Validation of pharmacogenetic markers: systematic reviews and meta-analysis

eta-analysis is a statistical technique that aims to combine the results from different studies, conducted on a particular topic, in order to obtain a quantitative estimate of the overall effect of a particular intervention or variable on a defined outcome. The statistical combination of all relevant studies allows to increase the number of subjects available, and consequently the statistical power, and to provide a more accurate estimation of the effect size.

The Center is currently involved in a number of systematic reviews and meta-analyses on published data evaluating the impact of genetic variants in response to specific pharmacological treatments. The identification of genetic determinants with proven clinical value would provide the basis for the use of pharmacogenetic tests in order to improve the safety and efficacy of pharmacological treatments.


Project leaders: Salvatore Terrazzino, Armando Genazzani.


Publications

Terrazzino S, Cargnin S, Viana M, Sances G and Tassorelli C. Brain-Derived Neurotrophic Factor Val66Met Gene Polymorphism Impacts on Migraine Susceptibility: A Meta-analysis of Case–Control Studies. Front. Neurol. 2017; 8:159. doi: 10.3389/fneur.2017.00159

Cargnin S, Terrazzino S. Comment to: GSTP1, GSTM1 and GSTT1 polymorphisms as predictors of response to chemotherapy in patients with breast cancer: a meta-analysis. Cancer Chemother Pharmacol. 2017;79(2):435-436.

Cargnin S, Canonico PL, Genazzani AA, Terrazzino S. Quantitative analysis of circulating cell-free DNA for correlation with lung cancer survival: a systematic review and meta-analysis. J Thorac Oncol 2017;12(1):43-53.

Cargnin S, Massarotti A, Terrazzino S. BDNF Val66Met and clinical response to antipsychotic drugs: a systematic review and meta-analysis. Eur Psychiatry 2016,33: 45–53.

Cargnin S, Quaglia M, Canonico PL, Piero Stratta P, Terrazzino S. Impact of recipient ACE I/D genotype on kidney function in renal transplant patients: a meta-analysis of cross-sectional and longitudinal studies. Pharmacogenomics 2015;16(16):1887-902.

Cargnin S, Jommi C, Canonico PL, Genazzani AA, Terrazzino S. Diagnostic accuracy of HLA-B*57:01 screening for the prediction of abacavir hypersensitivity and clinical utility of the test: a meta-analytic review. Pharmacogenomics 2014;15(7):963-976.

Terrazzino S, Cargnin S, Del Re M, Danesi R, Canonico PL, Genazzani AA. DPYD IVS14+1G>A and 2846A>T genotyping for the prediction of severe fluoropyrimidine-related toxicity: a meta-analysis. Pharmacogenomics 2013;14(11):1255-72.

Terrazzino S, Quaglia M, Stratta P, Canonico PL, Genazzani AA. The effect of CYP3A5 6986A>G and ABCB1 3435C>T on tacrolimus dose-adjusted trough levels and acute rejection rates in renal transplant patients: a systematic review and meta-analysis. Pharmacogenetics and Genomics 2012;22(8):642-5.