Scandinavian journal of clinical and laboratory investigation. Supplementum最新文献

{"title":"Guidelines for the use of biomarkers: principles, processes and practical considerations.","authors":"Andrea R Horvath,&nbsp;Erika Kis,&nbsp;Eva Dobos","doi":"10.3109/00365513.2010.493424","DOIUrl":"https://doi.org/10.3109/00365513.2010.493424","url":null,"abstract":"<p><p>With the growing availability of new health care technologies and rapidly emerging biomarker discoveries, clinicians need advice on the clinical validity and utility of new tests and whether they improve clinical, patient-centred, organizational or economic outcomes. High quality clinical practice guidelines (CPGs), based on well-designed and conducted test evaluation studies, are tools for translating research into practice and in promoting a value- and evidence-based approach for clinical utilization and reimbursement of new biomarkers. Such study protocols should be appropriate for the questions addressed at each stage of biomarker development: 1/ Basic research into the association of disease with the new biomarker; 2/ Modelling the potential use of the new biomarker in clinical practice; Studies on the 3/ analytic validity; 4/ clinical validity (efficacy); 5/ clinical utility (effectiveness); and 6/ clinical impact (efficiency) of testing. Irrespective of the facts that CPGs potentially influence important clinical decisions and thus patient outcomes, current approaches to CPG development often do not follow the rigorous processes of scientific publications. Guidelines should be outcome oriented; reliable and free from any forms of bias; based on high quality research or on formal consensus when evidence is conflicting or lacking; multidisciplinary; flexible and applicable to various clinical circumstances and patient preferences; clear; cost-effective; appropriately disseminated and implemented; amenable to measurement of their impact in practice; and regularly reviewed and updated. Therefore until guideline-making and reporting standards are improved, all CPGs should be carefully scrutinized for methodological and content validity before being adopted, adapted and used in clinical practice.</p>","PeriodicalId":76518,"journal":{"name":"Scandinavian journal of clinical and laboratory investigation. Supplementum","volume":"242 ","pages":"109-16"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/00365513.2010.493424","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29027518","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}

{"title":"Standardization of protein biomarker measurements: is it feasible?","authors":"Heinz Schimmel,&nbsp;Ingrid Zegers,&nbsp;Hendrik Emons","doi":"10.3109/00365513.2010.493362","DOIUrl":"https://doi.org/10.3109/00365513.2010.493362","url":null,"abstract":"<p><p>The standardisation of measurements of protein biomarkers, which are potentially heterogeneous in terms of fragmentation, modification, substitution, primary, secondary, tertiary and quaternary structure, is a demanding task. However, they are a prime target for standardisation efforts due to the importance of protein biomarkers in diagnostics and health care and the typically observed significant discrepancies in measurement results obtained with non-standardized platforms. Based on the experience gathered during successfully completed projects for the production of reference materials, pragmatic approaches are described how standardisation could become feasible despite the fuzziness of the target analytes.</p>","PeriodicalId":76518,"journal":{"name":"Scandinavian journal of clinical and laboratory investigation. Supplementum","volume":"242 ","pages":"27-33"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/00365513.2010.493362","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29028123","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}

{"title":"Measurement performance goals: how they can be estimated and a view to managing them.","authors":"Anders Kallner","doi":"10.3109/00365513.2010.493364","DOIUrl":"https://doi.org/10.3109/00365513.2010.493364","url":null,"abstract":"<p><p>Abstract prediction and monitoring of disease. Evaluation of results is based on evidence and practical experience. In both cases consistency and transferability of results is needed. For diagnosis and prediction a result is compared to a reference value or reference interval whereas in monitoring it is more important to compare results of measurements with previous results. The analytical goals may therefore vary depending on the intended use of the results and both trueness and precision will need to be considered. The analytical goals may also be influenced by the disease characteristics. A brief review of available methods and principles will be given.</p>","PeriodicalId":76518,"journal":{"name":"Scandinavian journal of clinical and laboratory investigation. Supplementum","volume":"242 ","pages":"34-9"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/00365513.2010.493364","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29028124","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}

{"title":"When do new biomarkers make economic sense?","authors":"Mitchell G Scott","doi":"10.3109/00365513.2010.493411","DOIUrl":"https://doi.org/10.3109/00365513.2010.493411","url":null,"abstract":"<p><p>Cost-effectiveness and cost-utility studies are commonly used to make payment decisions for new drugs and expensive interventions. Such studies are relatively rare for evaluating the cost-utility of clinical laboratory tests. As medical costs continue to increase in the setting of decreased resources it is likely that new biomarkers may increasingly be examined with respect to their economic benefits in addition to clinical utility. This will represent an additional hurdle for routine use of new biomarkers. Before reaching the final economic hurdle new biomarkers will still need to demonstrate clinical usefulness. Thus a new biomarker will never make economic sense if it is not clinically useful. Once diagnostic accuracy and potential clinical usefulness is established there are several types of economic studies that new biomarkers may undergo. The most common of these are cost-utility studies which estimate the ratio between the cost of an intervention or test and the benefit it produces in the number of years gained in full health. The quantity used most often to describe this is amount of money per quality adjusted life year (QALY) gained. The threshold for being considered cost-effective is generally USD 50,000 per QALY gained. Examples of biomarkers that have been subjected to economic analyses will be provided.</p>","PeriodicalId":76518,"journal":{"name":"Scandinavian journal of clinical and laboratory investigation. Supplementum","volume":"242 ","pages":"90-5"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/00365513.2010.493411","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29027515","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}

