Literature DB >> 22129183

Prevalence of abnormalities influences cytologists' error rates in screening for cervical cancer.

Karla K Evans1, Rosemary H Tambouret, Andrew Evered, David C Wilbur, Jeremy M Wolfe.   

Abstract

CONTEXT: Medical screening tasks are often difficult, visual searches with low target prevalence (low rates of disease). Under laboratory conditions, when targets are rare, nonexpert searchers show decreases in false-positive results and increases in false-negative results compared with results when targets are common. This prevalence effect is not due to vigilance failures or target unfamiliarity.
OBJECTIVE: To determine whether prevalence effects could be a source of elevated false-negative errors in medical experts.
DESIGN: We studied 2 groups of cytologists involved in cervical cancer screening (Boston, Massachusetts, and South Wales, UK). Cytologists evaluated photomicrographs of cells at low (2% or 5%) or higher (50%) rates of abnormality prevalence. Two versions of the experiment were performed. The Boston, Massachusetts, group made decisions of normal or abnormal findings using a 4-point rating scale. Additionally, the group from South Wales localized apparent abnormalities.
RESULTS: In both groups, there is evidence for prevalence effects. False-negative errors were 17% (higher prevalence), rising to 30% (low prevalence) in the Boston, Massachusetts, group. The error rate was 27% (higher prevalence), rising to 42% (low prevalence) in the South Wales group. (Comparisons between the 2 groups are not meaningful because the stimulus sets were different.)
CONCLUSIONS: These results provide the first evidence, to our knowledge, that experts are not immune to the effects of prevalence even with stimuli from their domain of expertise. Prevalence is a factor to consider in screening for disease by human observers and has significant implications for cytology-based cervical cancer screening in the post-human papillomavirus vaccine era, when prevalence rates of high-grade lesions in the population are expected to decline.

Entities:  

Mesh:

Year:  2011        PMID: 22129183      PMCID: PMC3966132          DOI: 10.5858/arpa.2010-0739-OA

Source DB:  PubMed          Journal:  Arch Pathol Lab Med        ISSN: 0003-9985            Impact factor:   5.534


  12 in total

1.  The cervical cancer epidemic that screening has prevented in the UK.

Authors:  Julian Peto; Clare Gilham; Olivia Fletcher; Fiona E Matthews
Journal:  Lancet       Date:  2004 Jul 17-23       Impact factor: 79.321

2.  Low target prevalence is a stubborn source of errors in visual search tasks.

Authors:  Jeremy M Wolfe; Todd S Horowitz; Michael J Van Wert; Naomi M Kenner; Skyler S Place; Nour Kibbi
Journal:  J Exp Psychol Gen       Date:  2007-11

3.  Differences between Papanicolaou smears with correct and incorrect diagnoses.

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Review 6.  Cancer screening in theory and in practice.

Authors:  Otis W Brawley; Barnett S Kramer
Journal:  J Clin Oncol       Date:  2005-01-10       Impact factor: 44.544

Review 7.  Chapter 20: Issues in planning cervical cancer screening in the era of HPV vaccination.

Authors:  Eduardo L Franco; Jack Cuzick; Allan Hildesheim; Silvia de Sanjosé
Journal:  Vaccine       Date:  2006-06-08       Impact factor: 3.641

Review 8.  Human papillomavirus and cervical cancer.

Authors:  Mark Schiffman; Philip E Castle; Jose Jeronimo; Ana C Rodriguez; Sholom Wacholder
Journal:  Lancet       Date:  2007-09-08       Impact factor: 79.321

9.  Varying target prevalence reveals two dissociable decision criteria in visual search.

Authors:  Jeremy M Wolfe; Michael J Van Wert
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10.  A case-control study of true-positive versus false-negative cervical smears in women with cervical intraepithelial neoplasia (CIN) III.

Authors:  J P O'Sullivan; R P A'Hern; P A Chapman; L Jenkins; R Smith; A al-Nafussi; M T Brett; A Herbert; M E McKean; C A Waddell
Journal:  Cytopathology       Date:  1998-06       Impact factor: 2.073

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  23 in total

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2.  Prevalence effects in newly trained airport checkpoint screeners: trained observers miss rare targets, too.

Authors:  Jeremy M Wolfe; David N Brunelli; Joshua Rubinstein; Todd S Horowitz
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3.  Impact of prevalence and case distribution in lab-based diagnostic imaging studies.

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5.  The effect of expert knowledge on medical search: medical experts have specialized abilities for detecting serious lesions.

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7.  Let's Use Cognitive Science to Create Collaborative Workstations.

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8.  Failures of perception in the low-prevalence effect: Evidence from active and passive visual search.

Authors:  Michael C Hout; Stephen C Walenchok; Stephen D Goldinger; Jeremy M Wolfe
Journal:  J Exp Psychol Hum Percept Perform       Date:  2015-04-27       Impact factor: 3.332

Review 9.  HOW DO RADIOLOGISTS USE THE HUMAN SEARCH ENGINE?

Authors:  Jeremy M Wolfe; Karla K Evans; Trafton Drew; Avigael Aizenman; Emilie Josephs
Journal:  Radiat Prot Dosimetry       Date:  2015-12-08       Impact factor: 0.972

10.  Suboptimality in Perceptual Decision Making.

Authors:  Dobromir Rahnev; Rachel N Denison
Journal:  Behav Brain Sci       Date:  2018-02-27       Impact factor: 12.579

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