Estimating the growth rates of primary lung tumours from samples with missing measurements.
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.
Gorlova
Olga
O
Department of Epidemiology, University of Texas M. D. Anderson Cancer Center, Houston, TX 77030, USA. oygorlova@mdanderson.org
Peng
Bo
B
Yankelevitz
David
D
Henschke
Claudia
C
Kimmel
Marek
M
D048708:Cell Growth Processes / Q000502:physiology; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D016013:Likelihood Functions; D008175:Lung Neoplasms / Q000473:pathology*; D008954:Models, Biological; D013902:Radiography, Thoracic; D014057:Tomography, X-Ray Computed