Suchergebnisse

Family history interviews are widely used in psychiatric research, as well as in genetic and twin studies, and provide a way to collect family history information quickly and economically. To obtain a valid assessment of family history, it is important to investigate which family member will be able to provide accurate information. Previous research shows that the validity of family history reporting can be influenced by characteristics of the informant, such as age, gender and personal history of psychiatric disorder. The aim of this study was to investigate the role of a subject's position in a pedigree on the validity of data collection. Family history data on diabetes and psychiatric disorders were collected in three generations of 33 families by interviewing both an index subject (3rd generation) and his or her mother (2nd generation). Mothers were shown to report higher rates of diabetes and psychiatric disorder in the family compared to the index subjects. There was no significant difference in the disease rate reported by male and female index subject. Mothers who experienced a depressive episode indicated significantly more family members as having a psychiatric disorder than mothers who never experienced such an episode. This could be explained by the presence of informant bias, but may also result from the fact that depression is a heritable disorder and is therefore actually more prevalent in these families. Our findings suggest that family interview data should be collected by interviewing subjects who have a central position in the pedigree and can therefore provide information on his/her own generation, the previous and the next. In addition, psychiatric status of the informant should be carefully addressed.

Aims: The aim of this study was to estimate the cost-effectiveness of nivolumab versus everolimus for second-line treatment of renal cell carcinoma (RCC) based on mature data, updated safety and decreased everolimus price. Materials and methods: A 3-state (pre-progression/progression-free disease, progressive disease and death) Markov model was developed from the perspective of the Australian health care system. Two scenarios were tested. Scenario 1 used 30-months clinical data and scenario 2 used updated 80-months clinical data with updated everolimus price. Inputs for quality-of-life and costs were informed by the literature and government sources. Incremental cost-effectiveness ratio (ICER) per quality adjusted life years (QALY) gained was reported and an ICER threshold of AU$75,000 was assumed. Threshold analysis was performed, and uncertainty was explored using one-way and probabilistic sensitivity analyses. Results: In scenario 1, the model estimated 1.73 QALYs at a cost of AU$105,000 for nivolumab and 1.48 QALYs at AU$38,000 for everolimus with an ICER = AU$266,871/QALY gained. A rebate of 54.4% was needed for nivolumab to reach the ICER threshold. For scenario 2, 1.93 QALYs at AU$111,418 was estimated for nivolumab and 1.60 QALYs at AU$31,942 for everolimus with an ICER of AU$213,320/QALY gained. The rebate needed to reach the ICER threshold was 54.9%. One-way sensitivity analyses for both scenarios showed that the cost of nivolumab, time horizon and utilities were main drivers. The cost-effectiveness acceptability curves highlighted the differences in cost-effectiveness of the two scenarios, as well as significant uncertainty in the results. Conclusions: A 54% rebate of the published price is needed for nivolumab to be cost-effective in Australia for the treatment of RCC. At that rebate, nivolumab remains cost-effective despite severe price erosion of everolimus because of improved longer term follow-up data. We recommend that generic price erosion should be accounted for when performing cost-effectiveness analysis.

NIH Public Access Policy requires that published journal articles resulting from NIH-funded research be made available to the public no later than 12 months after the date of publication. The public access mandate has been extended to NSF-funded research as well, and the government is moving toward making it a requirement for ALL federal funding. Non-compliance with this policy affects researchers because federal funding could be withheld. This presentation will introduce best practices for achieving compliance, and provide access to helpful resources, like the NIH Public Access Compliance video produced by UCI's Office of Research.