Overestimated lead times in cancer screening has led to substantial underestimation of overdiagnosis

Abstract

Background:Published lead time estimates in breast cancer screening vary from 1 to 7 years and the percentages of overdiagnosis vary from 0 to 75%. The differences are usually explained as random variations. We study how much can be explained by using different definitions and methods.Methods:We estimated the clinically relevant lead time based on the observed incidence reduction after attending the last screening round in the Norwegian mammography screening programme. We compared this estimate with estimates based on models that do not take overdiagnosis into account (model-based lead times), for varying levels of overdiagnosis. Finally, we calculated overdiagnosis adjusted for clinical and model-based lead times and compared results.Results:Clinical lead time was about one year based on the reduction in incidence in women previously offered screening. When overdiagnosed tumours were included, the estimates increased to 4–9 years, depending on the age at which screening begins and the level of overdiagnosis. Including all breast cancers detected in women long after the end of the screening programme dilutes the level of overdiagnosis by a factor of 2–3.Conclusion:When overdiagnosis is not taken into account, lead time is substantially overestimated. Overdiagnosis adjusted for model-based lead time is a function tending to zero, with no simple interpretation. Furthermore, the estimates are not in general comparable, because they depend on both the duration of screening and duration of follow-up. In contrast, overdiagnosis adjusted for clinically relevant tumours is a point estimate (and interpreted as percentage), which we find is the most reasonable method.

Lead-Time Models Should Not Be Used to Estimate Overdiagnosis in Cancer Screening

“…2 There are two different leadtime approaches. The classical lead-time adjustment method includes all cancers diagnosed in a long time period after screening has stopped (10-15 years) in both the screening and the control group when comparing cumulative hazard rates.…”

“…7 This ratio is initially equal to the excess-incidence estimate, but rapidly approaches zero difference between the two groups with increasing follow-up. 2 Another leadtime approach is using a multistage statistical model where all tumors are assumed to grow (but with different speed), which estimates overdiagnosis as the fraction of tumors detected at screening that would never become clinical during the lifetime of the patient. This approach is highly model dependent; for example, three different lead-time models gave overdiagnosis estimates ranging from 23 % to 42 % using the same Dutch data set.…”

“…This approach is highly model dependent; for example, three different lead-time models gave overdiagnosis estimates ranging from 23 % to 42 % using the same Dutch data set. 2 The MISCAN model represents such an approach, and the assumptions in this model are multiple and not transparent. 1,2 The lead time models always give lower overdiagnosis estimates than the excess-incidence approach if screening detects dormant tumors or tumors that regress spontaneously.…”

“…We have recently published a comparison of the two approaches. 2 We concluded that the excess-incidence approach is preferable. The lead-time approach seriously underestimates overdiagnosis because of flawed assumptions about how much screening advances the time of diagnosis.…”

“…The lead-time approach seriously underestimates overdiagnosis because of flawed assumptions about how much screening advances the time of diagnosis. 2 It is generally accepted that prostate specific antigen (PSA) screening for prostate cancer leads to about 50 % overdiagnosis, which means that one in three prostate cancers in a population offered screening are overdiagnosed. This estimate is based on the excessincidence approach applied to the randomized trials.…”