Identification of causal effects on binary outcomes using structural mean models

Structural mean models (SMMs) were originally formulated to estimate causal effects among those selecting treatment in randomized controlled trials affected by nonignorable noncompliance. It has already been established that SMMs can identify these causal effects in randomized placebo-controlled trials under fairly weak assumptions. SMMs are now being used to analyze other types of study where identification depends on a no effect modification assumption. We highlight how this assumption depends crucially on the unknown causal model that generated the data, and so is difficult to justify. However, we also highlight that, if treatment selection is monotonic, additive and multiplicative SMMs do identify local (or complier) causal effects, but that the double-logistic SMM estimator does not without further assumptions. We clarify the proper interpretation of inferences from SMMs by means of an application and a simulation study. © 2010 The Author

Enhanced analysis of real-time PCR data by using a variable efficiency model: FPK-PCR

Current methodology in real-time Polymerase chain reaction (PCR) analysis performs well provided PCR efficiency remains constant over reactions. Yet, small changes in efficiency can lead to large quantification errors. Particularly in biological samples, the possible presence of inhibitors forms a challenge. We present a new approach to single reaction efficiency calculation, called Full Process Kinetics-PCR (FPK-PCR). It combines a kinetically more realistic model with flexible adaptation to the full range of data. By reconstructing the entire chain of cycle efficiencies, rather than restricting the focus on a ‘window of application’, one extracts additional information and loses a level of arbitrariness. The maximal efficiency estimates returned by the model are comparable in accuracy and precision to both the golden standard of serial dilution and other single reaction efficiency methods. The cycle-to-cycle changes in efficiency, as described by the FPK-PCR procedure, stay considerably closer to the data than those from other S-shaped models. The assessment of individual cycle efficiencies returns more information than other single efficiency methods. It allows in-depth interpretation of real-time PCR data and reconstruction of the fluorescence data, providing quality control. Finally, by implementing a global efficiency model, reproducibility is improved as the selection of a window of application is avoided.JRC.I.3-Molecular Biology and Genomic

PROPEL: implementation of an evidence based pelvic floor muscle training intervention for women with pelvic organ prolapse: a realist evaluation and outcomes study protocol

Abstract Background Pelvic Organ Prolapse (POP) is estimated to affect 41%–50% of women aged over 40. Findings from the multi-centre randomised controlled “Pelvic Organ Prolapse PhysiotherapY” (POPPY) trial showed that individualised pelvic floor muscle training (PFMT) was effective in reducing symptoms of prolapse, improved quality of life and showed clear potential to be cost-effective. However, provision of PFMT for prolapse continues to vary across the UK, with limited numbers of women’s health physiotherapists specialising in its delivery. Implementation of this robust evidence from the POPPY trial will require attention to different models of delivery (e.g. staff skill mix) to fit with differing care environments. Methods A Realist Evaluation (RE) of implementation and outcomes of PFMT delivery in contrasting NHS settings will be conducted using multiple case study sites. Involving substantial local stakeholder engagement will permit a detailed exploration of how local sites make decisions on how to deliver PFMT and how these lead to service change. The RE will track how implementation is working; identify what influences outcomes; and, guided by the RE-AIM framework, will collect robust outcomes data. This will require mixed methods data collection and analysis. Qualitative data will be collected at four time-points across each site to understand local contexts and decisions regarding options for intervention delivery and to monitor implementation, uptake, adherence and outcomes. Patient outcome data will be collected at baseline, six months and one year follow-up for 120 women. Primary outcome will be the Pelvic Organ Prolapse Symptom Score (POP-SS). An economic evaluation will assess the costs and benefits associated with different delivery models taking account of further health care resource use by the women. Cost data will be combined with the primary outcome in a cost effectiveness analysis, and the EQ-5D-5L data in a cost utility analysis for each of the different models of delivery. Discussion Study of the implementation of varying models of service delivery of PFMT across contrasting sites combined with outcomes data and a cost effectiveness analysis will provide insight into the implementation and value of different models of PFMT service delivery and the cost benefits to the NHS in the longer term

