PMID: 9436967Jan 22, 1998Paper

Neural networks as a prognostic tool for patients with non-small cell carcinoma of the lung

Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc
M BellottiA M Marchevsky

Abstract

Patients with non-small cell carcinoma of the lung (NSCLC) have a poor prognosis (64 and 41% survival rates in Stages I and II). It is currently not possible to predict which patients with Stage I or II NSCLC will survive the disease. Sixty-seven patients with NSCLC, including 49 patients with Stage I NSCLC and 18 with Stage II disease (11 with squamous cell carcinomas, 35 with adenocarcinomas, and 21 with large cell carcinomas) were treated with lobectomy and followed for a minimum of 5 years. The tumors were studied with DNA flow cytometry and quantitative immunocytochemical studies for proliferation cell nuclear antigen, p53 protein, and MIB-1. The data were analyzed with backpropagation neural networks, univariate analysis of variance, the Kaplan-Meier survival method, and Cox proportional hazards model. The dependent variables were "free of disease" and "recurrence or dead from disease." Twenty neural network models were trained, using all cases but one, after 1883 to 2000 training cycles. At 5 years, 30 patients were free of disease and 37 were dead or had recurrence. Proliferating cell nuclear antigen was the only statistically significant prognostic factor by univariate analysis of variance and Cox proportional hazards ...Continue Reading

Related Concepts

Related Feeds

Carcinoma, Squamous Cell

Basal cell carcinoma is a form of malignant skin cancer found on the head and neck regions and has low rates of metastasis. Discover the latest research on basal cell carcinoma here.