Assessment of the confidence interval in the multivariable normal tissue complication probability model for predicting radiation-induced liver disease in primary liver cancer.

We developed a confidence interval-(CI) assessing model in multivariable normal tissue complication probability (NTCP) modeling for predicting radiation-induced liver disease (RILD) in primary liver cancer patients using clinical and dosimetric data. Both the mean NTCP and difference in the mean NTCP (ΔNTCP) between two treatment plans of different radiotherapy modalities were further evaluated and their CIs were assessed. Clinical data were retrospectively reviewed in 322 patients with hepatocellular carcinoma (n = 215) and intrahepatic cholangiocarcinoma (n = 107) treated with photon therapy. Dose-volume histograms of normal liver were reduced to mean liver dose (MLD) based on the fraction size-adjusted equivalent uniform dose. The most predictive variables were used to build the model based on multivariable logistic regression analysis with bootstrapping. Internal validation was performed using the cross-validation leave-one-out method. Both the mean NTCP and the mean ΔNTCP with 95% CIs were calculated from computationally generated multivariate random sets of NTCP model parameters using variance-covariance matrix information. RILD occurred in 108/322 patients (33.5%). The NTCP model with three clinical and one dosimetric parameter (tumor type, Child-Pugh class, hepatitis infection status and MLD) was most predictive, with an area under the receiver operative characteristics curve (AUC) of 0.79 (95% CI 0.74-0.84). In eight clinical subgroups based on the three clinical parameters, both the mean NTCP and the mean ΔNTCP with 95% CIs were able to be estimated computationally. The multivariable NTCP model with the assessment of 95% CIs has potential to improve the reliability of the NTCP model-based approach to select the appropriate radiotherapy modality for each patient.

A novel therapeutic approach for thrombocytopenia by minibody agonist of the thrombopoietin receptor.

Antibodies have brought valuable therapeutics in the clinical treatment of various diseases without serious adverse effects through their intrinsic features such as specific binding to the target antigen with high affinity, clinical safety as serum proteins, and long half-life. Agonist antibodies, furthermore, could be expected to maximize the value of therapeutic antibodies. Indeed, several IgG/IgM antibodies have been reported to induce cellular growth/differentiation and apoptosis. These agonist antibodies, however, should be further improved to exert more potent biologic activities and appropriate serum half-life depending upon the disease indications. Here, we report that IgG antibodies against the thrombopoietin receptor (Mpl), which have an absence or very weak agonist activity, can be engineered to be agonist minibodies, which include diabody or sc(Fv)2 as potent as natural ligand. Through this technological development, minibodies have been successfully constructed to bind and activate 2 types of dysfunctional mutant Mpls that cause congenital amegakaryocytic thrombocytopenia (CAMT). This drastic conversion of biologic activities by designing minibodies can be widely applicable to generate agonist minibodies for clinical application, which will constitute a new paradigm in antibody-based therapeutics.