Consolidated health economic evaluation reporting standards (CHEERS) statement

<p>Economic evaluations of health interventions pose a particular challenge for reporting. There is also a need to consolidate and update existing guidelines and promote their use in a user friendly manner. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement is an attempt to consolidate and update previous health economic evaluation guidelines efforts into one current, useful reporting guidance. The primary audiences for the CHEERS statement are researchers reporting economic evaluations and the editors and peer reviewers assessing them for publication.</p> <p>The need for new reporting guidance was identified by a survey of medical editors. A list of possible items based on a systematic review was created. A two round, modified Delphi panel consisting of representatives from academia, clinical practice, industry, government, and the editorial community was conducted. Out of 44 candidate items, 24 items and accompanying recommendations were developed. The recommendations are contained in a user friendly, 24 item checklist. A copy of the statement, accompanying checklist, and this report can be found on the ISPOR Health Economic Evaluations Publication Guidelines Task Force website (www.ispor.org/TaskForces/EconomicPubGuidelines.asp).</p> <p>We hope CHEERS will lead to better reporting, and ultimately, better health decisions. To facilitate dissemination and uptake, the CHEERS statement is being co-published across 10 health economics and medical journals. We encourage other journals and groups, to endorse CHEERS. The author team plans to review the checklist for an update in five years.</p&gt

Stakeholder involvement in Multi-Criteria Decision Analysis

This brief perspective highlights the importance of decision maker buy-in and ownership through stakeholder engagement in the co-construction of the multi-criteria decision analysis (MCDA) model. A brief historical overview of MCDA is presented before outlining the importance of bridging the gap (and to gain trust) between the tool developers and users. The issues with the current MCDA tool development and testing efforts are highlighted, and the ownership and routine adoption of the MCDA process is discussed

Human diploid fibroblast growth on polystyrene microcarriers in aggregates

Polystyrene microcarriers were prepared in four size ranges (53–63 μm, 90–125 μm, 150–180 μm and 300–355 μm) and examined for ability to support attachment and growth of human diploid fibroblasts. Cells attached rapidly to the microcarriers and there was a direct relationship between cell attachment and microcarrier aggregation. Phasecontrast and scanning electron microscopic studies revealed that while aggregation was extensive, most of the aggregate consisted of void volume. Cell growth studies demonstrated that human diploid fibroblasts proliferated well in microcarrier aggregates, reaching densities of 2.5–3×10 6 cells per 2 ml dish after 6 days from an inoculum of 0.5×10 6 cells per dish. When cells were added to the microcarriers at higher density (up to 5×10 6 cells per 2-ml culture), there was little net growth but the cells remained viable over a 7-day period. In contrast, cells died when plated under the same conditions in monolayer culture. When the microcarriers were used in suspension culture, rapid cell attachment and rapid microcarrier aggregation also occurred. In 100-ml suspension culture, a cell density of 0.7×10 6 cells per ml was reached after 7 days from an inoculum of 0.1×10 6 cells. Based on these data, we conclude that microcarrier aggregation is not detrimental to fibroblast growth. These data also indicate that small microcarriers (53–63 μm) (previously thought to be too small to support the growth of diploid fibroblasts) can support fibroblast growth and this occurs primarily because microcarriers in this size range efficiently form aggregates with the cells.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42617/1/10616_2004_Article_BF00353930.pd

Exploring the perspectives and preferences for HTA across German healthcare stakeholders using a multi-criteria assessment of a pulmonary heart sensor as a case study

Background Health technology assessment and healthcare decision-making are based on multiple criteria and evidence, and heterogeneous opinions of participating stakeholders. Multi-criteria decision analysis (MCDA) offers a potential framework to systematize this process and take different perspectives into account. The objectives of this study were to explore perspectives and preferences across German stakeholders when appraising healthcare interventions, using multi-criteria assessment of a heart pulmonary sensor as a case study. Methods An online survey of 100 German healthcare stakeholders was conducted using a comprehensive MCDA framework (EVIDEM V2.2). Participants were asked to provide i) relative weights for each criterion of the framework; ii) performance scores for a health pulmonary sensor, based on available data synthesized for each criterion; and iii) qualitative feedback on the consideration of contextual criteria. Normalized weights and scores were combined using a linear model to calculate a value estimate across different stakeholders. Differences across types of stakeholders were explored. Results The survey was completed by 54 participants. The most important criteria were efficacy, patient reported outcomes, disease severity, safety, and quality of evidence (relative weight >0.075 each). Compared to all participants, policymakers gave more weight to budget impact and quality of evidence. The quantitative appraisal of a pulmonary heart sensor revealed differences in scoring performance of this intervention at the criteria level between stakeholder groups. The highest value estimate of the sensor reached 0.68 (on a scale of 0 to 1, 1 representing maximum value) for industry representatives and the lowest value of 0.40 was reported for policymakers, compared to 0.48 for all participants. Participants indicated that most qualitative criteria should be considered and their impact on the quantitative appraisal was captured transparently. Conclusions The study identified important variations in perspectives across German stakeholders when appraising a healthcare intervention and revealed that MCDA can demonstrate the value of a specified technology for all participating stakeholders. Better understanding of these differences at the criteria level, in particular between policymakers and industry representatives, is important to focus innovation aligned with patient health and healthcare system values and constraints

