Review Article: FNAC and Biobanking

By: Jana Sullinger, MD  On: Sun 22 of Apr., 2012 01:08 MDT  (2901 Reads)
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Review Article

Review Article
arrow Review Article: FNAC and Biobanking(external link)
by The Populist Cytologist
I thought this review article on Fine-Needle? Aspiration Cytology Is an Alternative Source of High Quality Archival Samples in Biobanking, written by Sani Abubakar Malami (© 2011), published in the ISRN Pathology was an interesting discussion. Those of us in the field of cytopathology are facing a challenge with respect to the reshaping of our field. This article describes potential uses of FNAC in biobanking, which currently hasn’t been utilized in any established fashion. The author concludes that in order “to accomplish the current requirements of the scientific community, archival FNAC tissue banks, like all other biobanks, need to address some essential challenges that include management strategies, consensus on standard operating procedures, appropriate design, harmonized and unique policies of utilization, and sustainability, all of them within the framework of the appropriate ethical, legal, and social considerations 2.”

Continue reading on The Populist Cytologist...(external link)

RESEARCH: Screening and cervical cancer cure: population based cohort study

By: Jana Sullinger, MD  On: Sat 03 of Mar., 2012 19:48 MST  (4560 Reads)
Rating: star star star star star star star star star half star (9.99/10)
Review Article

Screening and cervical cancer cure: population based cohort study
BMJ 2012; 344 doi: 10.1136/bmj.e900 (Published 1 March 2012)
Cite this as: BMJ 2012;344:e900
Download article here(external link).

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Review Article

A preliminary study of the potential of tree classifiers in triage of high-grade squamous intraepithelial lesions. Anal Quant Cytol Histol. 2011 Jun;33(3):132-40
Authors: Karakitsos P, Pouliakis A, Meristoudis C, Margari N, Kassanos D, Kyrgiou M, Panayiotides JG, Paraskevaidis E


OBJECTIVE: To investigate the potential value of tree classifiers for the triage of high-grade squamous intraepithelial lesions.

STUDY DESIGN: The dataset comprised 808 histologically confirmed cases having a complete range of the cytologic sample assessments--liquid-based cytology, reflex human papillomavirus (HPV) DNA test, E6/E7 HPV mRNA test, and p16 immunocytochemical examinations. Data include 488 histologically negative (cervical intraepithelial neoplasia CIN 1 and below) or clinically negative cases and 320 with histologic diagnosis of CIN 2 or worse. Cytologic diagnosis was made according to the criteria of the Bethesda System. Cases were classified in two groups according to histology: those with CIN 2 or worse and those with CIN 1 and below. Fifty percent were randomly selected as a training set and the remaining were as a test set.

RESULTS: Application of tree classifier on the test set gave correct classification of 66.9% for CIN 2 and above cases and 97.3% for CIN 1 and below, producing overall accuracy of 91.5%, outperforming cytologic diagnosis alone.

CONCLUSION: Application of tree classifiers, based on standard cytologic diagnosis and expression of studied biomarkers, produces improved classification results for cervical precancerous lesions and cancer diagnosis and

PMID: 21980616

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