| 1. |
- Eriksson, Niclas, 1978-
(författare)
-
On the Prediction of Warfarin Dose
- 2012
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Warfarin is one of the most widely used anticoagulants in the world. Treatment is complicated by a large inter-individual variation in the dose needed to reach adequate levels of anticoagulation i.e. INR 2.0 – 3.0. The objective of this thesis was to evaluate which factors, mainly genetic but also non-genetic, that affect the response to warfarin in terms of required maintenance dose, efficacy and safety with special focus on warfarin dose prediction.Through candidate gene and genome-wide studies, we have shown that the genes CYP2C9 and VKORC1 are the major determinants of warfarin maintenance dose. By combining the SNPs CYP2C9 *2, CYP2C9 *3 and VKORC1 rs9923231 with the clinical factors age, height, weight, ethnicity, amiodarone and use of inducers (carbamazepine, phenytoin or rifampicin) into a prediction model (the IWPC model) we can explain 43 % to 51 % of the variation in warfarin maintenance dose. Patients requiring doses < 29 mg/week and doses ≥ 49 mg/week benefitted the most from pharmacogenetic dosing. Further, we have shown that the difference across ethnicities in percent variance explained by VKORC1 was largely accounted for by the allele frequency of rs9923231. Other novel genes affecting maintenance dose (NEDD4 and DDHD1), as well as the replicated CYP4F2 gene, have small effects on dose predictions and are not likely to be cost-effective, unless inexpensive genotyping is available.Three types of prediction models for warfarin dosing exist: maintenance dose models, loading dose models and dose revision models. The combination of these three models is currently being used in the warfarin treatment arm of the European Pharmacogenetics of Anticoagulant Therapy (EU-PACT) study. Other clinical trials aiming to prove the clinical validity and utility of pharmacogenetic dosing are also underway.The future of pharmacogenetic warfarin dosing relies on results from these ongoing studies, the availability of inexpensive genotyping and the cost-effectiveness of pharmacogenetic driven warfarin dosing compared with new oral anticoagulant drugs.
|
|
| 2. |
- Hamberg, Anna-Karin, 1964-
(författare)
-
Pharmacometric Models for Individualisation of Warfarin in Adults and Children
- 2013
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Warfarin is one of the most widely used anticoagulants. Therapy is complicated by warfarin’s narrow therapeutic range and pronounced variability in individual dose requirements. Although warfarin therapy is uncommon in children, it is crucial for children with certain congenital or acquired heart diseases. Treatment in children is especially difficult due to the lack of i) a decision support tool for efficient and consistent dose adjustments, and ii) a flexible warfarin formulation for accurate and reproducible dosing.The overall aim of this thesis was to develop a PKPD-based pharmacometric model for warfarin that describes the dose-response relationship over time, and to identify important predictors that influence individual dose requirements both in adults and children. Special emphasis was placed on investigating the contribution of genetic factors to the observed variability.A clinically useful pharmacometric model for warfarin has been developed using NONMEM. The model has been successfully reformulated into a KPD-model that describes the relationship between warfarin dose and INR response, and that is applicable to both adults and children. From a clinical perspective, this is a very important change since it allows the use of information on dose and INR that is available routinely. The model incorporates both patient and clinical characteristics, such as age, weight, CYP2C9 and VKORC1 genotype, and baseline and target INR, for the prediction of an individualised starting dose. It also enables the use of information from previous doses and INR observations to further individualise the dose a posteriori using a Bayesian forecasting method.The NONMEM model has been transferred to a user-friendly, platform independent tool to aid use in clinical practice. The tool can be used for a priori and a posteriori individualisation of warfarin therapy in both adults and children. The tool should ensure consistent dose adjustment practices, and provide more efficient individualisation of warfarin dosing in all patients, irrespective of age, body weight, CYP2C9 or VKORC1 genotype, baseline or target INR. The expected outcome is improved warfarin therapy compared with empirical dosing, with patients achieving a therapeutic and stable INR faster and avoiding high INRs that increase the risk of bleeding.