{"title":"What is a biomarker? Research investments and lack of clinical integration necessitate a review of biomarker terminology and validation schema.","authors":"Adam S Ptolemy,&nbsp;Nader Rifai","doi":"10.3109/00365513.2010.493354","DOIUrl":"https://doi.org/10.3109/00365513.2010.493354","url":null,"abstract":"<p><p>A continual trend of annual growth can be seen within research devoted to the discovery and validation of disease biomarkers within both the natural and clinical sciences. This expansion of intellectual endeavours was quantified through database searches of (a) research grant awards provided by the various branches of the National Institutes of Health (NIH) and (b) academic publications. A search of awards presented between 1986 and 2009 revealed a total of 28,856 grants awarded by the NIH containing the term \"biomarker\". The total funds for these awards in 2008 and 2009 alone were over $2.5 billion. During the same respective time frames, searches of \"biomarker\" and either \"discovery\", \"genomics\", \"proteomics\" or \"metabolomics\" yielded a total of 4,928 NIH grants whose combined funding exceeded $1.2 billion. The derived trend in NIH awards paralleled the annual expansion in \"biomarker\" literature. A PubMed search for the term, between 1990 and 2009, revealed a total of 441,510 published articles, with 38,457 published in 2008. These enormous investments and academic outputs however have not translated into the expected integration of new biomarkers for patient care. For example no proteomics derived biomarkers are currently being utilized in routine clinical management. This translational chasm necessitates a review of the previously proposed biomarker definitions and evaluation schema. A subsequent discussion of both the analytical and pre-analytical considerations for such research is also presented within. This required knowledge should aid scientists in their pursuit and validation of new biological markers of disease.</p>","PeriodicalId":76518,"journal":{"name":"Scandinavian journal of clinical and laboratory investigation. Supplementum","volume":"242 ","pages":"6-14"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/00365513.2010.493354","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29027650","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}

{"title":"Molecular biology tools: proteomics techniques in biomarker discovery.","authors":"Friedrich Lottspeich, Josef Kellermann, Eva-Maria Keidel","doi":"10.3109/00365513.2010.493359","DOIUrl":"10.3109/00365513.2010.493359","url":null,"abstract":"<p><p>Despite worldwide efforts biomarker discovery by plasma proteomics was not successful so far. Several reasons for this failure are obvious. Mainly, proteome diversity is remarkable between different individuals and is caused by genetic, environmental and life style parameters. To recognize disease related proteins that could serve as potential biomarkers is only feasible by investigating a non realizable large number of patients. Furthermore, plasma proteomics comprises enormous technical hurdles for quantitative analysis. High reproducibility of blood sampling in clinical routine is hard to achieve. Quantitative proteome analysis has to struggle with the complexity of millions of protein species comprising typical plasma proteins, cellular leakage proteins and antibodies and concentration differences of more than 1011 between high and low abundant proteins. Therefore, no successful quantitative and comprehensive plasma proteome analysis is reported so far. A novel proteomics strategy is proposed for biomarker discovery in plasma. Instead of comparing the plasma proteome of different individuals it is recommended to analyze the proteomes of different time points of a single individual during the development of a disease. This strategy is realized by the use of plasma of the Bavarian Red Cross Blood Bank, were three million samples are stored under standardized conditions. To achieve reliable data the isotope coded protein labelling proteomics technology was used.</p>","PeriodicalId":76518,"journal":{"name":"Scandinavian journal of clinical and laboratory investigation. Supplementum","volume":"242 ","pages":"19-22"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/00365513.2010.493359","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29027652","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}

