Estimating the growth rates of primary lung tumours from samples with missing measurements.

TitleEstimating the growth rates of primary lung tumours from samples with missing measurements.
Publication TypeJournal Article
Year of Publication2005
AuthorsGorlova O, Peng B, Yankelevitz D, Henschke C, Kimmel M
JournalStat Med
Volume24
Issue7
Pagination1117-34
Date Published2005 Apr 15
ISSN0277-6715
KeywordsCell Growth Processes, Computer Simulation, Data Interpretation, Statistical, Humans, Likelihood Functions, Lung Neoplasms, Models, Biological, Radiography, Thoracic, Tomography, X-Ray Computed
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.

DOI10.1002/sim.1987
Alternate JournalStat Med
PubMed ID15568189
Grant ListCAU01-97431 / CA / NCI NIH HHS / United States
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