1,092 research outputs found
Risks and benefits of weaning immunosuppression in liver transplant recipients: Long-term follow-up
Probabilistic models of set-dependent and attribute-level best-worst choice
We characterize a class of probabilistic choice models where the choice probabilities depend on two scales, one with a value for each available option and the other with a value for the set of available options. Then, we develop similar results for a task in which a person is presented with a profile of attributes, each at a pre-specified level, and chooses the best or the best and the worst of those attribute-levels. The latter design is an important variant on previous designs using best-worst choice to elicit preference information, and there is various evidence that it yields reliable interpretable data. Nonetheless, the data from a single such task cannot yield separate measures of the "importance" of an attribute and the "utility" of an attribute-level. We discuss various empirical designs, involving more than one task of the above general type, that may allow such separation of importance and utility. © 2008 Elsevier Inc. All rights reserved
Discrete choice experiments are not conjoint analysis
We briefly review and discuss traditional conjoint analysis (CA) and discrete choice experiments (DCEs), widely used stated preference elicitation methods in several disciplines. We pay particular attention to the origins and basis of CA, and show that it is generally inconsistent with economic demand theory, and is subject to several logical inconsistencies that make it unsuitable for use in applied economics, particularly welfare and policy assessment. We contrast this with DCEs that have a long-standing, well-tested theoretical basis in random utility theory, and we show why and how DCEs are more general and consistent with economic demand theory. Perhaps the major message, though, is that many studies that claim to be doing conjoint analysis are really doing DCE
Immunosuppression for liver transplantation in HCV-infected patients: Mechanism-based principles
We retrospectively analyzed 42 hepatitis C virus (HCV)-infected patients who underwent cadaveric liver transplantation under two strategies of immunosuppression: (1) daily tacrolimus (TAC) throughout and an initial cycle of high-dose prednisone (PRED) with subsequent gradual steroid weaning, or (2) intraoperative antithymocyte globulin (ATG) and daily TAC that was later space weaned. After 36 ± 4 months, patient and graft survival in the first group was 18/19 (94.7%) with no examples of clinically serious HCV recurrence. In the second group, the three-year patient survival was 12/23 (52%), and graft survival was 9/23 (39%); accelerated recurrent hepatitis was the principal cause of the poor results. The data were interpreted in the context of a recently proposed immunologic paradigm that is equally applicable to transplantation and viral immunity. In the framework of this paradigm, the disparate hepatitis outcomes reflected different equilibria reached under the two immunosuppression regimens between the relative kinetics of viral distribution (systemically and in the liver) and the slowly recovering HCV-specific T-cell response. As a corollary, the aims of treatment of the HCV-infected liver recipients should be to predict, monitor, and equilibrate beneficial balances between virus distribution and the absence of an immunopathologic antiviral T-cell response. In this view, favorable equilibria were accomplished in the nonweaned group of patients but not in the weaned group. In conclusion, since the anti-HCV response is unleashed when immunosuppression is weaned, treatment protocols that minimize disease recurrence in HCV-infected allograft recipients must balance the desire to reduce immunosuppression or induce allotolerance with the need to prevent antiviral immunopathology. Copyright © 2005 by the American Association for the Study of Liver Diseases
Weaning of immunosuppression in long - Term liver transplant recipients
Seventy-two long-surviving liver transplant recipients were evaluated prospectively, including a baseline allograft biopsy for weaning off of immunosuppression. Thirteen were removed from candidacy because of chronic rejection (n=4), hepatitis (n=2), patient anxiety (n=5), or lack of cooperation by the local physician (n=2). The other 59, aged 12-68 years, had stepwise drug weaning with weekly or biweekly monitoring of liver function tests. Their original diagnoses were PBC (n=9), HCC (n=l), Wilson’s disease (n=4), hepatitides (n=15), Laennec’s cirrhosis (n=l), biliary atresia (n=16), cystic fibrosis (n=l), hemochromatosis (n=l), hepatic trauma (n=l), alpha-l-antitrypsin deficiency (n=9), and secondary biliary cirrhosis (n=l). Most of the patients had complications of long-term immunosuppression, of which the most significant were renal dysfunction (n=8), squamous cell carcinoma (n=2) or verruca vulgaris of skin (n=9), osteoporosis and/or arthritis (n=12), obesity (n=3), hypertension (n=ll), and opportunistic infections (n=2). When azathioprine was a third drug, it was stopped first. Otherwise, weaning began with prednisone, using the results of corticotropin stimulation testing as a guide. If adrenal insufficiency was diagnosed, patients reduced to <5 mg/day prednisone were considered off of steroids. The baseline agents (azathioprine, cyclospo-rine, or FK506) were then gradually reduced in monthly decrements. Complete weaning was accomplished in 16 patients (27.1%) with 3-19 months drug-free follow-up, is progressing in 28 (47.4%), and failed in 15 (25.4%) without graft losses or demonstrable loss of graft function from the rejections. This and our previous experience with self-weaned and other patients off of immunosuppression indicate that a significant percentage of appropriately selected long-surviving liver recipients can unknowingly achieve drug-free graft acceptance. Such attempts should not be contemplated until 5-10 years posttransplantation and then only with careful case selection, close monitoring, and prompt reinstitution of immunosuppression when necessary. © 1995 by Williams & Wilkins
Valuing the ICECAP capability index for older people
