5,153 research outputs found

    Orphan drugs and the NHS: Should we value rarity

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    Cost effectiveness plays an important part in current decisions about the funding of health technologies. Drugs for rare disease (orphan drugs) are often expensive to produce and, by definition, will benefit only small numbers of patients. Several countries have put measures in place to safeguard research and development of orphan drugs, but few get close to meeting the cost effectiveness criteria for funding by healthcare providers. We examine the justifications for special status for rare diseases and ask whether the cost effectiveness of drugs for rare or very rare diseases should be treated differently from that of other drugs and interventions

    Drugs for exceptionally rare diseases: a commentary on Hughes et al

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    Recently in this journal, Hughes and colleagues discussed special funding status to ultra-orphan drugs. They concluded that there should be a uniform policy for the provision of orphan drugs across Europe; that complete restriction was impractical, and that UK policy should aspire to the values of the EU directive on orphan drugs. We critically assess these arguments, demonstrating that they failed to justify special status for treatments for rare diseases

    Drugs for exceptionally rare diseases: a commentary on Hughes et al

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    Recently in this journal, Hughes and colleagues discussed special funding status to ultra-orphan drugs. They concluded that there should be a uniform policy for the provision of orphan drugs across Europe; that complete restriction was impractical, and that UK policy should aspire to the values of the EU directive on orphan drugs. We critically assess these arguments, demonstrating that they failed to justify special status for treatments for rare diseases

    Modelling the cost effectiveness of interferon beta and glatiramer acetate in the management of multiple sclerosis

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    OBJECTIVE: To evaluate the cost effectiveness of four disease modifying treatments (interferon betas and glatiramer acetate) for relapsing remitting and secondary progressive multiple sclerosis in the United Kingdom. DESIGN: Modelling cost effectiveness. SETTING: UK NHS. PARTICIPANTS: Patients with relapsing remitting multiple sclerosis and secondary progressive multiple sclerosis. MAIN OUTCOME MEASURES: Cost per quality adjusted life year gained. RESULTS: The base case cost per quality adjusted life year gained by using any of the four treatments ranged from £42 000 ($66 469; 61 630) to £98 000 based on efficacy information in the public domain. Uncertainty analysis suggests that the probability of any of these treatments having a cost effectiveness better than £20 000 at 20 years is below 20%. The key determinants of cost effectiveness were the time horizon, the progression of patients after stopping treatment, differential discount rates, and the price of the treatments. CONCLUSIONS: Cost effectiveness varied markedly between the interventions. Uncertainty around point estimates was substantial. This uncertainty could be reduced by conducting research on the true magnitude of the effect of these drugs, the progression of patients after stopping treatment, the costs of care, and the quality of life of the patients. Price was the key modifiable determinant of the cost effectiveness of these treatments

    Estimating population cardinal health state valuation models from individual ordinal (rank) health state preference data

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    Ranking exercises have routinely been used as warm-up exercises within health state valuation surveys. Very little use has been made of the information obtained in this process. Instead, research has focussed upon the analysis of health state valuation data obtained using the visual analogue scale, standard gamble and time trade off methods. Thurstone’s law of comparative judgement postulates a stable relationship between ordinal and cardinal preferences, based upon the information provided by pairwise choices. McFadden proposed that this relationship could be modelled by estimating conditional logistic regression models where alternatives had been ranked. In this paper we report the estimation of such models for the Health Utilities Index Mark 2 and the SF-6D. The results are compared to the conventional regression models estimated from standard gamble data, and to the observed mean standard gamble health state valuations. For both the HUI2 and the SF-6D, the models estimated using rank data are broadly comparable to the models estimated on standard gamble data and the predictive performance of these models is close to that of the standard gamble models. Our research indicates that rank data has the potential to provide useful insights into community health state preferences. However, important questions remain

    Estimating population cardinal health state valuation models from individual ordinal (rank) health state preference data

