Australian Utility Weights for the EORTC QLU-C10D, a Multi-Attribute Utility Instrument Derived from the Cancer-Specific Quality of Life Questionnaire, EORTC QLQ-C30.

BACKGROUND: The EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely used cancer-specific quality-of-life (QOL) questionnaire, EORTC QLQ-C30. The QLU-C10D contains ten dimensions (Physical, Role, Social and Emotional Functioning; Pain, Fatigue, Sleep, Appetite, Nausea, Bowel Problems), each with four levels. To be used in cost-utility analysis, country-specific valuation sets are required. OBJECTIVE: The aim of this study was to provide Australian utility weights for the QLU-C10D. METHODS: An Australian online panel was quota-sampled to ensure population representativeness by sex and age (≥ 18 years). Participants completed a discrete choice experiment (DCE) consisting of 16 choice-pairs. Each pair comprised two QLU-C10D health states plus life expectancy. Data were analysed using conditional logistic regression, parameterised to fit the quality-adjusted life-year framework. Utility weights were calculated as the ratio of each QOL dimension-level coefficient to the coefficient on life expectancy. RESULTS: A total of 1979 panel members opted in, 1904 (96%) completed at least one choice-pair, and 1846 (93%) completed all 16 choice-pairs. Dimension weights were generally monotonic: poorer levels within each dimension were generally associated with greater utility decrements. The dimensions that impacted most on choice were, in order, Physical Functioning, Pain, Role Functioning and Emotional Functioning. Oncology-relevant dimensions with moderate impact were Nausea and Bowel Problems. Fatigue, Trouble Sleeping and Appetite had relatively small impact. The value of the worst health state was -0.096, somewhat worse than death. CONCLUSIONS: This study provides the first country-specific value set for the QLU-C10D, which can facilitate cost-utility analyses when applied to data collected with the EORTC QLQ-C30, prospectively and retrospectively.

Deriving a Preference-Based Measure for Myelofibrosis from the EORTC QLQ-C30 and the MF-SAF.

BACKGROUND: Utility values are required for economic evaluation using cost-utility analyses. Often, generic measures such as the EuroQol five-dimensional questionnaire are used, but this may not appropriately reflect the health-related quality of life of patients with cancer including myelofibrosis. OBJECTIVE: To derive a condition-specific preference-based measure for myelofibrosis using appropriate existing measures, the Myelofibrosis-Symptom Assessment Form and the European Organisation for Research and Treatment of Cancer Quality of Life 30 Questionnaire. METHODS: Data from the Controlled Myelofibrosis Study with Oral JAK Inhibitor Treatment trial (n = 309) were used to derive the health state classification system. Psychometric and factor analyses were used to determine the dimensions of the classification system. Psychometric and Rasch analyses were then used to select an item to represent each dimension. Item selection was validated with experts. A selection of health states was valued by members of the general population using time trade-off. Finally, health state values were modeled using regression analysis to produce utility values for every state. RESULTS: The Myelofibrosis 8 dimensions has eight dimensions: physical functioning, emotional functioning, fatigue, itchiness, pain under ribs on the left side, abdominal discomfort, bone or muscle pain, and night sweats. Regression models were estimated using time trade-off data from 246 members of the general population valuing a total of 33 states. The best performing model was a random effects maximum likelihood model producing utility values ranging from 0.089 to 1. CONCLUSIONS: The Myelofibrosis 8 dimensions is a condition-specific preference-based measure for myelofibrosis. This measure can be used to generate utility values for myelofibrosis for any data set containing the Myelofibrosis-Symptom Assessment Form and the European Organisation for Research and Treatment of Cancer Quality of Life 30 Questionnaire data.

Mapping Functions in Health-Related Quality of Life: Mapping from Two Cancer-Specific Health-Related Quality-of-Life Instruments to EQ-5D-3L.

