Literature DB >> 17535088

The problems and promise of central pathology review: development of a standardized procedure for the Children's Oncology Group.

Lisa A Teot1, Richard Sposto, Anita Khayat, Stephen Qualman, Gregory Reaman, David Parham.   

Abstract

The practice of central histopathologic review by expert pathologists has accompanied entry of patients onto multi-institutional therapeutic research protocols for the past half-century, and it is still a key component in the majority of therapeutic protocols conducted by the Children's Oncology Group (COG). Policies regarding pathology review have historically varied but have recently been standardized by the COG. Pretreatment central pathology review has been used to improve the accuracy of pathology data that is critical to the conduct of the study and to ensure that ineligible patients are not enrolled on a study. Pretreatment central review is unnecessary when there are established criteria for diagnosis, when institutions can uniformly apply these criteria, and when diagnoses are reliably reported. Pretreatment central review is appropriate when there are established diagnostic criteria and expert reviewers can consistently apply them but when institutional diagnoses show significant variability. It is inappropriate when there are no standard criteria or when variability exists among experts. Retrospective reviews (for example, those performed after protocol entry and treatment have occurred) historically have been used to verify institutional diagnoses and to record other features of tumors, prior to analysis of research questions. However, delayed reporting of discrepant diagnoses from retrospective reviews introduced obvious concerns regarding the appropriateness of treatment and exposed institutional pathologists and clinicians to significant professional risks. This article examines the historical usage and current status of the central pathology review process and the rationale and indications for its performance.

Entities:  

Mesh:

Year:  2007        PMID: 17535088     DOI: 10.2350/06-06-0121.1

Source DB:  PubMed          Journal:  Pediatr Dev Pathol        ISSN: 1093-5266


  9 in total

Review 1.  Computer-Aided Histopathological Image Analysis Techniques for Automated Nuclear Atypia Scoring of Breast Cancer: a Review.

Authors:  Asha Das; Madhu S Nair; S David Peter
Journal:  J Digit Imaging       Date:  2020-10       Impact factor: 4.056

2.  Computer-aided evaluation of neuroblastoma on whole-slide histology images: Classifying grade of neuroblastic differentiation.

Authors:  J Kong; O Sertel; H Shimada; K L Boyer; J H Saltz; M N Gurcan
Journal:  Pattern Recognit       Date:  2009-06       Impact factor: 7.740

3.  Computer-aided Prognosis of Neuroblastoma on Whole-slide Images: Classification of Stromal Development.

Authors:  O Sertel; J Kong; H Shimada; U V Catalyurek; J H Saltz; M N Gurcan
Journal:  Pattern Recognit       Date:  2009-06       Impact factor: 7.740

4.  Non-parametric and integrated framework for segmenting and counting neuroblastic cells within neuroblastoma tumor images.

Authors:  Siamak Tafavogh; Karla Felix Navarro; Daniel R Catchpoole; Paul J Kennedy
Journal:  Med Biol Eng Comput       Date:  2013-01-29       Impact factor: 2.602

5.  Automated mitosis detection in histopathology using morphological and multi-channel statistics features.

Authors:  Humayun Irshad
Journal:  J Pathol Inform       Date:  2013-05-30

6.  Adaptive localization of focus point regions via random patch probabilistic density from whole-slide, Ki-67-stained brain tumor tissue.

Authors:  Yazan M Alomari; Siti Norul Huda Sheikh Abdullah; Reena Rahayu MdZin; Khairuddin Omar
Journal:  Comput Math Methods Med       Date:  2015-02-22       Impact factor: 2.238

7.  Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach.

Authors:  Humayun Irshad; Sepehr Jalali; Ludovic Roux; Daniel Racoceanu; Lim Joo Hwee; Gilles Le Naour; Frédérique Capron
Journal:  J Pathol Inform       Date:  2013-03-30

8.  Cellular quantitative analysis of neuroblastoma tumor and splitting overlapping cells.

Authors:  Siamak Tafavogh; Daniel R Catchpoole; Paul J Kennedy
Journal:  BMC Bioinformatics       Date:  2014-08-11       Impact factor: 3.169

9.  Rationale for the Cytogenomics of Cardiovascular Malformations Consortium: A Phenotype Intensive Registry Based Approach.

Authors:  Robert B Hinton; Kim L McBride; Steven B Bleyl; Neil E Bowles; William L Border; Vidu Garg; Teresa A Smolarek; Seema R Lalani; Stephanie M Ware
Journal:  J Cardiovasc Dev Dis       Date:  2015-04-29
  9 in total

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