Objective:To establish a risk prediction model for postoperative control of chronic sinusitis with nasal polyps. Methods:Retrospective analysis was done on the clinical of patients who underwent endoscopic sinus surgery in the Department of Otolaryngology of the First Affiliated Hospital of Soochow University during August 2020 to June 2021. Patients were classified into uncontrolled group（40 cases） and controlled group（104 cases）, based on the European Position Paper on rhinosinusitis and nasal polyps（EPOS 2020）, and the clinical and pathological characteristics of the two groups were compared. The least absolute shrinkage and selection operator（LASSO） regression was used to screen the factors that might affect the prognosis of chronic sinusitis with nasal polyps and multivariate logistic regression was performed. The Receiver operating characteristic curve（ROC） was ploted, the area under curve（AUC） was calculated, and the ability of the prediction model was evaluated using the consistency index（C-index）. Results:A total of 144 patients with CRS with nasal polyps 1 year after operation were enrolled in this study, including 40 patients in the uncontrolled group and 104 patients in the control group（complete control or partial control）. 12 risk factors（allergic rhinitis, allergic dermatitis, olfactory dysfunction, E/M ratio, serum alkaline phosphatase, number of pathological eosinophils, number of pathological lymphocytes, number of plasma cells in pathological tissues, percentage of eosinophils in pathological tissues, stromal edema, basement membrane thickening, and hyperplasia of goblet cells） were found to be associated with postoperative recurrence of chronic sinusitis with nasal polyps. The seven variables（allergic rhinitis, olfactory dysfunction, E/M ratio, pathological eosinophilic percentage, stromal edema, basement membrane thickening, and hyperplasia of goblet cell） were extracted after reduced by LASSO regression. Multivariate logistic regression analysis showed that the 7 variables were risk factors for postoperative recurrence of chronic sinusitis with nasal polyps（P<0.05）. Nomogram prediction model for postoperative recurrence of chronic sinusitis with nasal polyps were established based on the 7 variables above. The verification results of the model showed that the C-index and AUC of the model were 0.937 and 0.937（95%CI 0.901-0.973）, suggesting that the nomogram model had a relatively accurate prediction ability. Conclusion:Combined with the basic clinical data of patients, the prediction model established in this study can facilitate the risk prediction of postoperative control of chronic sinusitis with nasal polyps, and thus help to formulate better therapeutic plans for patients.
目的：建立慢性鼻窦炎伴鼻息肉（chronic sinusitis with nasal polyps，CRSwNP）术后控制情况的风险列线图预测模型。 方法：回顾性分析2020年8月至2021年6月于苏州大学附属第一医院耳鼻咽喉科行鼻窦炎伴鼻息肉手术的患者的临床资料，按照欧洲鼻窦炎和鼻息肉意见书（EPOS 2020）疗效评定方法分为未控制组40例和控制组（完全控制、部分控制）104例，比较2组的临床和病理特征。以LASSO回归筛选可能影响CRSwNP预后的因素并进行多因素logistic回归。绘制列线图的受试者的工作特征曲线（ROC），计算曲线下面积（AUC），使用一致性指数（C-index）评估预测模型的能力。 结果：144例CRSwNP术后1年的患者中，未控制组40例，控制组104例。进行组间差异性分析显示12个因素[变应性鼻炎、变应性皮炎、嗅觉障碍、鼻窦CT评分中筛窦总分与上颌窦总分的比值（E/M值）、血清碱性磷酸酶、鼻息肉组织中嗜酸性粒细胞计数、鼻息肉组织中淋巴细胞计数、鼻息肉组织中浆细胞计数、鼻息肉组织中嗜酸性粒细胞百分比、固有层水肿、基底膜厚度、杯状细胞增生情况]差异有统计学意义。应用LASSO回归对上述因素进行降维处理后得到7个变量，分别为变应性鼻炎、嗅觉障碍、E/M值、鼻息肉组织中嗜酸性粒细胞百分比、固有层水肿、基底膜厚度、杯状细胞增生情况。多因素logistic回归分析结果显示，上述7个变量为影响CRSwNP术后控制情况的风险因素（P<0.05）。基于以上7个变量建立CRSwNP患者术后控制情况的列线图预测模型，经评估显示该模型的C-index为0.937，AUC为0.937（95%CI 0.901～0.973），提示该列线图模型具有较准确的预测能力。 结论：本研究建立的预测模型结合患者的基本临床数据，方便对临床工作中对CRSwNP术后控制情况进行风险预测，从而为患者制定更优的治疗方案。.
Keywords: LASSO regression; chronic sinusitis with nasal polyps; postoperative control.
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