    Get PDF
    Ranking exercises have routinely been used as warm-up exercises within health state valuation surveys. Very little use has been made of the information obtained in this process. Instead, research has focussed upon the analysis of health state valuation data obtained using the visual analogue scale, standard gamble and time trade off methods. Thurstone’s law of comparative judgement postulates a stable relationship between ordinal and cardinal preferences, based upon the information provided by pairwise choices. McFadden proposed that this relationship could be modelled by estimating conditional logistic regression models where alternatives had been ranked. In this paper we report the estimation of such models for the Health Utilities Index Mark 2 and the SF-6D. The results are compared to the conventional regression models estimated from standard gamble data, and to the observed mean standard gamble health state valuations. For both the HUI2 and the SF-6D, the models estimated using rank data are broadly comparable to the models estimated on standard gamble data and the predictive performance of these models is close to that of the standard gamble models. Our research indicates that rank data has the potential to provide useful insights into community health state preferences. However, important questions remain.health state valuation; HUI-2; SF-6D

    Estimating population cardinal health state valuation models from individual ordinal (rank) health state preference data

    Get PDF
    Ranking exercises have routinely been used as warm-up exercises within health state valuation surveys. Very little use has been made of the information obtained in this process. Instead, research has focussed upon the analysis of health state valuation data obtained using the visual analogue scale, standard gamble and time trade off methods. Thurstone’s law of comparative judgement postulates a stable relationship between ordinal and cardinal preferences, based upon the information provided by pairwise choices. McFadden proposed that this relationship could be modelled by estimating conditional logistic regression models where alternatives had been ranked. In this paper we report the estimation of such models for the Health Utilities Index Mark 2 and the SF-6D. The results are compared to the conventional regression models estimated from standard gamble data, and to the observed mean standard gamble health state valuations. For both the HUI2 and the SF-6D, the models estimated using rank data are broadly comparable to the models estimated on standard gamble data and the predictive performance of these models is close to that of the standard gamble models. Our research indicates that rank data has the potential to provide useful insights into community health state preferences. However, important questions remain

    Orphan drugs revisited : [comment]

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    Hughes et al.1 recently discussed arguments for and against giving special funding status to orphan drugs in this journal. They concluded that there should be a uniform policy across Europe, that complete restriction was impractical, and that UK policy should aspire to the values of the EU directive. The aims of this paper are to correct some inaccuracies in the original paper, develop some of the key issues, and to draw some conclusions regarding the question ‘Do drugs for exceptionally rare disease deserve special status for funding?’ For ease, our paper adopts the same structure as the original

    Plane of nutrition affects the phylogenetic diversity and relative abundance of transcriptionally active methanogens in the bovine rumen

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    peer-reviewedMethane generated during enteric fermentation in ruminant livestock species is a major contributor to global anthropogenic greenhouse gas emissions. A period of moderate feed restriction followed by ad libitum access to feed is widely applied in cattle management to exploit the animal’s compensatory growth potential and reduce feed costs. In the present study, we utilised microbial RNA from rumen digesta samples to assess the phylogenetic diversity of transcriptionally active methanogens from feed-restricted and non-restricted animals. To determine the contribution of different rumen methanogens to methanogenesis during dietary restriction of cattle, we conducted high-throughput mcrA cDNA amplicon sequencing on an Illumina MiSeq and analysed both the abundance and phylogenetic origin of different mcrA cDNA sequences. When compared to their unrestricted contemporaries, in feed-restricted animals, the methanogenic activity, based on mcrA transcript abundance, of Methanobrevibacter gottschalkii clade increased while the methanogenic activity of the Methanobrevibacter ruminantium clade and members of the Methanomassiliicoccaceae family decreased. This study shows that the quantity of feed consumed can evoke large effects on the composition of methanogenically active species in the rumen of cattle. These data potentially have major implications for targeted CH4 mitigation approaches such as anti-methanogen vaccines and/or tailored dietary management
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