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Study Designs in Epidemiology01:20

Study Designs in Epidemiology

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Updated: May 18, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Population-based study designs in molecular epidemiology.

Montserrat García-Closas1, Roel Vermeulen, David Cox

  • 1Institute of Cancer Research, Surrey, UK. montse.garciaclosas@icr.ac.uk

IARC Scientific Publications
|September 25, 2012
PubMed
Summary
This summary is machine-generated.

This chapter explores using biomarkers in epidemiologic studies for disease cause investigations. It covers study designs like cohort and case-control, detailing biomarker integration and exposure assessment strategies.

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Last Updated: May 18, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Published on: December 7, 2021

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Area of Science:

  • Epidemiology
  • Biomarker Research
  • Public Health

Background:

  • Biomarkers are crucial for understanding disease etiology.
  • Integrating biomarkers into epidemiological studies requires careful design.
  • Existing literature often lacks comprehensive guidance on biomarker study design.

Purpose of the Study:

  • To outline design considerations for epidemiological studies employing biomarkers.
  • To detail the incorporation of biomarkers into various epidemiologic study frameworks.
  • To discuss the impact of study design on biomarker analysis and feasibility.

Main Methods:

  • Review of established epidemiological study designs (cross-sectional, longitudinal, cohort, case-control).
  • Discussion of biomarker integration within these designs.
  • Analysis of factors influencing exposure assessment and biospecimen handling.

Main Results:

  • Biomarker characterization is feasible with cross-sectional or short-term longitudinal designs.
  • Biomarker-disease associations are best evaluated using prospective cohort and case-control studies.
  • Study design significantly impacts the feasibility of exposure assessment and biospecimen logistics.

Conclusions:

  • Appropriate epidemiological study design is essential for valid biomarker research.
  • Choosing the right design balances biomarker characterization with association evaluation.
  • Consideration of practical aspects like biospecimen collection is key for successful biomarker studies.