You Benoit, Deng Wei, Hénin Emilie, Oza Amit, Osborne Raymond
*EMR UBCL/HCL 3738, Université Claude Bernard Lyon-1, Institut de Cancérologie des Hospices Civils de Lyon (IC-HCL), Centre de Référence des Maladie Trophoblastiques, Hospices Civils de Lyon, Lyon, France; †NRG Oncology Statistics and Data Management Center, Roswell Park Cancer Institute, Buffalo, NY; and ‡Department of Oncology, Princess Margaret Hospital; and §Department of Gynecology/Oncology, Toronto-Sunnybrook Regional Cancer Centre, Toronto, Ontario, Canada.
Int J Gynecol Cancer. 2016 Jan;26(1):208-15. doi: 10.1097/IGC.0000000000000581.
In low-risk gestational trophoblastic neoplasia, chemotherapy effect is monitored and adjusted with serum human chorionic gonadotrophin (hCG) levels. Mathematical modeling of hCG kinetics may allow prediction of methotrexate (MTX) resistance, with production parameter "hCGres." This approach was evaluated using the GOG-174 (NRG Oncology/Gynecologic Oncology Group-174) trial database, in which weekly MTX (arm 1) was compared with dactinomycin (arm 2).
Database (210 patients, including 78 with resistance) was split into 2 sets. A 126-patient training set was initially used to estimate model parameters. Patient hCG kinetics from days 7 to 45 were fit to: [hCG(time)] = hCG7 * exp(-k * time) + hCGres, where hCGres is residual hCG tumor production, hCG7 is the initial hCG level, and k is the elimination rate constant. Receiver operating characteristic (ROC) analyses defined putative hCGRes predictor of resistance. An 84-patient test set was used to assess prediction validity.
The hCGres was predictive of outcome in both arms, with no impact of treatment arm on unexplained variability of kinetic parameter estimates. The best hCGres cutoffs to discriminate resistant versus sensitive patients were 7.7 and 74.0 IU/L in arms 1 and 2, respectively. By combining them, 2 predictive groups were defined (ROC area under the curve, 0.82; sensitivity, 93.8%; specificity, 70.5%). The predictive value of hCGres-based groups regarding resistance was reproducible in test set (ROC area under the curve, 0.81; sensitivity, 88.9%; specificity, 73.1%). Both hCGres and treatment arm were associated with resistance by logistic regression analysis.
The early predictive value of the modeled kinetic parameter hCGres regarding resistance seems promising in the GOG-174 study. This is the second positive evaluation of this approach. Prospective validation is warranted.
在低风险妊娠滋养细胞肿瘤中，化疗效果通过血清人绒毛膜促性腺激素（hCG）水平进行监测和调整。hCG动力学的数学建模可能有助于预测甲氨蝶呤（MTX）耐药性，其产生参数为“hCGres”。本研究使用GOG-174（美国国立综合癌症网络肿瘤学/妇科肿瘤学组-174）试验数据库对该方法进行评估，该试验将每周使用MTX（第1组）与放线菌素D（第2组）进行了比较。
数据库（210例患者，包括78例耐药患者）被分为两组。最初使用126例患者的训练集来估计模型参数。将患者第7天至45天的hCG动力学拟合为：[hCG（时间）]=hCG7exp（-k时间）+hCGres，其中hCGres是hCG肿瘤残留产生量，hCG7是初始hCG水平，k是消除速率常数。通过受试者操作特征（ROC）分析确定耐药性的假定hCGRes预测指标。使用84例患者的测试集评估预测有效性。
hCGres可预测两组的结局，治疗组对动力学参数估计的 unexplained variability 无影响。区分耐药与敏感患者的最佳hCGres临界值在第1组和第2组分别为7.7和74.0 IU/L。通过将它们结合，定义了两个预测组（曲线下面积为0.82；敏感性为93.8%；特异性为70.5%）。基于hCGres的组对耐药性的预测价值在测试集中具有可重复性（曲线下面积为0.81；敏感性为88.9%；特异性为73.1%）。通过逻辑回归分析，hCGres和治疗组均与耐药性相关。
在GOG-174研究中，建模动力学参数hCGres对耐药性的早期预测价值似乎很有前景。这是对该方法的第二次阳性评估。有必要进行前瞻性验证。
