To evaluate genetic variants affecting mycophenolic acid (MPA) metabolism in Chinese renal transplant recipients. Total 11 SNPs of , , , , and were genotyped in 408 Chinese renal transplant recipients. Associations between SNPs and MPA concentration/dose ratio (C /D) were analyzed using different genetic models. Multivariate linear regression was used to analyze associations between log (C /D) and clinical factors. After adjustment by clinical factors, rs7662029 was associated with log (C /D) using a dominant (p = 0.041) and an additive (p = 0.038) model, rs717620 was associated with log (C /D) using a recessive model (p = 0.019). Using additive model, SNP-SNP interactions were identified (p = 0.002) between rs717620 and rs2741049, with interactions (p = 0.002) between rs717620 and rs1042597. Age, albumin and serum creatinine were associated with log (C /D). rs7662029 and rs717620 may affect MPA pharmacokinetics. SNP-SNP interactions and clinical factors may have significant effects on MPA metabolism.
This study aimed to assess the impact of and variation on venlafaxine (VEN) at steady state in patients from Trinidad and Tobago of Indian and African descent with major depressive disorder. Patients were phenotyped with dextromethorphan, genotyped for and , and metabolic ratios for VEN obtained at 2-week intervals. Of 61 patients, 55 were genotyped and phenotyped and 47 completed 8 weeks of VEN treatment. The majority of patients had metabolic ratios for VEN that were consistent with those for dextromethorphan and genotype-predicted phenotype using activity scores. One subject presented with a novel no-function allele, . No correlations were observed with genotype. genotype analysis provides valuable information to individualize drug therapy with VEN.
To analyze the impact of nongenetic factors and gene polymorphisms on warfarin dose requirements in elderly Shanghai Han Chinese patients. Genotypes of (rs1799853 and rs1057910), (rs7856096), (rs7412 and rs429358), (rs699664 and rs12714145), (rs4653436, rs1877724, rs1051740 and rs1131873), (rs1800566 and rs10517), (rs1045642), (rs9923231) and (rs2108622) in 214 patients with stable warfarin dose were determined and their demographic characteristics were recorded. Multiple linear regression analysis revealed that rs9923231, rs1057910, rs7412, age, BMI and concomitant amiodarone could explain 37.0% of the individual variations of daily stable warfarin dose. rs9923231, rs1057910, rs7412, age, BMI and concomitant amiodarone play an important role in stable dose variation of warfarin in elderly Shanghai Han Chinese patients, whereas rs1045642 is not a significant genetic factor.
To evaluate the impact of , and polymorphisms on tacrolimus concentrations, efficacy and tolerance in pediatric primary nephrotic syndrome. Dose-adjusted concentrations (C /D), daily dose, frequency and time to relapse, cumulative remission days, and adverse reactions in 65 Chinese patients with various genotypes were retrospectively collected and compared. C /D increased in , and diplotype carriers by 38.4, 69.7 and 40.9% compared with , and noncarriers, respectively. Recurrence risks were decreased in (0.43 of hazard ratio to ) and carriers (0.43 of hazard ratio to ). None of polymorphisms was linked to adverse reactions. The genotypes of and rather than potentially predicted tacrolimus exposure and clinical response in pediatric primary nephrotic syndrome.
Therapy with low-dose amitriptyline is commonly used to treat painful diabetic peripheral neuropathy. There is a knowledge gap, however, regarding the role of variable CYP2D6-mediated drug metabolism and side effects (SEs). We aimed to generate pilot data to demonstrate that SEs are more frequent in patients with variant alleles. To that end, 31 randomly recruited participants were treated with low-dose amitriptyline for painful diabetic peripheral neuropathy and their gene sequenced. Patients with predicted normal or ultra-rapid metabolizer phenotypes presented with less SEs compared with individuals with decreased CYP2D6 activity. Hence, genotype contributes to treatment outcome and may be useful for guiding drug therapy. Future investigations in a larger patient population are planned to support these preliminary findings.
