Literature DB >> 8625182

Objective malignancy grading of squamous cell carcinoma of the lung. Stereologic estimates of mean nuclear size are of prognostic value, independent of clinical stage of disease.

M Ladekarl1, T Bæk-Hansen, R Henrik-Nielsen, C Mouritzen, U Henriques, F B Sørensen.   

Abstract

BACKGROUND: The prognostic value of quantitative histopathologic parameters was evaluated in 55 consecutively treated patients with operable lung carcinoma of squamous (N = 39) and mixed, adenosquamous (N = 16) cell type. Patients alive were followed for at least 12 years.
METHODS: Using a projection microscope and a simple test system in fields of vision systematically selected from the whole tumor area of one routine section, five quantitative histopathologic variables were estimated: the mean nuclear volume, the mean nuclear profile area, the density of nuclear profiles, the volume fraction of nuclei to tissue, and the number of mitotic profiles per 10(3) nuclear profiles. For each patient, information was recorded regarding sex, age at diagnosis, and clinical stage of disease.
RESULTS: Single-factor analyses showed that a favorable prognosis was associated with early clinical stages (Stages I and II) and young age (P < or = 0.03), and that females tended to do better than males (P = 0.09). Estimates of the mean nuclear volume were of prognostic significance (P = 0.02), small nuclei being associated with the worst prognosis. In a multivariate Cox analysis, clinical stage, age, and mean nuclear volume were found to be parameters of significant, independent prognostic value.
CONCLUSIONS: The present feasibility study indicates that estimates of the mean nuclear volume are of prognostic value, independent of the clinical stage of disease. This quantitative histopathologic variable is highly reproducible and easily obtained using an unbiased stereologic method. Thus, the mean nuclear volume may be a parameter of future importance in the clinical management of patients with carcinoma of the lung.

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Year:  1995        PMID: 8625182     DOI: 10.1002/1097-0142(19950901)76:5<797::aid-cncr2820760513>3.0.co;2-m

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  2 in total

1.  Histology image analysis for carcinoma detection and grading.

Authors:  Lei He; L Rodney Long; Sameer Antani; George R Thoma
Journal:  Comput Methods Programs Biomed       Date:  2012-03-20       Impact factor: 5.428

2.  Chemical Interrogation of Nuclear Size Identifies Compounds with Cancer Cell Line-Specific Effects on Migration and Invasion.

Authors:  Sylvain Tollis; Andrea Rizzotto; Nhan T Pham; Sonja Koivukoski; Aishwarya Sivakumar; Steven Shave; Jan Wildenhain; Nikolaj Zuleger; Jeremy T Keys; Jayne Culley; Yijing Zheng; Jan Lammerding; Neil O Carragher; Valerie G Brunton; Leena Latonen; Manfred Auer; Mike Tyers; Eric C Schirmer
Journal:  ACS Chem Biol       Date:  2022-02-24       Impact factor: 5.100

  2 in total

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