Patient-reported outcomes; Comparative effectiveness research; Patient-centered outcomes research; PRO; CER; PCOR
To link pediatric health-related quality of life (HRQOL) and health conditions by establishing clinically meaningful cutoff scores for a HRQOL instrument, the PedsQL.
We conducted telephone interviews with 1745 parents whose children were between 2–18 years old and enrolled in the Florida KidCare program and Children’s Medical Services Network in 2006. Two anchors, the Children with Special Health Care Needs (CSHCN) Screener and the Clinical Risk Groups (CRGs), were used to identify children with special health care needs or chronic conditions. We established cutoff scores for the PedsQL’s physical, emotional, social, school, and total functioning using the areas under the curves (AUCs) to determine the discriminative property of the PedsQL referring to the anchors.
The discriminative property of the PedsQL was superior, especially in total functioning (AUC > 0.7), between children with special health care needs (based on the CSHCN Screener) and with moderate and major chronic conditions (based on the CRGs) as compared to healthy children. For children < 8 years, the recommended cutoff scores for using total functioning to identify CSHCN were 83, 79 for moderate and 77 for major chronic conditions. For children ≥ 8 years, the cutoff scores were 78, 76 and 70, respectively.
Pediatric HRQOL varied with health conditions. Establishing cutoff scores for the PedsQL’s total functioning is a valid and convenient means to potentially identify children with special health care needs or chronic conditions. The cutoff sores can help clinicians to conduct further in-depth clinical assessments.
Children; clinically meaningful difference; cutoff; health-related quality of life; PedsQL
Generic preference-based measures were criticized for being inappropriate in some conditions. One solution is to include “bolt-on” dimensions describing additional specific health problems.
This study aimed to develop bolt-on dimensions to the EuroQol five-dimensional questionnaire (EQ-5D) and assess their impact on health state values.
Bolt-on dimensions were developed for vision problems, hearing problems, and tiredness. Each bolt-on dimension had three severity levels to match the EQ-5D. Three “core” EQ-5D states across a range of severity were selected, and each level of a bolt-on item was added, resulting in nine states in each condition. Health states with and without the bolt-on dimensions were valued by 300 members of the UK general public using time trade-off in face-to-face interviews, and mean health state values were compared using t tests. Regression analysis examined the impact of the bolt-on variants and the level of the bolt-on items after controlling for sociodemographic characteristics.
Bolt-on dimensions had an impact on health state values of the EQ-5D; however, the size, direction, and significance of the impact depend on the severity of the core EQ-5D state and of the bolt-on dimension. Regression analysis demonstrated that after controlling for possible differences in sociodemographic characteristics between the groups, there were no significant differences in health state values between the three bolt-on dimensions but confirmed that the impact depended on the severity of the EQ-5D health state and the levels of bolt-on dimensions.
The impact of a bolt-on dimension on the EQ-5D depends on the core health state and the level of the bolt-on dimension. Further research in this area is encouraged.
bolt-on; EQ-5D; health state valuation; hearing; tiredness; vision
Evidence-based healthcare decisions are best informed by comparisons of all relevant interventions used to treat conditions in specific patient populations. Observational studies are being performed to help fill evidence gaps. However, widespread adoption of evidence from observational studies has been limited due to a variety of factors, including the lack of consensus regarding accepted principles for their evaluation and interpretation. Two Task Forces were formed to develop questionnaires to assist decision makers in evaluating observational studies, with one Task Force addressing retrospective research and the other prospective research. The intent was to promote a structured approach to reduce the potential for subjective interpretation of evidence and drive consistency in decision-making. Separately developed questionnaires were combined into a single questionnaire consisting of 33 items. These were divided into two domains: relevance and credibility. Relevance addresses the extent to which findings, if accurate, apply to the setting of interest to the decision maker. Credibility addresses the extent to which the study findings accurately answer the study question. The questionnaire provides a guide for assessing the degree of confidence that should be placed from observational studies and promotes awareness of the subtleties involved in evaluating those.
