• Qin Zhao, Jianguo Sun, Yifu Tao, Shukui Wang, Chunzhi Jiang, Yubing Zhu, Feng Yu, and Junrong Zhu.
• Department of Clinical Pharmacology, Nanjing First Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China.
• Pharmacogenomics. 2014 Mar 1;15(4):487-95.

AimThis study was performed to develop an algorithm using polymorphisms of CYP2D6, p-gp, OPRM1, COMT and psychological variables to predict tramadol response in Chinese patients recovering from upper limb fracture internal fixation surgery.MethodsA total of 250 Han Chinese patients recovering from fracture in the upper limb were enrolled. CYP2D6*10, p-gp G2677T, p-gp C3435T, OPRM1 A118G and COMT Val158Met were detected by the ligase detection reaction (LDR) method. The algorithm was developed with binary logistic regression in cohort 1 (200 patients) and assessed with Wilcoxon signed-rank test in cohort 2 (50 patients).ResultsAccording to cohort 1, the predictive equation was calculated with the following logistic regression parameters: Logit (1) = 2.304-4.841 × (anxiety I) - 23.709 × (anxiety II) + 2.823 × (p-gp 3435CT) + 5.737 × (p-gp 3435 TT) - 1.586 × (CYP2D6*10 CT) - 4.542 × (CYP2D6*10 TT). The cutoff point for the prediction was defined as a probability value ≥0.5. The equation's positive predictive value is 90%. When applied to a new sample, the equation's positive predictive value is 86%. The Nagelkerke R² of the model is 0.819, the results of the Hosmer and Leme test show a value of 0.981. The nonparametric correlations between predicted and observed response showed significant correlation (coefficient = 0.879; p < 0.001).ConclusionThe algorithm we have developed might predict tramadol response in Chinese upper limb fracture patients.

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