目的 构建基于临床数据的列线图预测模型，探讨影响生物反馈（BFT）治疗盆底痉挛综合征（SPFS）的疗效因素，为早期识别疗效不佳的患者指导个体化治疗提供依据。 方法 选取2020年6月至2025年6月在河北医科大学第三医院胃肠外科接受1个疗程（10次）生物反馈的175例患者治疗前后的临床资料。将数据集划分为70%训练集（n = 122）和30%验证集（n = 53），定义治疗后ODS评分下降> 50%且肛门肌电图排便模式正常化为疗效满意，根据疗效划分有效组（TE）和无效组（TIE）。通过单因素logistic回归、Lasso回归与多因素logistic回归逐步筛选特征变量，构建列线图并采用受试者工作特征曲线（ROC）、Calibrate校正曲线、Hosmer-Lemeshow检验和决策曲线分析（DCA）评估模型区分度、校准度、拟合度与临床价值。 结果 最终多因素logistic回归显示肛门静息压、手助排便、使用泻药、使用灌肠、排便不尽感、患者满意度为疗效的独立危险因素。训练集和验证集的AUC分别为0.959（95%CI：0.921 ~ 0.996）和0.971（95%CI：0.918 ~ 1.000），校正曲线显示出良好的校准度，Hosmer-Lemeshow检验表明，训练集和验证集的实际概率与预测概率差异无统计学意义（P > 0.05）。DCA曲线和5折交叉验证均表明模型在0.1 ~ 0.8范围存在临床净收益。 结论 本研究整合了SPFS患者临床症状、检查等指标，对接受BFT治疗的疗效具有良好的预测效能，有助于筛查高风险患者为临床决策提供依据。

Objective To construct a prediction model based on clinical data， explore the factors influencing the efficacy of biofeedback treatment for spastic pelvic floor syndrome， and provide a basis for guiding individualized treatment through early identification of patients with poor treatment outcomes. Methods A total of 175 patients who underwent one course （10 sessions） of biofeedback treatment in the Department of Gastrointestinal Surgery， Third Hospital of Hebei Medical University， from June 2020 to June 2025， were selected for analysis. Clinical data before and after the treatment were collected. The dataset was partitioned into a training set （70%， n = 122） and a validation set （30%， n = 53）. Efficacy was defined as a reduction of over 50% in the ODS score and the normalization of the anorectal manometry defecation pattern. Based on the efficacy， patients were categorized into the treatment-effective group（TE） and treatment-ineffective group（TIE）. Feature variables were selected step-by-step through univariate logistic regression， Lasso regression， and multivariate logistic regression. A nomogram was constructed， and the discriminatory ability， calibration， fit， and clinical value of the model were evaluated using the receiver operating characteristic（ROC） curve， calibration curve， Hosmer-Lemeshow test， and decision curve analysis（DCA）. Results Multivariate logistic regression analysis revealed that anal resting pressure， digital evacuation， use of laxatives， use of enemas， sensation of incomplete evacuation， and patient satisfaction were independent risk factors influencing treatment efficacy. The area under the curve （AUC） values for the training and validation sets were 0.959 （95%CI： 0.921-0.996） and 0.971 （95%CI： 0.918-1.000）， respectively. The calibration curve indicated good calibration， and the Hosmer-Lemeshow test demonstrated no statistically significant difference between the actual and predicted probabilities in both the training and validation sets （P > 0.05）. DCA curves and 5-fold cross-validation suggested that the model provided clinical net benefits within a probability range of 0.1-0.8. Conclusions This study comprehensively integrates the clinical symptoms and diagnostic indicators of SPFS patients， thereby providing a reliable prediction model for the efficacy of BFT. This integration not only aids in the identification of high-risk patients but also offers valuable evidence for clinical decision-making.