bias; checklist; comparative effectiveness research; confounding; consensus; credibility; decision-making; epidemiologic research design; observational study methods; prospective observational study; publishing standards; quality; questionnaire; relevance; retrospective observational study; validity
The appropriate development of a model begins with understanding the problem that is being represented. The aim of this article was to provide a series of consensus-based best practices regarding the process of model conceptualization. For the purpose of this series of articles, we consider the development of models whose purpose is to inform medical decisions and health-related resource allocation questions. We specifically divide the conceptualization process into two distinct components: the conceptualization of the problem, which converts knowledge of the health care process or decision into a representation of the problem, followed by the conceptualization of the model itself, which matches the attributes and characteristics of a particular modeling type with the needs of the problem being represented. Recommendations are made regarding the structure of the modeling team, agreement on the statement of the problem, the structure, perspective, and target population of the model, and the interventions and outcomes represented. Best practices relating to the specific characteristics of model structure and which characteristics of the problem might be most easily represented in a specific modeling method are presented. Each section contains a number of recommendations that were iterated among the authors, as well as among the wider modeling taskforce, jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.
conceptualization; best practices; methods; modeling
The phase 3 trial, RESPOND-2, demonstrated that the addition of boceprevir (BOC) to peginterferon-ribavirin (PR) resulted in significantly higher rates of sustained virologic response (SVR) in previously treated patients with chronic hepatitis C virus (HCV) genotype-1 infection as compared with PR alone. We evaluated the cost-effectiveness of treatment with boceprevir in previously treated chronic hepatitis C patients in the United States utilizing treatment related data from RESPOND-2 and PROVIDE.
We developed a Markov cohort model to project the burden of HCV disease, lifetime costs and quality-adjusted life years (QALY) associated with PR and two BOC-based therapies—response-guided therapy (BOC/RGT) and fixed-duration therapy for 48 weeks (BOC/PR48). We estimated treatment related inputs (efficacy, adverse events, and discontinuations) from clinical trials and obtained disease progression rates, costs and quality-of-life data from published studies. We estimated the incremental cost-effectiveness ratio (ICER) for BOC-based regimens as studied in RESPOND-2, as well as by patient’s prior response to treatment and IL-28B genotype.
Boceprevir-based regimens were projected to reduce the lifetime incidence of liver-related complications by 43–53% in comparison with treatment with PR. The ICER of BOC/RGT in comparison with PR was $30,200, and the ICER of BOC/PR48 in comparison with BOC/RGT was $91,500. At $50,000 willingness-to-pay, the probabilities BOC/RGT and BOC/PR48 being the preferred option were 0.74 and 0.25, respectively.
In patients previously treated for chronic HCV genotype-1 infection, boceprevir was projected to increase QALYs and reduce the lifetime incidence of liver complications. In addition, boceprevir-based therapies were projected to be cost-effective in comparison with PR alone at commonly used willingness-to-pay thresholds.
protease inhibitor; Hepatitis C; Markov model; decision analytic
To estimate the cost-effectiveness of a trial of labor after one previous cesarean (TOLAC) when incorporating long-term events and outcomes.
A Markov model comparing TOLAC with elective repeat cesarean delivery (ERCD) was developed for a hypothetical cohort with no contraindication to a TOLAC. Women were selected from a prospective study to derive probability estimates for potential events through three subsequent pregnancies. Probabilities for cerebral palsy and stress urinary incontinence, cost data, and quality adjusted life years (QALYs) were obtained from the literature. The primary outcome was cost-effectiveness measured as the marginal cost per QALY gained, with a $50,000 threshold per QALY used to define cost-effectiveness.
The TOLAC strategy dominated the ERCD strategy at baseline, with $164.2 million saved and 500 QALYs gained per 100,000 women. The model was sensitive to six variables: the probability of uterine rupture and successful TOLAC among women with no prior vaginal delivery, the frequency of stress urinary incontinence, and the costs of failed TOLAC, successful TOLAC, and ERCD. When the probability of TOLAC success was at the base value, 67.2%, TOLAC was preferred if the probability of uterine rupture was 3.1% or less. When the probability of uterine rupture was at the base value, 0.8%, the TOLAC strategy was preferred as long as the probability of success was 47.2% or more. Probabilistic sensitivity analysis confirmed the base-case analysis.
Under baseline circumstances, TOLAC is less expensive and more effective than an ERCD when considering long-term consequences when the likelihood of success is 47.2% or more.
cost-effectiveness; trial of labor; elective repeat; accreta
Radical cystectomy (RC) is the standard treatment for muscle-invasive Urothelial carcinoma of the bladder (UCB). Tri-modality bladder preserving therapy (BPT) is an alternative to RC, but randomized comparisons of RC versus BPT have proven infeasible. To compare RC versus BPT, we undertook an observational cohort study using registry and administrative claims data from the SEER-Medicare database.
