IARC scientific publications最新文献_第9页

Cancer survival in Busan, Republic of Korea, 1996-2001. 1996-2001年大韩民国釜山的癌症存活率。

IARC scientific publications Pub Date : 2011-01-01

H R Shin, D H Lee, S Y Lee, J T Lee, H K Park, S H Rha, I K Whang, K W Jung, Y J Won, H J Kong

引用次数: 0

Cancer survival in Incheon, Republic of Korea, 1997-2001. 1997-2001年大韩民国仁川市癌症存活率

IARC scientific publications Pub Date : 2011-01-01

Z H Woo, Y C Hong, W C Kim, Y K Pu

引用次数: 0

Cancer survival in Chiang Mai, Thailand, 1993-1997. 1993-1997年泰国清迈的癌症存活率。

IARC scientific publications Pub Date : 2011-01-01

Y Sumitsawan, S Srisukho, A Sastraruji, U Chaisaengkhum, P Maneesai, N Waisri

{"title":"Cancer survival in Chiang Mai, Thailand, 1993-1997.","authors":"Y Sumitsawan, S Srisukho, A Sastraruji, U Chaisaengkhum, P Maneesai, N Waisri","doi":"","DOIUrl":"","url":null,"abstract":"The Chiang Mai tumour registry was established in 1978 as a hospital-based cancer registry, and population-based cancer registration started in 1986, with retrospective data collection on cancer incidence and mortality since 1983. Registration of cases is done by active methods. Data on survival for 36 cancer sites or types registered during 1993-1997 are reported here. Follow-up has been carried out predominantly by active methods, with median follow-up ranging between 1-39 months for different cancers. The proportion of histologically verified diagnosis for various cancers ranged between 28-100%; death certificate only (DCO) cases comprised 0-56%; 33-92% of total registered cases were included for survival analysis. Complete followup at five years ranged from 59-100% for different cancers. The 5-year age-standardized relative survival rates was the highest for Hodgkin lymphoma (70%) followed by thyroid (65%), cervix (57%), breast (56%) and corpus uteri (49%). The 5-year relative survival by age group showed either an inverse relationship or was fluctuating. An overwhelmingly high proportion of cases were diagnosed with a regional spread of disease, ranging between 44-82% for different cancers and survival decreased with increasing extent of disease for all cancers studied.","PeriodicalId":13149,"journal":{"name":"IARC scientific publications","volume":" 162","pages":"199-209"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29938669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cancer survival in Africa, Asia, the Caribbean and Central America. Foreword. 非洲、亚洲、加勒比和中美洲的癌症存活率。前言。

IARC scientific publications Pub Date : 2011-01-01

Christopher P Wild

引用次数: 0

Platforms for biomarker analysis using high-throughput approaches in genomics, transcriptomics, proteomics, metabolomics, and bioinformatics. 使用基因组学、转录组学、蛋白质组学、代谢组学和生物信息学等高通量方法进行生物标志物分析的平台。

IARC scientific publications Pub Date : 2011-01-01

B Alex Merrick, Robert E London, Pierre R Bushel, Sherry F Grissom, Richard S Paules

{"title":"Platforms for biomarker analysis using high-throughput approaches in genomics, transcriptomics, proteomics, metabolomics, and bioinformatics.","authors":"B Alex Merrick, Robert E London, Pierre R Bushel, Sherry F Grissom, Richard S Paules","doi":"","DOIUrl":"","url":null,"abstract":"Global biological responses that reflect disease or exposure biology are kinetic and highly dynamic phenomena. While high-throughput DNA sequencing continues to drive genomics, the possibility of more broadly measuring changes in gene expression has been a recent development manifested by a diversity of technical platforms. Such technologies measure transcripts, proteins and small biological molecules, or metabolites, and respectively define the fields of transcriptomics, proteomics and metabolomics that can be performed at a cell-, tissue-, or organism-wide basis. Bioinformatics is the discipline that derives knowledge from the large quantity and diversity of biological, genetic, genomic and gene expression data by integrating computer science, mathematics, statistics and graphic arts. Gene, protein and metabolite expression profiles can be thought of as snapshots of the current, poorly-mapped molecular landscape. The ultimate aim of genomic platforms is to fully map this landscape to more completely describe all of the biological interactions within a living system, during disease and toxicity, and define the behaviour and relationships of all the components of a biological system. The development of databases and knowledge bases will support the integration of data from multiple domains, as well as computational modelling. This chapter will describe the technical platform methods involving DNA sequencing, mass spectrometry, nuclear magnetic resonance combined with separation systems, and bioinformatics to derive genomic and gene expression data and include the relevant bioinformatic tools for analysis. These genomic, or omics platforms should have wide application to epidemiological studies.","PeriodicalId":13149,"journal":{"name":"IARC scientific publications","volume":" 163","pages":"121-42"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30921803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dietary intake and nutritional status. 膳食摄入量和营养状况。

