Evaluating Matching‐Adjusted Indirect Comparisons in Practice: A Case Study of Patients with Attention‐Deficit/Hyperactivity Disorder

Differences in patient characteristics across trials may bias efficacy estimates from indirect treatment comparisons. To address this issue, matching‐adjusted indirect comparison (MAIC) measures treatment efficacy after weighting individual patient data to match patient characteristics across trials. To date, however, there is no consensus on how best to implement MAIC. To address this issue, we applied MAIC to measure how two attention‐deficit/hyperactivity disorder (ADHD) treatments (guanfacine extended release and atomoxetine hydrochloride) affect patients' ADHD symptoms, as measured by the ADHD Rating Scale IV score. We tested MAIC sensitivity to: matched patient characteristics, matched statistical moments, weighting matrix, and placebo‐arm matching (i.e., matching on outcomes in the placebo arm). After applying MAIC, guanfacine and atomoxetine had similar reductions in ADHD symptoms (Δ: 0.4, p < 0.737). The results were similar for three of four sensitivity analyses. When we applied MAIC with placebo‐arm matching, however, guanfacine reduced symptoms more than atomoxetine (Δ: ?3.9, p < 0.004). We discuss the implication of this finding and advise MAIC practitioners to carefully consider the use of placebo‐arm matching, depending on the presence of residual confounding across trials. Copyright © 2016 John Wiley & Sons, Ltd.     

How Assessment-Schedule Matching Limits Bias When Comparing Progression-Free Survival in Single-Arm Studies: An Application in Second-Line Urothelial Carcinoma Treatments

ObjectivesPopulation-adjusted comparisons of progression-free survival (PFS) from single-arm trials of cancer treatments can be derived using matching-adjusted indirect comparisons (MAICs); however, results are still susceptible to bias, particularly if the trials had different tumor assessment schedules. This study aims to assess the effects of assessment-schedule matching (ASM) on the relative effectiveness on the PFS of avelumab versus approved comparator immunotherapies or chemotherapy after population matching in the second-line (2L) setting for metastatic urothelial carcinoma.MethodsThe MAIC used patient-level data for avelumab from the JAVELIN Solid Tumor trial (NCT01772004). PFS was compared with published curves for other treatments to obtain population-adjusted hazard ratios (HRs). The MAIC was repeated after conducting ASM for differences in tumor assessment scheduled first at 6 weeks for avelumab and durvalumab and at 8 or 9 weeks for other treatments.ResultsMAIC adjustment alone altered the HR estimates up to 23%, whereas MAIC plus ASM resulted in up to 32.7% reductions from naive comparisons. Even in cases in which MAIC had little effect, ASM brought an additional change of 11.1% to 15.4%. Overall, the HR range of avelumab versus other treatments changed from 0.83 to 1.25 for naive comparisons to 0.76 to 0.99 after ASM plus MAIC, numerically favoring avelumab.ConclusionsSmall variations in assessment schedules can introduce bias in unanchored indirect treatment comparisons of interval-censored time-to-event outcomes. In this study, adjusted PFS was comparable across second-line urothelial carcinoma treatment options, numerically favoring avelumab versus immunotherapies and chemotherapy agents. Correcting this bias is especially important when HRs are applied in cost-effectiveness models to transition patients between states.     

Matching-Adjusted Indirect Comparisons: A New Tool for Timely Comparative Effectiveness Research

