Comparison of Low-Value Care Among Commercial and Medicaid Enrollees.

BACKGROUND: Low-value healthcare is costly and inefficient and may adversely affect patient outcomes. Despite increases in low-value service use, little is known about how the receipt of low-value care differs across payers. OBJECTIVE: To evaluate differences in the use of low-value care between patients with commercial versus Medicaid coverage. DESIGN: Retrospective observational analysis of the 2017 Rhode Island All-payer Claims Database, estimating the probability of receiving each of 14 low-value services between commercial and Medicaid enrollees, adjusting for patient sociodemographic and clinical characteristics. Ensemble machine learning minimized the possibility of model misspecification. PARTICIPANTS: Medicaid and commercial enrollees aged 18-64 with continuous coverage and an encounter at which they were at risk of receiving a low-value service. INTERVENTION: Enrollment in Medicaid or Commercial insurance. MAIN MEASURES: Use of one of 14 validated measures of low-value care. KEY RESULTS: Among 110,609 patients, Medicaid enrollees were younger, had more comorbidities, and were more likely to be female than commercial enrollees. Medicaid enrollees had higher rates of use for 7 low-value care measures, and those with commercial coverage had higher rates for 5 measures. Across all measures of low-value care, commercial enrollees received more (risk difference [RD] 6.8 percentage points; CI: 6.6 to 7.0) low-value services than their counterparts with Medicaid. Commercial enrollees were also more likely to receive low-value services typically performed in the emergency room (RD 11.4 percentage points; CI: 10.7 to 12.2) and services that were less expensive (RD 15.3 percentage points; CI 14.6 to 16.0). CONCLUSION: Differences in the provision of low-value care varied across measures, though average use was slightly higher among commercial than Medicaid enrollees. This difference was more pronounced for less expensive services indicating that financial incentives may not be the sole driver of low-value care.

Assessments of the Value of New Interventions Should Include Health Equity Impact.

A formal evaluation of the health equity impact of a new intervention is hardly ever performed as part of a health technology assessment to understand its value. This should change, in our view. An evidence-based quantitative assessment of the health equity impact can help decision makers develop coverage policies, programme designs, and quality initiatives focused on optimizing both total health and health equity given the treatment options available. We outline the conceptual basis of how a new intervention can impact health equity and adopt distributional cost-effectiveness analysis based on decision-analytic models to assess this quantitatively, using a newly US FDA-approved drug for Alzheimer's disease (aducanumab) as an example. We argue that gaps in the evidence base for the new intervention, for example, due to limited clinical research participation among racial and ethnic minority groups, do not preclude such an evaluation. Understanding these uncertainties has implications for fair pricing, decision making, and future research. If we are serious about population-level decision making that not only is focused on improving total health but also aims to improve health equity, we should consider routinely assessing the health equity impact of new interventions.

Estimated costs and quality-adjusted life-years lost due to N. gonorrhoeae infections acquired in 2015 in the United States: A modelling study of overall burden and disparities by age, race/ethnicity, and other factors.

Background: Disparities in the health and economic burden of gonorrhoea have not been systematically quantified. We estimated population-level health losses and costs associated with gonococcal infection and sequelae in the United States. Methods: We used probability-tree models to capture gonorrhoea sequelae and to estimate attributable disease burden in terms of the discounted lifetime costs and quality-adjusted life-years (QALYs) lost due to incident infections acquired during 2015 from the healthcare system perspective. Numbers of infections in 2015 were obtained from a published gonorrhoea transmission model. We evaluated population-level disease burden, disaggregated by sex, age, race/ethnicity, and for men who have sex with men (MSM). We conducted a multivariate sensitivity analysis for key parameters. Findings: Discounted lifetime QALYs lost per incident gonococcal infection were estimated as 0.093 (95% uncertainty interval [UI] 0.022-0.22) for women, 0.0020 (0.0015-0.0024) for heterosexual men, and 0.0015 (0.00070-0.0021) for MSM. Discounted lifetime costs per incident infection were USD 261 (109-480), 169 (88-263), and 133 (50-239), respectively. At the population level, total discounted lifetime QALYs lost due to infections acquired during 2015 were 53,293 (12,326-125,366) for women, 621 (430-872) for heterosexual men, and 1,078 (427-1,870) for MSM. Total discounted lifetime costs were USD 150 million (64-277 million), 54 million (25-92 million), and 97 million (34-197 million), respectively. The highest total burden of both QALYs and costs at the population-level was observed in Non-Hispanic Black women, and highest burden per 1,000 person-years was identified in MSM among men and American Indian/Alaska Native among women. Interpretation: Gonorrhoea causes substantial health losses and costs in the United States. These results can inform planning and prioritization of prevention services. Funding: Centers for Disease Control and Prevention, Charles A. King Trust.

