Literature DB >> 33165721

Diagnostic Accuracy of Nipple Aspirate Fluid Cytology in Asymptomatic Patients: A Meta-analysis and Systematic Review of the Literature.

Natasha Jiwa1, Rishikesh Gandhewar2, Hemali Chauhan2, Hutan Ashrafian2, Swathica Kumar3, Corrina Wright4, Zoltan Takats2, Daniel Richard Leff2.   

Abstract

PURPOSE: To calculate the diagnostic accuracy of nipple aspirate fluid (NAF) cytology.
BACKGROUND: Evaluation of NAF cytology in asymptomatic patients conceptually offers a non-invasive method for either screening for breast cancer or else predicting or stratifying future cancer risk.
METHODS: Studies were identified by performing electronic searches up to August 2019. A meta-analysis was conducted to attain an overall pooled sensitivity and specificity of NAF for breast cancer detection.
RESULTS: A search through 938 studies yielded a total of 19 studies. Overall, 9308 patients were examined, with cytology results from 10,147 breasts [age (years), mean ± SD = 49.73 ± 4.09 years]. Diagnostic accuracy meta-analysis of NAF revealed a pooled specificity of 0.97 (95% CI 0.97-0.98), and sensitivity of 0.64 (95% CI 0.62-0.66).
CONCLUSIONS: The diagnostic accuracy of nipple smear cytology is limited by poor sensitivity. If nipple fluid assessment is to be used for diagnosis, then emerging technologies for fluid biomarker analysis must supersede the current diagnostic accuracy of NAF cytology.

Entities:  

Year:  2020        PMID: 33165721     DOI: 10.1245/s10434-020-09313-9

Source DB:  PubMed          Journal:  Ann Surg Oncol        ISSN: 1068-9265            Impact factor:   5.344


  41 in total

1.  Breast cancer risk prediction: should nipple aspiration fluid cytology be incorporated into clinical practice?

Authors:  C J Fabian; B F Kimler
Journal:  J Natl Cancer Inst       Date:  2001-12-05       Impact factor: 13.506

2.  Cytologic evaluation of breast secretions.

Authors:  G N PAPANICOLAOU; G M BADER; D G HOLMQUIST; E A FALK
Journal:  Ann N Y Acad Sci       Date:  1956-03-30       Impact factor: 5.691

3.  American Cancer Society guidelines for breast screening with MRI as an adjunct to mammography.

Authors:  Debbie Saslow; Carla Boetes; Wylie Burke; Steven Harms; Martin O Leach; Constance D Lehman; Elizabeth Morris; Etta Pisano; Mitchell Schnall; Stephen Sener; Robert A Smith; Ellen Warner; Martin Yaffe; Kimberly S Andrews; Christy A Russell
Journal:  CA Cancer J Clin       Date:  2007 Mar-Apr       Impact factor: 508.702

4.  Diagnostic accuracy of digital breast tomosynthesis versus digital mammography for benign and malignant lesions in breasts: a meta-analysis.

Authors:  Junqiang Lei; Pin Yang; Li Zhang; Yinzhong Wang; Kehu Yang
Journal:  Eur Radiol       Date:  2014-03       Impact factor: 5.315

5.  Evaluation of the Tyrer-Cuzick (International Breast Cancer Intervention Study) model for breast cancer risk prediction in women with atypical hyperplasia.

Authors:  Judy C Boughey; Lynn C Hartmann; Stephanie S Anderson; Amy C Degnim; Robert A Vierkant; Carol A Reynolds; Marlene H Frost; V Shane Pankratz
Journal:  J Clin Oncol       Date:  2010-07-06       Impact factor: 44.544

6.  Limitations of the Gail model in the specialized breast cancer risk assessment clinic.

Authors:  David M Euhus; A Marilyn Leitch; James F Huth; George N Peters
Journal:  Breast J       Date:  2002 Jan-Feb       Impact factor: 2.431

Review 7.  Missed breast carcinoma: pitfalls and pearls.

Authors:  Aneesa S Majid; Ellen Shaw de Paredes; Richard D Doherty; Neil R Sharma; Xavier Salvador
Journal:  Radiographics       Date:  2003 Jul-Aug       Impact factor: 5.333

8.  Evaluation of mathematical models for breast cancer risk assessment in routine clinical use.

Authors:  Peter A Fasching; Mayada R Bani; Carolin Nestle-Krämling; Tim O Goecke; Dieter Niederacher; Matthias W Beckmann; Michael P Lux
Journal:  Eur J Cancer Prev       Date:  2007-06       Impact factor: 2.497

9.  Evaluation of breast cancer risk assessment packages in the family history evaluation and screening programme.

Authors:  E Amir; D G Evans; A Shenton; F Lalloo; A Moran; C Boggis; M Wilson; A Howell
Journal:  J Med Genet       Date:  2003-11       Impact factor: 6.318

Review 10.  Breast cancer risk-assessment models.

Authors:  D Gareth R Evans; Anthony Howell
Journal:  Breast Cancer Res       Date:  2007       Impact factor: 6.466

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  3 in total

Review 1.  Nipple aspirate fluid and its use for the early detection of breast cancer.

Authors:  Natasha Jiwa; Ahmed Ezzat; Josephine Holt; Dhuleep S Wijayatilake; Zoltan Takats; Daniel Richard Leff
Journal:  Ann Med Surg (Lond)       Date:  2022-04-18

Review 2.  Nipple Aspirate Fluid at a Glance.

Authors:  Susana I S Patuleia; Karijn P M Suijkerbuijk; Elsken van der Wall; Paul J van Diest; Cathy B Moelans
Journal:  Cancers (Basel)       Date:  2021-12-29       Impact factor: 6.639

3.  The changing microRNA landscape by color and cloudiness: a cautionary tale for nipple aspirate fluid biomarker analysis.

Authors:  Susana I S Patuleia; Elsken van der Wall; Carla H van Gils; Marije F Bakker; Agnes Jager; Marleen M Voorhorst-Ogink; Paul J van Diest; Cathy B Moelans
Journal:  Cell Oncol (Dordr)       Date:  2021-10-16       Impact factor: 7.051

  3 in total

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