ObjectiveIn the absence of head-to-head randomized trials, indirect comparisons of treatments across separate trials can be performed. However, these analyses may be biased by cross-trial differences in patient populations, sensitivity to modeling assumptions, and differences in the definitions of outcome measures. The objective of this study was to demonstrate how incorporating individual patient data (IPD) from trials of one treatment into indirect comparisons can address several limitations that arise in analyses based only on aggregate data.MethodsMatching-adjusted indirect comparisons (MAICs) use IPD from trials of one treatment to match baseline summary statistics reported from trials of another treatment. After matching, by using an approach similar to propensity score weighting, treatment outcomes are compared across balanced trial populations. This method is illustrated by reviewing published MAICs in different therapeutic areas. A novel analysis in attention deficit/hyperactivity disorder further demonstrates the applicability of the method. The strengths and limitations of MAICs are discussed in comparison to those of indirect comparisons that use only published aggregate data.ResultsExample applications were selected to illustrate how indirect comparisons based only on aggregate data can be limited by cross-trial differences in patient populations, differences in the definitions of outcome measures, and sensitivity to modeling assumptions. The use of IPD and MAIC is shown to address these limitations in the selected examples by reducing or removing the observed cross-trial differences. An important assumption of MAIC, as in any comparison of nonrandomized treatment groups, is that there are no unobserved cross-trial differences that could confound the comparison of outcomes.ConclusionsIndirect treatment comparisons can be limited by cross-trial differences. By combining IPD with published aggregate data, MAIC can reduce observed cross-trial differences and provide decision makers with timely comparative evidence.     

Assessing the performance of population adjustment methods for anchored indirect comparisons: A simulation study

Standard network meta-analysis and indirect comparisons combine aggregate data from multiple studies on treatments of interest, assuming that any factors that interact with treatment effects (effect modifiers) are balanced across populations. Population adjustment methods such as multilevel network meta-regression (ML-NMR), matching-adjusted indirect comparison (MAIC), and simulated treatment comparison (STC) relax this assumption using individual patient data from one or more studies, and are becoming increasingly prevalent in health technology appraisals and the applied literature. Motivated by an applied example and two recent reviews of applications, we undertook an extensive simulation study to assess the performance of these methods in a range of scenarios under various failures of assumptions. We investigated the impact of varying sample size, missing effect modifiers, strength of effect modification and validity of the shared effect modifier assumption, validity of extrapolation and varying between-study overlap, and different covariate distributions and correlations. ML-NMR and STC performed similarly, eliminating bias when the requisite assumptions were met. Serious concerns are raised for MAIC, which performed poorly in nearly all simulation scenarios and may even increase bias compared with standard indirect comparisons. All methods incur bias when an effect modifier is missing, highlighting the necessity of careful selection of potential effect modifiers prior to analysis. When all effect modifiers are included, ML-NMR and STC are robust techniques for population adjustment. ML-NMR offers additional advantages over MAIC and STC, including extending to larger treatment networks and producing estimates in any target population, making this an attractive choice in a variety of scenarios.     

Alternative Weighting Approaches for Anchored Matching-Adjusted Indirect Comparisons via a Common Comparator

Background

Adjusted indirect comparisons (anchored via a common comparator) are an integral part of health technology assessment. These methods are challenged when differences between studies exist, including inclusion/exclusion criteria, outcome definitions, patient characteristics, as well as ensuring the choice of a common comparator.

Critical Appraisal of Published Indirect Comparisons and Network Meta-Analyses of Competing Interventions for Multiple Myeloma

ObjectivesIn the field of relapsed or refractory multiple myeloma (RRMM), between-trial or indirect comparisons are required to estimate relative treatment effects between competing interventions based on the available evidence. Two approaches are frequently used in RRMM: network meta-analysis (NMA) and unanchored matching-adjusted indirect comparison (MAIC). The objective of the current study was to evaluate the relevance and credibility of published NMA and unanchored MAIC studies aiming to estimate the comparative efficacy of treatment options for RRMM.MethodsTwelve relevant studies were identified in the published literature (n = 7) and from health technology assessment agencies (n = 5). Data from trials were extracted to identify between-trial differences that may have biased results. Credibility of the performed analyses and relevance of the research questions were critically appraised using the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) checklist and feedback based on consultations with clinical experts.ResultsThe identified studies concerned NMAs of randomized controlled trials (RCTs; n = 7), unanchored MAICs (n = 4), or both types of analyses (n = 1). According to clinical expert consultation, the majority of the identified NMAs did not consider differences in prior therapies or treatment duration across the RCTs included in the analyses, thereby compromising the relevance.ConclusionBased on the results and feedback from clinicians, the majority of NMAs did not consider prior treatment history or treatment duration, which resulted in nonrelevant comparisons. Furthermore, it may have compromised the credibility of the estimates owing to differences in effect-modifiers between the different trials. Pairwise comparisons by means of unanchored MAICs require clear justification given the reliance on non-randomized comparisons.     