BACKGROUND: Clinical trials in cancer frequently include cancer-specific measures of health but not preference-based measures such as the EQ-5D that are suitable for economic evaluation. Mapping functions have been developed to predict EQ-5D values from these measures, but there is considerable uncertainty about the most appropriate model to use, and many existing models are poor at predicting EQ-5D values. This study aims to investigate a range of potential models to develop mapping functions from 2 widely used cancer-specific measures (FACT-G and EORTC-QLQ-C30) and to identify the best model. METHODS: Mapping models are fitted to predict EQ-5D-3L values using ordinary least squares (OLS), tobit, 2-part models, splining, and to EQ-5D item-level responses using response mapping from the FACT-G and QLQ-C30. A variety of model specifications are estimated. Model performance and predictive ability are compared. Analysis is based on 530 patients with various cancers for the FACT-G and 771 patients with multiple myeloma, breast cancer, and lung cancer for the QLQ-C30. RESULTS: For FACT-G, OLS models most accurately predict mean EQ-5D values with the best predicting model using FACT-G items with similar results using tobit. Response mapping has low predictive ability. In contrast, for the QLQ-C30, response mapping has the most accurate predictions using QLQ-C30 dimensions. The QLQ-C30 has better predicted EQ-5D values across the range of possible values; however, few respondents in the FACT-G data set have low EQ-5D values, which reduces the accuracy at the severe end. CONCLUSIONS: OLS and tobit mapping functions perform well for both instruments. Response mapping gives the best model predictions for QLQ-C30. The generalizability of the FACT-G mapping function is limited to populations in moderate to good health.

Comparison of general population, patient, and carer utility values for dementia health states.

Utility values to estimate quality-adjusted life years (QALYs) for use in cost-utility analyses are usually elicited from members of the general population. Public attitudes and understanding of dementia in particular may mean that values elicited from the general population may differ from patients and carers for dementia health states. This study examines how the population impacts utility values elicited for dementia health states using interviewer-administered time tradeoff valuation of health states defined by the dementia-specific preference-based measures DEMQOL-U (patient-report) and DEMQOL-Proxy-U (carer-report). Eight DEMQOL-U states were valued by 78 members of the UK general population and 71 patients with dementia of mild severity. Eight DEMQOL-Proxy-U states were valued by 77 members of the UK general population and 71 carers of patients with dementia of mild severity. Random-effects generalized least squares regression estimated the impact of population, dementia health state, and respondent sociodemographic characteristics on elicited values, finding that values for dementia health states differed by population and that the difference varied across dementia health states. Patients with dementia and carers of patients with dementia gave systematically lower values than members of the general population that were not due to differences in the sociodemographic characteristics of the populations. Our results suggest that the population used to produce dementia health state values could impact the results of cost-utility analyses and potentially affect resource allocation decisions; yet, currently, only general population values are available for usage.

Deriving a preference-based utility measure for cancer patients from the European Organisation for the Research and Treatment of Cancer's Quality of Life Questionnaire C30: a confirmatory versus exploratory approach.

BACKGROUND: Multi attribute utility instruments (MAUIs) are preference-based measures that comprise a health state classification system (HSCS) and a scoring algorithm that assigns a utility value to each health state in the HSCS. When developing a MAUI from a health-related quality of life (HRQOL) questionnaire, first a HSCS must be derived. This typically involves selecting a subset of domains and items because HRQOL questionnaires typically have too many items to be amendable to the valuation task required to develop the scoring algorithm for a MAUI. Currently, exploratory factor analysis (EFA) followed by Rasch analysis is recommended for deriving a MAUI from a HRQOL measure. AIM: To determine whether confirmatory factor analysis (CFA) is more appropriate and efficient than EFA to derive a HSCS from the European Organisation for the Research and Treatment of Cancer's core HRQOL questionnaire, Quality of Life Questionnaire (QLQ-C30), given its well-established domain structure. METHODS: QLQ-C30 (Version 3) data were collected from 356 patients receiving palliative radiotherapy for recurrent/metastatic cancer (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and CFA, the latter informed by the established QLQ-C30 structure and views of both patients and clinicians on which are the most relevant items. Dimensions determined by EFA or CFA were then subjected to Rasch analysis. RESULTS: CFA results generally supported the proposed QLQ-C30 structure (comparative fit index =0.99, Tucker-Lewis index =0.99, root mean square error of approximation =0.04). EFA revealed fewer factors and some items cross-loaded on multiple factors. Further assessment of dimensionality with Rasch analysis allowed better alignment of the EFA dimensions with those detected by CFA. CONCLUSION: CFA was more appropriate and efficient than EFA in producing clinically interpretable results for the HSCS for a proposed new cancer-specific MAUI. Our findings suggest that CFA should be recommended generally when deriving a preference-based measure from a HRQOL measure that has an established domain structure.

