Predictive models for fentanyl dose requirement and postoperative pain using clinical and genetic factors in patients undergoing major breast surgery.

Fentanyl exhibits interindividual variability in its dose requirement due to various nongenetic and genetic factors such as single nucleotide polymorphisms (SNPs). This study aims to develop and cross-validate robust predictive models for postoperative fentanyl analgesic requirement and other related outcomes in patients undergoing major breast surgery. Data regarding genotypes of 10 candidate SNPs, cold pain test (CPT) scores, pupillary response to fentanyl (PRF), and other common clinical characteristics were recorded from 257 patients undergoing major breast surgery.

Impact of Genetic Variants on Postoperative Pain and Fentanyl Dose Requirement in Patients Undergoing Major Breast Surgery: A Candidate Gene Association Study.

Background: Postoperative analgesia is crucial for the early and effective recovery of patients undergoing surgery. Although postoperative multimodal analgesia is widely practiced, opioids such as fentanyl are still one of the best analgesics. The analgesic response of fentanyl varies widely among individuals, probably due to genetic and nongenetic factors.

GSTM1 and GSTT1 double null genotypes determining cell fate and proliferation as potential risk factors of relapse in children with hematological malignancies after hematopoietic stem cell transplantation.

Purpose: This study aimed to retrospectively evaluate the genetic association of null variants of glutathione S-transferases GSTM1 and GSTT1 with relapse incidence in children with hematological malignancies (HMs) undergoing busulfan (BU)- containing allogeneic hematopoietic stem cell transplantation (HSCT) and to assess the impact of these variants on BU-induced cytotoxicity on the immortalized lymphoblastoid cell lines (LCLs) and tumor THP1 GST gene-edited cell models.

Methods: GSTM1- and GSTT1-null alleles were genotyped using germline DNA from whole blood prior to a conditioning BU-based regimen. Association of GSTM1- and GSTT1-null variants with relapse incidence was analyzed using multivariable competing risk analysis.

Impact of computerised physician order entry (CPOE) on the incidence of chemotherapy-related medication errors: a systematic review.

Purpose: Computerised prescriber (or physician) order entry (CPOE) implementation is one of the strategies to reduce medication errors. The extent to which CPOE influences the incidence of chemotherapy-related medication errors (CMEs) was not previously collated and systematically reviewed. Hence, this study was designed to collect, collate, and systematically review studies to evaluate the effect of CPOE on the incidence of CMEs.

Indo-Swiss symposium on advances in pharmacogenomic strategies for implementation of personalized medicine.

The Indo-Swiss symposium on advances in pharmacogenomic strategies for implementation of personalized medicine was conducted as a part of the JIPMER Integrated Pharmacogenomics Program (JIPP), held in Puducherry, India on 23 November 2019. The symposium focused on the growing contribution of pharmacogenomic information in designing treatment strategies and promoting better approaches to personalized medicine. The primary objective of this symposium was to bridge gaps in understanding the basics and recent advances in the field of pharmacogenomics.

Haplotype structures of common variants of CYP2C8, CYP2C9, and ADRB1 genes in a South Indian population.

Introduction: In association with candidate genes, the observed trait may be due to either one of the variant alleles or the interaction of variant alleles at different loci, which are in linkage disequilibrium.

Aim: The objective of this study was to investigate the baseline allele and genotype frequencies, linkage disequilibrium (LD) patterns, and haplotype structures of common variants of the CYP2C8, CYP2C9, and ADRB1 genes located on chromosome 10.

Methods: Two hundred and forty-five healthy subjects were recruited from South India and were compared with the HapMap Project's population for LD pattern, allele and genotype frequencies, and haplotype structures.