Future Directions for Cost-effectiveness Analyses in Health and Medicine.

OBJECTIVES: In 2016, the Second Panel on Cost-effectiveness in Health and Medicine updated the seminal work of the original panel from 2 decades earlier. The Second Panel had an opportunity to reflect on the evolution of cost-effectiveness analysis (CEA) and to provide guidance for the next generation of practitioners and consumers. In this article, we present key topics for future research and policy. METHODS: During the course of its deliberations, the Second Panel discussed numerous topics for advancing methods and for improving the use of CEA in decision making. We identify and consider 7 areas for which the panel believes that future research would be particularly fruitful. In each of these areas, we highlight outstanding research needs. The list is not intended as an exhaustive inventory but rather a set of key items that surfaced repeatedly in the panel's discussions. In the online Appendix , we also list and expound briefly on 8 other important topics. RESULTS: We highlight 7 key areas: CEA and perspectives (determining, valuing, and summarizing elements for the analysis), modeling (comparative modeling and model transparency), health outcomes (valuing temporary health and path states, as well as health effects on caregivers), costing (a cost catalogue, valuing household production, and productivity effects), evidence synthesis (developing theory on learning across studies and combining data from clinical trials and observational studies), estimating and using cost-effectiveness thresholds (empirically representing 2 broad concepts: opportunity costs and public willingness to pay), and reporting and communicating CEAs (written protocols and a quality scoring system). CONCLUSIONS: Cost-effectiveness analysis remains a flourishing and evolving field with many opportunities for research. More work is needed on many fronts to understand how best to incorporate CEA into policy and practice.

Comparative Effectiveness and Safety of Bariatric Procedures in Medicare-Eligible Patients: A Systematic Review.

Importance: The prevalence of obesity in patients older than 65 years is increasing. A substantial number of beneficiaries covered by Medicare meet eligibility criteria for bariatric procedures. Objective: To assess the comparative effectiveness and safety of bariatric procedures in the Medicare-eligible population. Evidence Review: This systematic review was conducted according to the PRISMA guidelines. Articles were identified through searches of PubMed, Embase, CINAHL, PsycINFO, Cochrane Central Trials Registry, Cochrane Database of Systematic Reviews, and scientific information packages from manufacturers, ClinicalTrials.gov, World Health Organization International Clinical Trials Registry Platform, and US Food and Drug Administration drugs and devices portals from January 1, 2000, to June 31, 2017. Randomized and nonrandomized comparative studies that evaluated bariatric procedures in the Medicare-eligible population were eligible. Six researchers extracted data on design, interventions, outcomes, and study quality. Findings were synthesized qualitatively; a planned meta-analysis was not undertaken owing to clinical heterogeneity. Findings: A total of 11 455 citations were screened for eligibility. Of those, 16 met the eligibility criteria. Compared with no surgery or conventional weight-loss treatment, bariatric surgery results in greater weight loss. Overall mortality after 30 days is lower among bariatric patients (hazard ratio, HR, 0.50; 95% CI, 0.31-0.79, in the study with the longest follow-up of 5.9 years), although, based on 1 study, mortality within 30 days of surgery was higher than in nonsurgically treated controls (1.55% vs 0.53%; P < .001). Bariatric surgery is associated with lower risk of cardiovascular disease (HR, 0.59; 95% CI, 0.44-0.79 in the largest study comparison) and with improvements in respiratory, musculoskeletal, metabolic, and renal outcomes (increase in estimated glomerular filtration rate, 9.84; 95% CI, 8.05-11.62 mL/min/1.73m2). Compared with sleeve gastrectomy (SG) and adjustable gastric banding (AGB), Roux-en-Y gastric bypass (RYGB) appears to be associated with greater weight loss (percent excess weight loss, 23.8% [95% CI, 16.2%-31.4%] at the longest follow-up of 4 years) but the 3 procedures have similar associations with most non-weight loss outcomes. Overall postoperative complications are not statistically significantly different between RYGB and SG, although major and/or serious complications are more common after RYGB. However, these associations are susceptible to at least moderate risk of confounding, selection, or measurement biases. Conclusions and Relevance: In the Medicare population, there is low to moderate strength of evidence that bariatric surgery as a weight loss treatment improves non-weight loss outcomes. Well-designed comparative studies are needed to credibly determine the treatment effects for bariatric procedures in this patient population.