{"title":"Classification versus association models: should the same methods apply?","authors":"Ziding Feng","doi":"10.3109/00365513.2010.493387","DOIUrl":"10.3109/00365513.2010.493387","url":null,"abstract":"<p><p>Association and classification models differ fundamentally in objectives, measurements, and clinical context specificity. Association studies aim to identify biomarker association with disease in a study population and provide etiologic insights. Common association measurements are odds ratio, hazard ratio, and correlation coefficient. Classification studies aim to evaluate biomarker use in aiding specific clinical decisions for individual patients. Common classification measurements are sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Good association is usually a necessary, but not a sufficient, condition for good classification. Methods for developing classification models have mainly used the criteria for association models, usually minimizing total classification error without consideration of clinical application settings, and therefore are not optimal for classification purposes. We suggest that developing classification models by focusing on the region of receiver operating characteristic (ROC) curve relevant to the intended clinical application optimizes the model for the intended application setting.</p>","PeriodicalId":76518,"journal":{"name":"Scandinavian journal of clinical and laboratory investigation. Supplementum","volume":"242 ","pages":"53-8"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3140431/pdf/nihms284052.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29028128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the impact of biomarkers on patient outcome: an obligatory step.","authors":"David E Bruns,&nbsp;James C Boyd","doi":"10.3109/00365513.2010.493410","DOIUrl":"https://doi.org/10.3109/00365513.2010.493410","url":null,"abstract":"<p><p>Payers for healthcare increasingly require evidence about health outcomes of medical interventions. Outcomes research uses various study designs to provide such evidence, with the highest level of evidence provided by randomized controlled trials (RCTs). Among published studies of biomarkers, however, relatively few determine the relationship of biomarker testing to outcomes, and only a small fraction of those studies are RCTs, and fewer still follow the CONSORT standards for reporting of trials. Outcomes studies of biomarkers are difficult to carry out. During an outcomes study, clinicians may be expected to use the results of the test (e.g., troponin) along with other information (e.g., symptoms of an acute coronary syndrome) to decide about use of another intervention (such as cardiac catheterization) that is hoped to improve an outcome (e.g., mortality rate) at some time in the future. Studies of diagnostic tests frequently lack evidence that test results were acted upon at all, much less according to a defined protocol. The potential for a biomarker to improve outcomes depends upon a wide range of variables. These variables include the diagnostic accuracy of the test and the effectiveness of the therapeutic intervention, both of which will, predictably, vary with the patient population studied. Thus outcomes studies performed in one patient population leave unanswered questions regarding outcomes in other populations. The questions are infinite, but resources are finite. Simulation modelling studies are attractive as an adjunct to patient studies to address multiple patient variables and multiple treatment approaches without the expense of multiple clinical studies.</p>","PeriodicalId":76518,"journal":{"name":"Scandinavian journal of clinical and laboratory investigation. Supplementum","volume":"242 ","pages":"85-9"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/00365513.2010.493410","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29027514","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}

{"title":"Improving the clinical value of laboratory information and permitting a common global approach to diseases. Foreword.","authors":"Mauro Panteghini","doi":"10.3109/00365513.2010.493457","DOIUrl":"https://doi.org/10.3109/00365513.2010.493457","url":null,"abstract":"With the main objective of improving the clinical value of laboratory information and permitting a common global approach to diseases, the Scientifi c Division of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) organises Bergmeyer Conferences, usually on a biennial frequency. The series of IFCC Master Discussions as fora for experts and brainstorming sessions is dedicated to Professor Hans-Ulrich Bergmeyer to honour his outstanding achievements in biochemistry and the area of standardization. The series began 22 years ago and is still generously fully sponsored by Roche Diagnostics (Table I). The 12th Bergmeyer Conference was entitled “ Novel Biomarkers: From Discovery to Clinical Application ” and focused on approaches and challenges related to the new biomarker discovery and qualifi cation, assay optimization and performance specifi cations for biomarker evaluation and validation, requirements for introducing new biomarkers in clinical practice, and description of some examples from different indication areas. The Conference programme refl ected the multidisciplinary approach in attempts to promote a closer working relationship among laboratory professionals, basic researchers, epidemiologists, biostatisticians, clinicians, and representatives from manufacturers, regulatory bodies, and reference material providers, working on discovery, qualifi cation, validation, and clinical implementation of novel biomarkers. It is signifi cant that so many outstanding scientists have not only accepted an invitation to make presentations on their own specifi c fi eld, but also to actively discuss and gain further insight into this important subject. All lectures and contributions, including plenary discussions, given during the 2010 Conference are published in the present volume. As for all the previous Conferences, Anders Kallner again took over the main responsibility of editing these proceedings. Janet Smith put discussions in their proper context. Paola Bramati at the IFCC offi ce supported the organization of the scientifi c aspects of the Conference. Last but not least, Franz Baumann and his staff carried the burden of organizing the Conference in Eibsee, Germany, and in achieving, once again, the expectations of an outstanding meeting.","PeriodicalId":76518,"journal":{"name":"Scandinavian journal of clinical and laboratory investigation. Supplementum","volume":"242 ","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/00365513.2010.493457","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29027648","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}

{"title":"Anti-CCP: challenges in quantifying auto-antibodies and creating international reference materials.","authors":"Michael Rottmann","doi":"10.3109/00365513.2010.493381","DOIUrl":"https://doi.org/10.3109/00365513.2010.493381","url":null,"abstract":"<p><p>Anti-CCP assays (antibody to cyclic citrullinated peptides) possess a high specificity for RA (rheumatoid arthritis). In lack of an international reference material the absolute values among different assays strongly diversify. The cut-off showed a variance from 5 U/mL Euroimmun anti-CCP to 25 U/mL Euro-Diagnostica Immunosan RA. The Autoantibody Standardization Committee is currently trying to establish a reference specimen of human polyclonal anti-CCP.</p>","PeriodicalId":76518,"journal":{"name":"Scandinavian journal of clinical and laboratory investigation. Supplementum","volume":"242 ","pages":"44-5"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/00365513.2010.493381","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29028126","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}