Correlations between comorbidities in trials and the community: an individual-level participant data meta-analysis

Background: People with comorbidities are under-represented in randomised controlled trials, and it is unknown whether patterns of comorbidity are similar in trials and the community. Methods: Individual-level participant data were obtained for 83 clinical trials (54,688 participants) for 16 index conditions from two trial repositories: Yale University Open Data Access (YODA) and the Centre for Global Clinical Research Data (Vivli). Community data (860,177 individuals) were extracted from the Secure Anonymised Information Linkage (SAIL) databank for the same index conditions. Comorbidities were defined using concomitant medications. For each index condition, we estimated correlations between comorbidities separately in trials and community data. For the six commonest comorbidities we estimated all pairwise correlations using Bayesian multivariate probit models, conditioning on age and sex. Correlation estimates from trials with the same index condition were combined into a single estimate. We then compared the trial and community estimates for each index condition. Results: Despite a higher prevalence of comorbidities in the community than in trials, the correlations between comorbidities were mostly similar in both settings. On comparing correlations between the community and trials, 21% of correlations were stronger in the community, 10% were stronger in the trials and 68% were similar in both. In the community, 5% of correlations were negative, 21% were null, 56% were weakly positive and 18% were strongly positive. Equivalent results for the trials were 11%, 33%, 45% and 10% respectively. Conclusions: Comorbidity correlations are generally similar in both the trials and community, providing some evidence for the reporting of comorbidity-specific findings from clinical trials

Treatment effect modification due to comorbidity : Individual participant data meta-analyses of 120 randomised controlled trials

BACKGROUND: People with comorbidities are underrepresented in clinical trials. Empirical estimates of treatment effect modification by comorbidity are lacking, leading to uncertainty in treatment recommendations. We aimed to produce estimates of treatment effect modification by comorbidity using individual participant data (IPD). METHODS AND FINDINGS: We obtained IPD for 120 industry-sponsored phase 3/4 trials across 22 index conditions (n = 128,331). Trials had to be registered between 1990 and 2017 and have recruited ≥300 people. Included trials were multicentre and international. For each index condition, we analysed the outcome most frequently reported in the included trials. We performed a two-stage IPD meta-analysis to estimate modification of treatment effect by comorbidity. First, for each trial, we modelled the interaction between comorbidity and treatment arm adjusted for age and sex. Second, for each treatment within each index condition, we meta-analysed the comorbidity-treatment interaction terms from each trial. We estimated the effect of comorbidity measured in 3 ways: (i) the number of comorbidities (in addition to the index condition); (ii) presence or absence of the 6 commonest comorbid diseases for each index condition; and (iii) using continuous markers of underlying conditions (e.g., estimated glomerular filtration rate (eGFR)). Treatment effects were modelled on the usual scale for the type of outcome (absolute scale for numerical outcomes, relative scale for binary outcomes). Mean age in the trials ranged from 37.1 (allergic rhinitis trials) to 73.0 (dementia trials) and percentage of male participants range from 4.4% (osteoporosis trials) to 100% (benign prostatic hypertrophy trials). The percentage of participants with 3 or more comorbidities ranged from 2.3% (allergic rhinitis trials) to 57% (systemic lupus erythematosus trials). We found no evidence of modification of treatment efficacy by comorbidity, for any of the 3 measures of comorbidity. This was the case for 20 conditions for which the outcome variable was continuous (e.g., change in glycosylated haemoglobin in diabetes) and for 3 conditions in which the outcomes were discrete events (e.g., number of headaches in migraine). Although all were null, estimates of treatment effect modification were more precise in some cases (e.g., sodium-glucose co-transporter-2 (SGLT2) inhibitors for type 2 diabetes-interaction term for comorbidity count 0.004, 95% CI -0.01 to 0.02) while for others credible intervals were wide (e.g., corticosteroids for asthma-interaction term -0.22, 95% CI -1.07 to 0.54). The main limitation is that these trials were not designed or powered to assess variation in treatment effect by comorbidity, and relatively few trial participants had >3 comorbidities. CONCLUSIONS: Assessments of treatment effect modification rarely consider comorbidity. Our findings demonstrate that for trials included in this analysis, there was no empirical evidence of treatment effect modification by comorbidity. The standard assumption used in evidence syntheses is that efficacy is constant across subgroups, although this is often criticised. Our findings suggest that for modest levels of comorbidities, this assumption is reasonable. Thus, trial efficacy findings can be combined with data on natural history and competing risks to assess the likely overall benefit of treatments in the context of comorbidity

