A Prediction Model of Tumor Progression and Survival in HER2-Positive Metastatic Gastric Cancer Patients Treated with Trastuzumab and Chemotherapy

The effects of different patient factors and dose levels of chemotherapeutic agents on clinical outcomes in advanced gastric cancer are not as yet fully characterized. We aimed at developing an integrative model that incorporates dose and covariate information to predict tumor growth and patient sur...

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Veröffentlicht in:The AAPS journal 2018-07, Vol.20 (4), p.72-72, Article 72
Hauptverfasser: Chae, Dongwoo, Nam, Chung Mo, Kim, Joo Hoon, Lee, Choong-Kun, Kim, Seung-Seob, Kim, Hyo Song, Jung, Minkyu, Cheong, Jae Ho, Chung, Hyun Cheol, Rha, Sun Young, Park, Kyungsoo
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container_end_page 72
container_issue 4
container_start_page 72
container_title The AAPS journal
container_volume 20
creator Chae, Dongwoo
Nam, Chung Mo
Kim, Joo Hoon
Lee, Choong-Kun
Kim, Seung-Seob
Kim, Hyo Song
Jung, Minkyu
Cheong, Jae Ho
Chung, Hyun Cheol
Rha, Sun Young
Park, Kyungsoo
description The effects of different patient factors and dose levels of chemotherapeutic agents on clinical outcomes in advanced gastric cancer are not as yet fully characterized. We aimed at developing an integrative model that incorporates dose and covariate information to predict tumor growth and patient survival in advanced gastric cancer patients treated with trastuzumab (T), 5-FU(F)/capecitabine (X) (F or X), and cisplatin (P). Sixty-nine patients (training dataset) were used for model building and a separate 86 patients (test dataset) for model validation. A fraction of tumor cells sensitive to each drug was incorporated as a model parameter, and T was assumed as cytostatic and X/F and P as cytotoxic. Cox proportional hazards analyses were performed on model parameters and patient covariates. The model well described the time course of observed tumor size changes, and revealed that the pretreatment tumor growth rate constant k g , which was formulated as a function of pretreatment disease duration and baseline tumor size, was positively correlated with baseline tumor size ( p  = 0.0084) and histologic grade ( p  = 0.034), and the efficacy of 5-FU with body weight ( p  
doi_str_mv 10.1208/s12248-018-0223-8
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We aimed at developing an integrative model that incorporates dose and covariate information to predict tumor growth and patient survival in advanced gastric cancer patients treated with trastuzumab (T), 5-FU(F)/capecitabine (X) (F or X), and cisplatin (P). Sixty-nine patients (training dataset) were used for model building and a separate 86 patients (test dataset) for model validation. A fraction of tumor cells sensitive to each drug was incorporated as a model parameter, and T was assumed as cytostatic and X/F and P as cytotoxic. Cox proportional hazards analyses were performed on model parameters and patient covariates. The model well described the time course of observed tumor size changes, and revealed that the pretreatment tumor growth rate constant k g , which was formulated as a function of pretreatment disease duration and baseline tumor size, was positively correlated with baseline tumor size ( p  = 0.0084) and histologic grade ( p  = 0.034), and the efficacy of 5-FU with body weight ( p  &lt; 2e−16) and that of cisplatin with histologic grade ( p  = 0.00013). Prior gastrectomy and Eastern Cooperative Oncology Group scores were significant prognostic factors for progression-free survival (PFS). For hazards analysis, a unit increase of k g was associated with a relative risk of 3.19 for PFS ( p  = 0.00055) and 4.45 for OS ( p  = 2e−04) in the test dataset, with a similar trend observed in the training dataset. 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subjects Biochemistry
Biomedical and Life Sciences
Biomedicine
Biotechnology
Pharmacology/Toxicology
Pharmacy
Research Article
title A Prediction Model of Tumor Progression and Survival in HER2-Positive Metastatic Gastric Cancer Patients Treated with Trastuzumab and Chemotherapy
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