridge Strangeways Research Laboratory Cambridge UK. Department of Gynecologic Oncology Moffitt Cancer Center Tampa FL USA Department of Cancer Epidemiology Moffitt Cancer Center Tampa FL USA. Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA. Department of Preventive Medicine University of Southern California Keck School of Medicine 1450 Biggy Street Los Angeles CA USA. Department of Genetics Ribeirão Preto Medical School University of São Paulo 14049-900 Brazil. Institute for Clinical and Translational Research Department of Medicine Baylor School of Medicine HoustonTX USA. Department of Obstetrics and Gynecology John A. Burns School of Medicine University of Hawaii Honolulu HI USA. Genetics and Computational Biology Department QIMR Berghofer Medical Research Institute 300 Herston Road Herston QLD 4006 Australia. Department of Preventive Medicine Seoul National University College of Medicine Seoul Republic of Korea Cancer Research Institute Seoul National University Seoul Republic of Korea Department of Biomedical Science Graduate School Seoul National Un

OBJECTIVE:Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women. METHODS:Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations. RESULTS:At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10). SNP rs6902488 at 6p25.2 (r = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10). CONCLUSION:While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

关键词： Asian ancestry Enhancer Epithelial ovarian cancer Gene regulation Genome-wide association study eQTL

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Ten quick tips for deep learning in biology

arXiv

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arXiv 2021年

作者： Lee, Benjamin D. Gitter, Anthony Greene, Casey S. Raschka, Sebastian Maguire, Finlay Titus, Alexander J. Kessler, Michael D. Lee, Alexandra J. Chevrette, Marc G. Stewart, Paul Allen Britto-Borges, Thiago Cofer, Evan M. Yu, Kun-Hsing Carmona, Juan Jose Fertig, Elana J. Kalinin, Alexandr A. Signal, Beth Lengerich, Benjamin J. Triche, Timothy J. Boca, Simina M. In-Q-Tel Labs School of Engineering and Applied Sciences Harvard University Department of Genetics Harvard Medical School United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI United States Morgridge Institute for Research MadisonWI United States Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine AuroraCO United States Center for Health AI University of Colorado School of Medicine AuroraCO United States Department of Statistics University of Wisconsin Madison United States Faculty of Computer Science Dalhousie University Canada University of New Hampshire Bioeconomy.XYZ United States Department of Oncology Johns Hopkins University United States Institute for Genome Sciences University of Maryland School of Medicine United States Genomics and Computational Biology Graduate Program University of Pennsylvania United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania United States Wisconsin Institute for Discovery Department of Plant Pathology University of Wisconsin-Madison United States Department of Biostatistics and Bioinformatics Moffitt Cancer Center TampaFL United States Section of Bioinformatics and Systems Cardiology Klaus Tschira Institute for Integrative Computational Cardiology University Hospital Heidelberg Germany University Hospital Heidelberg Germany Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ United States Graduate Program in Quantitative and Computational Biology Princeton University PrincetonNJ United States Department of Biomedical Informatics Harvard Medical School United States Department of Pathology Brigham and Women's Hospital United States Philips Healthcare CambridgeMA United States Philips Research

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. Artificial neural networks are a particular class of machine learning algorithms and models that evolved into what is now described as deep learning. Given the computational advances made in the last decade, deep learning can now be applied to massive data sets and in innumerable contexts. Therefore, deep learning has become its own subfield of machine learning. In the context of biological research, it has been increasingly used to derive novel insights from high-dimensional biological data. To make the biological applications of deep learning more accessible to scientists who have some experience with machine learning, we solicited input from a community of researchers with varied biological and deep learning interests. These individuals collaboratively contributed to this manuscript's writing using the GitHub version control platform and the Manubot manuscript generation toolset. The goal was to articulate a practical, accessible, and concise set of guidelines and suggestions to follow when using deep learning. In the course of our discussions, several themes became clear: the importance of understanding and applying machine learning fundamentals as a baseline for utilizing deep learning, the necessity for extensive model comparisons with careful evaluation, and the need for critical thought in interpreting results generated by deep learning, among others. © 2021, CC BY.

