| 1. |
- Boedeker, Wolfgang, et al.
(författare)
-
The scientific assessment of combined effects of risk factors - lessons from experimental biosciences for epidemiology?
- 2010
-
Ingår i: European Journal of Epidemiology (invited contribution, under review). - : Springer Science and Business Media LLC. - 0393-2990 .- 1573-7284. ; 25:8, s. 539-546
-
Tidskriftsartikel (refereegranskat)abstract
- The analysis of combined effects of substances or risk factors has been a subject to science for more than a century. With different goals, combined effect analysis was addressed in almost all experimental biosciences. The major theoretical foundation can be traced back to two distinct origins. First, to the work by the pharmacologist Loewe on the concept of concentration additivity and second to the biometrician Bliss and the concept of independent action. In the search for a general solution and a unified terminology the interrelations of the concepts have extensively been studied and experimental findings reviewed. Meanwhile there seems to be consensus in experimental sciences that each concept has its role in predicting combined effect of agents and both are used for hazard und risk management. In contrast, epidemiologists describe combined effects mainly in terms of interactions in regression models. Although this approach started from a probabilistic model equivalent to the concept of independent action this origin is rarely acknowledged and effect summation is usually the preferred concept nowadays. Obscure biological meaning, the scale dependency of interaction terms as well as unavoidable residual confounding are taken as reasons why no new insights in combined effect analysis are likely to occur from epidemiology. In this paper we sketch the history of ideas and the state of the arts in combined effect analysis. We point to differences and common grounds in experimental biosciences and epidemiology.
|
|
| 2. |
|
|
| 3. |
- Vendelbo Lind, Mads, 1988, et al.
(författare)
-
The use of mass spectrometry for analysing metabolite biomarkers in epidemiology: methodological and statistical considerations for application to large numbers of biological samples
- 2016
-
Ingår i: European Journal of Epidemiology. - : Springer Science and Business Media LLC. - 1573-7284 .- 0393-2990. ; 31:8, s. 717-733
-
Forskningsöversikt (refereegranskat)abstract
- Data quality is critical for epidemiology, and as scientific understanding expands, the range of data available for epidemiological studies and the types of tools used for measurement have also expanded. It is essential for the epidemiologist to have a grasp of the issues involved with different measurement tools. One tool that is increasingly being used for measuring biomarkers in epidemiological cohorts is mass spectrometry (MS), because of the high specificity and sensitivity of MS-based methods and the expanding range of biomarkers that can be measured. Further, the ability of MS to quantify many biomarkers simultaneously is advantageously compared to single biomarker methods. However, as with all methods used to measure biomarkers, there are a number of pitfalls to consider which may have an impact on results when used in epidemiology. In this review we discuss the use of MS for biomarker analyses, focusing on metabolites and their application and potential issues related to large-scale epidemiology studies, the use of MS "omics" approaches for biomarker discovery and how MS-based results can be used for increasing biological knowledge gained from epidemiological studies. Better understanding of the possibilities and possible problems related to MS-based measurements will help the epidemiologist in their discussions with analytical chemists and lead to the use of the most appropriate statistical tools for these data.
|
|