Matching-Adjusted Indirect Comparisons of Lorlatinib Versus Chemotherapy for Patients With Second-Line or Later Anaplastic Lymphoma Kinase–Positive Non–Small Cell Lung Cancer

ObjectivesThis study aimed to compare the relative efficacy of lorlatinib, an anaplastic lymphoma kinase–tyrosine kinase inhibitor, with chemotherapy, for patients with second-line or later advanced anaplastic lymphoma kinase–positive non–small cell lung cancer. The endpoints of interest were overall survival (OS) and progression-free survival (PFS).MethodsEvidence for lorlatinib was informed by the single-arm phase I/II trial B7461001. A systematic literature review (SLR) was performed to identify OS and PFS data for chemotherapy. Unanchored matching-adjusted indirect comparisons (MAICs) between lorlatinib and chemotherapy (pemetrexed/docetaxel, platinum-based, or systemic therapy) were performed.ResultsThe SLR identified 3 relevant studies reporting PFS. Lorlatinib was associated with a significant decrease in the hazard of progression versus the 2 types of chemotherapy assessed. For PFS, the MAIC of lorlatinib versus the combined treatment arm of docetaxel or pemetrexed resulted in an adjusted hazard ratio (HR) of 0.22 (95% confidence interval [CI] 0.15-0.31). When lorlatinib was compared with platinum-based chemotherapy through an MAIC, the adjusted HR for PFS was 0.40 (95% CI 0.29-0.55). An exploratory comparison was performed for OS with evidence for systemic therapy (assumed equivalent to chemotherapy) not identified in the SLR. Lorlatinib provided a significant decrease in hazard of death (OS) versus systemic therapy, with HRs ranging from 0.12 (95% CI 0.05-0.27) to 0.43 (95% CI 0.27-0.60).ConclusionsLorlatinib demonstrated a significant improvement in PFS compared with chemotherapy, although limitations in the analyses were identified. The evidence informing OS comparisons was highly limited but suggested benefit of lorlatinib compared with systemic therapy.     

Development and Validation of a Lifespan Prediction Model in Chinese Adults Aged 65 Years or Older

ObjectivesPrevious studies investigated factors associated with mortality. Nevertheless, evidence is limited regarding the determinants of lifespan. We aimed to develop and validate a lifespan prediction model based on the most important predictors.DesignA prospective cohort study.Setting and ParticipantsA total of 23,892 community-living adults aged 65 years or older with confirmed death records between 1998 and 2018 from 23 provinces in China.MethodsInformation including demographic characteristics, lifestyle, functional health, and prevalence of diseases was collected. The risk prediction model was generated using multivariate linear regression, incorporating the most important predictors identified by the Lasso selection method. We used 1000 bootstrap resampling for the internal validation. The model performance was assessed by adjusted R², root mean square error (RMSE), mean absolute error (MAE), and intraclass correlation coefficient (ICC).ResultsTwenty-one predictors were included in the final lifespan prediction model. Older adults with longer lifespans were characterized by older age at baseline, female, minority race, living in rural areas, married, with healthier lifestyles and more leisure engagement, better functional status, and absence of diseases. The predicted lifespans were highly consistent with observed lifespans, with an adjusted R² of 0.893. RMSE was 2.86 (95% CI 2.84–2.88) and MAE was 2.18 (95% CI 2.16–2.20) years. The ICC between observed and predicted lifespans was 0.971 (95% CI 0.971–0.971).Conclusions and ImplicationsThe lifespan prediction model was validated with good performance, the web-based prediction tool can be easily applied in practical use as it relies on all easily accessible variables.     

