title: Cultivating cohort studies for observational translational research.
abstract: BACKGROUND
  "Discovery" research about molecular markers for diagnosis, prognosis, or prediction of response to therapy has frequently produced results that were not reproducible in subsequent studies. What are the reasons, and can observational cohorts be cultivated to provide strong and reliable answers to those questions? Experimental
  
  
  METHODS
  Selected examples are used to illustrate: (i) what features of research design provide strength and reliability in observational studies about markers of diagnosis, prognosis, and response to therapy? (ii) How can those design features be cultivated in existing observational cohorts, for example, within randomized controlled clinical trial (RCT), other existing observational research studies, or practice settings like health maintenance organization (HMOs)?
  
  
  RESULTS
  Examples include a study of RNA expression profiles of tumor tissue to predict prognosis of breast cancer, a study of serum proteomics profiles to diagnose ovarian cancer, and a study of stool-based DNA assays to screen for colon cancer. Strengths and weaknesses of observational study design features are discussed, along with lessons about how features that help assure strength might be "cultivated" in the future.
  
  
  CONCLUSIONS
  By considering these examples and others, it may be possible to develop a process of "cultivating cohorts" in ongoing RCTs, observational cohort studies, and practice settings like HMOs that have strong features of study design. Such an effort could produce sources of data and specimens to reliably answer questions about the use of molecular markers in diagnosis, prognosis, and response to therapy.
authors: UNC-CH, Chapel Hill, NC 27599, USA. ransohof@med.unc.edu
authors: David F
authors: DF
authors: Ransohoff
mesh_terms: D035843:Biomedical Research; D015331:Cohort Studies; D018849:Controlled Clinical Trials as Topic; D019317:Evidence-Based Medicine; D006801:Humans; D019370:Observation; D012107:Research Design; D057170:Translational Research, Biomedical