|
|
| 3. |
- Karlsson Sundbaum, Johanna, 1969-
(författare)
-
Studies of drug safety in the treatment of rheumatoid arthritis
- 2020
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Rheumatoid arthritis (RA) is a chronic inflammatory disease affecting mainly smaller joints. Patients are at risk for complications as joint destruction, but starting treatment soon after onset of disease, has reduced the risk for complications. Methotrexate (MTX) is the anchor drug in the treatment of RA and has proven effects on both inflammatory symptoms and joint destruction. apy. Identifying patients at risk for MTX-induced hepatotoxicity before treatment could be a way to minimize the risk for Adverese effects.Following the introduction of pre-treatment screening, the risk of tuberculosis (TB) among patients with RA starting biologic treatment has decreased. By contrast, the risk remains several-fold increased in RA patients non-exposed to biological treatment. Knowledge about risk factors for TB and TB characteristics in this group of patients, and thus optimal clinical risk stratification and preven-tion, is still limited.In Paper I, only a small number of ALT tests (7%) performed during MTX therapy in RA patients, capture an elevation of ALT > upper limit of normal (ULN). ALT >1.5 × ULN was observed in 44 (21%) patients and the strongest predictor was a pre-treatment elevation of ALT. Recurrent elevations occurred in 70% of patients who continued treatment, and the proportion was similar in those with and without interventions. The results support a more individualized approach to monitoring and handling of ALT elevations during MTX therapy. In Paper II MTHFR A1298C (rs1801131) was nominally associated with ALT >1.5 x ULN within 6 months after the start of MTX (OR=1.7 [95% CI 1.04-2.9], p=0.03). In a multi-ple regression analysis for ALT >1.5 X ULN within 6 months of treatment start, including known risk factors for ALT elevation and MTHFR A1298C, the C-statistic was 0.734. A mod-el containing clinical risk factors and MTHFR A1298C might be used for prediction of ALT elevation in MTX treated patients. In Paper III a Genome-Wide Association Study (GWAS) and analysis of candidate Single Nucleotide Polymorphisms (SNPs) were performed. Four SNPs in and upstream of the ribonucleoprotein, PTB Binding 2 gene on chromosome 1 were associated with max ALT within 6 months on a genome wide level (p<5x10-8). Our results indicate that the RAVER2 and/or JAK1 genes might play a role in MTX- induced hepatotoxici-ty, but further studies are necessary for confirmation of the results. In Paper IV, we performed a population based case-control study. Several RA-associated risk factors (treatment with leflunomide, azathioprine or prednisolone and concomitant obstructive lung disease) may contribute to the increased TB risk in biologics-naïve RA patients. We could not confirm previous findings of an association with the use of moderate to high doses of prednisolone (≥15 mg). TB risk seems difficult to predict with precision in the individual biologics-naïve patient based on RA-associated risk factors. This suggests TB screening should be considered in biologics-naïve patients.In conclusion, results from these studies suggest that several factors could increase the risk of AEs in RA patients. The risk might be reduced by utilizing prediction models that include knowledge about the medical history of the individual patient and genetic data in combination with screening for TB.
|
|
| 4. |
- Wadelius, Mia
(författare)
-
Pharmacogenetic analysis in sickness and in health - for better or for worse
- 1999
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- An individual's pharmacogenetic constitution may predict response to drugs, hormones and toxins, and might be a susceptibility factor for disease. Pharmacogenetic diversity is especially pronounced for drug metabolising enzymes. In these studies the following five enzymes have been genotyped: N-acetyltransferase 2 (NAT2), sparteine/debrisoquine hydroxylase (CYP2D6), mephenytoin hydroxylase (CYP2C19), steroid 17α-hydroxylase (CYP17), and glutathione S-transferase P1 (GSTP1).A simplified method for genotyping NAT2 was verified by phenotyping with isoniazid. All phenotypes: slow, intermediate and fast acetylators were correctly identified by genotyping. This method was used to genotype control subjects and patients who reacted to sulphasalazine with agranulocytosis. The incidence of slow acetylation was equal in agranulocytosis patients and population-based controls. However, the incidence of slowacetylation was significantly reduced in patients who tolerated sulphasalazine compared with both agranulocytosis patients and population-based controls.Different genotypes of the enzymes NAT2, CYP2D6, CYP2C19, GSTP1 and CYP17 were studied as possible susceptibility factors for prostate cancer in a case-control study. No association was found between prostate cancer and NAT2, CYP2D6, CYP2C19 orGSTP1 genotypes. A certain genotype of CYP17, encoding a key enzyme in testosterone synthesis, was associated with prostate cancer, a finding that warrants further studies. CYP2D6 is not considered to be an inducible enzyme, but phenotyping of pregnant women showed that CYP2D6 activity is increased during pregnancy. This may be caused by enzyme induction, suggesting possible impact on drug treatment during pregnancy. In the future, as more pharmacogenetic information becomes available, predicting individual drug responses will become an essential part of therapy.
|
|