Abortion providers,stigma and professional quality of life

ObjectivesThe Providers Share Workshop (PSW) provides abortion providers safe space to discuss their work experiences. Our objectives were to assess changes in abortion stigma over time and explore how stigma is related to aspects of professional quality of life, including compassion satisfaction, burnout and compassion fatigue for providers participating in the workshops.Study DesignSeventy-nine providers were recruited to the PSW study. Surveys were completed prior to, immediately following and 1 year after the workshops. The outcome measures were the Abortion Provider Stigma Survey and the Professional Quality of Life (ProQOL) survey. Baseline ProQOL scores were compared to published averages using t tests. Changes in abortion stigma and aspects of professional quality of life were assessed by fitting a two-level random-effects model with repeated measures at level 1 (period-level) and static measures (e.g., demographic data) at level 2 (person-level). Potential covariates included age, parenting status, education, organizational tenure, job type and clinic type (stand-alone vs. hospital-based clinics).ResultsCompared to other healthcare workers, abortion providers reported higher compassion satisfaction (t= 2.65, p=.009) and lower burnout (t= 5.13, p<.0001). Repeated-measures analysis revealed statistically significant decreases in stigma over time. Regression analysis identified abortion stigma as a significant predictor of lower compassion satisfaction, higher burnout and higher compassion fatigue.ConclusionsParticipants in PSW reported a reduction in abortion stigma over time. Further, stigma is an important predictor of compassion satisfaction, burnout and compassion fatigue, suggesting that interventions aimed at supporting the abortion providing workforce should likely assess abortion stigma.ImplicationsStigma is an important predictor of compassion satisfaction, burnout and compassion fatigue among abortion care providers. Therefore, strengthening human resources for abortion care requires stigma reduction efforts. Participants in the PSWs show reductions in stigma over time.     

Need for Speed: An Efficient Algorithm for Calculation of Single-Parameter Expected Value of Partial Perfect Information

BackgroundThe expected value of partial perfect information (EVPPI) is a theoretically justifiable and informative measure of uncertainty in decision-analytic cost-effectiveness models, but its calculation is computationally intensive because it generally requires two-level Monte Carlo simulation. We introduce an efficient, one-level simulation method for the calculation of single-parameter EVPPI.ObjectiveWe show that under mild regularity assumptions, the expectation-maximization-expectation sequence in EVPPI calculation can be transformed into an expectation-maximization-maximization sequence. By doing so, calculations can be performed in a single-step expectation by using data generated for probabilistic sensitivity analysis. We prove that the proposed estimator of EVPPI converges in probability to the true EVPPI.Methods and ResultsThe performance of the new method was empirically demonstrated by using three exemplary decision models. Our proposed method seems to achieve remarkably higher accuracy than the two-level method with a fraction of its computation costs, though the achievement in accuracy was not uniform and varied across the parameters of the models. Software is provided to calculate single-parameter EVPPI based on the probabilistic sensitivity analysis data.ConclusionsThe new method, though applicable only to single-parameter EVPPI, is fast, accurate, and easy to implement. Further research is needed to evaluate the performance of this method in more complex scenarios and to extend such a concept to similar measures of decision uncertainty.     

Home-based care: barriers and facilitators to expanded personal support worker roles in Ontario,Canada

ABSTRACT

To accommodate the increasing demand for home care in Ontario, Canada, some care tasks traditionally performed by regulated health professionals are being transferred to personal support workers (PSW). However, this expansion of PSW roles is not uniform across the province. Between December 2014 and April 2015, barriers and facilitators to expansion of PSW roles in home care were explored in a series of 13 focus groups. Home care staff identified seven categories of factors affecting the expansion of PSW roles in home care including: communication and documentation; organization and structures of care; attitudes and perceptions of the expanding PSW role; adequate staffing; education, training and support; PSW role clarity and variation in practices, policies, and procedures. Addressing barriers and promoting facilitators at the funder and employer levels will enable the provision of safe, effective, and equitable care by PSWs.     