Cost-effectiveness of Testing and Treatment for Latent Tuberculosis Infection in Residents Born Outside the United States With and Without Medical Comorbidities in a Simulation Model.

Importance: Testing for and treating latent tuberculosis infection (LTBI) is among the main strategies to achieve TB elimination in the United States. The best approach to testing among non-US born residents, particularly those with comorbid conditions, is uncertain. Objective: To estimate health outcomes, costs, and cost-effectiveness of LTBI testing and treatment among non-US born residents with and without medical comorbidities. Design, Setting, and Participants: Decision analytic tree and Markov cohort simulation model among non-US born residents with no comorbidities, with diabetes, with HIV infection, or with end-stage renal disease (ESRD) using a health care sector perspective with 3% annual discounting. Strategies compared included no testing, tuberculin skin test (TST), interferon gamma release assay (IGRA), confirm positive (initial TST, IGRA only for TST-positive results; both tests positive indicates LTBI), and confirm negative (initial IGRA, then TST for IGRA-negative; any test positive indicates LTBI). All strategies were coupled to treatment with 3 months of self-administered rifapentine and isoniazid. Main Outcomes and Measures: Number needed to test and treat to prevent 1 case of TB reactivation, discounted quality-adjusted life-years (QALYs), discounted lifetime medical costs, and incremental cost-effectiveness ratios (ICERs). Results: Improving health outcomes increased costs, with choice of test dependent on willingness to pay. Strategies ranked by ascending costs and benefits: no testing, confirm positive, TST, IGRA, and confirm negative. The ICERs varied by non-US born patient risk group: patients with no comorbidities, IGRA was likely cost-effective at $83 000/QALY; patients with diabetes, both confirm positive ($53 000/QALY) and IGRA ($120 000/QALY) were likely cost-effective; patients with HIV, confirm negative was clearly preferred ($63 000/QALY); and patients with ESRD, no testing was cost-effective. Increased LTBI prevalence and reduced return for TST reading improved IGRA's relative performance. In 10 000 probabilistic simulations among non-US born patients with no comorbidities, with diabetes, and with HIV, some form of testing was virtually always cost-effective. These simulations highlight the uncertainty of test choice for non-US born patients with no comorbidities and non-US born patients with diabetes, but strategies including IGRA were preferred in over 60% of simulations for all non-US born populations except those with ESRD. Conclusions and Relevance: Testing for and treating LTBI among non-US born residents with and without selected comorbidities is likely cost-effective except among those with ESRD in whom competing risks of death limit benefits. Strategies including IGRA fell below a $100 000/QALY willingness-to-pay threshold for non-US born patients with no comorbidities, patients with diabetes, and patients with HIV.

Recommendations for the Conduct and Reporting of Modeling and Simulation Studies in Health Technology Assessment.

