title: Nonparametric estimation of asymptomatic duration from a randomized prospective cancer screening trial.
abstract: We propose a nonparametric estimation of preclinical duration distribution in cancer based on data from a randomized early detection trial. In cancer screening studies, the preclinical duration of a disease is of great interest for better understanding the natural history of the disease, and for developing optimal screening strategies. To estimate the sojourn time distribution nonparametrically, we first estimate the distribution of the age at onset of preclinical disease nonparametrically using data from the screening arm in a randomized screening trial, and the distribution for the age at onset of clinical disease from the control arm of the randomized screening trial. Finally, by using deconvolution the two estimated distributions lead to a nonparametric estimate of the distribution for the gap time between the onset of preclinical disease and the onset of clinical disease. We illustrate the methodology using data from a randomized breast cancer screening trial.
authors.affiliation: Department of Biostatistics and Applied Mathematics, MD Anderson Cancer Center, University of Texas, Houston, 77030, USA. yshen@mdanderson.org
authors.forename: Yu
authors.initials: Y
authors.lastname: Shen
authors.forename: Xuelin
authors.initials: X
authors.lastname: Huang
mesh_terms: D000328:Adult; D017668:Age of Onset; D001943:Breast Neoplasms / Q000175:diagnosis; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008403:Mass Screening / Q000379:methods*; D008875:Middle Aged; D009010:Monte Carlo Method; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D018709:Statistics, Nonparametric