IARC scientific publications Pub Date : 2011-01-01

Jiyoung Ahn, Christian C Abnet, Amanda J Cross, Rashmi Sinha

引用次数: 0

Molecular epidemiology: principles and practices. Preface. 分子流行病学:原理和实践。前言。

IARC scientific publications Pub Date : 2011-01-01

引用次数: 0

Biomarkers in clinical medicine. 临床医学中的生物标志物。

IARC scientific publications Pub Date : 2011-01-01

Xiao-He Chen, Shuwen Huang, David Kerr

{"title":"Biomarkers in clinical medicine.","authors":"Xiao-He Chen, Shuwen Huang, David Kerr","doi":"","DOIUrl":"","url":null,"abstract":"Biomarkers have been used in clinical medicine for decades. With the rise of genomics and other advances in molecular biology, biomarker studies have entered a whole new era and hold promise for early diagnosis and effective treatment of many diseases. A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacologic responses to a therapeutic intervention (1). They can be classified into five categories based on their application in different disease stages: 1) antecedent biomarkers to identify the risk of developing an illness, 2) screening biomarkers to screen for subclinical disease, 3) diagnostic biomarkers to recognize overt disease, 4) staging biomarkers to categorise disease severity, and 5) prognostic biomarkers to predict future disease course, including recurrence, response to therapy, and monitoring efficacy of therapy (1). Biomarkers can indicate a variety of health or disease characteristics, including the level or type of exposure to an environmental factor, genetic susceptibility, genetic responses to environmental exposures, markers of subclinical or clinical disease, or indicators of response to therapy. This chapter will focus on how these biomarkers have been used in preventive medicine, diagnostics, therapeutics and prognostics, as well as public health and their current status in clinical practice.","PeriodicalId":13149,"journal":{"name":"IARC scientific publications","volume":" 163","pages":"303-22"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30921207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cancer. 癌症。

IARC scientific publications Pub Date : 2011-01-01

Frederica P Perera, Paolo Vineis

{"title":"Cancer.","authors":"Frederica P Perera, Paolo Vineis","doi":"","DOIUrl":"","url":null,"abstract":"Molecular epidemiology was introduced in the study of cancer in the early 1980s, with the expectation that it would help overcome some important limitations of epidemiology and facilitate cancer prevention. The first generation of biomarkers has indeed contributed to our understanding of mechanisms, risk and susceptibility as they relate largely to genotoxic carcinogens, resulting in interventions and policy changes to reduce risk from several important environmental carcinogens. New and promising biomarkers are now becoming available for epidemiological studies, including alterations in gene methylation and gene expression, proteomics and metabolomics. However, most of these newer biomarkers have not been adequately validated, and their role in the causal paradigm is not clear. Systematic validation of these newer biomarkers is urgently needed and can take advantage of the principles and criteria established over the past several decades from experience with the first generation of biomarkers. Prevention of only 20% of cancers in the United States alone would result in 300 000 fewer new cases annually, avoidance of incalculable suffering, and a savings in direct financial costs of over US$20 billion each year (1). Molecular epidemiology can play a valuable role in achieving this goal.","PeriodicalId":13149,"journal":{"name":"IARC scientific publications","volume":" 163","pages":"337-62"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30921209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Work-related lung diseases. 与工作有关的肺病。

IARC scientific publications Pub Date : 2011-01-01

Ainsley Weston

{"title":"Work-related lung diseases.","authors":"Ainsley Weston","doi":"","DOIUrl":"","url":null,"abstract":"Work-related respiratory diseases affect people in every industrial sector, constituting approximately 60% of all disease and injury mortality and 70% of all occupational disease mortality. There are two basic types: interstitial lung diseases, that is the pneumoconioses (asbestosis, byssinosis, chronic beryllium disease, coal workers' pneumoconiosis (CWP), silicosis, flock workers' lung, and farmers' lung disease), and airways diseases, such as work-related or exacerbated asthma, chronic obstructive pulmonary disease and bronchiolitis obliterans (a disease that was recognized in the production of certain foods only 10 years ago). Common factors in the development of these diseases are exposures to dusts, metals, allergens and other toxins, which frequently cause oxidative damage. In response, the body reacts by activating primary immune response genes (i.e. cytokines that often lead to further oxidative damage), growth factors and tissue remodelling proteins. Frequently, complex imbalances in these processes contribute to the development of disease. For example, tissue matrix metalloproteases can cause the degradation of tissue, as in the development of CWP small profusions, but usually overexpression of matrix metalloproteases is controlled by serum protein inhibitors. Thus, disruption of such a balance can lead to adverse tissue damage. Susceptibility to these types of lung disease has been investigated largely through candidate gene studies, which have been characteristically small, often providing findings that have been difficult to corroborate. An important exception to this has been the finding that the HLA-DPB11(E69) allele is closely associated with chronic beryllium disease and beryllium sensitivity. Although chronic beryllium disease is only caused by exposure to beryllium, inheritance of HLA-DPB1(E69) carries an increased risk of between two- and 30-fold in beryllium exposed workers. Most, if not all, of these occupationally related diseases are preventable; therefore, it is disturbing that rates of CWP, for example, are again increasing in the United States in the 21st century.","PeriodicalId":13149,"journal":{"name":"IARC scientific publications","volume":" 163","pages":"387-405"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30922740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0