Models and simulations are valuable tools for addressing the uncertainty, tradeoffs, and heterogeneous preferences that complicate research questions in health technology assessment. This article presents recommendations for the conduct and reporting of modeling and simulation studies based on a systematic review of published recommendation statements, a survey of Web sites of international health technology assessment organizations, and input from experts and other stakeholders. The recommendations apply to mathematical models that represent structural relationships among model components and integrate information from multiple sources; they address model identification, estimation, verification, and validation, as well as the conduct of sensitivity, stability, and uncertainty analyses. They are organized into model conceptualization and structure, data, model assessment and consistency, and interpreting and reporting results. They should contribute to increased use and better conduct and reporting of modeling and simulation studies in health technology assessment.

Recommendations for Conduct, Methodological Practices, and Reporting of Cost-effectiveness Analyses: Second Panel on Cost-Effectiveness in Health and Medicine.

IMPORTANCE: Since publication of the report by the Panel on Cost-Effectiveness in Health and Medicine in 1996, researchers have advanced the methods of cost-effectiveness analysis, and policy makers have experimented with its application. The need to deliver health care efficiently and the importance of using analytic techniques to understand the clinical and economic consequences of strategies to improve health have increased in recent years. OBJECTIVE: To review the state of the field and provide recommendations to improve the quality of cost-effectiveness analyses. The intended audiences include researchers, government policy makers, public health officials, health care administrators, payers, businesses, clinicians, patients, and consumers. DESIGN: In 2012, the Second Panel on Cost-Effectiveness in Health and Medicine was formed and included 2 co-chairs, 13 members, and 3 additional members of a leadership group. These members were selected on the basis of their experience in the field to provide broad expertise in the design, conduct, and use of cost-effectiveness analyses. Over the next 3.5 years, the panel developed recommendations by consensus. These recommendations were then reviewed by invited external reviewers and through a public posting process. FINDINGS: The concept of a "reference case" and a set of standard methodological practices that all cost-effectiveness analyses should follow to improve quality and comparability are recommended. All cost-effectiveness analyses should report 2 reference case analyses: one based on a health care sector perspective and another based on a societal perspective. The use of an "impact inventory," which is a structured table that contains consequences (both inside and outside the formal health care sector), intended to clarify the scope and boundaries of the 2 reference case analyses is also recommended. This special communication reviews these recommendations and others concerning the estimation of the consequences of interventions, the valuation of health outcomes, and the reporting of cost-effectiveness analyses. CONCLUSIONS AND RELEVANCE: The Second Panel reviewed the current status of the field of cost-effectiveness analysis and developed a new set of recommendations. Major changes include the recommendation to perform analyses from 2 reference case perspectives and to provide an impact inventory to clarify included consequences.

Using data sources beyond PubMed has a modest impact on the results of systematic reviews of therapeutic interventions.

OBJECTIVES: Searching multiple sources when conducting systematic reviews is considered good practice. We aimed to investigate the impact of using sources beyond PubMed in systematic reviews of therapeutic interventions. STUDY DESIGN AND SETTING: We randomly selected 50 Cochrane reviews that searched the PubMed (or MEDLINE) and EMBASE databases and included a meta-analysis of ≥10 studies. We checked whether each eligible record in each review (n = 2,700) was retrievable in PubMed and EMBASE. For the first-listed meta-analysis of ≥10 studies in each review, we examined whether excluding studies not found in PubMed affected results. RESULTS: A median of one record per review was indexed in EMBASE but not in PubMed; a median of four records per review was not indexed in PubMed or EMBASE. Meta-analyses included a median of 13.5 studies; a median of zero studies per meta-analysis was indexed in EMBASE but not in PubMed; a median of one study per meta-analysis was not indexed in PubMed or EMBASE. Meta-analysis using only PubMed-indexed vs. all available studies led to a different conclusion in a single case (on the basis of conventional criteria for statistical significance). In meta-regression analyses, effects in PubMed- vs. non-PubMed-indexed studies were statistically significantly different in a single data set. CONCLUSION: For systematic reviews of the effects of therapeutic interventions, gains from searching sources beyond PubMed, and from searching EMBASE in particular are modest.

Chapter 10: deciding whether to complement a systematic review of medical tests with decision modeling.