Improvement in nutritional status reduces the clinical impact of infections in older adults.

OBJECTIVES: To determine the effect of a dietary intervention and micronutrient supplementation on self-reported infections in older adults. DESIGN: A randomized, placebo-controlled intervention trial. SETTING: Community living older people in South Yorkshire, United Kingdom. PARTICIPANTS: Two-hundred seventeen older adults aged 65 to 85. INTERVENTION: Participants were randomized to a dietary intervention, a daily micronutrient supplement, or placebo for 3 months, with a 3-month follow-up. MEASUREMENTS: Self-reported measures of infection were reported over the 6-month study period. Secondary outcome measures were nutritional status, dietary intake, quality of life, and depression. RESULTS: Self-reported measures of infection over the 6-month duration of the study were significantly different between the treatment groups. The number of weeks in which illness affected life and the number of general practitioner and hospital visits were significantly lower in the food and micronutrient groups than in the placebo group. The number of weeks in which symptoms of an infection were described was significantly lower in the food group than the placebo and micronutrient groups. Significant improvements in biomarkers of micronutrient status were achieved in the food and micronutrient groups and showed significantly greater change than observed in the placebo group. Significant improvement in dietary intakes was observed in the food group only. CONCLUSION: Improving dietary intake and micronutrient status reduces the clinical impact of self-reported infections in older adults.

Improving the measurement of QALYs in dementia: developing patient- and carer-reported health state classification systems using Rasch analysis.

OBJECTIVES: Cost-utility analysis is increasingly used to inform resource allocation. This requires a means of valuing health states before and after intervention. Although generic measures are typically used to generate values, these do not perform well with people with dementia. We report the development of a health state classification system amenable to valuation for use in studies of dementia, derived from the DEMQOL system, measure of health-related quality of life in dementia by patient self-report (DEMQOL) and carer proxy-report (DEMQOL-Proxy). METHODS: Factor analysis was used to determine the dimensional structure of DEMQOL and DEMQOL-Proxy. Rasch analysis was subsequently used to investigate item performance across factors in terms of item-level ordering, functioning across subgroups, model fit, and severity-range coverage. This enabled the selection of one item from each factor for the classification system. A sample of people with a diagnosis of mild/moderate dementia (n = 644) and a sample of carers of those with mild/moderate dementia (n = 683) were used. RESULTS: Factor analysis found different five-factor solutions for DEMQOL and DEMQOL-Proxy. Following item reduction and selection by using Rasch analysis, a five-dimension classification for DEMQOL and a four-dimension classification for DEMQOL-Proxy were developed. Each item contained four health state levels. CONCLUSION: Combining Rasch and classical psychometric analysis is a valid method of selecting items for dementia health state classifications from both the patient and carer perspectives. The next stage is to obtain preference weights so that the measure can be used in the economic evaluation of treatment, care, and support arrangements for dementia.

Estimating preference-based single index measures for dementia using DEMQOL and DEMQOL-Proxy.

OBJECTIVE: Although condition-specific measures are commonly used in dementia, they cannot be used in analyses of cost per quality-adjusted life-year because they do not incorporate preferences. We addressed this gap by estimating two preference-based single index measures: the DEMQOL-U from the self-report DEMQOL (mild-to-moderate dementia severity) and the DEMQOL-Proxy-U from the carer-report DEMQOL-Proxy (all levels of dementia severity). METHODS: We conducted valuation studies on 593 members of the general population (306 for the DEMQOL-U, 287 for the DEMQOL-Proxy-U) using the time trade-off elicitation technique. We then fitted a range of mean and individual-level multivariate regression models to the valuation data to derive preference weights for each measure. We applied the estimated weights to a large, clinically representative sample. RESULTS: Mean observed time trade-off values ranged from 0.18 to 0.95 for DEMQOL-U and from 0.33 to 0.96 for DEMQOL-Proxy-U. The best performing models for each measure were main effects models estimated using individual-level data. DEMQOL-Proxy-U had inconsistent but insignificant coefficient estimates for one dimension. Models were estimated to remove these inconsistencies. CONCLUSION: Preference-based single index measures from DEMQOL and DEMQOL-Proxy for use in economic evaluation will enable economic evaluation using quality-adjusted life-years to be undertaken for people across the full range of dementia severity. Future research will examine how the utilities from each measure can be used and combined to populate cost-effectiveness models.

