定量CT身体组分分析预测乳腺癌手术联合辅助治疗预后研究

The value of quantitative CT body composition analysis to predict the prognosis of breast cancer patients treated by surgery and adjuvant therapy

目的:探讨手术联合辅助治疗前后的定量CT(QCT)身体组分参数的变化在评估乳腺癌患者预后中的价值。方法:回顾性分析91例平均年龄(49.69±9.72)岁患者经术后病理证实为乳腺癌的临床病理资料。对所有患者术前和辅助治疗后分别进行QCT扫描,并测量治疗前后两次的QCT参数,包括L_(1)、L_(2)椎体水平骨密度(BMD)和L_(3)椎体水平总肌肉面积(TMA)、皮下脂肪面积(SFA)、内脏脂肪面积(VFA)、总脂肪面积(TFA)。将QCT扫描时间间隔标准化为365天,计算所有参数治疗前后的变化率。用受试者工作特征曲线(ROC)评估各参数预测效能并计算最佳截断点。用独立样本t检验、Mann-Whitney U检验及单因素方差分析进行单因素分析,对单因素分析有意义的参数进行多因素logistics回归分析筛选出影响乳腺癌预后的独立危险因素。结果:治疗前后ΔBMD、ΔSFA、ΔVFA、ΔTFA、ΔTMA分别为-20.47%,9.26%,22.17%,18.51%和-2.81%;单因素分析显示,ΔSFA、ΔVFA及ΔTFA是乳腺癌预后的影响因素(P<0.05);多因素logistics回归分析显示,ΔVFA是乳腺癌患者预后的独立危险因素(P<0.05)。结论:ΔVFA与接受手术联合辅助治疗的乳腺癌患者的预后有关,QCT身体组分分析在乳腺癌的预后评估中具有重要的价值。

Objective:To explore the value of quantitative CT(QCT)body component parameters in predicting the prognosis of breast cancer patients treated with surgery and adjuvant therapy.Methods:A retrospective analysis was performed for 91 cases with breast cancer confirmed by surgical pathology.The average age was 49.69±9.72 years.All patients underwent QCT scans before and after treatment.L_(1),L_(2) bone mineral density(BMD),L_(3)-level parabertebral total muscle area(TMA),subcutaneous fat area(SFA),visceral fat area(VFA)and total fat area(TFA)were measured,and the change of QCT parameters were calculated,with QCT scan interval standardized as 365 days.The diagnostic accuracy of parameters and best cut-off values were determined by drawing receiver operating characteristic(ROC)curve.The statistical comparison was conducted by using independent sample t test,Mann-Whitney U test or one-way ANOVA test.For the factors with significant differences,multivariate logistics regression was conducted to determine the independent factors in predicting the prognosis of breast cancer.Results:ΔBMD,ΔSFA,ΔVFA,ΔTFA,ΔTMA were-20.47%,9.26%,22.17%,18.51%and-2.81%,respectively.Univariate analysis showed that theΔSFA,ΔVFA andΔTFA were the influencing factors for the prognosis of breast cancer(P<0.05).Multivariate logistics regression analysis showed thatΔVFA was an independent risk factor for the prognosis of breast cancer patients(P<0.05).Conclusion:ΔVFA is related to the prognosis of breast cancer patients receiving surgery combined with adjuvant therapy.QCT body composition analysis is valuable in the prognosis assessment of breast cancer.