National Cancer Registry Ireland, Cork, T12 CDF7, Ireland.
Department of Mathematics, Cork Institute of Technology, Cork, T12 P928, Ireland.
Breast Cancer Res Treat. 2018 Nov;172(1):133-142. doi: 10.1007/s10549-018-4877-9. Epub 2018 Jul 13.
We examined whether demographic and tumour characteristics (including subtype) were different for women with breast cancer diagnosed via mammography screening compared with women with interval breast cancers, lapsed attenders of the screening programme and non-participants of the screening programme. In addition, we explored whether there were survival differences between the groups, taking into account lead time bias.
We used linked data from National Cancer Registry Ireland and the national breast screening programme BreastCheck. Multinomial logistic regression was used to test the association of covariates with screening status. For survival analysis, we corrected the survival time for screen-detected cases for lead time bias, examined Kaplan-Meier curves and then used Cox regression to investigate differences in survival by screening status.
Subtype (HER2 over-expressing, triple negative), stage (III/IV), grade (poor), having co-morbidities, area of deprivation, smoking status and age were associated with having interval cancer or being a non-participant of the screening programme in the multivariable model. After correcting for lead time bias, and adjusting for variables associated with screening status, there was no evidence that risk of breast-cancer death for women with screen-detected cancer was different from women with interval cancer (HR = 0.76, 95% CI 0.56-1.03), non-participants (HR = 1.07, 95% CI 0.84-1.37) and lapsed attenders (HR = 0.97, 95% CI 0.65-1.45).
Screening status was strongly associated with subtype and this association persisted after adjustment for covariates including tumour stage and grade. After correcting for lead-time bias and adjusting for stage, subtype, grade and socio-demographic variables, no significant survival difference was demonstrated for women with screen-detected cancer in the 5-year period post-diagnosis. Since we are adjusting for stage, subtype and other variables, the lack of difference between these groups would be expected but has not been demonstrated in studies which do not correct for lead time bias.
我们研究了通过乳房 X 光筛查诊断的乳腺癌女性与间隔期乳腺癌女性、筛查项目漏检者和筛查项目非参与者在人口统计学和肿瘤特征(包括亚型)方面是否存在差异。此外,我们还探讨了在考虑到领先时间偏差的情况下,这些组之间是否存在生存差异。
我们使用了爱尔兰国家癌症登记处和国家乳房筛查计划 BreastCheck 的链接数据。使用多项逻辑回归来检验协变量与筛查状态的关联。对于生存分析,我们对筛查发现的病例的生存时间进行了领先时间偏差的校正,检查了 Kaplan-Meier 曲线,然后使用 Cox 回归来研究筛查状态对生存的影响。
在多变量模型中,亚型(HER2 过表达、三阴性)、分期(III/IV 期)、分级(差)、合并症、贫困地区、吸烟状况和年龄与间隔期癌症或不参与筛查计划有关。在纠正了领先时间偏差,并调整了与筛查状态相关的变量后,没有证据表明筛查发现的癌症女性的乳腺癌死亡风险与间隔期癌症女性(HR=0.76,95%CI 0.56-1.03)、不参与者(HR=1.07,95%CI 0.84-1.37)和漏检者(HR=0.97,95%CI 0.65-1.45)不同。
筛查状态与亚型密切相关,这种关联在调整包括肿瘤分期和分级在内的协变量后仍然存在。在纠正领先时间偏差并调整分期、亚型、分级和社会人口统计学变量后,在诊断后 5 年内,筛查发现的癌症女性的生存差异无统计学意义。由于我们正在调整分期、亚型和其他变量,因此这些组之间的差异预计不会存在,但在没有纠正领先时间偏差的研究中尚未得到证实。