Rasch analysis in the development of a simplified version of the National Eye Institute Visual-Function Questionnaire-25 for utility estimation.

PURPOSE: Preference-based health measures value how people feel about the desirability of a health state. Generic measures may not effectively capture the impact of vision loss from ocular diseases. Disease-targeted measures could address this limitation. This study developed a vision-targeted health state classification system based on the National Eye Institute Visual Function Questionnaire-25 (NEI VFQ-25). METHODS: Secondary analysis of NEI VFQ-25 data from studies of patients with central (n = 932)- and peripheral-vision loss (n = 2,451) were used to develop a health state classification system. Classical test theory and Rasch analyses were used to identify a smaller set of NEI VFQ-25 items suitable for the central- and peripheral-vision-loss groups. RESULTS: Rasch analysis of the NEI VFQ-25 items using the peripheral vision-loss data indicated that 11 items fit a unidimensional model, while 14 NEI VFQ-25 items fit using the central-vision-loss data. Combining peripheral-vision-loss data and central-vision-loss data resulted in 9 items fitting a unidimensional model. Six items covering near vision, distance vision, social vision, role difficulties, vision dependency, and vision-related mental health were selected for the health-state classification. CONCLUSIONS: The derived health-state classification system covers relevant domains of vision-related functioning and well-being.

The use of rasch analysis in reducing a large condition-specific instrument for preference valuation: the case of moving from AQLQ to AQL-5D.

The majority of health-related quality-of-life instruments are not preference-based measures and so cannot be used within cost utility analysis. The Asthma Quality of Life Questionnaire (AQLQ) is one such instrument. The aim of this study was to develop a health state classification that was amenable to valuation from the AQLQ, this being the 1st stage in developing a condition-specific preference-based measure for asthma patients. Rasch models were applied to samples of responders to the AQLQ with the aim of selecting a number of items for a preference-based utility measure (AQL-5D). Selection of items for the evaluation survey was supported with classical psychometric criteria for item selection (feasibility, internal consistency, floor and ceiling effects, and responsiveness). Rasch analysis proved to be a useful tool in assisting in the initial process of selecting items from an existing health-related quality-of-life instrument in the construction of the AQL-5D. The method is recommended for use alongside classical psychometric testing to aid in the development of preference-based measures.

Estimating a preference-based index for a 5-dimensional health state classification for asthma derived from the asthma quality of life questionnaire.

BACKGROUND: This article presents a valuation study to estimate a preference-based index for a 5-dimensional health state classification for asthma (AQL-5D) derived from the Asthma Quality of Life Questionnaire (AQLQ). METHODS: A sample of 307 members of the UK general population valued 99 asthma health states selected from the AQL-5D using the time tradeoff technique. Models were estimated to predict all possible 3125 health states defined by the AQL-5D, and the models were compared in terms of their ability to predict mean values for the 99 states. RESULTS: Mean health state values ranged from 0.39 to 0.94 based on an average of 22 valuations per state. A main effects model estimated on mean health state values and adjusted for consistency had the best predictive ability (mean absolute error of 0.047 and only 9/98 states with errors >0.1) and the most logical consistency with levels of the AQL-5D. The low number of valuations per state may have resulted in unreliable estimates for the models. Preference-based condition specific measures are limited in their ability to make cross-disease comparisons. CONCLUSION: This is the first study to derive a condition-specific preference-based measure from an existing measure of health-related quality of life in asthma for use in economic evaluation.

Using Rasch analysis to form plausible health states amenable to valuation: the development of CORE-6D from a measure of common mental health problems (CORE-OM).

