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A serious complication of replacement therapy in patients with bleeding disorders is the development of 'inhibitors', particularly FVIII inhibitors in haemophilia A patients. This leads to an increase in the management cost, morbidity and mortality, especially post-operatively. The mechanism of FVIII inhibitor development is quite complex and it is difficult to predict inhibitor development, but a prompt and accurate diagnosis is critical as early therapy can save lives. The aim of this study was to screen patients with bleeding disorders in India for inhibitors, and to analyse and compare the prevalence of inhibitors in different regions in India. Patient details were recorded and blood samples were collected in sodium citrate vacutainers from 1,505 patients with bleeding disorders, in different cities in India. Coagulation and inhibitor screening assays were performed, followed by the Bethesda assay in inhibitor positive samples to quantify the FVIII inhibitor titre. Out of the 1,505 samples analysed, 1,285 were Haemophilia A patients, out of which 78 (6.07 %) were positive for 'FVIII Inhibitors'. The highest incidence of FVIII Inhibitors was seen in South India (13.04 %). The highest incidence of 20.99 % was observed in Chennai, followed by Hyderabad (13.33 %), Jammu (9.90 %) and Guwahati (8.51 %), respectively, with respect to the samples analysed. The other regions showed an inhibitor incidence <8 %. The incidence of inhibitors in haemophilia A patients is different in different regions of India; this may be due to the intensity of treatment, type of product or the genetic characteristics of these patients.

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The main aim of this study was to screen various genetic and nongenetic factors that are known to alter warfarin response and to generate a model to predict stable warfarin maintenance dose for Indian patients. The study comprised of 300 warfarin-treated patients. Followed by extensive literature review, 10 single-nucleotide polymorphisms, that is, VKORC1-1639 G>A (rs9923231), CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), FVII R353Q (rs6046), GGCX 12970 C>G (rs11676382), CALU c.*4A>G (rs1043550), EPHX1 c.337T>C (rs1051740), GGCX: c.214+597G>A (rs12714145), GGCX: 8016G>A (rs699664), and CYP4F2 V433M (rs2108622), and 5 nongenetic factors, that is, age, gender, smoking, alcoholism, and diet, were selected to find their association with warfarin response. The univariate analysis was carried out for 15 variables (10 genetic and 5 nongenetic). Five variables, that is, VKORC1-1639 G>A, CYP2C9*2, CYP2C9*3, age, and diet, were found to be significantly associated with warfarin response in univariate analysis. These 5 variables were entered in stepwise and multiple regression analysis to generate a prediction model for stable warfarin maintenance dose. The generated model scored R of .67, which indicates that this model can explain 67% of warfarin dose variability. The generated model will help in prescribing more accurate warfarin maintenance dosing in Indian patients and will also help in minimizing warfarin-induced adverse drug reactions and a better quality of life in these patients.