不同方法在中枢神经系统感染病原学诊断中的价值

目的 探讨自动化核酸快速检测设备FilmArray meningitis/encephalitis (FA ME) panel、宏基因组第二代测序(mNGS)在中枢神经系统(CNS)感染病原学诊断中的价值。方法 收集2020年6月—2021年1月中山大学附属第三医院收治的29例疑似CNS感染患者脑脊液标本,进行FA ME检测及mNGS,结合细菌/真菌培养,以及病毒核酸/血清学结果,比较FA ME、mNGS在CNS感染病原学诊断中的效果。结果 FA ME、mNGS细菌阳性率分别为7.1%、9.1%,数值略高于细菌培养3.4%,差异无统计学意义(P=1.000)。真菌方面,FA ME、mNGS阳性率分别为10.7%、13.6%,均低于真菌培养(17.2%),差异具有统计学意义(P=0.003)。FA ME、mNGS检测病毒的阳性率分别为3.6%、18.2%,高于院内病毒核酸/血清学检测(0)。结论 FA ME、mNGS目前不足以代替院内常规检测,但可作为传统检测的补充手段提高CNS感染病原体检出水平。     

The z-difference can be used to measure covariate balance in matched propensity score analyses

ObjectivesThe propensity score (PS) method is increasingly used to assess treatment effects in nonrandomized trials. Although there are several methods to use the PS for analysis, matching treated and untreated patients by the PS is recommended by most researchers among other reasons because this allows assessing covariate balance before and after matching. Although the standardized difference is commonly applied to compute a measure of balance, it has two deficiencies: its distribution depends on the sample size and one cannot compare standardized differences for baseline covariates on different scales, that is, continuous, binary, ordinal, or nominal covariates.Study Design and SettingWe introduce the z-difference to measure covariate balance in matched PS analyses and illustrate it by a recent matched PS analysis from cardiac surgery.ResultsThe z-difference is simple to calculate, can be used with second moments for continuous covariates, and in most cases can also be computed from published data. Its full advantage emerges after displaying z-differences in a Q–Q plot, which allows balance comparisons with respect to (1) a randomized trial and (2) a perfectly matched PS analysis in the sense of Rubin and Thomas.ConclusionThe z-difference can be used to measure covariate balance in matched PS analyses.     

Directed acyclic graphs can help understand bias in indirect and mixed treatment comparisons

ObjectiveTo introduce and advocate directed acyclic graphs (DAGs) as a useful tool to understand when indirect and mixed treatment comparisons are invalid and guide strategies that limit bias.Study Design and SettingBy means of DAGs, it is heuristically explained when indirect and mixed treatment comparisons are biased, and whether statistical adjustment of imbalances in study and patient characteristics across different comparisons in the network of RCTs is appropriate.ResultsA major threat to the validity of indirect and mixed treatment comparisons is a difference in modifiers of the relative treatment effect across comparisons, and statistically adjusting for these differences can improve comparability and remove bias. However, adjustment for differences in covariates across comparisons that are not effect modifiers is not necessary and can even introduce bias. As a special case, we outline that adjustment for the baseline risk might be useful to improve similarity and consistency, but may also bias findings.ConclusionDAGs are useful to evaluate conceptually the assumptions underlying indirect and mixed treatment comparison, to identify sources of bias and guide the implementation of analytical methods used for network meta-analysis of RCTs.     

Effect of environmental temperature on the interactive developmental toxicity of radiofrequency radiation and 2-methoxyethanol in rats

Objective: This research was conducted to determine if altered environmental temperatures would affect the interactive developmental toxicity of radiofrequency (RF) radiation and the industrial solvent, 2-methoxyethanol (2ME). This is important because RF radiation is used in a variety of workplaces that have poorly controlled environmental temperatures, and many workers are concurrently exposed to various chemicals. Furthermore, we have previously demonstrated that combined exposure to RF radiation (10 MHz) and 2ME produces enhanced teratogenicity in rats. Methods: RF radiation sufficient to maintain colonic temperatures at the control value (38°), 39.0° or 40.0 °C for 2 or 4 h combined with either 0 or 100 mg/kg 2ME at environmental temperatures of 18°, 24° and 30 °C (65°, 75°, and 85 °F) were given on gestation day 13 to Sprague-Dawley rats. Dams were killed on gestation day 20, and the fetuses were examined for external malformations. Results and conclusions: Environmental temperature does affect the specific absorption rate (SAR) necessary to maintain a specific colonic temperature but does not affect the interactive developmental toxicity of RF radiation and 2ME in rats. These results, consistent with the literature, add to the evidence that the developmental toxicity of RF radiation (combined or alone) is associated with colonic temperature, not with SAR. Received: 17 September 1997 / Accepted: 13 February 1998     