PURPOSE: To describe a new approach for deriving a preference-based index from a condition specific measure that uses Rasch analysis to develop health states. METHODS: The CORE-OM is a 34-item instrument monitoring clinical outcomes of people with common mental health problems. The CORE-OM is characterised by high correlation across its domains. Rasch analysis was used to reduce the number of items and response levels in order to produce a unidimensional measure and to generate a credible set of health states corresponding to different levels of symptom severity using the Rasch item threshold map. RESULTS: The proposed methodology resulted in the development of CORE-6D, a 2-dimensional health state descriptive system consisting of a unidimensional 5-item emotional component (derived from Rasch analysis) and a physical symptom item. Inspection of the Rasch item threshold map of the emotional component helped identify a set of 11 plausible health states, which, combined with 3 physical symptom item levels, form 33 plausible health states that can be used for the valuation of the instrument, resulting in the development of a preference-based index. CONCLUSIONS: This is a useful new approach to develop preference-based measures from existing instruments with high correlations across domains. The CORE-6D preference-based index will enable calculation of Quality-Adjusted Life Years in people with common mental health problems.

Developing preference-based health measures: using Rasch analysis to generate health state values.

PURPOSE: Condition-specific measures may not always have independent items, yet existing techniques of developing health state utility values from these measures are inappropriate when items are not independent. This study develops methods for deriving and valuing health states for a condition-specific preference-based measure where items are not independent. METHODS: The analysis has three stages: firstly, Rasch analysis is used to develop a health state classification system from the Flushing Symptoms Questionnaire (FSQ) that is amenable to valuation and to identify a set of health states for valuation. Secondly, a valuation survey of the health states using time-trade-off (TTO) methods is conducted to elicit health state values. Finally, regression models are applied to map the relationship between mean TTO values and Rasch logit values. The model is then used to estimate health state values for all possible health states. RESULTS: Rasch models were fitted to 1,270 responders to the FSQ and a series of 16 health states were identified for the valuation exercise. An ordinary least squares model best described the relationship between mean TTO values and Rasch logit values (R (2) = 0.958; root mean square error = 0.042). CONCLUSIONS: This study demonstrates how health state utility values can be mapped onto Rasch logit values in order to value all states defined by the FSQ, a condition-specific measure where items are not independent. This should significantly enhance research in this field.

Folate status and aberrant DNA methylation are associated with HPV infection and cervical pathogenesis.

Aberrant DNA methylation is a recognized feature of human cancers, and folate is directly involved in DNA methylation via one-carbon metabolism. Previous reports also suggest that folate status is associated with the natural history of human papillomavirus (HPV) infection. A cross-sectional study was conducted to test the hypothesis that folate status and aberrant DNA methylation show a progressive change across stages of cervical pathology from normal cells to cervical cancer. Additionally, we postulated that a gene-specific hypermethylation profile might be used as a predictive biomarker of cervical cancer risk. DNA hypermethylation of seven tumor suppressor genes, global DNA hypomethylation, systemic folate status, and HPV status were measured in 308 women with a diagnosis of normal cervix (n = 58), low-grade cervical intraepithelial neoplasia (CIN1; n = 68), high-grade cervical intraepithelial neoplasia (CIN2, n = 56; and CIN3, n = 76), or invasive cervical cancer (ICC; n = 50). Lower folate status was associated with high-risk HPV infection (P = 0.031) and with a diagnosis of cervical intraepithelial neoplasia or invasive cervical cancer (P < 0.05). Global DNA hypomethylation was greater in women with invasive cervical cancer than all other groups (P < 0.05). A cluster of three tumor suppressor genes, CDH1, DAPK, and HIC1, displayed a significantly increased frequency of promoter methylation with progressively more severe cervical neoplasia (P < 0.05). These findings are compatible with a role for folate in modulating the risk of cervical cancer, possibly through an influence over high-risk HPV infection. DAPK, CDH1, and HIC1 genes are potential biomarkers of cervical cancer risk.

Cost implications of introducing a telecardiology service to support fetal ultrasound screening.

