Division of Oncology and Pathology, Department of Clinical Sciences, Lund University, Skane University Hospital, Barngatan 4, 221 85, Lund, Sweden.
Department of Translational Medicine, Medical Radiation Physics, Lund University, Skane University Hospital, Malmö, Sweden.
Cancer Causes Control. 2021 Mar;32(3):251-260. doi: 10.1007/s10552-020-01379-w. Epub 2020 Dec 30.
Personalized cancer treatment requires predictive biomarkers, including image-based biomarkers. Breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT) are in a clinically vulnerable situation with the tumor present. This study investigated whether mammographic density (MD), assessed pre-NACT, is predictive of pathological complete response (pCR).
A total of 495 BC patients receiving NACT in Sweden 2005-2019 were included, merged from two different cohorts. Cohort 1 was retrospectively collected (n = 295) and cohort 2 was prospectively collected (n = 200). Mammograms were scored for MD pre-NACT according to the Breast Imaging-Reporting and Data System (BI-RADS), 5th Edition. The association between MD and accomplishing pCR post-NACT was analyzed using logistic regression models-for the whole cohort, stratified by menopausal status, and in different St. Gallen surrogate subtypes.
In comparison to patients with low MD (BI-RADS a), the multivariable-adjusted odds ratio (OR) of accomplishing pCR following NACT was on a descending scale: 0.62 (95% confidence interval (CI) 0.24-1.57), 0.38 (95% CI 0.14-1.02), and 0.32 (95% CI 0.09-1.08) for BI-RADS b, c, and d, respectively. For premenopausal patients selectively, the corresponding point estimates were lower, although wider CIs: 0.31 (95% CI 0.06-1.62), 0.24 (95% CI 0.04-1.27), and 0.13 (95% CI 0.02-0.88). Subgroup analyses based on BC subtypes resulted in imprecise estimates, i.e., wide CIs.
It seemed as though patients with higher MD at baseline were less likely to reach pCR after NACT-a finding more pronounced in premenopausal women. Larger multicenter studies are needed to enable analyses and interpretation for different BC subtypes.
个性化癌症治疗需要预测性生物标志物,包括基于图像的生物标志物。接受新辅助化疗(NACT)的乳腺癌(BC)患者在肿瘤存在的情况下处于临床脆弱状态。本研究调查了新辅助化疗前评估的乳腺密度(MD)是否可预测病理完全缓解(pCR)。
本研究共纳入了 2005 年至 2019 年在瑞典接受 NACT 的 495 例 BC 患者,这些患者来自两个不同的队列。队列 1 是回顾性收集的(n=295),队列 2 是前瞻性收集的(n=200)。在新辅助化疗前,根据乳腺影像报告和数据系统(BI-RADS)第 5 版对乳腺 X 线照片进行 MD 评分。使用逻辑回归模型分析 MD 与新辅助化疗后 pCR 之间的关系,分析对象为整个队列、按绝经状态分层以及不同圣加仑替代亚型。
与 MD 较低的患者(BI-RADS a)相比,新辅助化疗后实现 pCR 的多变量调整比值比(OR)呈下降趋势:分别为 0.62(95%置信区间(CI)为 0.24-1.57)、0.38(95%CI 为 0.14-1.02)和 0.32(95%CI 为 0.09-1.08),分别对应 BI-RADS b、c 和 d。对于选择性的绝经前患者,虽然置信区间(CI)较宽,但相应的点估计值较低:0.31(95%CI 为 0.06-1.62)、0.24(95%CI 为 0.04-1.27)和 0.13(95%CI 为 0.02-0.88)。基于 BC 亚型的亚组分析得出的估计值不够精确,即 CI 较宽。
似乎基线时 MD 较高的患者在接受 NACT 后达到 pCR 的可能性较低,这一发现在前绝经妇女中更为明显。需要更大规模的多中心研究来对不同的 BC 亚型进行分析和解释。