Crop Updates 2002 - Farming Systems

This session covers forty one papers from different authors: INTRODUCTION 1. Future Farming Systems session for Crop Updates 2002 Peter Metcalf, FARMING SYSTEMS SUBPROGRAM MANAGER GRAINS PROGRAM Department of Agriculture 2. Perennial pastures in annual cropping systems: Lucerne and beyond, the ‘Big Picture’, Mike Ewing, Deputy CEO CRC for Plant-based Management of Dryland Salinity, Department of Agriculture 3. Perennial pastures in annual cropping systems: lucerne and beyond, Roy Latta and Keith Devenish, Department of Agriculture 4. Establishing Lucerne with a cover crop, Diana Fedorenko1, Clayton Butterly1, Chantelle Butterly1, Kim and Neil Diamond2, Stuart McAlpine2, Bill Bowden1, Jessica Johns3, 1Centre for Cropping Systems, Northam, 2Farmer, Buntine, 3Department of Agriculture 5. Overcropping: Chemical suppression of Lucerne, Terry Piper1, Diana Fedorenko1, Clayton Butterly1, Chantelle Butterly1, Stuart McAlpine2, Jessica Johns3, 1Centre for Cropping Systems, Northam, 2Farmer, Buntine, 3Department of Agriculture 6. Overcropping: Effect of Lucerne density on crop yield, Diana Fedorenko1, Bill Bowden1, Clayton Butterly1, Chantelle Butterly1, Stuart McAlpine2, Terry Piper1,1Centre for Cropping Systems, Department of Agriculture, Northam, 2Farmer, Buntine 7. Residual effect of weed management in the third year of Lucerne on the following wheat crop, Diana Fedorenko1, Clayton Butterly1, Chantelle Butterly1, Stuart McAlpine2,Terry Piper1, David Bowran1, Jessica Johns3,1Centre for Cropping Systems, Northam, 2Farmer, Buntine, 3Department of Agriculture 8. Production of Lucerne and serradella in four soil types, Diana Fedorenko1 Clayton Butterly1, Chantelle Butterly1, Robert Beard2 1Centre for Cropping Systems, Department of Agriculture, 2Farmer, Cunderdin 9. The effect of spray topping on newly established Lucerne, Keith Devenish, Agriculture Western Australia 10. Leakage from phase rotations involving Lucerne, Phil Ward, CSIRO Plant Industry 11. Fungal diseases present in Western Australian Lucerne crops, Dominie Wright and Nichole Burges, Department of Agriculture 12. Survey of Western Australian Lucerne stands reveals widespread virus infection, Roger Jones and Danae Harman, Crop Improvement Institute, Department of Agriculture, and Centre for Legumes in Mediterranean Agriculture, University of WA ANNUAL PASTURE SYSTEMS 13. The use of Twist Fungus as a biosecurity measure against Annual Ryegrass Toxicity (ARGT), Greg Shea, GrainGuard Coordinator and George Yan, Biological and Resource Technology 14.Limitations and opportunities for increasing water use by annual crops and pastures, David Tennant1, Phil Ward2and David Hall1 1Department of Agriculture, 2CSIRO, Plant Industries, Floreat Park 15. Developing pasture species mixtures for more productive and sustainable cropping systems – 2001 crop performance, Anyou Liu, Clinton Revell and Candy Hudson, Centre for Cropping Systems, Department of Agriculture 16. Developing pasture species mixtures for more productive and sustainable cropping systems – weed management in regenerating mixtures, Anyou Liu and Clinton Revell, Centre for Cropping Systems, Department of Agriculture 17. Aphid tolerance of annual pasture legumes, Andrew Blake, Natalie Lauritsen, Department of Agriculture 18. Selecting the right variety for phase pasture systems, Keith Devenish, Department of Agriculture 19. Responses of alternative annual pasture and forage legumes to challenge with infectious subterranean clover mottle virus, John Fosu-Nyarko, Roger Jones, Lisa Smith, Mike Jones and Geoff Dwyer, State Agricultural Biotechnology Centre and Centre for Bioinformatics and Biological Computing, Murdoch