Limited by what is reported in the literature, most systematic reviews of medical tests focus on "test accuracy" (or better, test performance), rather than on the impact of testing on patient outcomes. The link between testing, test results and patient outcomes is typically complex: even when testing has high accuracy, there is no guarantee that physicians will act according to test results, that patients will follow their orders, or that the intervention will yield a beneficial endpoint. Therefore, test performance is typically not sufficient for assessing the usefulness of medical tests. Modeling (in the form of decision or economic analysis) is a natural framework for linking test performance data to clinical outcomes. We propose that (some) modeling should be considered to facilitate the interpretation of summary test performance measures by connecting testing and patient outcomes. We discuss a simple algorithm for helping systematic reviewers think through this possibility, and illustrate it by means of an example.

Toward modernizing the systematic review pipeline in genetics: efficient updating via data mining.

PURPOSE: The aim of this study was to demonstrate that modern data mining tools can be used as one step in reducing the labor necessary to produce and maintain systematic reviews. METHODS: We used four continuously updated, manually curated resources that summarize MEDLINE-indexed articles in entire fields using systematic review methods (PDGene, AlzGene, and SzGene for genetic determinants of Parkinson disease, Alzheimer disease, and schizophrenia, respectively; and the Tufts Cost-Effectiveness Analysis (CEA) Registry for cost-effectiveness analyses). In each data set, we trained a classification model on citations screened up until 2009. We then evaluated the ability of the model to classify citations published in 2010 as "relevant" or "irrelevant" using human screening as the gold standard. RESULTS: Classification models did not miss any of the 104, 65, and 179 eligible citations in PDGene, AlzGene, and SzGene, respectively, and missed only 1 of 79 in the CEA Registry (100% sensitivity for the first three and 99% for the fourth). The respective specificities were 90, 93, 90, and 73%. Had the semiautomated system been used in 2010, a human would have needed to read only 605/5,616 citations to update the PDGene registry (11%) and 555/7,298 (8%), 717/5,381 (13%), and 334/1,015 (33%) for the other three databases. CONCLUSION: Data mining methodologies can reduce the burden of updating systematic reviews, without missing more papers than humans.

Decision-analytic modeling to evaluate benefits and harms of medical tests: uses and limitations.

The clinical utility of medical tests is measured by whether the information they provide affects patient-relevant outcomes. To a large extent, effects of medical tests are indirect in nature. In principle, a test result affects patient outcomes mainly by influencing treatment choices. This indirectness in the link between testing and its downstream effects poses practical challenges to comparing alternate test-and-treat strategies in clinical trials. Keeping in mind the broader audience of researchers who perform comparative effectiveness reviews and technology assessments, the authors summarize the rationale for and pitfalls of decision modeling in the comparative evaluation of medical tests by virtue of specific examples. Modeling facilitates the interpretation of test performance measures by connecting the link between testing and patient outcomes, accounting for uncertainties and explicating assumptions, and allowing the systematic study of tradeoffs and uncertainty. The authors discuss challenges encountered when modeling test-and-treat strategies, including but not limited to scarcity of data on important parameters, transferring estimates of test performance across studies, choosing modeling outcomes, and obtaining summary estimates for test performance data.

Vitamin D and calcium: a systematic review of health outcomes.

