Adherence to bisphosphonates therapy and hip fracture risk in osteoporotic women.

UNLABELLED: Adherence is now one of the major issues in the management of osteoporosis and several papers have suggested that vertebral fractures might be increased in patients who do not follow appropriately their prescriptions. This paper relates the strong relationship existing between adherence to anti-osteoporosis treatment and the risk of subsequent hip fracture. INTRODUCTION: A study was performed to investigate adherence to bisphosphonate (BP) therapy and the impact of adherence on the risk of hip fracture (Fx). METHODS: An exhaustive search of the Belgian national social security database was conducted. Patients enrolled in the study were postmenopausal women, naive to BP, who received a first prescription of alendronate. Compliance at 12 months was quantified using the medication possession ratio (MPR). Persistence was calculated as the number of days from the initial prescription to a gap of more than 5 weeks after completion of the previous refill. A logistic regression model was used to estimate the impact of compliance on the risk of hip fracture. The impact of persistence on hip fracture risk was analysed using the Cox proportional hazards model. RESULTS: The mean MPR at 12 months was significantly higher among patients receiving weekly (n = 15.021) compared to daily alendronate (n = 14,136) (daily = 58.6%; weekly = 70.5%; p < 0.001). At 12 months, the rate of persistence was 39.45%. For each decrease of the MPR by 1%, the risk of hip Fx increased by 0.4% (OR: 0.996; CI 95%: 0.994-0.998; p < 0.001). The relative risk reduction for hip Fx was 60% (HR: 0.404; CI 95%: 0.357-0.457; p < 0.0001) for persistent compared to non-persistent patients. CONCLUSION: These results confirm that adherence to current therapeutic regimens remains suboptimal.

Development and optimisation of a flow injection assay for fluticasone propionate using an asymmetrical design and the variable-size simplex algorithm.

A flow injection analysis method is described to determine fluticasone propionate, based upon a novel adaptation of the reaction of o-phthalaldehyde with a thiol and a primary amine. The method, which allows both UV and fluorescence detection, has been optimised using experimental design. First a screening is executed to select the significant factors and in a second step these factors are optimised with the variable-size simplex algorithm. In the screening step, a two-level fractional factorial design is compared with an asymmetrical design containing the same number of experiments, but in which one factor is at three levels. It was found that in both designs the same significant variables are detected for the two-level factors, but that for the three-level factor the asymmetrical design confirms an expectation of having a (local) optimum in the examined domain, whilst from the two-level design this is not at all apparent. Complete optimisation was carried out for both UV and fluorescence detection. The two detection methods did not have the same significant variables. For the UV detection, the temperature and the pH adjustment on-line (concentration of sodium hydroxide and amount of boric acid) were the most critical parameters. For the fluorimetric detection the temperature and the fraction of methanol were critical. Moreover the conditions found to be optimal are different for both detection methods.

An experimental design approach to the optimisation of a flow injection analysis method for glycine.

A flow injection analysis method for the determination of glycine, based on the reaction with ortho-phtalaldehyde and N-acetylcysteine in a basic buffer, was optimised. In the first step screening of the variables, to select the most important ones, was performed using: (i) a half-fraction factorial design and (ii) a quarter-fraction factorial design, for five factors at two levels. The effects of the factors on the peak height were calculated from both screening designs and compared. For the half-fraction factorial design (resolution IV), the significance of the factor effects on the peak height was checked by: (i) comparing them with a critical effect, calculated from two-factor interactions and based on a t-test, (ii) using a non parametric approach and (iii) drawing a normal probability plot. For the quarter-fraction factorial design (resolution III) the significance of the effects of the factors on the peak height was checked using: (i) a randomization test method, (ii) the non parametric method and (iii) a normal probability plot. In the second step, the factor found to be of importance was optimised using the uniplex method.

Use of experimental design to optimise a flow injection analysis assay for L-N-monomethylarginine.

A flow injection analysis (FIA) method to determine L-N-monomethylarginine, based on the reaction with ortho-phthalaldehyde in the presence of a suitable thiol-group, was optimised using experimental design. Two different approaches were followed wherein, (i) critical factors were identified in a screening design, and (ii) the simplex algorithm was used for further optimisation. In the first approach, the chemical reaction was optimised off-line and the optimal chemical conditions were transferred to the FIA-system. In the second approach the reaction and the FIA-system parameters were optimised together. The on-line approach is preferred.