Evaluating serial observations of precancerous lesions for further study as a trigger for early intervention.
Many long-term studies of the early detection of cancer involve serial observations of precancerous lesions and information as to whether or not the subject was diagnosed with cancer during the study period. Often the purpose of these studies is to decide whether or not the precancerous lesion should be studied in a future trial as a trigger for early intervention. A general approach to the analysis of cancer biomarkers is to estimate false and true positive rates to determine if they fall in the target region of those false and true positives that indicate promise for further study. The challenge with analysing serial data on precancerous lesions is estimating false and true positive rates when the number of observations varies among subjects. To solve this problem, we propose a Markov chain model in reverse time. The methodology is illustrated using serial observations of precancerous lesions found on sputum cytology.
Baker
Stuart G
SG
Biometry Research Group, Division of Cancer Prevention, National Cancer Institute, EPN 3131, 6130 Executive Blvd MSC 7354, Bethesda, MD 20892-7354, USA. sb16i@nih.gov
Tockman
Melvyn S
MS
D005188:False Negative Reactions; D005189:False Positive Reactions; D006801:Humans; D008137:Longitudinal Studies; D008175:Lung Neoplasms / Q000175:diagnosis / Q000473:pathology*; D008297:Male; D008390:Markov Chains; D011230:Precancerous Conditions / Q000175:diagnosis / Q000473:pathology*; D013183:Sputum / Q000166:cytology