Abstract Background Budget impact analyses (BIAs) are an essential part of a comprehensive economic assessment of a health care intervention and are increasingly required by reimbursement authorities as part of a listing or reimbursement submission. Objectives The objective of this report was to present updated guidance on methods for those undertaking such analyses or for those reviewing the results of such analyses. This update was needed, in part, because of developments in BIA methods as well as a growing interest, particularly in emerging markets, in matters related to affordability and population health impacts of health care interventions. Methods The Task Force was approved by the International Society for Pharmacoeconomics and Outcomes Research Health Sciences Policy Council and appointed by its Board of Directors. Members were experienced developers or users of BIAs; worked in academia and industry and as advisors to governments; and came from several countries in North America and South America, Oceania, Asia, and Europe. The Task Force solicited comments on the drafts from a core group of external reviewers and, more broadly, from the membership of the International Society for Pharmacoeconomics and Outcomes Research. Results The Task Force recommends that the design of a BIA for a new health care intervention should take into account relevant features of the health care system, possible access restrictions, the anticipated uptake of the new intervention, and the use and effects of the current and new interventions. The key elements of a BIA include estimating the size of the eligible population, the current mix of treatments and the expected mix after the introduction of the new intervention, the cost of the treatment mixes, and any changes expected in condition-related costs. Where possible, the BIA calculations should be performed by using a simple cost calculator approach because of its ease of use for budget holders. In instances, however, in which the changes in eligible population size, disease severity mix, or treatment patterns cannot be credibly captured by using the cost calculator approach, a cohort or patient-level condition-specific model may be used to estimate the budget impact of the new intervention, accounting appropriately for those entering and leaving the eligible population over time. In either case, the BIA should use data that reflect values specific to a particular decision maker’s population. Sensitivity analysis should be of alternative scenarios chosen from the perspective of the decision maker. The validation of the model should include at least face validity with decision makers and verification of the calculations. Data sources for the BIA should include published clinical trial estimates and comparator studies for the efficacy and safety of the current and new interventions as well as the decision maker’s own population for the other parameter estimates, where possible. Other data sources include the use of published data, well-recognized local or national statistical information, and, in special circumstances, expert opinion. Reporting of the BIA should provide detailed information about the input parameter values and calculations at a level of detail that would allow another modeler to replicate the analysis. The outcomes of the BIA should be presented in the format of interest to health care decision makers. In a computer program, options should be provided for different categories of costs to be included or excluded from the analysis. Conclusions We recommend a framework for the BIA, provide guidance on the acquisition and use of data, and offer a common reporting format that will promote standardization and transparency. Adherence to these good research practice principles would not necessarily supersede jurisdiction-specific BIA guidelines but may support and enhance local recommendations or serve as a starting point for payers wishing to promulgate methodology guidelines.
Chronic HCV infection comprises a broad spectrum of liver disease, ranging from no or minimal activity to active hepatitis that in time may progress to severe liver fibrosis, cirrhosis and hepatocellular carcinoma if left untreated. This review describes the impact of genetic variants of interleukin 28B ( ; also known as interferon-lambda 3), inosine triphosphate pyrophosphatase ( ) and patatin-like phospholipase domain-containing 3 ( ) on therapeutic outcome and liver disease severity in HCV-infected patients.
Beaches are dynamic transitional environments subject to numerous natural and anthropic alterations. In these ecosystems, the infralittoral-sublittoral macrofauna communities play a key role in the food web. The objective of this study was to compare macrofauna communities on six beaches on the Gulf of Cádiz coast, which were classified according to the anthropic alterations they support, and evaluate the influence of abiotic factors on the species distribution. Sampling was done in the infralittoral-sublittoral zone of each beach using a modified manual dredge. Five perpendicular transects of 25 m, each separated by 10 m, were performed per beach, with a total sample area of 43.75 m per beach. A total of 27 species were found, of which , and were the most abundant. Anthropogenic effects are appreciable in the infralittoral-sublittoral although they are areas that are permanently submerged and less exposed than the intertidal. Beach nourishments carried out with large volumes of sand can alter the grain size, the most influential parameter on the distribution of the species, and consequently, affect the macrofauna community that inhabits these beaches.