We identified patients age 65 years or older diagnosed between 1995 and 2005 who received RC (n=1,426) or BPT (n=417). We examined confounding and stage misclassification in the comparison of RC and BPT using multivariable adjustment, propensity score-based adjustment, instrumental variable (IV) analysis and simulations.
Patients who received BPT were older and more likely to have comorbid disease. After propensity score adjustment, BPT was associated with an increased hazard of death from any cause (HR 1.26; 95% CI, 1.05 – 1.53) and from bladder cancer (HR 1.31; 95% CI, 0.97 – 1.77). Using the local area cystectomy rate as an instrument, IV analysis demonstrated no differences in survival between BPT and RC (death from any cause HR 1.06; 95% CI, 0.78 – 1.31; death from bladder cancer HR 0.94; 95% CI, 0.55 – 1.18). Simulation studies for stage misclassification yielded results consistent with the IV analysis.
Survival estimates in an observational cohort of patients who underwent RC versus BPT differ by analytic method. Multivariable and propensity score adjustment revealed greater mortality associated with BPT relative to RC, while IV analysis and simulation studies suggest that the two treatments are associated with similar survival outcomes.
Comparative Effectiveness Research; Urinary bladder neoplasms; Cystectomy; Radiotherapy; Chemotherapy; SEER Program
The SF-6D preference-based scoring system was developed several years after the SF-12 and SF-36 instruments. A method to predict SF-6D scores from information in previous reports would facilitate backwards comparisons and the use of these reports in cost-effectiveness analyses.
This report uses data from the 2001–2003 Medical Expenditures Panel Survey (MEPS), the Beaver Dam Health Outcomes Survey, and the National Health Measurement Study. SF-6D scores were modeled using age, sex, mental component summary (MCS) score, and physical component summary (PCS) score from the 2002 MEPS. The resulting SF-6D prediction equation was tested with the other datasets for groups of different sizes and groups stratified by age, MCS score, PCS score, sum of MCS and PCS scores, and SF-6D score.
The equation can be used to predict an average SF-6D score using average age, proportion female, average MCS score, and average PCS score. Mean differences between actual and predicted average SF-6D scores in out-of-sample tests was −0.001 (SF-12 version 1), −0.013 (SF-12 version 2), −0.007 (SF-36 version 1), and −0.010 (SF-36 version 2). Ninety-five percent credible intervals around these point estimates range from ±0.045 for groups with 10 subjects to ±0.008 for groups with more than 300 subjects. These results were consistent for a wide range of ages, MCS scores, PCS scores, sum of MCS and PCS scores, and SF-6D scores. SF-6D scores from the SF-36 and SF-12 from the same data set were found to be substantially different.
Simple equation predicts an average SF-6D preference-based score from widely published information.
MCS; PCS; prediction; SF-6D; SF-36; SF-12
Invasive pneumococcal disease is a major cause of preventable morbidity and mortality in the United States, particularly among the elderly (>65 years). There are large racial disparities in pneumococcal vaccination rates in this population. Here, we estimate the cost-effectiveness of a hypothetical national vaccination intervention program designed to eliminate racial disparities in pneumococcal vaccination in the elderly.
In an exploratory analysis, a Markov decision-analysis model was developed, taking a societal perspective and assuming a 1-year cycle length, 10-year vaccination program duration, and lifetime time horizon. In the base-case analysis, it was conservatively assumed that vaccination program promotion costs were $10 per targeted minority elder per year, regardless of prior vaccination status and resulted in the elderly African American and Hispanic pneumococcal vaccination rate matching the elderly Caucasian vaccination rate (65%) in year 10 of the program.
The incremental cost-effectiveness of the vaccination program relative to no program was $45,161 per quality-adjusted life-year gained in the base-case analysis. In probabilistic sensitivity analyses, the likelihood of the vaccination program being cost-effective at willingness-to-pay thresholds of $50,000 and $100,000 per quality-adjusted life-year gained was 64% and 100%, respectively.
