Literature DB >> 25594725

A Call to Standardize Preanalytic Data Elements for Biospecimens, Part II.

James A Robb, Lynn Bry, Patrick M Sluss, Elizabeth A Wagar, Mary F Kennedy1.   

Abstract

CONTEXT: Biospecimens must have appropriate clinical annotation (data) to ensure optimal quality for both patient care and research. Additional clinical preanalytic variables are the focus of this continuing study.
OBJECTIVE: To complete the identification of the essential preanalytic variables (data fields) that can, and in some instances should, be attached to every collected biospecimen by adding the additional specific variables for clinical chemistry and microbiology to our original 170 variables.
DESIGN: The College of American Pathologists Diagnostic Intelligence and Health Information Technology Committee sponsored a second Biorepository Working Group to complete the list of preanalytic variables for annotating biospecimens. Members of the second Biorepository Working Group are experts in clinical pathology and microbiology. Additional preanalytic area-specific variables were identified and ranked along with definitions and potential negative impacts if the variable is not attached to the biospecimen. The draft manuscript was reviewed by additional national and international stakeholders.
RESULTS: Four additional required preanalytic variables were identified specifically for clinical chemistry and microbiology biospecimens that can be used as a guide for site-specific implementation into patient care and research biorepository processes.
CONCLUSIONS: In our collective experience, selecting which of the many preanalytic variables to attach to any specific set of biospecimens used for patient care and/or research is often difficult. The additional ranked list should be of practical benefit when selecting preanalytic variables for a given biospecimen collection.

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Mesh:

Year:  2015        PMID: 25594725     DOI: 10.5858/arpa.2014-0572-CP

Source DB:  PubMed          Journal:  Arch Pathol Lab Med        ISSN: 0003-9985            Impact factor:   5.534


  7 in total

Review 1.  Proceedings of the 1st Puerto Rico Biobanking Workshop.

Authors:  Edna Mora; James A Robb; Gustavo Stefanoff; Robert Hunter Mellado; Domenico Coppola; Teresita Muñoz-Antonia; Idhaliz Flores
Journal:  Rev Recent Clin Trials       Date:  2014

2.  Standard Operating Procedures for Biospecimen Collection, Processing, and Storage: From the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer.

Authors:  William E Fisher; Zobeida Cruz-Monserrate; Amy L McElhany; Gregory B Lesinski; Phil A Hart; Ria Ghosh; George Van Buren; Douglas S Fishman; Jo Ann S Rinaudo; Jose Serrano; Sudhir Srivastava; Thomas Mace; Mark Topazian; Ziding Feng; Dhiraj Yadav; Stephen J Pandol; Steven J Hughes; Robert Y Liu; Emily Lu; Robert Orr; David C Whitcomb; Amer S Abouhamze; Hanno Steen; Zachary M Sellers; David M Troendle; Aliye Uc; Mark E Lowe; Darwin L Conwell
Journal:  Pancreas       Date:  2018 Nov/Dec       Impact factor: 3.327

3.  Storage Conditions and Immunoreactivity of Breast Cancer Subtyping Markers in Tissue Microarray Sections.

Authors:  Angela R Omilian; Gary R Zirpoli; Ting-Yuan David Cheng; Song Yao; Leighton Stein; Warren Davis; Karen L Head; Priya Nair; Thaer Khoury; Christine B Ambrosone; Wiam Bshara
Journal:  Appl Immunohistochem Mol Morphol       Date:  2020-04

4.  Early stage lung cancer detection in systemic sclerosis does not portend survival benefit: a cross sectional study.

Authors:  Jeremy B Katzen; Kirtee Raparia; Rishi Agrawal; Jyoti D Patel; Alfred Rademaker; John Varga; Jane E Dematte
Journal:  PLoS One       Date:  2015-02-17       Impact factor: 3.240

5.  Consensus-Driven Development of a Terminology for Biobanking, the Duke Experience.

Authors:  Helena Ellis; Mary-Beth Joshi; Aenoch J Lynn; Anita Walden
Journal:  Biopreserv Biobank       Date:  2017-03-24       Impact factor: 2.300

6.  Leveraging artificial intelligence to predict ERG gene fusion status in prostate cancer.

Authors:  Vipulkumar Dadhania; Daniel Gonzalez; Mustafa Yousif; Jerome Cheng; Todd M Morgan; Daniel E Spratt; Zachery R Reichert; Rahul Mannan; Xiaoming Wang; Anya Chinnaiyan; Xuhong Cao; Saravana M Dhanasekaran; Arul M Chinnaiyan; Liron Pantanowitz; Rohit Mehra
Journal:  BMC Cancer       Date:  2022-05-05       Impact factor: 4.638

7.  Accuracy of whole slide image based image analysis is adversely affected by preanalytical factors such as stained tissue slide and paraffin block age.

Authors:  Nada Shaker; Ruhani Sardana; Satoshi Hamasaki; David G Nohle; Leona W Ayers; Anil V Parwani
Journal:  J Pathol Inform       Date:  2022-06-28
  7 in total

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