Objective Guidelines mandate expert pathology review of Barrett's oesophagus (BO) biopsies that reveal dysplasia, but there are no evidence-based standards to corroborate expert reviewer status. We investigated BO concordance rates and pathologist features predictive of diagnostic discordance. Design Pathologists (n=51) from over 20 countries assessed 55 digitised BO biopsies from across the diagnostic spectrum, before and after viewing matched p53 labelling. Extensive demographic and clinical experience data were obtained via online questionnaire. Reference diagnoses were obtained from a review panel (n=4) of experienced Barrett's pathologists. Results We recorded over 6000 case diagnoses with matched demographic data. Of 2805 H&E diagnoses, we found excellent concordance (>70%) for non-dysplastic BO and high-grade dysplasia, and intermediate concordance for low-grade dysplasia (42%) and indefinite for dysplasia (23%). Major diagnostic errors were found in 248 diagnoses (8.8%), which reduced to 232 (8.3%) after viewing p53 labelled slides. Demographic variables correlating with diagnostic proficiency were analysed in multivariate analysis, which revealed that at least 5 years of professional experience was protective against major diagnostic error for H&E slide review (OR 0.48, 95% CI 0.31 to 0.74). Working in a non-teaching hospital was associated with increased odds of major diagnostic error (OR 1.76, 95% CI 1.15 to 2.69); however, this was neutralised when pathologists viewed p53 labelled slides. Notably, neither case volume nor self-identifying as an expert predicted diagnostic proficiency. Extrapolating our data to real-world case prevalence suggests that 92.3% of major diagnostic errors are due to overinterpreting non-dysplastic BO. Conclusion Our data provide evidence-based criteria for diagnostic proficiency in Barrett's histopathology.
Histopathologist features predictive of diagnostic concordance at expert level among a large international sample of pathologists diagnosing Barrett's dysplasia using digital pathology
Fassan M.
2020
Abstract
Objective Guidelines mandate expert pathology review of Barrett's oesophagus (BO) biopsies that reveal dysplasia, but there are no evidence-based standards to corroborate expert reviewer status. We investigated BO concordance rates and pathologist features predictive of diagnostic discordance. Design Pathologists (n=51) from over 20 countries assessed 55 digitised BO biopsies from across the diagnostic spectrum, before and after viewing matched p53 labelling. Extensive demographic and clinical experience data were obtained via online questionnaire. Reference diagnoses were obtained from a review panel (n=4) of experienced Barrett's pathologists. Results We recorded over 6000 case diagnoses with matched demographic data. Of 2805 H&E diagnoses, we found excellent concordance (>70%) for non-dysplastic BO and high-grade dysplasia, and intermediate concordance for low-grade dysplasia (42%) and indefinite for dysplasia (23%). Major diagnostic errors were found in 248 diagnoses (8.8%), which reduced to 232 (8.3%) after viewing p53 labelled slides. Demographic variables correlating with diagnostic proficiency were analysed in multivariate analysis, which revealed that at least 5 years of professional experience was protective against major diagnostic error for H&E slide review (OR 0.48, 95% CI 0.31 to 0.74). Working in a non-teaching hospital was associated with increased odds of major diagnostic error (OR 1.76, 95% CI 1.15 to 2.69); however, this was neutralised when pathologists viewed p53 labelled slides. Notably, neither case volume nor self-identifying as an expert predicted diagnostic proficiency. Extrapolating our data to real-world case prevalence suggests that 92.3% of major diagnostic errors are due to overinterpreting non-dysplastic BO. Conclusion Our data provide evidence-based criteria for diagnostic proficiency in Barrett's histopathology.
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Histopathologist features predictive of diagnostic concordance at expert level among a large international sample of pathologists diagnosing Barrett’s dysplasia using digital pathology - Bolero Paper_complete.pdf
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