Department of Oncology & Department of Breast Surgery, The Second Hospital of Dalian Medical University, Dalian, China.
Medicine (Baltimore). 2021 Nov 19;100(46):e27595. doi: 10.1097/MD.0000000000027595.
The main purpose of this study was to build a prediction model for patients with contralateral breast cancer (CBC) using competing risks methodology. The aim is to help clinicians predict the probability of CBC in breast cancer (BC) survivors.We reviewed data from the Surveillance, Epidemiology, and End Results database of 434,065 patients with BC. Eligible patients were used to quantify the association between the development of CBC and multiple characteristics of BC patients using competing risk models. A nomogram was also created to facilitate clinical visualization and analysis. Finally, the stability of the model was verified using concordance index and calibration plots, and decision curve analysis was used to evaluate the clinical utility of the model by calculating the net benefit.Four hundred thirty-four thousand sixty-five patients were identified, of whom 6944 (1.6%) developed CBC in the 10 years follow-up. The 10-year cumulative risk of developing CBC was 2.69%. According to a multivariate competing risk model, older patients with invasive lobular carcinoma who had undergone unilateral BC surgery, and whose tumor was better differentiated, of smaller size and ER-negative/PR-positive, had a higher risk of CBC. The calibration plots illustrated an acceptable correlation between the prediction by nomogram and actual observation, as the calibration curve was closed to the 45° diagonal line. The concordance index for the nomogram was 0.65, which indicated it was well calibrated for individual risk of CBC. Decision curve analysis produced a wide range of risk thresholds under which the model we built would yield a net benefit.BC survivors remain at high risk of developing CBC. Patients with CBC have a worse clinical prognosis compared to those with unilateral BC. We built a predictive model for the risk of developing CBC based on a large data cohort to help clinicians identify patients at high risk, which can then help them plan individualized surveillance and treatment.
本研究的主要目的是使用竞争风险方法为患有对侧乳腺癌（CBC）的患者建立预测模型。其目的是帮助临床医生预测乳腺癌（BC）幸存者中 CBC 的概率。
我们回顾了来自 Surveillance, Epidemiology, and End Results 数据库的 434,065 例 BC 患者的数据。使用竞争风险模型来量化 CBC 发展与 BC 患者多种特征之间的关联，以此确定合格患者。还创建了一个列线图以方便临床可视化和分析。最后，通过一致性指数和校准图验证模型的稳定性，并通过计算净效益来评估模型的临床实用性，通过决策曲线分析。
共确定了 434,065 例患者，其中 6944 例（1.6%）在 10 年随访中发生 CBC。10 年发生 CBC 的累积风险为 2.69%。根据多变量竞争风险模型，年龄较大的浸润性小叶癌患者，接受单侧 BC 手术后，肿瘤分化程度更好，肿瘤体积更小，ER 阴性/PR 阳性，发生 CBC 的风险更高。列线图的校准图表明了预测与实际观察之间的可接受相关性，因为校准曲线接近 45°对角线。列线图的一致性指数为 0.65，表明它对 CBC 的个体风险校准良好。决策曲线分析在风险阈值范围内产生了广泛的变化，在该范围内，我们构建的模型会产生净收益。
BC 幸存者仍然存在发生 CBC 的高风险。与单侧 BC 患者相比，患有 CBC 的患者的临床预后更差。我们基于大型数据队列为 CBC 发展风险建立了预测模型，以帮助临床医生识别高危患者，从而帮助他们制定个性化的监测和治疗计划。
