Stability of diagnostic rate in a cohort of 38,813 colorectal polyp specimens and implications for histomorphology and statistical process control

Abstract This work sought to quantify pathologists’ diagnostic bias over time in their evaluation of colorectal polyps to assess how this may impact the utility of statistical process control (SPC). All colorectal polyp specimens(CRPS) for 2011–2017 in a region were categorized using a validated fre...

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Autores principales: Michael Bonert, Asghar Naqvi, Mozibur Rahman, John K. Marshall, Ted Xenodemetropoulos, Paul Arora, Justin Slater, Pierre Major
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/21e4bea2014a47bf971f4e75a91a9cf2
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Sumario:Abstract This work sought to quantify pathologists’ diagnostic bias over time in their evaluation of colorectal polyps to assess how this may impact the utility of statistical process control (SPC). All colorectal polyp specimens(CRPS) for 2011–2017 in a region were categorized using a validated free text string matching algorithm. Pathologist diagnostic rates (PDRs) for high grade dysplasia (HGD), tubular adenoma (TA_ad), villous morphology (TVA + VA), sessile serrated adenoma (SSA) and hyperplastic polyp (HP), were assessed (1) for each pathologist in yearly intervals with control charts (CCs), and (2) with a generalized linear model (GLM). The study included 64,115 CRPS. Fifteen pathologists each interpreted > 150 CRPS/year in all years and together diagnosed 38,813. The number of pathologists (of 15) with zero or one (p < 0.05) outlier in seven years, compared to their overall PDR, was 13, 9, 9, 5 and 9 for HGD, TVA + VA, TA_ad, HP and SSA respectively. The GLM confirmed, for the subset where pathologists/endoscopists saw > 600 CRPS each(total 52,760 CRPS), that pathologist, endoscopist, anatomical location and year were all strongly correlated (all p < 0.0001) with the diagnosis. The moderate PDR stability over time supports the hypothesis that diagnostic rates are amendable to calibration via SPC and outcome data.