A district hospital in south-east England used a telecardiology service for fetal cardiac diagnosis alongside an existing arrangement for referring pregnant women directly to perinatal cardiologists in London for detailed fetal echocardiography. Women were identified for referral according to local protocols when having a second trimester anomaly scan. For the telemedicine referrals, the sonographers video-recorded images from the anomaly scans for transmission during monthly videoconferences. The cost of the women's antenatal care was calculated from the specialist assessment until delivery, while family costs were collected in a postal survey. Over 15 months, telemedicine was used in 52 cases, while 24 women were seen in London. The London women were more likely to have had an ultrasound abnormality (29% v 10%, P = 0.047). A telemedicine assessment of 5 min duration was more costly than an examination in London (mean cost per referral of pound206 v pound74, P < 0.001). However, the telecardiology service was cost neutral after 14 days and for the extended period until delivery. Travel costs for London women averaged pound37 compared with pound5.50 for the telemedicine referrals. Telemedicine may be useful to support perinatal cardiologists in the UK whose workloads are expanding in response to improved standards in antenatal ultrasound screening.

Effects of 4-hydroxynonenal on mitochondrial 3-hydroxy-3-methylglutaryl (HMG-CoA) synthase.

Chronic ethanol consumption causes increased production of reactive oxygen species in hepatic mitochondria accompanied by elevations in products of lipid peroxidation such as 4-hydroxynonenal (4-HNE). In the current study we investigated the effects of chronic ethanol consumption on a prominent protein-4-HNE adduct in liver mitochondria. Male Sprague-Dawley rats were fed a liquid diet for 31 days in which ethanol constituted 36% of total calories. Immunoblot analyses of liver mitochondria from ethanol-fed and control animals, using an antibody to a 4-HNE-protein adduct, demonstrated elevated 4-HNE binding (+50%) to a mitochondrial protein of approximately 55 kDa due to chronic ethanol consumption. Analysis of this protein using AspN digestion and tandem mass spectrometry identified it as the mitochondrial form of 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) synthase. Activity of the activated form of this enzyme was unchanged in livers from ethanol-fed animals, but the protein level was elevated by 36%, which suggests a compensatory mechanism to maintain constant levels of synthase activity in the mitochondrion in the face of continuous inactivation by 4-HNE. Treatment of isolated mitochondria with 4-HNE demonstrated that the enzyme activity decreased as a function of 4-HNE concentration and with time of exposure. This study demonstrates that ethanol consumption increases the formation of a 4-HNE adduct with mitochondrial HMG-CoA synthase, which has the potential to inactivate the enzyme in situ.

Telemedicine in pediatric and perinatal cardiology: economic evaluation of a service in English hospitals.

OBJECTIVES: Pediatric cardiology has an expanding role in fetal and pediatric screening. The aims of this study were to observe how district hospitals use a pediatric telecardiology service, and to compare the costs and outcomes of patients referred to specialists by means of this service or conventionally. METHODS: A telemedicine service was set up between a pediatric cardiac center in London and four district hospitals for referrals of second trimester women, newborn babies, and older children. Clinicians in each hospital decided on the role for their service. Clinical events were audited prospectively and costed, and patient surveys were conducted. RESULTS: The hospitals differed in their selection of patient groups for the service. In all, 117 telemedicine patients were compared with 387 patients seen in London or in outreach clinics. Patients selected for telemedicine were generally healthier. For all patients, the mean cost for the initial consultation was 411 UK pounds for tele-referrals and 277 UK pounds for conventional referrals, a nonsignificant difference. Teleconsultations for women and children were significantly more expensive because of technology costs, whereas for babies, ambulance transfers were much more costly. After 6-months follow-up, the difference between referral methods for all patients was nonsignificant (telemedicine, 3,350 UK pounds; conventional referrals, 2,172 UK pounds), and nonsignificant within the patient groups. CONCLUSIONS: Telemedicine was perceived by cardiologists, district clinicians, and families as reliable and efficient. The equivocal 6-month cost results indicate that investment in the technology is warranted to enhance pediatric and perinatal cardiology services.

Chronic ethanol consumption decreases mitochondrial and glycolytic production of ATP in liver.

