Department of Epidemiology and Evaluation, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
Research Network on Health Services in Chronic Diseases (REDISSEC), Spain.
Cancer Epidemiol Biomarkers Prev. 2018 Aug;27(8):908-916. doi: 10.1158/1055-9965.EPI-17-0995. Epub 2018 May 31.
We aimed to evaluate survival and disease-free survival in different subtypes of interval cancers by breast density, taking into account clinical and biological characteristics. We included 374 invasive breast tumors (195 screen-detected cancers; 179 interval cancers, classified into true interval, false-negatives, occult tumors and minimal-sign cancers) diagnosed in women ages 50-69 years undergoing biennial screening from 2000-2009, followed up to 2014. Breast density was categorized into non-dense (<25% dense tissue) and mixed dense breasts (≥25%). Survival curves were generated by the Kaplan-Meier method and compared by the log-rank test. Cox proportional hazard regression models were computed to estimate the adjusted hazard ratios (aHRs) and 95% confidence intervals (95% CIs) for death and recurrences by comparing women with interval and true interval cancers versus women with screen-detected cancers, controlling for tumor and patient characteristics. All analyses were stratified by breast density. Interval cancers were detected in younger women, at more advanced stages, in denser breasts and showed a higher proportion of triple-negative cancers, especially among true interval cancers. Women with interval cancer and non-dense breasts had an aHR for death of 3.40 (95% CI, 0.92-12.62). Women with true interval cancers detected in non-dense breasts had the highest adjusted risk of death (aHR, 6.55; 95% CI, 1.37-31.39). Women with true interval cancer in non-dense breasts had a higher risk of death than women with screen-detected cancers. These results support the advisability of routinely collecting information on breast density, both for further tailoring of screening strategies and as a prognostic factor for diagnosed breast cancers. .
我们旨在评估不同乳腺密度亚组中间隔期乳腺癌的生存和无病生存情况,并考虑到临床和生物学特征。我们纳入了 374 例 50-69 岁接受每两年一次筛查的女性的浸润性乳腺癌肿瘤(195 例筛查检出癌症;179 例间隔期癌症,分为真性间隔期癌症、假阴性、隐匿性肿瘤和微小原位癌),这些患者的诊断时间为 2000-2009 年,随访至 2014 年。乳腺密度分为非致密(<25%致密组织)和混合致密乳腺(≥25%)。生存曲线采用 Kaplan-Meier 法生成,并通过对数秩检验进行比较。Cox 比例风险回归模型用于估计死亡和复发的调整后危险比(aHR)和 95%置信区间(95%CI),比较间隔期和真性间隔期癌症患者与筛查检出癌症患者,控制肿瘤和患者特征。所有分析均按乳腺密度分层。间隔期癌症患者更年轻、分期更晚、乳腺密度更高,且三阴性癌症比例更高,尤其是真性间隔期癌症。间隔期癌症患者且乳腺非致密患者的死亡 aHR 为 3.40(95%CI,0.92-12.62)。乳腺非致密的真性间隔期癌症患者的死亡调整风险最高(aHR,6.55;95%CI,1.37-31.39)。乳腺非致密的真性间隔期癌症患者的死亡风险高于筛查检出癌症患者。这些结果支持常规收集乳腺密度信息的建议,不仅可以进一步定制筛查策略,还可以作为诊断乳腺癌的预后因素。