Background: Breast cancer survivors (BCSs) undergoing taxane-based chemotherapy frequently experience chemotherapy-induced peripheral neuropathy (CIPN), potentially affecting their quality of life. Early identification of high-risk survivors can help mitigate the severity of CIPN.

Objective: To construct and validate a predictive model for CIPN in BCSs receiving taxane-based chemotherapy.

Methods: In this multicenter cross-sectional study conducted across 10 hospitals in China between April 2022 and March 2023, 569 BCSs were randomly assigned to development (n = 401) or validation (n = 168) sets (ratio, 7:3). Predictive factors were identified by multiple logistic regression, and a nomogram was constructed. Model discrimination was evaluated using receiver operating characteristic curves and area under the curve values, whereas calibration was assessed with the Hosmer-Lemeshow test and calibration curves. Decision curve analysis was performed to evaluate clinical utility.

Results: CIPN was observed in 82.8% of the survivors. The nomogram included 5 factors: treatment with paclitaxel liposome, treatment with albumin-bound paclitaxel, number of chemotherapy cycles, vitamin D deficiency, and fatigue levels. The area under the curve values for the development and validation sets were 0.866 (95% confidence interval, 0.817-0.914) and 0.848 (95% confidence interval, 0.761-0.935), respectively, indicating good performance. The Hosmer-Lemeshow test and decision curve analysis confirmed good calibration and clinical utility.

Conclusions: The nomogram model demonstrates good discrimination and calibration, offering a practical and visual tool for identifying high-risk survivors for CIPN.

Implications for practice: This predictive model can assist clinicians in the early identification of BCSs at high risk for CIPN and in promptly implementing preventive measures.

Keywords: Breast cancer; Chemotherapy-induced peripheral neuropathy; Nomogram; Predictive model.

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背景：背景:

乳腺癌幸存者（BCSs）在使用以紫杉烷为基础的化疗时，经常会经历由化疗引起的外周神经病变（CIPN），这可能影响其生活质量。早期识别高风险患者可以帮助减轻 CIPN 的严重程度。

目标：

构建并验证针对接受以紫杉烷为基础的化疗的乳腺癌幸存者预测 CIPN 的模型。

方法：

在 2022 年 4 月至 2023 年 3 月期间，这项在中国十家医院进行的多中心横断面研究中，569 名乳腺癌幸存者被随机分配到开发（n = 401）或验证（n = 168）组（比例为 7:3）。通过多元逻辑回归识别预测因素，并构建了诺莫图。使用受试者工作特征曲线和曲线下面积值评估模型的区分能力，而使用 Hosmer-Lemeshow 检验和校准曲线进行校准评估。决策曲线分析用于评估临床效用。

结果：

在幸存者中观察到 CIPN 的比例为 82.8%。诺莫图包括以下五个因素：使用紫杉醇脂质体治疗、使用白蛋白结合型紫杉醇治疗、化疗周期数、维生素 D 缺乏和疲劳水平。开发组和验证组的曲线下面积值分别为 0.866（95% 置信区间，0.817-0.914）和 0.848（95% 置信区间，0.761-0.935），表明模型性能良好。Hosmer-Lemeshow 检验和决策曲线分析证实了良好的校准和临床效用。

结论：

诺莫图模型显示出了良好的区分能力和校准能力，为识别高风险 CIPN 幸存者提供了一种实用且可视化的工具。

实践意义：

该预测模型可以帮助临床医生在早期识别出有较高风险发生 CIPN 的乳腺癌幸存者，并及时实施预防措施。

关键词：

乳腺癌；化疗引起的外周神经病变；诺莫图；预测模型。