University, Department of Agriculture, and Centre for Legumes in Mediterranean Agriculture SOIL AND LAND MANAGEMENT 20. Nutrition in 2002: Decisions to be made as a result of last season, Bill Bowden,Western Australia Department of Agriculture 21. Profitability of deep banding lime, Michael O\u27Connell, Chris Gazey and David Gartner, Department of Agriculture 22. Lime efficiency percentage…the new measure of lime effectiveness for Western Australia, Amanda Miller, Department of Agriculture 23. Boron – should we be worried about it, Richard W. BellA, K. FrostA, Mike WongBand Ross BrennanC ASchool of Environmental Science, Murdoch University, BCSIRO Land and Water, CDepartment of Agriculture 24. Impact of claying and other amelioration on paddock profit, N.J. Blake1, G. McConnell2, D. Patabendige1and N. Venn11Department of Agriculture, 2PlanFarm P/L 25. Raised bed farming in the 2001 growing season, Derk Bakker, Greg Hamilton, Dave Houlbrooke and Cliff Spann, Department of Agriculture 26. Economics of tramline farming systems, Paul Blackwell and Bindi Webb, Department of Agriculture, Stuart McAlpine, Liebe Group. 27. Relay planting from Tramlines to increase water use and productivity os summer crops, Dr Paul Blackwell, Department of Agriculture, Neil and Kim Diamond, Buntine. Liebe Group 28.Evidence-based zone management of paddock variability to improve profits and environmental outcomes, M.T.F. WongA, D. PatabendigeB, G. LyleA and K. WittwerA ACSIRO Land and Water, BDepartment of Agriculture 29. How much soil water is lost over summer in sandy soils? Perry Dolling1, Senthold Asseng2, Ian Fillery2, Phil Ward2and Michael Robertson3 1University of Western Australia/Department of Agriculture Western Australia/CSIRO, 2CSIRO Plant Industry 3CSIRO Sustainable Ecosystems, Indooroopilly, Queensland FARMER DECISION SUPPORT AND ADOPTION 30. Economic comparisons of farming systems for the medium rainfall northern sandplain, No 1, Caroline Peek and David Rogers, Department of Agriculture 31. Sensitivity analysis of farming systems for the medium rainfall northern sandplain No 2, Caroline Peek and David Rogers, Department of Agriculture 32. Transition analysis of farming systems in the medium rainfall northern sandplain. No 3, Caroline Peek and David Rogers, Department of Agriculture 33. Implementing on-farm quality assurance, Peter Portmann, Manager Research and Development, The Grain Pool of Western Australia 34. On-farm research – principles of the ‘Test As You Grow’ kit, Jeff Russell, Department of Agriculture 35. Broadscale wheat variety comparisons featuring Wyalkatchem, Jeff Russell, Department of Agriculture 36. GrainGuardÔ - A biosecurity plan for the Canola Industry,Greg Shea Department of Agriculture 37. Are Western Australian broadacre farms efficient? Ben Henderson, University of Western Australia, Ross Kingwell, Department of Agriculture and University of Western Australia DISEASE MODELLING WORKSHOP 38. WORKSHOP: Pest and disease forecasts for you! An interactive forum, Tresslyn Walmsley, Jean Galloway, Debbie Thackray, Moin Salam and Art Diggle, Centre for Legumes in Mediterranean Agriculture and Department of Agriculture 39. Blackspot spread: Disease models are based in reality (Workshop paper 1), JeanGalloway,Department of Agriculture 40. Blackspot spread: Scaling-up field data to simulate ‘Baker’s farm’ (Workshop paper 2), Moin U. Salam, Jean Galloway, Art J. Diggle and William J. MacLeod, Department of Agriculture, Western Australia 41. A decision support system for control of aphids and CMV in lupin crops (Workshop paper 3), Debbie Thackray, Jenny Hawkes and Roger Jones, Centre for Legumes in Mediterranean Agriculture and Department of Agricultur

