Predicting pulmonary adenocarcinoma outcome based on a cytology grading system. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Pulmonary adenocarcinoma (AD) has a variety of architectural patterns. Recently, a 3-tiered histological pattern-based grading system was developed for stage I lung AD, stratifying patients into low, intermediate, and high risk for recurrence. However, cytology may serve as the primary method for diagnosis in patients with inoperable disease. Attempts to correlate architecture between parallel cytological and histological preparations have not been successful. Therefore, we evaluated cytomorphologic features of previously histologically graded AD to identify features of potential prognostic significance. METHODS: One hundred and thirteen fine-needle aspirations with excised adenocarcinomas were reviewed. In the liquid-based preparation, we evaluated cell arrangements(flat sheets vs 3-D clusters vs single cells), nuclear features (size variability, shape, and contour),nucleoli (prominent or inconspicuous), presence of nuclear inclusions, chromatin (fine, coarse,or clumped), and quality of background. The features were tested by multivariate analysis to identify associations with histological grade and disease-free survival (DFS), and a cytological score was generated. RESULTS: Nuclear size, chromatin pattern, and nuclear contours showed a significant association with histological grade and DFS. These features were included in the composite cytological score (range,0-5). By grouping the cytological scores, we stratified the tumors into low (median DFS, 100%), intermediate(median DFS, 78%), and high (median DFS, 55%) rate of recurrence (P ΒΌ .008). There was a good correlation with the histological grading system. CONCLUSIONS: In liquid-based preparations, distinctive cytological features of pulmonary adenocarcinoma correlate with levels of histological differentiation and can be combined into a score with prognostic significance.

publication date

  • February 25, 2012

Research

keywords

  • Adenocarcinoma
  • Cytodiagnosis
  • Lung Neoplasms
  • Neoplasm Grading

Identity

Scopus Document Identifier

  • 84859791404

Digital Object Identifier (DOI)

  • 10.1002/cncy.20185

PubMed ID

  • 22083932

Additional Document Info

volume

  • 120

issue

  • 1