Literature DB >> 16927641

Interobserver variation in breast cancer grading: a statistical modeling approach.

Nilotpal Chowdhury1, Muktha R Pai, Flora D Lobo, Hema Kini, Rebecca Varghese.   

Abstract

OBJECTIVE: To study random and the systematic error in breast cancer grading, to find the source of disagreements and measure the reliability of graders so that appropriate corrective action can be taken. STUDY
DESIGN: Five independent observers graded 50 breast carcinoma slides from 50 consecutive breast cancer specimens according to the Nottingham criteria. The polychoric correlation was used to measure association. Stuart-Maxwell and McNemar tests were used to measure equality of thresholds.
RESULTS: The polychoric correlation among observers was high (mean = 0.803, 0.712, 0.797 and 0.602 for the final grade, tubule formation, nuclear pleomorphism and mitotic figures, respectively). However, there were significant differences in thresholds (6, 7, 7 and 9 pairs of 10 showing significant differences in classification of grades/scores for final grade, tubule formation, nuclear pleomorphism and mitotic counts, respectively).
CONCLUSION: The high polychoric correlations suggest that random error in grading breast cancers in this study was low, confirming the underlying reliability of grading and graders. However, significant differences in the thresholds lowers raw agreement. Such a scenario may be rectified by increased intradepartmental discussion.

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Mesh:

Year:  2006        PMID: 16927641

Source DB:  PubMed          Journal:  Anal Quant Cytol Histol        ISSN: 0884-6812            Impact factor:   0.302


  7 in total

Review 1.  Breast cancer prognostic classification in the molecular era: the role of histological grade.

Authors:  Emad A Rakha; Jorge S Reis-Filho; Frederick Baehner; David J Dabbs; Thomas Decker; Vincenzo Eusebi; Stephen B Fox; Shu Ichihara; Jocelyne Jacquemier; Sunil R Lakhani; José Palacios; Andrea L Richardson; Stuart J Schnitt; Fernando C Schmitt; Puay-Hoon Tan; Gary M Tse; Sunil Badve; Ian O Ellis
Journal:  Breast Cancer Res       Date:  2010-07-30       Impact factor: 6.466

2.  Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival.

Authors:  Mauro Tambasco; Misha Eliasziw; Anthony M Magliocco
Journal:  J Transl Med       Date:  2010-12-31       Impact factor: 5.531

3.  Histologic disorderliness in the arrangement of tumor cells as an objective measure of tumor differentiation.

Authors:  Sungwook Suh; Gyeongsin Park; Young Sub Lee; Yosep Chong; Youn Soo Lee; Yeong Jin Choi
Journal:  Korean J Pathol       Date:  2014-10-27

4.  Designing image segmentation studies: Statistical power, sample size and reference standard quality.

Authors:  Eli Gibson; Yipeng Hu; Henkjan J Huisman; Dean C Barratt
Journal:  Med Image Anal       Date:  2017-07-22       Impact factor: 8.545

5.  Optoacoustic imaging of the breast: correlation with histopathology and histopathologic biomarkers.

Authors:  Gisela L G Menezes; Ritse M Mann; Carla Meeuwis; Bob Bisschops; Jeroen Veltman; Philip T Lavin; Marc J van de Vijver; Ruud M Pijnappel
Journal:  Eur Radiol       Date:  2019-05-27       Impact factor: 5.315

6.  Diffusion-Weighted Imaging of Breast Cancer: Correlation of the Apparent Diffusion Coefficient Value with Pathologic Prognostic Factors.

Authors:  Şehnaz Tezcan; Nihal Uslu; Funda Ulu Öztürk; Eda Yılmaz Akçay; Tugan Tezcaner
Journal:  Eur J Breast Health       Date:  2019-10-01

Review 7.  Grading of invasive breast carcinoma: the way forward.

Authors:  C van Dooijeweert; P J van Diest; I O Ellis
Journal:  Virchows Arch       Date:  2021-07-01       Impact factor: 4.535

  7 in total

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