Bridging health technology assessment (HTA) with multicriteria decision analyses (MCDA): field testing of the EVIDEM framework for coverage decisions by a public payer in Canada

<p>Abstract</p> <p>Background</p> <p>Consistent healthcare decisionmaking requires systematic consideration of decision criteria and evidence available to inform them. This can be tackled by combining multicriteria decision analysis (MCDA) and Health Technology Assessment (HTA). The objective of this study was to field-test a decision support framework (EVIDEM), explore its utility to a drug advisory committee and test its reliability over time.</p> <p>Methods</p> <p>Tramadol for chronic non-cancer pain was selected by the health plan as a case study relevant to their context. Based on extensive literature review, a by-criterion HTA report was developed to provide synthesized evidence for each criterion of the framework (14 criteria for the MCDA Core Model and 6 qualitative criteria for the Contextual Tool). During workshop sessions, committee members tested the framework in three steps by assigning: 1) weights to each criterion of the MCDA Core Model representing individual perspective; 2) scores for tramadol for each criterion of the MCDA Core Model using synthesized data; and 3) qualitative impacts of criteria of the Contextual Tool on the appraisal. Utility and reliability of the approach were explored through discussion, survey and test-retest. Agreement between test and retest data was analyzed by calculating intra-rater correlation coefficients (ICCs) for weights, scores and MCDA value estimates.</p> <p>Results</p> <p>The framework was found useful by the drug advisory committee in supporting systematic consideration of a broad range of criteria to promote a consistent approach to appraising healthcare interventions. Directly integrated in the framework as a "by-criterion" HTA report, synthesized evidence for each criterion facilitated its consideration, although this was sometimes limited by lack of relevant data. Test-retest analysis showed fair to good consistency of weights, scores and MCDA value estimates at the individual level (ICC ranging from 0.676 to 0.698), thus lending some support for the reliability of the approach. Overall, committee members endorsed the inclusion of most framework criteria and revealed important areas of discussion, clarification and adaptation of the framework to the needs of the committee.</p> <p>Conclusions</p> <p>By promoting systematic consideration of all decision criteria and the underlying evidence, the framework allows a consistent approach to appraising healthcare interventions. Further testing and validation are needed to advance MCDA approaches in healthcare decisionmaking.</p

Can we apply the Mendelian randomization methodology without considering epigenetic effects?

<p>Abstract</p> <p>Introduction</p> <p>Instrumental variable (IV) methods have been used in econometrics for several decades now, but have only recently been introduced into the epidemiologic research frameworks. Similarly, Mendelian randomization studies, which use the IV methodology for analysis and inference in epidemiology, were introduced into the epidemiologist's toolbox only in the last decade.</p> <p>Analysis</p> <p>Mendelian randomization studies using instrumental variables (IVs) have the potential to avoid some of the limitations of observational epidemiology (confounding, reverse causality, regression dilution bias) for making causal inferences. Certain limitations of randomized controlled trials, such as problems with generalizability, feasibility and ethics for some exposures, and high costs, also make the use of Mendelian randomization in observational studies attractive. Unlike conventional randomized controlled trials (RCTs), Mendelian randomization studies can be conducted in a representative sample without imposing any exclusion criteria or requiring volunteers to be amenable to random treatment allocation.</p> <p>Within the last decade, epigenetics has gained recognition as an independent field of study, and appears to be the new direction for future research into the genetics of complex diseases. Although previous articles have addressed some of the limitations of Mendelian randomization (such as the lack of suitable genetic variants, unreliable associations, population stratification, linkage disequilibrium (LD), pleiotropy, developmental canalization, the need for large sample sizes and some potential problems with binary outcomes), none has directly characterized the impact of epigenetics on Mendelian randomization. The possibility of epigenetic effects (non-Mendelian, heritable changes in gene expression not accompanied by alterations in DNA sequence) could alter the core instrumental variable assumptions of Mendelian randomization.</p> <p>This paper applies conceptual considerations, algebraic derivations and data simulations to question the appropriateness of Mendelian randomization methods when epigenetic modifications are present.</p> <p>Conclusion</p> <p>Given an inheritance of gene expression from parents, Mendelian randomization studies not only need to assume a random distribution of alleles in the offspring, but also a random distribution of epigenetic changes (e.g. gene expression) at conception, in order for the core assumptions of the Mendelian randomization methodology to remain valid. As an increasing number of epidemiologists employ Mendelian randomization methods in their research, caution is therefore needed in drawing conclusions from these studies if these assumptions are not met.</p