In a conservative analysis biased against the vaccination program, a national vaccination intervention program to ameliorate racial disparities in pneumococcal vaccination would be cost-effective.
cost-effectiveness; disparities; invasive pneumococcal disease; vaccination
A new method is presented for both synthesizing treatment effects on multiple outcomes subject to measurement error and estimating coherent mapping coefficients between all outcomes. It can be applied to sets of trials reporting different combinations of patient- or clinician-reported outcomes, including both disease-specific measures and generic health-related quality-of-life measures. It is underpinned by a structural equation model that includes measurement error and latent common treatment effect factor. Treatment effects can be expressed on any of the test instruments that have been used.
This is illustrated in a synthesis of eight placebo-controlled trials of TNF-α inhibitors in ankylosing spondylitis, each reporting treatment effects on between two and five of a total six test instruments.
The method has advantages over other methods for synthesis of multiple outcome data, including standardization and multivariate normal synthesis. Unlike standardization, it allows synthesis of treatment effect information from test instruments sensitive to different underlying constructs. It represents a special case of previously proposed multivariate normal models for evidence synthesis, but unlike the former, it also estimates mappings. Combining synthesis and mapping as a single operation makes more efficient use of available data than do current mapping methods and generates treatment effects that are consistent with the mappings. A limitation, however, is that it can only generate mappings to and from those instruments on which some trial data exist.
The method should be assessed in a wide range of data sets on different clinical conditions, before it can be used routinely in health technology assessment.
congeneric tests; cross-walking; mapping; multioutcome synthesis
Patient reported outcomes (PRO) assessing multiple gastrointestinal symptoms are central to characterizing the therapeutic benefit of novel agents for irritable bowel syndrome (IBS). Common approaches that sum or average responses across different illness components must be unidimensional and have small unique variances to avoid aggregation bias and misinterpretation of clinical data. This study sought to evaluate the unidimensionality of the IBS Symptom Severity Scale (IBS-SSS) and to explore person centered cluster analytic methods for characterizing multivariate-based patient profiles.
Ninety-eight Rome-diagnosed IBS patients completed the IBS-SSS and a single, global item of symptom severity (UCLA Symptom Severity Scale) at pretreatment baseline of an NIH funded clinical trial. A k-means cluster analyses were performed on participants symptom severity scores.
The IBS-SSS was not unidimensional. Exploratory cluster analyses revealed four common symptom profiles across five items of the IBS-SSS. One cluster of patients (25%) had elevated scores on pain frequency and bowel dissatisfaction, with less elevated but still high scores on life interference and low pain severity ratings. A second cluster (19%) was characterized by intermediate scores on both pain dimensions, but more elevated scores on bowel dissatisfaction. A third cluster (18%) was elevated across all IBS-SSS sub-components. The fourth and most common cluster (37%) had relatively low scores on all dimensions except bowel dissatisfaction and life interference due to IBS symptoms.
PRO endpoints and research on IBS more generally relying on multicomponent assessments of symptom severity should take into account the multidimensional structure of symptoms to avoid aggregation bias and to optimize the sensitivity of detecting treatment effects.
disease severity; questionnaire development; outcome research; health status indicators; rating scale; psychometric properties; global assessment
An article by Lu et al. in this issue of Value in Health addresses the mapping of treatment or group differences in disease-specific measures (DSMs) of health-related quality of life onto differences in generic health-related quality-of-life scores, with special emphasis on how the mapping is affected by the reliability of the DSM. In the proposed mapping, a factor analytic model defines a conversion factor between the scores as the ratio of factor loadings. Hence, the mapping applies to convert true underlying scales and has desirable properties facilitating the alignment of instruments and understanding their relationship in a coherent manner. It is important to note, however, that when DSM means or differences in mean DSMs are estimated, their mapping is still of a measurement error–prone predictor, and the correct conversion coefficient is the true mapping multiplied by the reliability of the DSM in the relevant sample. In addition, the proposed strategy for estimating the factor analytic mapping in practice requires assumptions that may not hold. We discuss these assumptions and how they may be the reason we obtain disparate estimates of the mapping factor in an application of the proposed methods to groups of patients.
cross-walk; HRQOL; mapping; reliability
In health technology assessment, decisions about reimbursement for new health technologies are largely based on effectiveness estimates. Sometimes, however, the target effectiveness estimates are not readily available. This may be because many alternative instruments measuring these outcomes are being used (and not all always reported) or an extended follow-up time of clinical trials is needed to evaluate long-term end points, leading to the limited data on the target clinical outcome. In the areas of highest priority in health care, decisions are required to be made on a short time scale. Therefore, alternative clinical outcomes, including surrogate end points, are increasingly being considered for use in evidence synthesis as part of economic evaluation.
