Nuclear grading of primary pulmonary adenocarcinomas: correlation between nuclear size and prognosis

Cancer. 2010 Apr 15;116(8):2011-9. doi: 10.1002/cncr.24948.

Abstract

Background: According to the World Health Organization Classification of Tumors, the prognostic value of morphometric cytologic atypia has not been assessed in pulmonary adenocarcinoma.

Methods: Primary tumors of 133 pulmonary adenocarcinomas <or=2 cm were analyzed using an image processor for analytical pathology. The results were evaluated using receiver operator characteristic curve analysis, and survival curves were drawn by the Kaplan-Meier method. Furthermore, the results were applied to routine histological diagnosis. Four pathologists evaluated the nuclear factors relative to the size of small lymphocytes as a standard.

Results: By using the nuclear area and nuclear major axis dimension, lung adenocarcinomas were divisible into 2 groups showing extremely favorable prognosis and fairly favorable prognosis, without considering histological features or classification. A nuclear area level of <67 microm(2) was correlated with longer survival (P < .0001), and the 5-year survival rate was 90.4%. Similarly, a nuclear diameter level of <0.7 microm was correlated with longer survival (P = .0002), and the 5-year survival rate was 88.6%. The mean (+/-standard deviation [SD]) value of the kappa statistic for the 4 pathologists who evaluated the cases using the size of small lymphocytes as a standard was 0.58 +/- 0.10, and the mean (+/-SD) value of the accuracy metric was 0.66 +/- 0.10.

Conclusions: Nuclear area and nuclear major dimension are 2 useful independent markers for evaluating the prognosis of lung adenocarcinoma.

Publication types

  • Evaluation Study

MeSH terms

  • Adenocarcinoma / mortality
  • Adenocarcinoma / pathology*
  • Adult
  • Aged
  • Aged, 80 and over
  • Cell Nucleus / pathology*
  • Female
  • Humans
  • Karyometry / methods
  • Lung Neoplasms / mortality
  • Lung Neoplasms / pathology*
  • Male
  • Middle Aged
  • Observer Variation
  • Prognosis
  • Sensitivity and Specificity