A role for leukotrienes in cyclosporine nephrotoxicity

A role for leukotrienes in cyclosporine nephrotoxicity. Nephrotoxicity associated with cyclosporine A (CsA) administration is characterized by marked renal vasoconstriction, interstitial fibrosis, and arteriolar hypertrophy. While the molecular mechanisms of CsA toxicity are not well characterized, previous studies have demonstrated that altered arachidonic acid (AA) metabolism plays a role its pathogenesis. Using a rat renal transplant model, the purpose of this study was to examine the effects of CsA on the 5-lipoxygenase (5-LO) pathway of AA metabolism. The PVG (RT1c) strain of rats underwent kidney transplantation, and recipients of nonrejecting kidney transplants were treated with either 50 mg/kg/day CsA or vehicle (N = 24). To determine the physiologic significance of increased leukotriene (LT) production, the peptidoleukotriene receptor antagonist SKF 106203 was administered to CsA-treated animals for six days. CsA caused a substantial reduction in glomerular filtration rate (GFR) in the transplanted rats compared with the vehicle-treated controls (1.5 ± 0.6 vs. 4.1 ± 0.8 mL/min/kg, P < 0.05). The reduction in renal function was associated with enhanced urinary excretion of the peptidoleukotriene metabolites LTE4 (1431 ± 207 vs. 953 ± 125 pg/24 h, P < 0.05) and N-acetyl-LTE4 (4411 ± 848 vs. 463 ± 70 pg/24 h, P < 0.001). LT receptor blockade had a significant protective effect on renal transplant function in CsA-treated animals (GFR, 4.8 ± 1.1 vs. 1.7 ± 0.9 mL/min/kg, P < 0.05), such that CsA-treated animals that received SKF106203 maintained GFR at levels similar to controls that never received CsA (4.1 ± 0.8 mL/min/kg). Peptidoleukotriene receptor blockade also prevented the histomorphological abnormalities caused by CsA, including tubular vacuolization. These studies identify a critical role for LTs in the pathophysiology of CsA nephrotoxicity and suggest that LT antagonists may be useful in preventing CsA-associated kidney toxicity

Proton-decoupled phosphorus-31 magnetic resonance spectroscopy in the evaluation of native and well-functioning transplanted kidneys

Rationale and objectives: To evaluate whether decoupling improves signal-to-noise ratio and frequency resolution of in vivo kidney spectra, and to compare native and well-functioning transplant kidneys. Methods: Proton decoupling in conjunction with three-dimensional chemical shift imaging (3D-CSI) in phosphorus-31 magnetic resonance (MR) spectroscopy was used with a spatial resolution of 64 cm3 and 17-minute acquisition time to compare native (n = 10) and well-functioning transplant (n = 9) kidneys. Results: Proton decoupling improved peak amplitudes by almost 30%, as well as chemical shift resolution of in vivo kidney spectra. No statistically significant differences in phosphometabolite ratios and renal spectra were observed between healthy volunteers and patients with nonrejecting transplants. The phosphodiester-phosphomonoester ratio was 3.02 +/- 0.88, phosphomonoester-inorganic phosphate ratio was 1.07 +/- 0.44, and inorganic phosphate-adenosine triphosphate ratio was 0.58 +/- 0.22 after correction for saturation effects. Conclusion: Improved spectra of native and transplant kidneys can be obtained in vivo with MR spectroscopy by using a short acquisition time.</p

Correlations between comorbidities in trials and the community: An individual-level participant data meta-analysis

David McAllister was funded to complete this work via an Intermediate Clinical Fellowship and Beit Fellowship from the Wellcome Trust, who also supported other costs related to this project such as data access costs and database licences (“Treatment effectiveness in multimorbidity: Combining efficacy estimates from clinical trials with the natural history obtained from large routine healthcare databases to determine net overall treatment Benefits.” - 201492/Z/16/Z). Peter Hanlon is funded through a Clinical Research Training Fellowship from the Medical Research Council (Grant reference: MR/S021949/1).Background People with comorbidities are under-represented in randomised controlled trials, and it is unknown whether patterns of comorbidity are similar in trials and the community. Methods Individual-level participant data were obtained for 83 clinical trials (54,688 participants) for 16 index conditions from two trial repositories: Yale University Open Data Access (YODA) and the Centre for Global Clinical Research Data (Vivli). Community data (860,177 individuals) were extracted from the Secure Anonymised Information Linkage (SAIL) databank for the same index conditions. Comorbidities were defined using concomitant medications. For each index condition, we estimated correlations between comorbidities separately in trials and community data. For the six commonest comorbidities we estimated all pairwise correlations using Bayesian multivariate probit models, conditioning on age and sex. Correlation estimates from trials with the same index condition were combined into a single estimate. We then compared the trial and community estimates for each index condition. Results Despite a higher prevalence of comorbidities in the community than in trials, the correlations between comorbidities were mostly similar in both settings. On comparing correlations between the community and trials, 21% of correlations were stronger in the community, 10% were stronger in the trials and 68% were similar in both. In the community, 5% of correlations were negative, 21% were null, 56% were weakly positive and 18% were strongly positive. Equivalent results for the trials were 11%, 33%, 45% and 10% respectively. Conclusions Comorbidity correlations are generally similar in both the trials and community, providing some evidence for the reporting of comorbidity-specific findings from clinical trials.Peer reviewe