Dataset Information

Time-to-event modelling of effect of codrituzumab on overall survival in patients with hepatocellular carcinoma.

ABSTRACT:

Aims

Codrituzumab (GC33) is a recombinant, humanized mAb that binds to glypican-3 (GPC3), an oncofetal protein highly expressed in hepatocellular carcinoma (HCC). This investigation aimed to identify clinically relevant factors that may affect the overall survival (OS) in HCC patients treated with codrituzumab and to quantitatively annotate their effects.

Methods

Codrituzumab exposure was estimated by a population pharmacokinetics model with a nonlinear elimination pathway. Analysis of OS was performed using a time-to-event model in 181 patients with advanced HCC. The model was tested with the addition of various covariates, including levels of immune biomarkers, such as CD16 (measured in terms of molecules of equivalent soluble fluorophore; CD16_MESF ) and CD4, codrituzumab exposure and potential prognostic biomarkers of HCC such as baseline tumour size and soluble GPC3.

Results

The time-to-event model estimated a prolonged OS (>3 months) in patients with codrituzumab exposure of ?230 ?g ml^-1 and high CD16_MESF level (>5.26 × 10⁵ MESF at least). The Weibull model was selected as the base hazard model. The baseline tumour size was included in the hazard model as a parameter independent of the drug effect. A logistic model was applied to explain the effects of drug exposure and CD16_MESF level.

Conclusions

The final model indicates that adequate drug exposure plus a favourable immune environment are associated with prolonged OS. This quantitative model should be further validated with emerging data so as to guide study design in future clinical trials.

SUBMITTER: Nakamura M

PROVIDER: S-EPMC5903238 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Time-to-event modelling of effect of codrituzumab on overall survival in patients with hepatocellular carcinoma.

Nakamura Mikiko M Xu Chao C Diack Cheikh C Ohishi Norihisa N Lee Ruey-Min RM Iida Satofumi S Kawanishi Takehiko T Ohtomo Toshihiko T Abou-Alfa Ghassan K GK Chen Ya-Chi YC

British journal of clinical pharmacology 20180309 5

<h4>Aims</h4>Codrituzumab (GC33) is a recombinant, humanized mAb that binds to glypican-3 (GPC3), an oncofetal protein highly expressed in hepatocellular carcinoma (HCC). This investigation aimed to identify clinically relevant factors that may affect the overall survival (OS) in HCC patients treated with codrituzumab and to quantitatively annotate their effects.<h4>Methods</h4>Codrituzumab exposure was estimated by a population pharmacokinetics model with a nonlinear elimination pathway. Analys ...[more]

PMID: 29381229

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Project description:Hepatocellular carcinoma (HCC) is one of the most common public health challenges, worldwide. Because of molecular complexity and tumor heterogeneity, there are no effective predictive models for prognosis of HCC. This underlines the unmet need for accurate prognostic models for HCC. Analysis of GSE14520 data from gene omnibus (GEO) database identified multiple differentially expressed mRNAs (DEMs) between HCC and normal tissues. After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, nomogram, and decision curve analysis (DCA) to evaluate the predictive and overall survival value of a novel five-gene signature (CNIH4, SOX4, SPP1, SORBS2, and CCL19) within and across sets, separately and combined. We also validated the prognostic value of the five-gene signature using The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC), GSE54236 and International Cancer Genome Consortium (ICGC) sets. Multivariable Cox regression analysis revealed that the five-gene signature and tumor node metastasis (TNM) stage were independent prognostic factors for overall survival of HCC patients in GSE14520 and TCGA-LIHC. Combining TNM stage clinical pathological parameters and nomogram greatly improved the prognosis prediction of HCC. Further gene set enrichment analysis (GSEA) revealed enrichment of KEGG pathways related to cell cycle in the high-risk group and histidine metabolism in the low-risk group. Finally, all these five mRNAs are overexpressed between 12 pairs of HCC and adjacent normal tissues by quantitative real-time PCR validation. In brief, a five-gene prognostic signature and a nomogram were identified and constructed, respectively, and further validated for their HCC prognostic value. The five-gene risk score together with TNM stage models could aid in rationalizing customized therapies in HCC patients.

Dataset Information

Time-to-event modelling of effect of codrituzumab on overall survival in patients with hepatocellular carcinoma.

Aims

Methods

Results

Conclusions

Publications

Time-to-event modelling of effect of codrituzumab on overall survival in patients with hepatocellular carcinoma.

Similar Datasets

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