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Can ROMA algorithm stratify ovarian tumor patients better when being based on specific age ranges instead of the premenopausal and postmenopausal status?

机译:当基于特定年龄范围而不是绝经前和绝经后状态时ROMA算法能否更好地对卵巢肿瘤患者进行分层?

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摘要

After several years of research, HE4 was found to be characterized by slightly worse sensitivity but significantly higher specificity as compared with CA125. Further studies led to the diagnostic potential of both markers (CA125 and HE4) being combined in a single risk of malignancy algorithm (ROMA) algorithm. The objective of this study was to assess the diagnostic capabilities of the ROMA algorithm using age ranges instead of dichotomization of patients according to the pre- and postmenopausal status. A total of 413 female patients were included in the study, including 162 premenopausal and 251 postmenopausal women. Calculation of the final ROMA values was achieved by means of stepwise reduction of coefficients in the proposed formula of: %ROMA = exp(PI)/[1-exp(PI)]*100) and PI = A + W(HE4)*ln(HE4) + W(CA125)*ln (CA125) and the arrangement of values with consideration to the age group, HE4 level, differentiation of modification, and directional coefficients as well as determination of individual deviations affecting the widening of the median. The cutoff value of modified algorithm ROMA P for the entire study population was calculated from receiver operating characteristic (ROC) curve and DeLong method at the levels of 23.5 %. Marked higher sensitivity and negative predictive value (NPV) values are observed for the standard ROMA algorithm while higher specificity and positive predictive value (PPV) values are observed for the modified algorithm ROMA P. The proposed age-related modification of algorithm calculation does not require the patients being dichotomized according to their pre- or postmenopausal status, and satisfactory diagnostic values may be obtained using a single cutoff point for the entire population.
机译:经过数年的研究,与CA125相比,发现HE4的敏感性稍差,但特异性更高。进一步的研究导致将两种标记物(CA125和HE4)的诊断潜力结合在单一风险的恶性算法(ROMA)算法中。这项研究的目的是根据绝经前和绝经后的状况,使用年龄范围而不是根据患者的身分来评估ROMA算法的诊断能力。该研究共纳入413名女性患者,其中包括162名绝经前妇女和251名绝经后妇女。最终ROMA值的计算是通过逐步降低建议的公式中的系数来实现的:%ROMA = exp(PI)/ [1-exp(PI)] * 100)和PI = A + W(HE4)< sup> * ln(HE4)+ W(CA125) * ln(CA125)以及考虑年龄组,HE4水平,修饰差异和方向系数的值排列以及确定影响中位数扩大的个体偏差。根据接收者工作特征(ROC)曲线和DeLong方法,在23.5%的水平上计算出整个研究人群的改良算法ROMA P的临界值。对于标准ROMA算法,观察到明显更高的灵敏度和负预测值(NPV)值,而对于改进算法ROMA P,观察到更高的特异性和正预测值(PPV)。建议的与年龄相关的算法计算修改不需要根据绝经前或绝经后的状态将患者二等分,使用整个人群的单一临界点即可获得满意的诊断值。

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