AIMS: The synthesis of ATP in the liver of the chronic ethanol consumer is suppressed, particularly if the tissue becomes hypoxic. Moreover, the perivenous region of the liver lobule becomes even more oxygen deficient as a result of ethanol consumption. Synthesis of ATP in the perivenous region of the lobule may be depressed in the chronic ethanol consumer due to decreases in both mitochondrial and glycolytic activities. In this study the effects of hypoxia on hepatic ATP levels derived from synthesis by both oxidative phosphorylation and the glycolytic mechanisms were investigated. METHODS: Rats were pair-fed liquid diets containing 36% of calories as ethanol or an isocaloric control diet. The contributions of glycolysis and mitochondria to ATP production were assessed employing oligomycin, an inhibitor of oxidative phosphorylation. In order to localize the ethanol-elicited lesion in the glycolytic pathway, the metabolism of [3-(3)H] D-glucose was followed in hepatocytes from ethanol-fed and control animals. RESULTS: Under both hypoxic and normoxic conditions ATP losses were due to decreases in both glycolytic and mitochondrial ATP production. The rate of production of tritiated water from [3-(3)H] D-glucose was significantly decreased in hepatocytes from ethanol-fed animals, which indicates there is an ethanol-elicited lesion in glycolysis between glucose and glyceraldehyde-3-phosphate.

Estimating mean total costs in the presence of censoring: a comparative assessment of methods.

INTRODUCTION: Frequently, within economic evaluations, data are subject to censoring, and ignoring censored data will lead to an underestimation of mean total costs. Several techniques have been published that can be used to estimate mean total costs and standard errors, and allow for censoring within cost data. This paper reviews these techniques and compares the mean total costs estimates generated by each method for different types of censoring. METHODS: Nine techniques were identified that can be used to estimate mean total costs and standard errors in the presence of censoring: ignoring censoring; ignoring censored costs; Lin's method--with and without cost histories; weighted cost method--with and without cost histories; Lin's regression method--with and without cost histories; and Carides' regression method. These methods are compared across four different censoring mechanisms--random censoring, end-of-study censoring, informative censoring and partial censoring--by simulating the censoring mechanisms from a complete cohort of patients included in the CELT (Cost Effectiveness of Liver Transplantation) study. RESULTS: The observed mean cost and standard error from the CELT data were 36,045 pounds sterling and 1517 pounds sterling (1998 values). Estimates under informative censoring were the least accurate predictors of mean total costs and tended to overestimate mean costs by > 1000 pounds sterling. Carides' regression method predicted mean total costs to within 3 pounds sterling of the observed mean and represented one of the three most accurate methods for predicting mean total costs (together with the weighted cost method with known cost histories and Lin's method with unknown cost histories). Lin's method with known cost histories gave the least accurate estimates of mean total costs and underpredicted costs by 2137-4859 pounds sterling across censoring mechanisms. Carides' method did not predict uncertainty around the mean costs well, and the weighted cost method with known cost histories and ignoring censoring were the best methods to use for estimating the standard error of the mean cost. CONCLUSIONS: Further work should be carried out on other datasets to confirm the generalisability of these results. Although Carides' regression method and Lin's method with unknown cost histories were the best estimators of mean total costs across censoring mechanisms, the weighted cost method with known cost histories is the preferred method for obtaining an accurate estimate of the mean total cost alone and the uncertainty surrounding it; therefore, it should be used to estimate mean costs and standard errors when patient cost histories are known.

The importance of accounting for the uncertainty of published prognostic model estimates.

OBJECTIVES: Reported is the importance of properly reflecting uncertainty associated with prognostic model estimates when calculating the survival benefit of a treatment or technology, using liver transplantation as an example. METHODS: Monte Carlo simulation techniques were used to account for the uncertainty of prognostic model estimates using the standard errors of the regression coefficients and their correlations. These methods were applied to patients with primary biliary cirrhosis undergoing liver transplantation using a prognostic model from a historic cohort who did not undergo transplantation. The survival gain over 4 years from transplantation was estimated. RESULTS: Ignoring the uncertainty in the prognostic model, the estimated survival benefit of liver transplantation was 16.7 months (95 percent confidence interval [CI], 13.5 to 20.1), and was statistically significant (p < .001). After adjusting for model uncertainty using the standard errors of the regression coefficients, the estimated survival benefit was 17.5 months (95 percent CI, -3.9 to 38.5) and was no longer statistically significant. An additional adjustment for the correlation between regression coefficients widened the 95 percent confidence interval slightly: the estimated survival benefit was 17.0 months (95 percent CI: -4.6 to 38.6). CONCLUSIONS: It is important that the precision of regression coefficients is available for users of published prognostic models. Ignoring this additional information substantially underestimates uncertainty, which can then impact misleadingly on policy decisions.