Estimating the growth rates of primary lung tumours from samples with missing measurements. Academic Article uri icon

Overview

abstract

  • A method to estimate the population variability in tumour growth rate using incomplete data was developed. We assume exponential growth and lognormal distribution for the parameter of the growth curve. Estimates of growth rate obtained based on the cases with two measurements, one of which is obtained retrospectively, are biased towards lower growth rate. For the data sets where two measurements are available for some tumours and only one measurement for others (which means that no tumour was seen in retrospect for those cases), several approaches were developed that can eliminate or substantially reduce the bias. The relative error of the best estimates, as assessed by simulation, rarely exceeds 20 per cent. We found that the results of application of our estimation procedures to chest X-ray screening data agree well with the expectations.

publication date

  • April 15, 2005

Research

keywords

  • Data Interpretation, Statistical
  • Lung Neoplasms
  • Models, Biological

Identity

Scopus Document Identifier

  • 15844403823

Digital Object Identifier (DOI)

  • 10.1002/sim.1987

PubMed ID

  • 15568189

Additional Document Info

volume

  • 24

issue

  • 7