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Fig. 3 | BMC Cancer

Fig. 3

From: Construction of possible integrated predictive index based on EGFR and ANXA3 polymorphisms for chemotherapy response in fluoropyrimidine-treated Japanese gastric cancer patients using a bioinformatic method

Fig. 3

Comparison of AIC, AUC, and ROC curves between logistic regression models. a Parameters used for each model. b ROC curves for the following models: rs2293347, rs2867461, Cr + Chem, rs2867461 + rs2293347, and rs2867461 + rs2293347 + Cr. ROC: receiver operating characteristic, AUC: area under the ROC curve, NULL: model without any parameters. Each genetic factor indicates proportional odds model, AIC: Akaike’s information criterion, Sens.: sensitivity (%), Spec: specificity (%), Chem: a history of chemotherapy, Cr: grade of creatinine

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