Literature DB >> 26524350

Adequacy in voided urine cytology specimens: The role of volume and a repeat void upon predictive values for high-grade urothelial carcinoma.

Christopher J VandenBussche1, Dorothy L Rosenthal1, Matthew T Olson1.   

Abstract

BACKGROUND: Adequacy assessment is one of the most controversial and overlooked components in the daily practice of cytopathology, because it is generally determined from limited samples. Because voided urine varies widely in terms of its volume and cellularity, there is little consensus about the proper role for these variables in assessing specimen adequacy. In this study, the authors explored the role of volume in voided urine specimens to determine whether it plays a role in determining adequacy for the detection of high-grade urothelial carcinoma.
METHODS: Voided urine specimens received at the authors' laboratory over the 9.5 years since the introduction of the Johns Hopkins Template for Reporting Urinary Cytopathology were analyzed for correlations between volume, specimen adequacy, and the diagnosis of high-grade malignancy. The same data set also was queried to determine whether a patient who provided a voided low-volume specimen could yield a higher volume specimen and thereby increase adequacy.
RESULTS: In total, 15,731 voided urine specimens with a cumulative volume of 891 liters originating from 8594 individual patients were analyzed. Specimen adequacy increased linearly for each increment of volume submitted to the laboratory up to 30 mL, after which the correlation was nonlinear. Low-volume specimens below this cutoff also had lower fractions of specimens that were diagnosed as malignant or suspicious.
CONCLUSIONS: Volume is an important component in the evaluation of adequacy for voided urine cytology specimens.
© 2015 American Cancer Society.

Entities:  

Keywords:  The John Hopkins Hospital Template for Reporting Urinary Cytology; The Paris System for Reporting Urinary Cytology; bladder cancer; urinary cytology; urothelial carcinoma

Mesh:

Year:  2015        PMID: 26524350     DOI: 10.1002/cncy.21634

Source DB:  PubMed          Journal:  Cancer Cytopathol        ISSN: 1934-662X            Impact factor:   5.284


  3 in total

1.  Noninvasive diagnostic imaging using machine-learning analysis of nanoresolution images of cell surfaces: Detection of bladder cancer.

Authors:  I Sokolov; M E Dokukin; V Kalaparthi; M Miljkovic; A Wang; J D Seigne; P Grivas; E Demidenko
Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-03       Impact factor: 11.205

2.  [The Paris system for classification of urinary cytology].

Authors:  S Savic; T Vlajnic; L Bubendorf
Journal:  Pathologe       Date:  2017-09       Impact factor: 1.011

3.  The Paris System for reporting urinary cytology improves the negative predictive value of high-grade urothelial carcinoma.

Authors:  Mari Yamasaki; Rikiya Taoka; Kazuya Katakura; Toru Matsunaga; Naoya Kani; Tomoko Honda; Satoshi Harada; Yoichiro Tohi; Yuki Matsuoka; Takuma Kato; Homare Okazoe; Hiroyuki Tsunemori; Nobufumi Ueda; Reiji Haba; Mikio Sugimoto
Journal:  BMC Urol       Date:  2022-04-05       Impact factor: 2.264

  3 in total

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