关键词： Learning algorithms

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Adiposity does not modify the effect of the dietary inflammatory potential on type 2 diabetes incidence among a prospective cohort of men

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Journal of Nutrition and Intermediary Metabolism 2019年 16卷 100095-100095页

作者： Guinter, Mark A. Merchant, Anwar T. Tabung, Fred K. Wirth, Michael D. Shivappa, N. Hurley, Thomas G. Hebert, James R. Sui, Xuemei Blair, Steven N. Steck, Susan E. Behavioral and Epidemiology Research Group American Cancer Society Atlanta GA United States Department of Epidemiology and Biostatistics University of South Carolina Columbia SC United States Cancer Prevention and Control Program University of South Carolina Columbia SC United States Division of Medical Oncology Department of Internal Medicine The Ohio State University College of Medicine Columbus OH United States The Ohio State University Comprehensive Cancer Center - Arthur G. James Cancer Hospital and Richard J. Solove Institute Columbus OH United States Connecting Health Innovations LLC Columbia SC United States Department of Exercise Science University of South Carolina Columbia SC United States Center for Research in Nutrition and Health Disparities Arnold School of Public Health University of South Carolina Columbia SC United States

Purpose: Inflammatory contributions from diet and adiposity may interact with respect to the development of type 2 diabetes mellitus (T2DM). We investigated the degree to which adiposity modified the association between dietary inflammatory potential and incident T2DM. Methods: Data from 6,016 US men in the Aerobics Center Longitudinal Study who completed a 3-day diet record were used. The inflammatory potential of diet was characterized by the Dietary Inflammatory Index (DII^®), and adiposity was assessed with body mass index, waist circumference, body fat percentage (BF) and waist-to-height ratio. Inverse probability weights were used in modified Poisson regression models to examine whether adiposity modifies the relationship between the DII and T2DM, while accounting for selection bias from participants who were lost to follow-up. Results: There were 336 incident cases of T2DM after a mean follow-up of 6.5 years. DII scores were not significantly associated with T2DM incidence in multivariable models, but point estimates were consistently elevated across increasing DII quartiles compared to the most anti-inflammatory DII quartile. In the model that evaluated BF, the term for overall effect modification was significant (p = 0.02), but there was no evidence of effect modification on the multiplicative and additive scales when examined further. Effect modification was not present for any other adiposity measures. Conclusions: We did not observe evidence that a pro-inflammatory diet, as measured by the DII, is associated with incidence of T2DM, nor evidence that adiposity modifies a potential relationship. Further investigation is needed in larger cohorts with longer follow-up. © 2019 The Authors

关键词： Adiposity Dietary pattern Effect modification Epidemiology Inflammation Obesity

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Medical expenditure for esophageal cancer in China:a 10-year multicenter retrospective survey(2002-2011)

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Chinese Journal of cancer 2017年第11期36卷 548-559页

作者： Lan-Wei Guo Hui-Yao Huang Ju-Fang Shi Li-Hong Lv Ya-Na Bai A-Yan Mao Xian-Zhen Liao Guo-Xiang Liu Jian-Song Ren Xiao-Jie Sun Xin-Yu Zhu Jin-Yi Zhou Ji-Yong Gong Qi Zhou Lin Zhu Yu-Qin Liu Bing-Bing Song Ling-Bin Du Xiao-Jing Xing Pei-An Lou Xiao-Hua Sun Xiao Qi Shou-Ling Wu Rong Cao Li Lan Ying Ren Kai Zhang Jie He Jian.Gong Zhang Min Dai Department of Cancer Epidemiology Henan Office for Cancer Control and Research The Affiliated Cancer Hospital of Zhengzhou University Henan Cancer Hospital No. 127 Dongming Road Zhengzhou 450008 Henan P. R China Program Office for Cancer Screening in Urban China Cancer Hospital Chinese Academy of Medical Sciences (CAMS) Peking Union Medical College National Cancer Center of China No. 17 Panjiayuannanli Chaoyang District Beijing 100021 P. R. China Department of Human Resources The Affiliated Cancer Hospital of Zhengzhou University Henan Cancer Hospital Zhengzhou 450008 Henan P. R. China Institute of Epidemiology and Health Statistics Lanzhou University Lanzhou 730000 Gansu P. R. China Public Health Information Research Office Institute of Medical Information Chinese Academy of Medical Sciences (CAMS) Beijing 100020 P. R. China Hunan Office for Cancer Control and Research Hunan Provincial Cancer Hospital Changsha 410006 Hunan P. R. China Department of Health Economics School of Health Management Harbin Medical University Harbin 150081 Heilongjiang P. R. China Center for Health Management and Policy Key Lab of Health Economics and Policy Shandong University Jinan 250012 Shandong P. R. China Institute of Chronic Non.Communicable Diseases Prevention and Control Jiangsu Provincial Center for Disease Control and Prevention Nanjing 210009 Jiangsu P. R. China Science and Education Department Public Health Division Shandong Tumor Hospital Jinan 250117 Shandong P. R. China Chongqing Office for Cancer Control and Research Chongqing Cancer Hospital Chongqing 400030 P. R. China Teaching and Research Department Affiliated Cancer Hospital of Xinjiang Medical University ürümqi 830011 Xinjiang P. R. China Cancer Epidemiology Research Center Gansu Provincial Cancer Hospital Lanzhou 730050 Gansu P. R. China Heilongjiang Office for Cancer Control and Research Affiliated Cancer Hospital of Harbin Medical University Harbin 150081 Heilongjiang P R. China Zhejiang Office for Cancer