Salary Discrepancies Between Practicing Male and Female Physician Assistants

BackgroundSalary discrepancies between male and female physicians are well documented; however, gender-based salary differences among clinically practicing physician assistants (PAs) have not been studied since 1992 (Willis, 1992). Therefore, the objectives of the current study are to evaluate the presence of salary discrepancies between clinically practicing male and female PAs and to analyze the effect of gender on income and practice characteristics.MethodsUsing data from the 2009 American Academy of Physician Assistants’ (AAPA) Annual Census Survey, we evaluated the salaries of PAs across multiple specialties. Differences between men and women were compared for practice characteristics (specialty, experience, etc) and salary (total pay, base pay, on-call pay, etc) in orthopedic surgery, emergency medicine, and family practice.FindingsMen reported working more years as a PA in their current specialty, working more hours per month on-call, providing more direct care to patients, and more funding available from their employers for professional development (p < .001, all comparisons). In addition, men reported a higher total income, base pay, overtime pay, administrative pay, on-call pay, and incentive pay based on productivity and performance (p < .001, all comparisons). Multivariate analysis of covariance and analysis of variance revealed that men reported higher total income (p < .0001) and base pay (p = .001) in orthopedic surgery, higher total income (p = .011) and base pay (p = .005) in emergency medicine, and higher base pay in family practice (p < .001), independent of clinical experience or workload.ConclusionThese results suggest that certain salary discrepancies remain between employed male and female PAs regardless of specialty, experience, or other practice characteristics.     

Patient-Level Hospital Costs and Length of Stay After Conventional Versus Minimally Invasive Total Hip Replacement: A Propensity-Matched Analysis

ObjectivesA current trend in total hip replacement (THR) is the use of minimally invasive surgery. Little is known, however, about the impact of minimally invasive THR on resource use and length of stay. This study analyzed the effect of minimally invasive surgery on hospital costs and length of stay in German hospitals compared with conventional treatment in THR.MethodsWe used patient-level administrative hospital data from three German hospitals participating in the national cost data study. We conducted a propensity score matching to account for baseline differences between minimally invasively and conventionally treated patients. Subsequently, we estimated the treatment effect on costs and length of stay by conducting group comparisons, via paired t tests and Wilcoxon signed-rank tests, and regression analyses.ResultsThe three hospitals provided data from 2886 THR patients. The propensity score matching led to 812 matched pairs. Length of stay was significantly higher for conventionally treated patients (11.49 days vs. 10.90 days; P < 0.05), but total costs did not differ significantly (€6018 vs. €5986; P = 0.67). We found a difference in the allocation of costs, with significantly higher implant costs for minimally invasively treated patients (€1514 vs. €1375; P < 0.001) in contrast to significantly higher staff and overhead costs for conventionally treated patients.ConclusionsMinimally invasive surgery was compared with conventional THR and was found to be associated with a reduced length of stay. Total hospital costs, however, did not differ between the two treatment groups, because of higher implant costs for minimally invasively treated patients.     

