Literature DB >> 18683853

Do we truly see what we think we see? The role of cognitive bias in pathological interpretation.

T M Fandel1, M Pfnür, S C Schäfer, P Bacchetti, F W Mast, C Corinth, M Ansorge, S W Melchior, J W Thüroff, C J Kirkpatrick, H-A Lehr.   

Abstract

In the histomorphological grading of prostate carcinoma, pathologists have regularly assigned comparable scores for the architectural Gleason and the now-obsolete nuclear World Health Organization (WHO) grading systems. Although both systems demonstrate good correspondence between grade and survival, they are based on fundamentally different biological criteria. We tested the hypothesis that this apparent concurrence between the two grading systems originates from an interpretation bias in the minds of diagnostic pathologists, rather than reflecting a biological reality. Three pathologists graded 178 prostatectomy specimens, assigning Gleason and WHO scores on glass slides and on digital images of nuclei isolated out of their architectural context. The results were analysed with respect to interdependencies among the grading systems, to tumour recurrence (PSA relapse > 0.1 ng/ml at 48 months) and robust nuclear morphometry, as assessed by computer-assisted image analysis. WHO and Gleason grades were strongly correlated (r = 0.82) and demonstrated identical prognostic power. However, WHO grades correlated poorly with nuclear morphology (r = 0.19). Grading of nuclei isolated out of their architectural context significantly improved accuracy for nuclear morphology (r = 0.55), but the prognostic power was virtually lost. In conclusion, the architectural organization of a tumour, which the pathologist cannot avoid noticing during initial slide viewing at low magnification, unwittingly influences the subsequent nuclear grade assignment. In our study, the prognostic power of the WHO grading system was dependent on visual assessment of tumour growth pattern. We demonstrate for the first time the influence a cognitive bias can have in the generation of an error in diagnostic pathology and highlight a considerable problem in histopathological tumour grading.

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Year:  2008        PMID: 18683853     DOI: 10.1002/path.2395

Source DB:  PubMed          Journal:  J Pathol        ISSN: 0022-3417            Impact factor:   7.996


  9 in total

Review 1.  Systematic review: bias in imaging studies - the effect of manipulating clinical context, recall bias and reporting intensity.

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Review 2.  Methodological requirements for valid tissue-based biomarker studies that can be used in clinical practice.

Authors:  Lawrence D True
Journal:  Virchows Arch       Date:  2014-02-01       Impact factor: 4.064

3.  Tumor architecture exerts no bias on nuclear grading in breast cancer diagnosis.

Authors:  Braulio Mora; Dario Bombari; Stephan C Schaefer; Marcus Schmidt; Jean-Francois Delaloye; Fred Mast; Hans-Anton Lehr
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4.  Quantitative immunohistochemistry by measuring chromogen signal strength using a C# written program.

Authors:  Shaghayegh Haghjooy Javanmard; Ali Moeiny
Journal:  J Res Med Sci       Date:  2009-05       Impact factor: 1.852

5.  What was I thinking? Eye-tracking experiments underscore the bias that architecture exerts on nuclear grading in prostate cancer.

Authors:  Dario Bombari; Braulio Mora; Stephan C Schaefer; Fred W Mast; Hans-Anton Lehr
Journal:  PLoS One       Date:  2012-05-30       Impact factor: 3.240

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7.  Optimisation of an immunohistochemistry method for the determination of androgen receptor expression levels in circulating tumour cells.

Authors:  Jeffrey Cummings; Robert Sloane; Karen Morris; Cong Zhou; Matt Lancashire; David Moore; Tony Elliot; Noel Clarke; Caroline Dive
Journal:  BMC Cancer       Date:  2014-03-28       Impact factor: 4.430

8.  Predicting Diagnosis of Australian Canine and Feline Urinary Bladder Disease Based on Histologic Features.

Authors:  Emily Jones; John Alawneh; Mary Thompson; Chiara Palmieri; Karen Jackson; Rachel Allavena
Journal:  Vet Sci       Date:  2020-11-27

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Authors:  Neelam Sood
Journal:  Indian J Med Res       Date:  2019-09       Impact factor: 2.375

  9 in total

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