To illustrate the potential effect of reduced uncertainty around the clinical outcome on the utility when estimating it from a multivariate meta-analysis.
Bayesian multivariate meta-analysis has been used to synthesize data on correlated outcomes in rheumatoid arthritis and to incorporate external data in the model in the form of informative prior distributions. Estimates of Health Assessment Questionnaire were then mapped onto the health-related quality-of-life measure EuroQol five-dimensional questionnaire, and the effect was compared with mapping the Health Assessment Questionnaire obtained from the univariate approach.
The use of multivariate meta-analysis can lead to reduced uncertainty around the effectiveness parameter and ultimately uncertainty around the utility.
By allowing all the relevant data to be incorporated in estimating clinical effectiveness outcomes, multivariate meta-analysis can improve the estimation of health utilities estimated through mapping methods. While reduced uncertainty may have an effect on decisions based on economic evaluation of new health technologies, the use of short-term surrogate end points can allow for early decisions. More research is needed to determine the circumstances under which uncertainty is reduced.
Bayesian analysis; health technology assessment; meta-analysis; multiple end points; rheumatoid arthritis; surrogate end points
To examine cost responsiveness and total costs associated with a simulated “value based” insurance design (VBID) for statin therapy in a Medicare population with diabetes.
Four-year panels constructed from the 1997–2005 Medicare Current Beneficiary Survey selected by self-report or claims-based diagnoses of diabetes in Year 1, and use of statins in Year 2 (N= 899). We computed number of 30-day statin prescription fills, out-of-pocket (OOP) and third party drug costs, and Medicare Part A and B spending.
Multivariate ordinary least squares regression models predicted statins fills as a function of OOP costs, and a generalized linear model with log link predicted Medicare spending as a function of number of fills, controlling for baseline characteristics. Estimated coefficients were used to simulate changes in fills associated with copayment caps from $25 to $1, and to compute changes in 3rd-party payments and Medicare cost offsets associated with incremental fills. Analyses were stratified by patient cardiovascular event risk.
A simulated OOP price of $25[$1] increased plan drug spending by $340[$794], and generated Medicare Part A/B savings of $262[$531]. Medicare Part A/B savings were greater for higher risk patients, generating a net savings for the plans.
Reducing statin copayments for Medicare beneficiaries with diabetes resulted in modestly increased use, and reduced medical spending. The VBID simulation strategy met financial feasibility criteria, but only for higher risk patients.
diabetes; Medicare; medication adherence; cost offsets
To describe rank reversal as a source of inconsistent interpretation intrinsic to indirect comparison (Bucher et al., 1997) of treatments and to propose best practice.
We prove our main points with intuition, examples, graphs, and mathematical proofs. We also provide software and discuss implications for research and policy.
When comparing treatments by indirect means and sorting them by effect size, three common measures of comparison (risk ratio, risk difference, and odds ratio) may lead to vastly different rankings.
The choice of risk measure matters when making indirect comparisons of treatments. The choice should depend primarily on the study design and conceptual framework for that study.
risk ratio; risk difference; odds ratio; indirect comparisons; risk
To develop a set of EQ-5D health state values for the Argentine general population.
Consecutive subjects attending six primary care centers in Argentina were selected based on quota sampling and interviewed using the EuroQol Group protocol for measurement and valuation of health studies. Initially respondents were randomly assigned a unique card set; however, to improve efficiency, subjects were later randomly assigned to one of three fixed sets of EQ-5D states. Using the VAS and TTO responses for these states, we estimated a valuation model using ordinary least squares regression clustered by respondent. Predicted values for EQ-5D health states are compared to published values for the United States.
Six hundred eleven subjects were interviewed by 14 trained interviewers, rendering 6,887 TTO and 6,892 VAS responses. The model had an R2 of 0.897 and 0.928 for TTO and VAS respectively. The mean absolute difference between observed and predicted values was 0.039 for TTO and 0.020 for VAS, each showing a Lin’s concordance coefficient above 0.98. United States and Argentine TTO predicted values were highly correlated (Pearson’s rho=0.963), though the average absolute difference was clinically meaningful (0.06), rejecting the US values for nearly two thirds of the states (62.8%). The Argentine population placed lower values on mild states and higher values on severe states.
