Impact of Risk Factors on Different Interval Cancer Subtypes in a Population-Based Breast Cancer Screening Programme

Interval cancers are primary breast cancers diagnosed in women after a negative screening test and before the next screening invitation. Our aim was to evaluate risk factors for interval cancer and their subtypes and to compare the risk factors identified with those associated with incident screen-detected cancers. We analyzed data from 645,764 women participating in the Spanish breast cancer screening program from 2000-2006 and followed-up until 2009. A total of 5,309 screen-detected and 1,653 interval cancers were diagnosed. Among the latter, 1,012 could be classified on the basis of findings in screening and diagnostic mammograms, consisting of 489 true interval cancers (48.2%), 235 false-negatives (23.2%), 172 minimal-signs (17.2%) and 114 occult tumors (11.3%). Information on the screening protocol and women's characteristics were obtained from the screening program registry. Cause-specific Cox regression models were used to estimate the hazard ratios (HR) of risks factors for interval cancer and incident screen-detected cancer. A multinomial regression model, using screen-detected tumors as a reference group, was used to assess the effect of breast density and other factors on the occurrence of interval cancer subtypes. A previous false-positive was the main risk factor for interval cancer (HR = 2.71, 95%CI: 2.28-3.23); this risk was higher for false-negatives (HR = 8.79, 95%CI: 6.24-12.40) than for true interval cancer (HR = 2.26, 95%CI: 1.59-3.21). A family history of breast cancer was associated with true intervals (HR = 2.11, 95%CI: 1.60-2.78), previous benign biopsy with a false-negatives (HR = 1.83, 95%CI: 1.23-2.71). High breast density was mainly associated with occult tumors (RRR = 4.92, 95%CI: 2.58-9.38), followed by true intervals (RRR = 1.67, 95%CI: 1.18-2.36) and false-negatives (RRR = 1.58, 95%CI: 1.00-2.49). The role of women's characteristics differs among interval cancer subtypes. This information could be useful to improve effectiveness of breast cancer screening programmes and to better classify subgroups of women with different risks of developing cancer.