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The effects of the proton pump inhibitor esomeprazole alone or in combination with Coca-Cola on the absorption of Capecitabine in patients with cancer ‘the COCA study’

ABSTRACT: Primary objectives: 1. To evaluate the area under the plasma concentration-time curve (AUC) of capecitabine alone, compared to capecitabine used with esomeprazole and compared with capacitabine used with esomeprazole and the acid beverage Coca-Cola Classic in patients with CRC or other solid tumours. Primary endpoints: To evaluate the area under the plasma concentration-time curve (AUC) of capecitabine alone, compared to capecitabine used with esomeprazole and compared with capacitabine used with esomeprazole and the acid beverage Coca-Cola Classic in patients with CRC or other solid tumours.

DISEASE(S): Colorectal Carcinoma Or Other Solid Tumours,Colorectal Carcinoom Of Een Ander Type Solide Tumor

PROVIDER: 2537538 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

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2010-09-24 | E-GEOD-24245 | biostudies-arrayexpress

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Genome-wide SNP array data from Human Variation Panel by Illumina 650K

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Liu2023 - Predicting the efficacy of immune checkpoint inhibitors monotherapy in advanced non-small cell lung cancer: a machine learning method based on multidimensional data

Project description:Immunotherapy has improved the prognosis of patients with advanced non-small cell lung cancer (NSCLC), but only a small subset of patients achieved clinical benefit. The purpose of our study was to integrate multidimensional data using a machine learning method to predict the therapeutic efficacy of immune checkpoint inhibitors (ICIs) monotherapy in patients with advanced NSCLC.The authors retrospectively enrolled 112 patients with stage IIIB-IV NSCLC receiving ICIs monotherapy. The random forest (RF) algorithm was used to establish efficacy prediction models based on five different input datasets, including precontrast computed tomography (CT) radiomic data, postcontrast CT radiomic data, combination of the two CT radiomic data, clinical data, and a combination of radiomic and clinical data. The 5-fold cross-validation was used to train and test the random forest classifier. The performance of the models was assessed according to the area under the curve (AUC) in the receiver operating characteristic (ROC) curve. Among these models(RF MLP LR XGBoost), our reproduced onnx models have better performance, especially for random forest. The response variable with a value (1/0) indicates the (efficacy/inefficacy) of PD-1/PD-L1 monotherapy in patients with advanced NSCLC

2023-07-11 | BIOMD0000001074 | BioModels

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