局部晚期宫颈癌患者新辅助化疗疗效的影响因素及预测模型研究

Influencing factors and prediction model for the efficacy of neoadjuvant chemotherapy in patients with locally advanced cervical cancer

摘要:

目的 探讨局部晚期宫颈癌患者新辅助化疗疗效的影响因素并建立预测模型。方法 回顾性分析2021年8月—2023年6月在徐州医科大学附属徐州市妇幼保健院接受治疗的136例局部晚期宫颈癌患者的临床资料，根据新辅助化疗疗效分为有效组（96例）和无效组（40例）。比较两组患者的临床资料。多因素逐步Logistic回归分析局部晚期宫颈癌患者新辅助化疗疗效的影响因素；绘制受试者工作特征（ROC）曲线分析局部晚期宫颈癌患者新辅助化疗疗效预测模型预测新辅助化疗疗效的价值。结果 有效组鳞癌、病灶大小≤ 6 cm、化疗疗程2～3周期、无贫血、淋巴结转移阴性、血流丰富占比高于无效组（P <0.05）。多因素逐步Logistic回归分析结果显示：鳞癌［O^R=2.044（95% CI：1.211，3.450）］、病灶大小≤ 6 cm ［O^R=2.563（95% CI：1.305，5.034）］、化疗疗程2～3周期［O^R=1.845（95% CI：1.118，3.045）］、无贫血［O^R=1.229（95% CI：1.003，1.506）］、淋巴结转移阴性［O^R=3.174（95% CI：1.678，6.004）］、血流丰富［O^R=2.306（95% CI：1.242，4.282）］均是局部晚期宫颈癌患者新辅助化疗有效的影响因素（P <0.05）。根据多因素逐步Logistic回归分析结果建立局部晚期宫颈癌患者新辅助化疗疗效的预测模型，Logit（P）=-32.167+0.715×病理类型+0.941×病灶大小+0.612×化疗疗程+0.206×贫血+1.155×淋巴结转移+0.836×血流情况。ROC曲线分析结果表明，该模型预测新辅助化疗疗效的曲线下面积为0.952（95% CI：0.906，0.997），敏感性为89.6%（95% CI：0.843，0.956），特异性为85.0%（95% CI：0.812，0.906）。结论 局部晚期宫颈癌患者新辅助化疗疗效受病理类型、病灶大小、化疗疗程、贫血、淋巴结转移、血流情况等因素的影响，建立预测模型更有利于新辅助化疗疗效的评估。

Abstract:

Objective To investigate the factors influencing the curative effect of neoadjuvant chemotherapy in patients with locally advanced cervical cancer, thereby establishing a prediction model.Methods The clinical data of 136 patients with locally advanced cervical cancer who received treatment in Xuzhou Maternal and Child Health Hospital Affiliated to Xuzhou Medical University from August 2021 to June 2023 were retrospectively analyzed. According to the efficacy of neoadjuvant chemotherapy, the patients were divided into effective group (n = 96) and ineffective group (n = 96). The clinical data of the two groups were compared. Multivariable Logistic regression analysis was used to determine the influencing factors for the efficacy of neoadjuvant chemotherapy in patients with locally advanced cervical cancer. Receiver operating characteristic (ROC) curve was plotted to analyze the value of the prediction model for the efficacy of neoadjuvant chemotherapy in patients with locally advanced cervical cancer.Results The proportions of patients with squamous cell carcinoma, lesion size ≤ 6 cm, 2 to 3 cycles of chemotherapy, no anemia, absence of lymph node metastasis and rich blood flow through tumors in the effective group were higher than those in the ineffective group (P < 0.05). Multivariate Logistic regression analysis exhibited that squamous cell carcinoma [O^R = 2.044 (95% CI: 1.211, 3.450) ], lesion size ≤ 6 cm [O^R = 2.563 (95% CI: 1.305, 5.034) ], 2 to 3 cycles of chemotherapy [O^R = 1.845 (95% CI: 1.118, 3.045) ], no anemia [O^R = 1.229 (95% CI: 1.003, 1.506) ], absence of lymph node metastasis [O^R = 3.174 (95% CI: 1.678, 6.004) ], and rich blood flow through tumors [O^R = 2.306 (95% CI: 1.242, 4.282) ] were all factors affecting the efficacy of neoadjuvant chemotherapy in patients with locally advanced cervical cancer (P < 0.05). A prediction model for the efficacy of neoadjuvant chemotherapy in patients with locally advanced cervical cancer was established based on the multivariable Logistic regression analysis, which was expressed as Logit (P) = -32.167 + 0.715× pathological type + 0.941 × lesion size + 0.612 × chemotherapy course + 0.206× anemia + 1.155 × lymph node metastasis + 0.836× blood flow. The ROC curve analysis demonstrated that the area under the curve, sensitivity and specificity of the prediction model for the efficacy of neoadjuvant chemotherapy were 0.952 (95% CI: 0.906, 0.997), 0.896 (95% CI: 0.843, 0.956) and 0.850 (95% CI: 0.812, 0.906), respectively.Conclusions The efficacy of neoadjuvant chemotherapy in patients with locally advanced cervical cancer is affected by pathological type, lesion size, chemotherapy course, anemia, lymph node metastasis and blood flow among other factors. The establishment of a prediction model is more conducive to the evaluation of the efficacy of neoadjuvant chemotherapy.