Estimating screening test sensitivity and tumour progression using tumour size and time since previous screening

Abstract

As mammography screening aims to improve the prognosis through earlier detection/treatment, tumour progression and screening test sensitivity (STS) represent key parameters in the evaluation of screening programs. We will here study some methods for estimation of tumour progression and STS, and show how previously used methods can be combined and developed to utilise more of the data available in modern screening programs. Weedon-Fekjaer et al. recently suggested a study design using interview data about time since previous screening to estimate tumour progression and STS in a stepwise Markov model. While useful, the approach does not utilise tumour size measurements, nor link tumour progression to tumour size. Hence, we will here propose formulas for estimating tumour progression and STS using a continuous tumour growth model. To estimate tumour progression and STS, tumour growth curves are followed from one screening to the next, and probabilities for all combinations of tumour sizes at repeated screening examinations calculated. Based on the probabilities for screening detection on subsequent screening examinations, maximum likelihood estimates are calculated. Applied to Norwegian data, the new approach gives similar results to previously published results based on interval data, confirming the earlier estimated large variation in tumour growth rates.