Background: Esophageal cancer is associated with substantial disease burden in China, and data on the economic burden are fundamental for setting priorities in cancer interventions. The medical expenditure for the diagnosis and treatment of esophageal cancer in China has not been fully quantified. This study aimed to examine the medical expenditure of Chinese patients with esophageal cancer and the associated ***: From 2012 to 2014, a hospital-based multicenter retrospective survey was conducted in 37 hospitals in 13 provinces/municipalities across China as a part of the cancer Screening program of Urban China. For each esophageal cancer patient diagnosed between 2002 and 2011, clinical information and expense data were extracted by using structured questionnaires. All expense data were reported in Chinese Yuan(CNY; 1 CNY = 0.155 USD) based on the2011 value and inflated using the year-specific health care consumer price index for ***: A total of 14,967 esophageal cancer patients were included in the analysis. It was estimated that the overall average expenditure per patient was 38,666 CNY, and an average annual increase of 6.27% was observed from 2002(25,111 CNY) to 2011(46,124 CNY). The average expenditures were 34,460 CNY for stage Ⅰ,39,302 CNY for stage Ⅱ,40,353 CNY for stage Ⅲ, and 37,432 CNY for stage IV diseases(P < 0.01). The expenditure also differed by the therapy type, which was 38,492 CNY for surgery, 27,933 CNY for radiotherapy, and 27,805 CNY for chemotherapy(P < 0.05).Drugs contributed to 45.02% of the overall ***: These conservative estimates suggested that medical expenditures for esophageal cancer in China substantially increased in the last 10 years, treatment for early-stage esophageal cancer costs less than that for advanced cases, and spending on drugs continued to account for a considerable proportion of the overall expenditure.

关键词： Esophageal neoplasms Medical expenditure Diagnosis and treatment China

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Use and Predictors of Expectant Management of Low and Intermediate Risk Localized Prostate cancer in Elderly Men

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Urology Practice 2017年第2期4卷 132-139页

作者： Tsai, Huei-Ting Philips, George Taylor, Kathryn L. Kowalczyk, Keith Kuo, Huai-Ching Potosky, Arnold L. Cancer Prevention and Control Program Lombardi Comprehensive Cancer Center Department of Oncology Washington D.C. United States Department of Medicine Georgetown University Medical Center Washington D.C. United States Department of Urology Georgetown University Hospital Washington D.C. United States