This study provides an Argentine value set that could be used locally or regionally, with meaningful and significant differences with that of the US. Health policy in Latin America must incorporate local values for sovereignty and validity.
utility measurement; HRQOL; patient preference; cost effectiveness analysis
The EORTC QLQ-C30 is one of the most commonly used measures in cancer but in its current form cannot be used in economic evaluation as it does not incorporate preferences. We address this gap by estimating a preference-based single index for cancer from the EORTC QLQ-C30 for use in economic evaluation.
Factor analysis, Rasch analysis and other psychometric analyses were undertaken on a clinical trial dataset of 655 patients with Multiple Myeloma to derive a health state classification from the QLQ-C30 that is amenable to valuation. A valuation study was conducted of 350 members of the UK general population using ranking and time trade-off. A series of regression models were fitted to the data, including the episodic random utility model (RUM) to derive preference weights for the classification system.
The resulting health state classification system has 8 dimensions (physical functioning, role functioning, social functioning, emotional functioning, pain, fatigue and sleep disturbance, nausea, and constipation and diarrhoea) with 4 or 5 levels each. Mean and individual level additive multivariate regression models were estimated and compared. Mean absolute error ranges from 0.050 to 0.054 with no systematic errors. All models have few inconsistencies (0 to 2) in estimated preference weights.
It is feasible to derive a preference-based measure from the EORTC QLQ-C30 for use in economic evaluation, but this work needs to be extended to other countries and replicated across other conditions.
Preference-based measures; QALYs; EORTC QLQ-C30
It is well established that there are problems with the EQ-5D. This is in part due to the scoring methods used for the original UK EQ-5D (TTO) and in particular how negative-Time Trade Off (TTO) values were treated. [1–3] A revised scoring method has been published and this paper has used this to calculate utility estimates in an inflammatory arthritis cohort.
To examine the impact of a revised scoring system for the EQ-5D(UK) TTO on the utility estimates and compare these to estimates produced using the original scoring and the SF-6D. In the case of RA, to explore the impact of using different utility metrics on the on the ICER results of an economic model.
504 patients with inflammatory arthritis were rescored using a revised scoring system for the EQ-5D, which uses an episodic random utility model to deal with negative TTO values. Differences in utility scores were compared and the mapping coefficients were used in an economic model, to examine the impact on the ICER estimate.
In rheumatoid arthritis the overall change is less for the revised EQ-5D scoring than with the original EQ-5D (TTO) but greater than the SF-6D: EQ-5D UK −0.22 (95% CI −0.30, −0.15), revised EQ-5D UK −0.16 (95% CI −0.21, −0.10) and SF-6D −0.08 (95% CI −0.11, −0.05). A similar trend is seen in the psoriatic arthritis group. The economic model produced different ICERS, when different utility measures were used; EQ-5D (TTO) €42,402, SF-6D €111,788 and revised EQ-5D (TTO) €57,747.
In the context of inflammatory arthritis this article demonstrates that choice of utility measure may impact significantly on the output of the economic model and the subsequent reimbursement decision. In order to examine the heterogeneity between utility measures it may be useful to refit a cost effectiveness model using multiple metrics and produce a range of ICER estimates, to explore the uncertainty due to the choice of utility measure used.
To project the potential economic impact of pandemic influenza mitigation strategies from a societal perspective in the United States.
We use a stochastic agent-based model to simulate pandemic influenza in the community. We compare 17 strategies: targeted antiviral prophylaxis (TAP) alone and in combination with school closure as well as prevaccination.
In the absence of intervention, we predict a 50% attack rate with an economic impact of $187 per capita as loss to society. Full TAP is the most effective single strategy, reducing number of cases by 54% at the lowest cost to society ($127 per capita). Prevaccination reduces number of cases by 48% and is the second least costly alternative ($140 per capita). Adding school closure to full TAP or prevaccination further improves health outcomes, but increases total cost to society by approximately $2700 per capita.
Full targeted antiviral prophylaxis is an effective and cost-saving measure for mitigating pandemic influenza.
Influenza; Human Disease Outbreaks; Cost-Benefit Analysis; Economics; Pharmaceutical Models; Theoretical; Computer Simulation
To evaluate cost effectiveness of a socio-culturally adapted collaborative depression care program among low-income Hispanics with diabetes.