This paper reports the first application of the capabilities approach to the development and valuation of an instrument for use in the economic evaluation of health and social care interventions. The ICECAP index of capability for older people focuses on quality of life rather than health or other influences on quality of life, and is intended to be used in decision making across health and social care in the UK. The measure draws on previous qualitative work in which five conceptual attributes were developed: attachment, security, role, enjoyment and control. This paper details the innovative use within health economics of further iterative qualitative work in the UK among 19 informants to refine lay terminology for each of the attributes and levels of attributes used in the eventual index. For the first time within quality of life measurement for economic evaluation, a best-worst scaling exercise has been used to estimate general population values (albeit for the population of those aged 65+ years) for the levels of attributes, with values anchored at one for full capability and zero for no capability. Death was assumed to be a state in which there is no capability. The values obtained indicate that attachment is the attribute with greatest impact but all attributes contribute to the total estimation of capability. Values that were estimated are feasible for use in practical applications of the index to measure the impact of health and social care interventions. © 2008 Elsevier Ltd. All rights reserved
Estimating preferences for a dermatology consultation using Best-Worst Scaling: Comparison of various methods of analysis
Background: Additional insights into patient preferences can be gained by supplementing discrete choice experiments with best-worst choice tasks. However, there are no empirical studies illustrating the relative advantages of the various methods of analysis within a random utility framework.
Methods: Multinomial and weighted least squares regression models were estimated for a discrete choice experiment. The discrete choice experiment incorporated a best-worst study and was conducted in a UK NHS dermatology context. Waiting time, expertise of doctor, convenience of attending and perceived thoroughness of care were varied across 16 hypothetical appointments. Sample level preferences were estimated for all models and differences between patient subgroups were investigated using ovariateadjusted multinomial logistic regression.
Results: A high level of agreement was observed between results from the paired model (which is theoretically consistent with the 'maxdiff' choice model) and the marginal model (which is only an approximation to it). Adjusting for covariates showed that patients who felt particularly affected by their skin condition during the previous week displayed extreme preference for short/no waiting time and were less concerned about other aspects of the appointment. Higher levels of educational attainment were associated with larger differences in utility between the levels of all attributes, although the attributes per use had the same impact upon choices as those with lower levels of attainment. The study also demonstrated the high levels of agreement between summary analyses using weighted least squares and estimates from multinomial models.
Conclusion: Robust policy-relevant information on preferences can be obtained from discrete choice
experiments incorporating best-worst questions with relatively small sample sizes. The separation of the
effects due to attribute impact from the position of levels on the latent utility scale is not possible using
traditional discrete choice experiments. This separation is important because health policies to change the
levels of attributes in health care may be very different from those aiming to change the attribute impact
per se. The good approximation of summary analyses to the multinomial model is a useful finding, because weighted least squares choice totals give better insights into the choice model and promote greater familiarity with the preference data
Crohn's Disease Exacerbation Induced by Edwardsiella tarda Gastroenteritis
Exacerbations of Crohn's disease are not infrequently associated with bacterial gastroenteritis. The recognition of synchronous infections in such patients is vital for the initiation of appropriate antimicrobial therapy. Furthermore, the detection of active bacterial infections may lead the clinician to delay starting biological therapy. We report here a man presenting with an exacerbation of his Crohn's disease during a trip to Thailand. Stool cultures were positive for the unusual gut pathogen Edwardsiella tarda. The patient's symptoms resolved with concurrent antibiotic and steroid therapy. This finding demonstrates the value of performing stool culture in all patients presenting with exacerbations of inflammatory bowel diseases
Using geographically weighted regression to explore the spatially heterogeneous spread of bovine tuberculosis in England and Wales
An understanding of the factors that affect the spread of endemic bovine tuberculosis (bTB) is critical for the development of measures to stop and reverse this spread. Analyses of spatial data need to account for the inherent spatial heterogeneity within the data, or else spatial autocorrelation can lead to an overestimate of the significance of variables. This study used three methods of analysis—least-squares linear regression with a spatial autocorrelation term, geographically weighted regression (GWR) and boosted regression tree (BRT) analysis—to identify the factors that influence the spread of endemic bTB at a local level in England and Wales. The linear regression and GWR methods demonstrated the importance of accounting for spatial differences in risk factors for bTB, and showed some consistency in the identification of certain factors related to flooding, disease history and the presence of multiple genotypes of bTB. This is the first attempt to explore the factors associated with the spread of endemic bTB in England and Wales using GWR. This technique improves on least-squares linear regression approaches by identifying regional differences in the factors associated with bTB spread. However, interpretation of these complex regional differences is difficult and the approach does not lend itself to predictive models which are likely to be of more value to policy makers. Methods such as BRT may be more suited to such a task. Here we have demonstrated that GWR and BRT can produce comparable outputs
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