ABSTRACT
BACKGROUND: New technologies have enabled the potential for stratified medicine in psoriasis. It is important to understand patients' preferences to enable the informed introduction of stratified medicine, which is likely to involve a number of individual tests that could be collated into a prescribing algorithm for biological drug selection to be used in clinical practice. OBJECTIVES: To quantify patient preferences for an algorithm-based approach to prescribing biologics ('biologic calculator') in psoriasis. METHODS: An online survey comprising a discrete choice experiment (DCE) was conducted to elicit the preferences of two purposive samples of adults living with psoriasis in the UK, identified from a psoriasis patient organization (Psoriasis Association) and an online panel provider (Dynata). Respondents chose between two biologic calculators and conventional prescribing described using five attributes: treatment delay; positive predictive value; negative predictive value; risk of infection; and cost saving to the National Health Service. Each participant selected their preferred alternative from six hypothetical choice sets. Additional data, including sociodemographic characteristics, were collected. Choice data were analysed using conditional logit and fully correlated random parameters logit models. RESULTS: Data from 212 respondents (67 from the Psoriasis Association and 145 from Dynata) were analysed. The signs of all estimated coefficients were consistent with a priori expectations. Respondents had a strong preference for a high predictive accuracy and avoiding serious infection, but there was evidence of systematic differences in preferences between the samples. CONCLUSIONS: This study indicates that individuals with psoriasis would value a biologic calculator and suggested that such a biologic calculator should have sufficient accuracy to predict future response and risk of serious infection from the biologic.
Subject(s)
Patient Preference , Psoriasis , Adult , Choice Behavior , Humans , Logistic Models , Psoriasis/drug therapy , State Medicine , Surveys and QuestionnairesABSTRACT
Centronuclear myopathies (CNM) are a group of rare inherited muscular disorders leading to a significantly reduced quality of life and lifespan. To date, CNM epidemiologic reports provide limited incidence and prevalence data. Here, an integrated model utilizing available literature is proposed to obtain a better estimate of overall CNM patient numbers by age, causative gene, severity and geographic region. This model combines published epidemiology data and extrapolates limited data over CNM subtypes, resulting in patient numbers related to age and disease subtype. Further, the model calculates a CNM incidence twofold the current estimates. The estimated incidence of 17 per million births for severe X-linked myotubular myopathy (XLMTM), the main subtype of CNM, corresponds to an estimated prevalence of 2715 in the US, 1204 in the EU, 688 in Japan and 72 in Australia. In conclusion, the model provides an estimate of the CNM incidence, prevalence and survival, and indicates that the current estimates do not fully capture the true incidence and prevalence. With rapid advances in genetic therapies, robust epidemiologic data are needed to further quantify the reliability of incidence, prevalence and survival rates for the different CNM subtypes.
Subject(s)
Myopathies, Structural, Congenital/epidemiology , Humans , Incidence , Models, Theoretical , Myopathies, Structural, Congenital/genetics , PrevalenceABSTRACT
To study the effect of diet on 8-MOP plasma levels, these levels were measured three times in twenty PUVA patients with psoriasis; while fasting, after a low-fat breakfast, and after a fat-rich breakfast. No significant differences were found between the maximal 8-MOP plasma levels in the fasting condition and the levels after the low-fat breakfast, both peaking 2 h after ingestion. After the fat-rich breakfast, however, the 8-MOP plasma levels were not only significantly lower at 2 h but also peaked later, reaching their maximum at 3-4 h after intake. The drug should therefore be given in a dietetically standardized way. This raises the question whether some cases of therapy resistance can be dietetically influenced.
