Towards evidence-based follow-up intervals for breast cancer survivors: Estimates of the preclinical detectable phase of contralateral second breast cancer

PURPOSE

Follow-up schemes in breast cancer survivors are predominantly consensus-based. To determine evidence-based follow-up intervals, estimates of sensitivity of the screening test(s) and duration of the preclinical detectable phase (PCDP) are key. We estimated the sensitivity and the duration of the PCDP of clinical breast examination (CBE) and mammography for the detection of contralateral second breast cancers (CBC) in breast cancer survivors.

METHODS

Women with a CBC (N = 589) diagnosed in Florence between 1980 and 2005 were included. Test sensitivity and the duration of PCDP were estimated using a simple exponential model of PCDP duration. Analyses were stratified by follow-up period (0-5 vs. >5 years after primary diagnosis) and age at CBC diagnosis (<50 vs. ≥50 years).

RESULTS

For CBE, test sensitivity was 55% and the duration of the PCDP 16 months. Mammography sensitivity was 91% and duration of the PCDP 35 months. Stratified analyses showed a higher test sensitivity for CBE for women aged <50 (70% vs. 51%). No difference in the duration of PCDP of CBE was found. For mammography, test sensitivity and the duration of the PCDP were higher for women with longer follow-up and in older women.

CONCLUSIONS

Poor test sensitivity for CBE with a shorter duration of the PCDP compared with mammography were observed. Mammography had high test sensitivity and the potential to detect CBCs early. The estimated duration of the PCDP (35 months) was considerably longer than the recommended follow-up interval (12 months). Future studies are needed to determine whether a longer follow-up interval is appropriate.

Test sensitivity of mammography and mean sojourn time over 40 years of breast cancer screening in Nijmegen (The Netherlands)

Objectives

We investigated whether changes in mammographic technique and screening policy have improved mammographic sensitivity, and elongated the mean sojourn time, since the introduction of biennial breast cancer screening in Nijmegen, the Netherlands, in 1975.

Methods

Maximum likelihood estimation, non-linear regression, and Markov Chain Monte Carlo simulation were used to estimate test sensitivity, mean sojourn time, and underlying breast cancer incidence in four time periods, covering 40 years of breast cancer screening in Nijmegen (1975–2012).

Results

Maximum likelihood estimation generated an estimated test sensitivity of approximately 90% and a mean sojourn time around three years, while the estimates based on non-linear regression and Markov Chain Monte Carlo simulation were 80% and four years, respectively. All three methods estimated a rise in the underlying breast cancer incidence over time, with approximately one case more per 1000 women per year in the final period compared with the first period.

Conclusions

The three methods showed a slightly higher mammographic sensitivity and a longer mean sojourn time in the last period, after the introduction of digital mammography. Estimates were more realistic for the more sophisticated methods, non-linear regression and Markov Chain Monte Carlo simulation, while the simple closed form approximation of maximum likelihood estimation led to rather high estimates for sensitivity in the early periods.