RESEARCH DESIGN AND METHODS
A randomized controlled trial of 387 diabetes patients (96.5% Hispanic) with clinically significant depression followed over 18 months evaluated the cost-effectiveness of the Multifaceted Diabetes and Depression Program (MDDP) aimed at increasing patient exposure to evidenced-based depression psychotherapy and/or pharmacotherapy in two public safety net clinics. Patient medical care costs and utilization were captured from Los Angeles County Dept. of Health Services claims records. Patient reported outcomes included SF-12 and PHQ-9-calculated depression-free days (DFDs).
Intervention patients had significantly greater SF-12 utility improvement from baseline compared to controls over the 18 month evaluation period (4.8%; P<.001) and a corresponding significant improvement in DFDs (43.0; P<.001). Medical cost differences were not statistically significant in OLS and log-transformed cost regressions. The average costs of the MDDP study intervention were $515 per patient. The program cost effectiveness averaged $4,053/QALY per MDDP recipient and was more than 90% likely to fall below $12,000/QALY.
Socio-culturally adapted collaborative depression care improved utility and quality of life in predominantly low income Hispanic diabetes patients and was highly cost effective.
depression; Diabetes-related complications; Direct care health costs; Cost-utility analysis; randomized clinical trial
effectiveness; evidence-based; hypertension; RECORD trial
Inverse probability of treatment weighted (IPTW) Kaplan-Meier estimates have been developed to compare two treatments in the presence of confounders in observational studies. Recently, stabilized weights were developed to reduce the influence of extreme IPTW weights in estimating treatment effects. The objective of this paper was to use adjusted Kaplan-Meier estimates and modified log-rank and Wilcoxon tests to examine the effect of a treatment which varies over time in an observational study.
In this paper, we propose stabilized weight (SW) adjusted Kaplan-Meier estimates and modified log-rank and Wilcoxon tests when the treatment is time-varying over the follow-up period. We applied these new methods in examining the effect of an anti-platelet agent, clopidogrel, on subsequent events, including bleeding, myocardial infarction, and death after a Drug-Eluting Stent was implanted into a coronary artery. In this population, clopidogrel use may change over time based on patients' behavior (e.g., non-adherence) and physicians' recommendations (e.g., end of duration of therapy). Consequently, clopidogrel use was treated as a time-varying variable.
We demonstrate that 1) the sample sizes at three chosen time points are almost identical in the original and weighted datasets, and 2) the covariates between patients on and off clopidogrel were well balanced after SWs were applied to the original samples.
The SW-adjusted Kaplan-Meier estimates and modified log-rank and Wilcoxon tests are useful in presenting and comparing survival functions for time-varying treatments in observational studies while adjusting for known confounders.
Observational study; Kaplan Meier estimates; Stabilized weights; Time-varying treatment; Stents
The NIH Patient-Reported Outcomes Measurement Information System (PROMIS) Roadmap initiative is a cooperative group program of research designed to develop, evaluate, and standardize item banks to measure patient-reported outcomes relevant across medical conditions. For adults, 11 domains have been developed in physical, mental, and social health.
The objective of the current study was to assess feasibility and construct validity of PROMIS item banks versus legacy measures in a observational study in systemic sclerosis (SSc).
Patients with SSc in a single academic center completed computerized adaptive technology (CAT) administered PROMIS item banks during the clinic visit and legacy domains (using paper-and-pencil). The construct validity of PROMIS items was evaluated by examining correlations with corresponding legacy measures using multitrait-multimethod analysis.
Participants consisted of 143 SSc patients with an average age of 51.5 years; 71% were female and 68% were Caucasian. The average number of items completed for each CAT-administered item bank ranged from 5 to 8 (69 CAT items per patient), and the average time to complete each CAT-administered item bank ranged from 48 seconds to 1.9 minutes per patient (average time= 11.9 minutes/per patient for 11 banks). All correlations between PROMIS domains and respective legacy measures were large and in the hypothesized direction (ranged from .61 to .82).
Our study supports the construct validity of the CAT-administered PROMIS item banks and shows that they can be administered successfully in a clinic with support staff. Future studies should assess the feasibility of PROMIS item banks in a busy clinical practice
Systemic sclerosis; PROMIS; health-related quality of life; construct validity