BACKGROUND: Since the 1997 Dietary Reference Intake (DRI) values for vitamin D and calcium were established new data have become available on their relationship, both individually and combined, to a wide range of health outcomes. The Institute of Medicine/Food and Nutrition Board has constituted a DRI committee to undertake a review of the evidence and potential revision of the current DRI values for these nutrients. To support this review, several US and Canadian federal government agencies commissioned a systematic review of the scientific literature for use during the deliberations by the committee. The intent of providing a systematic review to the committee is to support transparency of the literature review process and provide a foundation for subsequent reviews of the nutrients. PURPOSE: To systematically summarize the evidence on the relationship between vitamin D, calcium, and a combination of both nutrients on a wide range of health outcomes as identified by the IOM, AHRQ and technical expert panel convened to support the project. DATA SOURCES: MEDLINE; Cochrane Central; Cochrane Database of Systematic Reviews; and the Health Technology Assessments; search limited to English-language articles in humans. STUDY SELECTION: Primary interventional or observational studies that reported outcomes of interest in human subjects in relation to vitamin D and/or calcium, as well as systematic reviews that met the inclusion and exclusion criteria. Cross sectional and retrospective case-control studies were excluded. DATA EXTRACTION: A standardized protocol with predefined criteria was used to extract details on study design, interventions, outcomes, and study quality. DATA SYNTHESIS: We summarized 165 primary articles and 11 systematic reviews that incorporated over 200 additional primary articles. Available evidence focused mainly on bone health, cardiovascular diseases or cancer outcomes. For many outcomes, it was difficult to draw firm conclusions on the basis of the available literature concerning the association of either serum 25(OH)D concentration or calcium intake, or the combination of both nutrients. Findings were inconsistent across studies for colorectal and prostate cancer, and pregnancy-related outcomes including preeclampsia. There were few studies for pancreatic cancer and immune function. Among trials of hypertensive adults, calcium supplementation lowered systolic, but not diastolic, blood pressure by 2-4 mm Hg. For body weight, the trials were consistent in finding no significant effect of increased calcium intake on weight. For growth rates, a meta-analysis did not find a significant effect on weight or height gain attributable to calcium supplement in children. For bone health, one systematic review found that vitamin D plus calcium supplementation resulted in small increases in BMD of the spine and other areas in postmenopausal women. For breast cancer, calcium intakes in premenopausal women were associated with a decreased risk. For prostate cancer, some studies reported that high calcium intakes were associated with an increased risk. LIMITATIONS: Studies on vitamin D and calcium were not specifically targeted at life stages (except for pregnant and postmenopausal women) specified for the determination of DRI. There is large variation on the methodological quality of studies examined. Use of existing systematic reviews limits analyses that could be performed on this source of information. CONCLUSIONS: The majority of the findings concerning vitamin D, calcium, or a combination of both nutrients on the different health outcomes were inconsistent. Synthesizing a dose-response relation between intake of either vitamin D, calcium, or both nutrients and health outcomes in this heterogeneous body of literature proved challenging.

Self-reported health in high and very high incomes.

The objective of the present study was to investigate whether self-reported health (SRH), an overall health indicator, continues to improve as individual income increases to very high levels or whether there is a threshold above which this relationship changes direction. We used data from the 2003 US Current Population Survey, focusing on the upper income decile. We modelled the relationship between income and SRH before and after adjustment for other socio-demographic parameters that are known to influence SRH. In the unadjusted model, SRH increased with increasing income up to the threshold of $326,000, above which SRH declined. After adjustment for all major socio-demographic parameters (age, gender, race, education, and marital status), the adjusted curve showed monotonically increasing SRH with increasing income. Adjustment for each of these parameters separately revealed that the threshold effect was lost only after adjusting for education. There were more people with low levels of educational attainment among those receiving more than $500,000 per year, compared to other people in the upper income decile. Increasing income does not always improve SRH. People in the very high income bracket tend to report slightly worse health, which may be explained by their lower education.

Decision analysis with Markov processes supports early surgery for large-angle infantile esotropia.

PURPOSE: To assess tradeoffs in time spent with aligned visual axes or stereopsis and risked reoperations between three strategies for the treatment of large-angle infantile esotropia: first surgery at 6, 24, or 48 months of age. DESIGN: Decision analysis. METHODS: We simulated three hypothetic cohorts of children with this condition until their eighth year. Potential achievement of stereopsis, the diagnosis of dissociated vertical divergence or inferior oblique overaction, and various complications were modeled. Probability estimates were obtained from a comprehensive literature review. Analyses aimed to determine the strategy that was associated with longer time spent with aligned eyes and/or stereopsis and fewer reoperations. RESULTS: Eight-year-old children are expected to spend 72.6 vs 58.0 vs 37.8 months with aligned eyes and 26.8 vs 9.0 vs 1.5 months with stereopsis and to receive on average 1.76 vs 1.67 vs 1.46 surgeries, if they first underwent operation at 6 vs 24 vs 48 months, respectively. Children at 8 years are expected to have stereopsis at the rate of 36.1% vs 17.2% vs 5.1%, respectively. Operation at 6 months instead of 48 months is expected to yield an additional 9% of total follow-up time in health states with eye alignment and 11% in health states with stereopsis, per 5% increase in risk for extra operations (5% and 7%, respectively, per 5% increase in risk for operation at 6 vs 24 months). Wide-range sensitivity analyses and long-term projections point to the same direction. CONCLUSION: Given the benefit/risk tradeoffs, it is probably warranted to attempt to correct large-angle infantile esotropia as early as possible.

