The screening illustrator: Separating the effects of lead-time and overdiagnosis in mammography screening

Abstract

Background: Mammography screening increases incidence because cancers are detected earlier in time and because of overdiagnosis. We developed an Excel-based model to visualize the expected increase from lead-time amplified by increasing background incidence. Subsequently, we added overdiagnosis to the model. Methods: We constructed two hypothetical populations of women aged 50–79 in 5-year age and calendar groups: one with screening for women aged 50–69 and one without. The user enters information on population at risk, number of breast cancers, trends in background incidence, average length of lead-time and, optionally, overdiagnosis. The model computes incidence rate ratios (IRRs) comparing incidence changes with screening to changes without in open and closed cohorts. Results: We entered information from Norway from 1990 to 1994, the period preceding the gradual introduction of a national mammography screening programme. As expected, the Screening Illustrator showed prevalence peaks and compensatory drops. Only the closed cohort approach remained unaffected by increasing background incidence. The model showed a 20% sustained increase in incidence (IRR: 1.20) from lead-time and increasing background incidence in the open cohort approach for women aged 50–69. However, real life Norwegian data show a corresponding 38% increase. For the model to achieve the observed incidence, 10–14% overdiagnosis had to be added. Conclusion: The observed breast cancer incidence increase in Norway after screening implementation could not be obtained from an average lead-time of 2.5 years and empirical background incidence trends, but had to incorporate overdiagnosis.