British journal of cancer · 2013
Early prediction of treatment resistance in low-risk gestational trophoblastic neoplasia using population kinetic modelling of hCG measurements.
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You B, Harvey R, Henin E, Mitchell H, Golfier F, Savage P M, Tod M, Wilbaux M, Freyer G, Seckl M J
Аннотация
BACKGROUND: In low-risk gestational trophoblastic neoplasia (GTN) patients, a predictive marker for early identification of methotrexate (MTX) resistance would be useful. We previously demonstrated that kinetic modelling of human chorionic gonadotrophin (hCG) measurements could provide such a marker. Here we validate this approach in a large independent patient cohort.
METHODS: Serum hCG measurements of 800 low-risk GTN patients treated with MTX were analysed. The cohort was divided into Model and Test data sets. hCG kinetics were described from initial treatment day to day 50 using: '(hCG(time))=hCG0*exp(-k*time)+hCGres', where hCGres is the modelled residual production, hCG0 is the baseline hCG level, and k is the rate constant. HCGres-predictive value was investigated against previously reported predictors of MTX resistance.
RESULTS: Declining hCG measurements were well fitted by the model. The best discriminator of MTX resistance in the Model data set was hCGres, categorised by an optimal cut-off value of >20.44 IU l(-1): receiver-operating characteristic (ROC) area under the curve (AUC)=0.87; Se=0.91; Sp=0.83. The predictive value of hCGres was reproducible using the Test data set: ROC AUC=0.87; Se=0.88; Sp=0.86. Multivariate analyses revealed hCGres as a better predictor of MTX resistance (HR=1.01, P<0.0001) and MTX failure-free survival (HR=13.25, P<0.0001) than other reported predictive factors.
CONCLUSION: hCGres, a modelled kinetic parameter calculated after fully dosed three MTX cycles, has a reproducible value for identifying patients with MTX resistance.
METHODS: Serum hCG measurements of 800 low-risk GTN patients treated with MTX were analysed. The cohort was divided into Model and Test data sets. hCG kinetics were described from initial treatment day to day 50 using: '(hCG(time))=hCG0*exp(-k*time)+hCGres', where hCGres is the modelled residual production, hCG0 is the baseline hCG level, and k is the rate constant. HCGres-predictive value was investigated against previously reported predictors of MTX resistance.
RESULTS: Declining hCG measurements were well fitted by the model. The best discriminator of MTX resistance in the Model data set was hCGres, categorised by an optimal cut-off value of >20.44 IU l(-1): receiver-operating characteristic (ROC) area under the curve (AUC)=0.87; Se=0.91; Sp=0.83. The predictive value of hCGres was reproducible using the Test data set: ROC AUC=0.87; Se=0.88; Sp=0.86. Multivariate analyses revealed hCGres as a better predictor of MTX resistance (HR=1.01, P<0.0001) and MTX failure-free survival (HR=13.25, P<0.0001) than other reported predictive factors.
CONCLUSION: hCGres, a modelled kinetic parameter calculated after fully dosed three MTX cycles, has a reproducible value for identifying patients with MTX resistance.