Genetic associations in large versus small studies: an empirical assessment.

BACKGROUND: Advances in human genetics could help us to assess prognosis on an individual basis and to optimise the management of complex diseases. However, different studies on the same genetic association sometimes have discrepant results. Our aim was to assess how often large studies arrive at different conclusions than smaller studies, and whether this situation arises more frequently when findings of first published studies disagree with those of subsequent research. METHODS: We examined the results of 55 meta-analyses (579 study comparisons) of genetic associations and tested whether the magnitude of the genetic effect differs in large versus smaller studies. FINDINGS: We noted significant between-study heterogeneity in 26 (47%) meta-analyses. The magnitude of the genetic effect differed significantly in large versus smaller studies in ten (18%), 20 (36%), and 21 (38%) meta-analyses with tests of rank correlation, regression on SE, and regression on inverse of variance, respectively. The largest studies generally yielded more conservative results than the complete meta-analyses, which included all studies (p=0.005). In 14 (26%) meta-analyses the proposed association was significantly stronger in the first studies than in subsequent research. Only in nine (16%) meta-analyses was the genetic association significant and replicated without hints of heterogeneity or bias. There was little concordance in first versus subsequent discrepancies, and large versus small discrepancies. INTERPRETATION: Genuine heterogeneity and bias could affect the results of genetic association studies. Genetic risk factors for complex diseases should be assessed cautiously and, if possible, using large scale evidence.

Electrocardiogram-gated single-photon emission computed tomography versus cardiac magnetic resonance imaging for the assessment of left ventricular volumes and ejection fraction: a meta-analysis.

OBJECTIVES: The purpose of this study was to evaluate the accuracy of electrocardiogram (ECG)-gated single-photon emission computed tomography (SPECT) for assessment of left ventricular (LV) end-diastolic volume (EDV), end-systolic volume (ESV) and ejection fraction (EF) compared with the gold standard of cardiac magnetic resonance imaging (MRI). BACKGROUND: Several comparisons of ECG-gated SPECT with cardiac MRI have been performed for evaluation of LV volumes and EF, but each has considered few subjects, thus leaving uncertainty about the frequency of discrepancies between the two methods. METHODS: We performed a meta-analysis of data on 164 subjects from nine studies comparing ECG-gated SPECT versus cardiac MRI. Data were pooled in correlation and regression analyses relating ECG-gated SPECT and cardiac MRI measurements. The frequency of discrepancies of at least 30 ml in EDV, 20 ml in ESV and 5% or 10% in EF and concordance for EF < or =40% versus >40% were determined. RESULTS: There was an overall excellent correlation between ECG-gated SPECT and cardiac MRI for EDV (r = 0.89), ESV (r = 0.92) and EF (r = 0.87). However, rates of discrepancies for individual subjects were considerable (37% [95% confidence interval [CI], 26% to 50%] for at least 30 ml in EDV; 35% [95% CI, 23% to 49%] for at least 20 ml in ESV; 52% [95% CI, 37% to 63%] for at least 5% in EF; and 23% [95% CI, 11% to 42%] for at least 10% in EF). The misclassification rate for the 40% EF cutoff was 11%. CONCLUSIONS: Electrocardiogram-gated SPECT measurements of EDV, ESV and EF show high correlation with cardiac MRI measurements, but substantial errors may occur in individual patients. Electrocardiogram-gated SPECT offers useful functional information, but cardiac MRI should be used when accurate measurement is required.