Journal of Medical Screening > Volume 15, Number 2 > Pp. 83-90

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Original Articles

Estimating mean sojourn time and screening sensitivity using questionnaire data on time since previous screening

Harald Weedon-Fekjær, Statistician  , Department of Etiological Cancer Research, Cancer Registry of Norway, Norway and PhD student Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Norway

Bo H Lindqvist, Professor , Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, Norway

Lars J Vatten, MD Professor , Department of Community Medicine and General Practice, Norwegian University of Science and Technology, Trondheim, Norway

Odd O Aalen, Professor , Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Norway

Steinar Tretli, Research Director , Cancer Registry of Norway, Norway and professor Department of Community Medicine and General Practice, Norwegian University of Science and Technology, Trondheim, Norway

Correspondence to: Harald Weedon-Fekjær, Kreftregisteret, Institute of Population-based Cancer Research, Montebello, N-0310 Oslo, Norway; harald.weedon-fekjaer{at}kreftregisteret.no

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Objectives Mean sojourn time (MST) and screening test sensitivity (STS), is usually estimated by Markov models using incidence data from the first screening round and the interval between screening examinations. However, several screening programmes do not have full registration of cancers submerging after screening, and increased use of opportunistic screening over time can raise questions regarding the quality of interval cancer registration.

Methods/settings Based on the earlier used Markov model, formulas for expected number of cases given time since former screening activity was developed. Using questionnaire data for 336,533 women in the Norwegian Breast Cancer Screening Programme (NBCSP), mean square regression estimates of MST and STS were calculated.

Results In contrast to the previously used method, the new approach gave satisfactory model fit. MST was estimated to 5.6 years for women aged 50–59 years, and 6.9 years for women aged 60–69 years, and STS was estimated to 55% and 60%, respectively. Attempts to add separate parameters for breast cancer incidence without screening, or previous STS, resulted in wide confidence intervals if estimated separately, and non-identifiably if combined.

Conclusion Previously published results of long MST and low screen test sensitivity were confirmed with the new approach. Questionnaire data on time since previous screening can be used to estimate MST and STS, but the approach is sensitive to relaxing the assumptions regarding the expected breast cancer incidence without screening and constant STS over time.

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