Introduction Expectant management reduces overtreatment in low risk but not intermediate risk localized prostate cancer. We assessed the use and predictors of expectant management to understand its uptake in practice in the United States. Methods Using the SEER (Surveillance, Epidemiology and End Results)-Medicare database, we conducted a retrospective cohort study of men 66 years or older diagnosed with low (25,506 patients) or intermediate risk (25,597) localized prostate cancer between 2004 and 2011 and followed through December 31, 2012. We defined expectant management as 1) no definitive therapy and at least 1 prostate specific antigen test or repeat biopsy 4 to 12 months after diagnosis or 2) receiving definitive therapy after prostate specific antigen testing or repeat biopsy 7 to 12 months after diagnosis. We performed separate analyses for low and intermediate risk groups using multiple logistic regressions. Results For men diagnosed with prostate cancer in 2004 to 2011 expectant management increased from 22% to 43% in the low risk group and from 15% to 18% in the intermediate risk group. In the low risk group expectant management increased with age (adjusted OR 1.26 for age 71 to 75 years, 2.21 for 76 to 80 years, 6.33 for greater than 80 years;all p <0.0001 compared to age 66 to 70 years). Expectant management uptake was higher among men with comorbidities (OR 1.29) and those residing in the Pacific region (adjusted OR 0.56 compared to East Coast). Conclusions In United States practice utilization of expectant management has steadily increased in low risk prostate cancer and remained low in intermediate risk prostate cancer through time. While men with comorbidities or advanced age were more likely to undergo expectant management, its use varied substantially by geographic region. Our findings bring attention to the presence of multiple barriers to expectant management implementation. © 2017 American Urological Association Education and Research, Inc.

关键词： prostate-specific antigen prostatic neoplasms SEER program watchful waiting

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Association Between Household Food Security and Disordered Eating Behaviors Among Young Adults with Diabetes: The SEARCH for Diabetes in Youth Study

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Current Developments in Nutrition 2020年第SUPPL 2期4卷 4141419-4141419页

作者： Jackson, Emahlea Liese, Angela Pihoker, Catherine Malik, Faisal Jones-Smith, Jessica Qu, Pingping Crow, Scott Loots, Beth Reboussin, Beth Dolan, Lawrence Igudesman, Daria Sauder, Katherine Shapiro, Allison Siegel, Karen Turley, Christine Mendoza, Jason University of Washington University of South Carolina Seattle Children's Research Institution Seattle Children's Research Institute The Emily Program St. Paul MN University of Minnesota Wake Forest University School of Medicine University of Cincinnati University of North Carolina at Chapel Hill University of Colorado Denver University of Colorado Anschutz Medical Campus Centers for Disease Control and Prevention Emory University Medical University of South Carolina Fred Hutchinson Cancer Research Center

AbstractObjectivesExamine the relationship between household food insecurity (HFS; i.e., access to nutritionally adequate and safe food) and disordered eating behaviors (i.e., restriction, bingeing, insulin manipulation, etc.) among a sample of young adults with youth-onset type 1 (T1D) or type 2 diabetes (T2D). MethodsWe used cross-sectional data from the SEARCH for Diabetes in Youth Study. Individuals ( n = 792) ages ≥18 years completed the U.S. Household Food Security Survey Module and the Diabetes Eating Problem Survey-Revised (DEPS-R) between 2016 and 2019. We converted HFS scores to a 10-point scale and dichotomized scores into food secure (HFS ≤ 2.2) vs. food insecure (HFS > 2.2). Multivariable linear regression was used to evaluate the association of HFS with continuous DEPS-R score (i.e., 0–80, with a greater score indicating greater symptoms of disordered eating), adjusting for potential confounders (i.e., sex, age, race/ethnicity, education, household income, insurance, depressive symptoms, and duration of diabetes). We further stratified analyses by diabetes type. ResultsParticipants were on average 23.8 ± 3.7 years, 59.6% female, 49.6% non-Latino white, and had a mean diabetes duration of 11.5 ± 3.1 years. The overall mean DEPS-R score was 17.3 ± 10.0 points. Mean DEPS-R scores in individuals living in food secure households ( n = 709) and food insecure households ( n = 83) were 16.6 ± 9.45 and 23.4 ± 12.4, respectively. The adjusted DEPS-R scores were 3.6 points (95% CI = 1.5, 5.7; P < 0.001) higher in food insecure compared to food secure households. In individuals with T1D ( n = 600), the adjusted DEPS-R scores were 5.0 points (95% CI = 2.6, 7.4; P < 0.001) higher in food insecure ( n = 55) compared to food secure ( n = 545) households. In individuals with T2D ( n = 192), there was no significant difference in mean DEPS-R scores between food insecure ( n = 28) versus food secure ( n = 164) households in unadjusted or adjusted models ( P > 0.05). Conc

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