Department of Surgery, Seoul National University College of Medicine, Laboratory of Breast Cancer Biology, Cancer Research Institute, Seoul National University College of Medicine, Seoul.
Center for Breast Cancer, National Cancer Center, Goyang.
Ann Oncol. 2016 May;27(5):828-33. doi: 10.1093/annonc/mdw036. Epub 2016 Jan 28.
We aimed to develop a prediction model to identify long-term survivors after developing distant metastasis from breast cancer.
From the institution's database, we collected data of 547 patients who developed distant metastasis during their follow-ups. We developed a model that predicts the post-metastasis overall survival (PMOS) based on the clinicopathologic factors of the primary tumors and the characteristics of the distant metastasis. For validation, the survival data of 254 patients from four independent institutions were used.
The median duration of the PMOS was 31.0 months. The characteristics of the initial primary tumor, such as tumor stage, hormone receptor status, and Ki-67 expression level, and the characteristics of the distant metastasis presentation including the duration of disease-free interval, the site of metastasis, and the presence of metastasis-related symptoms were independent prognostic factors determining the PMOS. The association between tumor stage and the PMOS was only seen in tumors with early relapses. The PMOS score, which was developed based on the above six factors, successfully identified patients with superior survival after metastasis. The median PMOS for patients with a PMOS score of <2 and for patients with a PMOS score of >5 were 71.0 and 12 months, respectively. The clinical significance of the PMOS score was further validated using independent multicenter datasets.
We have developed a novel prediction model that can classify breast cancer patients with distant metastasis according to their survival after metastasis. Our model can be a valuable tool to identify long-term survivors who can be potential candidates for more intensive multidisciplinary approaches. Furthermore, our model can provide a more reliable survival information for both physicians and patients during their informed decision-making process.
我们旨在开发一种预测模型,以识别发生远处转移后长期生存的乳腺癌患者。
我们从机构数据库中收集了 547 例在随访期间发生远处转移的患者数据。我们基于原发肿瘤的临床病理特征和远处转移的特征,开发了一种预测转移后总生存期(PMOS)的模型。为了验证,我们使用了来自四个独立机构的 254 例患者的生存数据。
PMOS 的中位持续时间为 31.0 个月。初始原发肿瘤的特征,如肿瘤分期、激素受体状态和 Ki-67 表达水平,以及远处转移表现的特征,包括无病间隔时间、转移部位和转移相关症状的存在,都是决定 PMOS 的独立预后因素。肿瘤分期与 PMOS 之间的关联仅见于早期复发的肿瘤中。PMOS 评分是基于上述六个因素开发的,它成功地识别出转移后生存较好的患者。PMOS 评分<2 和>5 的患者的中位 PMOS 分别为 71.0 和 12 个月。使用独立的多中心数据集进一步验证了 PMOS 评分的临床意义。
我们开发了一种新的预测模型,可以根据转移后患者的生存情况对发生远处转移的乳腺癌患者进行分类。我们的模型可以作为一种有价值的工具,识别出长期生存的患者,这些患者可能是更强化的多学科治疗的潜在候选者。此外,我们的模型可以在医生和患者进行知情决策过程中为他们提供更可靠的生存信息。