Background Total knee arthroplasty (TKA) relieves pain and improves quality of life for persons with advanced knee osteoarthritis. However, to our knowledge, the cost-effectiveness of TKA and the influences of hospital volume and patient risk on TKA cost-effectiveness have not been investigated in the United States. Methods We developed a Markov, state-transition, computer simulation model and populated it with Medicare claims data and cost and outcomes data from national and multinational sources. We projected lifetime costs and quality-adjusted life expectancy (QALE) for different risk populations and varied TKA intervention and hospital volume. Cost-effectiveness of TKA was estimated across all patient risk and hospital volume permutations. Finally, we conducted sensitivity analyses to determine various parameters’ influences on cost-effectiveness. Results Overall, TKA increased QALE from 6.822 to 7.957 quality-adjusted life years (QALYs). Lifetime costs rose from $37 100 (no TKA) to $57 900 after TKA, resulting in an incremental cost-effectiveness ratio of $18 300 per QALY. For high-risk patients, TKA increased QALE from 5.713 to 6.594 QALY, yielding a cost-effectiveness ratio of $28 100 per QALY. At all risk levels, TKA was more costly and less effective in low-volume centers than in high-volume centers. Results were insensitive to variations of key input parameters within policy-relevant, clinically plausible ranges. The greatest variations were seen for the quality of life gain after TKA and the cost of TKA. Conclusions Total knee arthroplasty appears to be cost-effective in the US Medicare-aged population, as currently practiced across all risk groups. Policy decisions should be made on the basis of available local options for TKA. However, when a high-volume hospital is available, TKAs performed in a high-volume hospital confer even greater value per dollar spent than TKAs performed in low-volume centers.

Background Obesity and knee osteoarthritis are among the most frequent chronic conditions affecting Americans aged 50 to 84 years. Objective To estimate quality-adjusted life-years lost due to obesity and knee osteoarthritis and health benefits of reducing obesity prevalence to levels observed a decade ago. Design The U.S. Census and obesity data from national data sources were combined with estimated prevalence of symptomatic knee osteoarthritis to assign persons aged 50 to 84 years to 4 subpopulations: nonobese without knee osteoarthritis (reference group), nonobese with knee osteoarthritis, obese without knee osteoarthritis, and obese with knee osteoarthritis. The Osteoarthritis Policy Model, a computer simulation model of knee osteoarthritis and obesity, was used to estimate quality-adjusted life-year losses due to knee osteoarthritis and obesity in comparison with the reference group. Setting United States. Participants U.S. population aged 50 to 84 years. Measurements Quality-adjusted life-years lost owing to knee osteoarthritis and obesity. Results Estimated total losses of per-person quality-adjusted life-years ranged from 1.857 in nonobese persons with knee osteoarthritis to 3.501 for persons affected by both conditions, resulting in a total of 86.0 million quality-adjusted life-years lost due to obesity, knee osteoarthritis, or both. Quality-adjusted life-years lost due to knee osteoarthritis and/or obesity represent 10% to 25% of the remaining quality-adjusted survival of persons aged 50 to 84 years. Hispanic and black women had disproportionately high losses. Model findings suggested that reversing obesity prevalence to levels seen 10 years ago would avert 178 071 cases of coronary heart disease, 889 872 cases of diabetes, and 111 206 total knee replacements. Such a reduction in obesity would increase the quantity of life by 6 318 030 years and improve life expectancy by 7 812 120 quality-adjusted years in U.S. adults aged 50 to 84 years. Limitations Comorbidity incidences were derived from prevalence estimates on the basis of life expectancy of the general population, potentially resulting in conservative underestimates. Calibration analyses were conducted to ensure comparability of model-based projections and data from external sources. Conclusion The number of quality-adjusted life-years lost owing to knee osteoarthritis and obesity seems to be substantial, with black and Hispanic women experiencing disproportionate losses. Reducing mean body mass index to the levels observed a decade ago in this population would yield substantial health benefits. Primary Funding Source The National Institutes of Health and the Arthritis Foundation.

BackgroundOrganisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses.ResultsWe identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses.ConclusionsOur meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3597-6) contains supplementary material, which is available to authorized users.

BackgroundSocial insects, such as honey bees, use molecular, physiological and behavioral responses to combat pathogens and parasites. The honey bee genome contains all of the canonical insect immune response pathways, and several studies have demonstrated that pathogens can activate expression of immune effectors. Honey bees also use behavioral responses, termed social immunity, to collectively defend their hives from pathogens and parasites. These responses include hygienic behavior (where workers remove diseased brood) and allo-grooming (where workers remove ectoparasites from nestmates). We have previously demonstrated that immunostimulation causes changes in the cuticular hydrocarbon profiles of workers, which results in altered worker-worker social interactions. Thus, cuticular hydrocarbons may enable workers to identify sick nestmates, and adjust their behavior in response. Here, we test the specificity of behavioral, chemical and genomic responses to immunostimulation by challenging workers with a panel of different immune stimulants (saline, Sephadex beads and Gram-negative bacteria E. coli).ResultsWhile only bacteria-injected bees elicited altered behavioral responses from healthy nestmates compared to controls, all treatments resulted in significant changes in cuticular hydrocarbon profiles. Immunostimulation caused significant changes in expression of hundreds of genes, the majority of which have not been identified as members of the canonical immune response pathways. Furthermore, several new candidate genes that may play a role in cuticular hydrocarbon biosynthesis were identified. Effects of immune challenge expression of several genes involved in immune response, cuticular hydrocarbon biosynthesis, and the Notch signaling pathway were confirmed using quantitative real-time PCR. Finally, we identified common genes regulated by pathogen challenge in honey bees and other insects.ConclusionsThese results demonstrate that honey bee genomic responses to immunostimulation are substantially broader than the previously identified canonical immune response pathways, and may mediate the behavioral changes associated with social immunity by orchestrating changes in chemical signaling. These studies lay the groundwork for future research into the genomic responses of honey bees to native honey bee parasites and pathogens.