1. To Screen or Not to Screen
L. Rachid Salmi, MD, PhD, Gaëlle Coureau, MD, PhD, Marion Bailhache, MD, MSc, Simone Mathoulin-Pélissier, MD, PhD 
Mayo Clinic Proceedings 
Volume 91, Issue 11, Pages (November 2016)
DOI: /j.mayocp
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2. Figure 1
Hypotheses underlying screening according to the individual (A) and population (B) perspectives. FN = false-negative; FP = false-positive; TN = true-negative; TP = true-positive.
Mayo Clinic Proceedings  , DOI: ( /j.mayocp )
Copyright © 2016 Mayo Foundation for Medical Education and Research Terms and Conditions

3. Figure 2
The course of a disorder and biases to consider in randomized trials, modeling, or cohort studies of the effects of screening programs. The solid lines indicate the possible transitions in the absence of screening; dashed lines, the additional possible transitions in the presence of screening. Nonspecific mortality also includes mortality related to competitive causes, which are neither disorder specific nor care related. DET = detection bias; LTB = lead-time bias; OVD = overdiagnosis; PSB = prevention success bias; SDB = sticky diagnosis bias; SEL = selection bias; SLB = slippery linkage bias; TIB = treatment improvement bias (see definitions in text).
Mayo Clinic Proceedings  , DOI: ( /j.mayocp )
Copyright © 2016 Mayo Foundation for Medical Education and Research Terms and Conditions

4. Figure 3
Seven key issues reconciling the individual and population perspectives on screening and their consequences for decisions (ovals) and implications for research (dotted-line boxes). Dark orange boxes indicate the only issues traditionally considered in the individual model; light orange boxes are suggested to be part of an evidence-based model (see the text for details).
Mayo Clinic Proceedings  , DOI: ( /j.mayocp )
Copyright © 2016 Mayo Foundation for Medical Education and Research Terms and Conditions