Ye Pingping, Duan Hongbo, Zhao Zhenya, Fang Shibo
Department of Ultrasonography, The Sixth Hospital of Ningbo City of Zhejiang Province, Ningbo, 315100, People's Republic of China.
Department of Imaging, The First Hospital of Ningbo City of Zhejiang Province, Ningbo, 315010, People's Republic of China.
Cancer Manag Res. 2021 Oct 9;13:7783-7793. doi: 10.2147/CMAR.S331384. eCollection 2021.
Clinical responses of neoadjuvant chemotherapy (NACT) are associated with prognosis in patients with breast cancer. The selection of suitable variables for the prediction of clinical responses remains controversial. Herein, we developed a predictive model based on ultrasound imaging and clinical indices to identify patients most likely to benefit from NACT.
We recruited a total of 225 consecutive patients who underwent NACT followed by surgery and axillary lymph node dissection at the Sixth Hospital of Ning Bo City of Zhe Jiang Province between January 1, 2018, and March 31, 2021. All patients had been diagnosed with breast cancer following the clinical examination. First, we created a training cohort of patients who underwent NACT+surgery (N=180) to develop a nomogram. We then validated the performance of the nomogram in a validation cohort of patients who underwent NACT+ surgery (N=45). Multivariate logistic regression was then used to identify independent risk factors that were associated with the response to NACT; these were then incorporated into the nomogram.
Multivariate logistic regression analysis identified several significant differences as to clinical responses of NACT, including neutrophil-lymphocyte ratio (NLR), body mass index (BMI), pulsatility index (PI), resistance index (RI), blood flow, Ki67, histological type, molecular subtyping, and tumor size. The performance of the nomogram score exhibited a robust C-index of 0.89 (95% confidence interval [CI]: 0.83 to 0.95) in the training cohort and a high C-index of 0.87 (95% CI: 0.81 to 0.93) in the validation cohort. Clinical impact curves showed that the nomogram had a good predictive ability.
We successfully established an accurate and optimized nomogram incorporated ultrasound imaging and clinical indices that could be used preoperatively to predict clinical responses of NACT. This model can be used to evaluate the risk of clinical responses to NACT and therefore facilitate the choice of personalized therapy.
新辅助化疗（NACT）的临床反应与乳腺癌患者的预后相关。选择合适的变量来预测临床反应仍存在争议。在此，我们基于超声成像和临床指标开发了一种预测模型，以识别最可能从NACT中获益的患者。
我们连续招募了225例患者，这些患者于2018年1月1日至2021年3月31日在浙江省宁波市第六医院接受了NACT，随后进行了手术和腋窝淋巴结清扫。所有患者经临床检查确诊为乳腺癌。首先，我们创建了一个接受NACT+手术的患者训练队列（N=180）以制定列线图。然后我们在一个接受NACT+手术的患者验证队列（N=45）中验证了列线图的性能。随后使用多因素逻辑回归来识别与NACT反应相关的独立危险因素；这些因素随后被纳入列线图。
多因素逻辑回归分析确定了NACT临床反应的几个显著差异，包括中性粒细胞与淋巴细胞比值（NLR）、体重指数（BMI）、搏动指数（PI）、阻力指数（RI）、血流、Ki67、组织学类型、分子亚型和肿瘤大小。列线图评分在训练队列中的C指数稳健，为0.89（95%置信区间[CI]：0.83至0.95），在验证队列中的C指数较高，为0.87（95%CI：0.81至0.93）。临床影响曲线表明列线图具有良好的预测能力。
我们成功建立了一个结合超声成像和临床指标的准确且优化的列线图，可用于术前预测NACT的临床反应。该模型可用于评估NACT临床反应的风险，从而有助于选择个性化治疗。