Cost Effectiveness of Guanfacine Extended-Release versus Atomoxetine for the Treatment of Attention-Deficit/Hyperactivity Disorder

Background: About 7% of children and adolescents are diagnosed with attention-deficit/hyperactivity disorder (ADHD) in the US. Patients with ADHD who are intolerant of or do not have an optimal response to stimulants often use non-stimulants as alternative therapies. Guanfacine extendedrelease (GXR) and atomoxetine (ATX) are the only non-stimulants approved by the US Food and Drug Administration for once-daily use in the treatment of children and adolescents with ADHD in the US. ATX has been on the market since 2002 while GXR was recently approved in 2009. To date, there is no comparative effectiveness or cost-effectiveness study comparing the two drugs. Objectives: The aim of this study was to assess the cost effectiveness of GXR versus ATX for the treatment of ADHD in children and adolescents, using the comparative efficacy results from a matching-adjusted indirect comparison (MAIC). Methods: The MAIC method was used to compare the efficacy between GXR (target dose and lower doses) and ATX (target dose) in the absence of head-to-head clinical trials. Individual patients in the GXR trials were weighted such that the summary baseline characteristics and the efficacy of the placebo arm of the GXR trials matched exactly with those from published ATX trials. After weighting, the efficacy (i.e. change in the ADHD rating scale, fourth edition [ADHD-RS-IV] total score from baseline) was compared between each GXR dosing group and the ATX group. The results from the MAIC analyses were used to populate a 1-year Markov model that is used to compare the cost effectiveness of GXR versus ATX from a US third-party payer perspective. Effectiveness outcomes for each treatment group were estimated as the proportion of responders, defined as patients with ≥25% reduction in ADHD-RS-IV total score from baseline, and average quality-adjusted life years (QALYs). Utilities associated with response/non-response and disutilities due to adverse events were applied in the model. Costs included drug and medical service costs and were inflated to 2011 US dollars ($US). Incremental cost/QALY and incremental cost/responder were estimated. Univariate sensitivity analyses were conducted by varying all model parameters, including costs, utilities, and response rate. Results: The target dose of GXR was 0.12mg/kg/day. In match-adjusted populations with balanced baseline characteristics, patients receiving GXR at the dose of 0.09–0.12 (p = 0.0009) and 0.075–0.09 mg/kg/day (p = 0.0248) had better efficacy, while those receiving GXR at the dose of 0.046–0.075 mg/kg/day had comparable efficacy (p = 0.0699), compared with patients receiving ATX at the target dose of 1.2 mg/kg/day. In the base case of the cost-effectiveness analysis (CEA), GXR had incremental cost-effectiveness ratios of $US10 637/QALY and $US853/responder, compared with ATX (incremental costs: $US74; incremental effectiveness: 0.007 QALYs and 86 responders per 1000 patients treated). Results of all univariate sensitivity analyses showed that the model results were robust to changes in model inputs. Conclusions: To our knowledge, this is the first application of the novel comparative efficacy method of MAIC to a CEA model. The MAIC results indicate that GXR (0.075–0.12 mg/kg/day) was more effective than ATX (1.2 mg/kg/day) in the trial population. The CEA results indicate that GXR is cost effective compared with ATX for the treatment of ADHD in children and adolescents.     

Pollution Characteristics and Health Risk Assessment of Phthalate Esters in PSW Recycling Sites: A Typical Case Study

The concentrations of six priority phthalate esters (PAEs) in 700 soil samples and 110 sediment samples from an area in China containing plastic solid waste (PSW) recycling sites were determined. The total concentrations of the six PAEs in soil and sediment were not detected – 274 and not detected – 597 mg kg^?1, respectively, and the mean concentrations in soil and sediment were 14.4 and 31.7 mg kg^?1, respectively. The dominant PAEs were di(2-ethylhexyl) phthalate and di-n-butyl phthalate. PAEs were detected in soil collected from the surface to 0.5 m below ground level around the PSW recycling sites, and the concentrations were markedly higher in these areas than at other polluted sites. PSW recycling is an important source of PAEs to soil and sediment. The di(2-ethylhexyl)phthalate concentrations in soil were higher than the relevant concentrations that pose environmental risks for sensitive land uses and non-sensitive land uses (42 and 121 mg kg^?1, respectively), indicating emissions of PAEs from PSW recycling sites may pose environmental risks. The results indicate that PAE pollution at PSW sites needs to be better controlled and managed.