1 Laboratory of Molecular Diagnosis of Cancer & Breast Medical Oncology, Clinical Research Center for Breast, West China Hospital, Sichuan University, Chengdu, China.
2 Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, China.
Int J Biol Markers. 2019 Mar;34(1):41-46. doi: 10.1177/1724600818824786. Epub 2019 Mar 11.
A nomogram is a reliable tool to generate individualized risk prediction by combining prognostic factors. We aimed to construct a nomogram for predicting the survival in patients with non-metastatic human epidermal growth factor receptor 2 (HER2) positive breast cancer in a prospective cohort.
We analyzed 1304 consecutive patients who were diagnosed with non-metastatic HER2 positive breast cancer between January 2008 and December 2016 in our institution. Independent prognostic factors were identified to build a nomogram using the COX proportional hazard regression model. The prediction of the nomogram was evaluated by concordance index (C-index), calibration and subgroup analysis. External validation was performed in a cohort of 6379 patients from the Surveillance, Epidemiology, and End Results (SEER) database.
Through the COX proportional hazard regression model, five independent prognostic factors were identified. The nomogram predicting overall survival achieved a C-index of 0.78 in the training cohort and 0.74 in the SEER cohort. The calibration plot displayed favorable accordance between the nomogram prediction and the actual observation for 3-year overall survival in both cohorts. The quartiles of the nomogram score classified patients into subgroups with distinct overall survival.
We developed and validated a novel nomogram for predicting overall survival in patients with non-metastatic HER2 positive breast cancer, which presented a favorable discrimination ability. This model may assist clinical decision making and patient-clinician communication in clinical practice.
列线图是一种通过结合预后因素来生成个体化风险预测的可靠工具。我们旨在构建一个列线图，用于预测非转移性人表皮生长因子受体 2（HER2）阳性乳腺癌患者的生存情况。
我们分析了 2008 年 1 月至 2016 年 12 月在我院诊断为非转移性 HER2 阳性乳腺癌的 1304 例连续患者。使用 COX 比例风险回归模型确定独立预后因素，以构建列线图。通过一致性指数（C-index）、校准和亚组分析评估列线图的预测能力。在来自监测、流行病学和最终结果（SEER）数据库的 6379 例患者的队列中进行外部验证。
通过 COX 比例风险回归模型，确定了五个独立的预后因素。预测总生存的列线图在训练队列中的 C-index 为 0.78，在 SEER 队列中的 C-index 为 0.74。校准图显示在两个队列中，3 年总生存率的列线图预测与实际观察之间存在良好的一致性。列线图评分的四分位数将患者分为具有不同总生存率的亚组。
我们开发并验证了一个用于预测非转移性 HER2 阳性乳腺癌患者总生存的新列线图，该列线图具有良好的区分能力。该模型可能有助于临床决策和患者-医生沟通。
