Using an Interaction Parameter in Model-Based Phase I Trials for Combination Treatments? A Simulation Study.

There is growing interest in Phase I dose-finding studies studying several doses of more than one agent simultaneously. A number of combination dose-finding designs were recently proposed to guide escalation/de-escalation decisions during the trials. The majority of these proposals are model-based: a parametric combination-toxicity relationship is fitted as data accumulates. Various parameter shapes were considered but the unifying theme for many of these is that typically between 4 and 6 parameters are to be estimated. While more parameters allow for more flexible modelling of the combination-toxicity relationship, this is a challenging estimation problem given the typically small sample size in Phase I trials of between 20 and 60 patients. These concerns gave raise to an ongoing debate whether including more parameters into combination-toxicity model leads to more accurate combination selection. In this work, we extensively study two variants of a 4-parameter logistic model with reduced number of parameters to investigate the effect of modelling assumptions. A framework to calibrate the prior distributions for a given parametric model is proposed to allow for fair comparisons. Via a comprehensive simulation study, we have found that the inclusion of the interaction parameter between two compounds does not provide any benefit in terms of the accuracy of selection, on average, but is found to result in fewer patients allocated to the target combination during the trial

BMP-7 Does Not Protect against Bleomycin-Induced Lung or Skin Fibrosis

Bone morphogenic protein (BMP)-7 is a member of the BMP family which are structurally and functionally related, and part of the TGFβ super family of growth factors. BMP-7 has been reported to inhibit renal fibrosis and TGFβ1-induced epithelial-mesenchymal transition (EMT), in part through negative interactions with TGFβ1 induced Smad 2/3 activation. We utilized in vivo bleomycin-induced fibrosis models in the skin and lung to determine the potential therapeutic effect of BMP-7. We then determined the effect of BMP-7 on TGFβ1-induced EMT in lung epithelial cells and collagen production by human lung fibroblasts. We show that BMP-7 did not affect bleomycin-induced fibrosis in either the lung or skin in vivo; had no effect on expression of pro-fibrotic genes by human lung fibroblasts, either at rest or following exposure to TGFβ1; and did not modulate TGFβ1 -induced EMT in human lung epithelial cells. Taken together our data indicates that BMP-7 has no anti-fibrotic effect in lung or skin fibrosis either in vivo or in vitro. This suggests that the therapeutic options for BMP-7 may be confined to the renal compartment

Crop Updates 2001 - Cereals

This session covers forty two papers from different authors: PLENARY 1. Planning your cropping program in season 2001, Dr Ross Kingwell, Agriculture Western Australia and University of Western Australia WORKSHOP 2. Can we produce high yields without high inputs? Wal Anderson, Centre for Cropping Systems, Agriculture Western Australia VARIETIES 3. Local and interstate wheat variety performance and $ return to WA growers, Eddy Pol, Peter Burgess and Ashley Bacon, Agritech Crop Research CROP ESTABLISHMENT 4 Soil management of waterlogged soils, D.M. Bakker, G.J. Hamilton, D. Houlbrooke and C. Spann, Agriculture Western Australia 5. Effect of soil amelioration on wheat yield in a very dry season, M.A Hamza and W.K. Anderson, Agriculture Western Australia 6. Fuzzy tramlines for more yield and less weed, Paul Blackwell1 and Maurice Black2 1Agriculture Western Australia, 2Harbour Lights Estate, Geraldton 7. Tramline farming for dollar benefits, Paul Blackwell, Agriculture Western Australia NUTRITION 8. Soil immobile nutrients for no-till crops, M.D.A. Bolland1, R.F. Brennan1,and W.L. Crabtree2, 1Agriculture Western Australia, 2Western Australian No-Tillage Farmers Association 9. Burn stubble windrows: to diagnose soil fertility problems, Bill Bowden, Chris Gazey and Ross Brennan, Agriculture Western Australia 10. Calcium: magnesium ratios; are they important? Bill Bowden1, Rochelle Strahan2, Bob Gilkes2 and Zed Rengel2 1Agriculture Western Australia, 2Department of Soil Science and Plant Nutrition, UWA 11. Responses to late foliar applications of Flexi-N, Stephen Loss, Tim O’Dea, Patrick Gethin, Ryan Guthrie, Lisa Leaver, CSBP futurefarm 12. A comparison of Flexi-N placements, Stephen Loss, Tim O’Dea, Patrick Gethin, Ryan Guthrie, Lisa Leaver, CSBP futurefarm 13. What is the best way to apply potassium? Stephen Loss, Tim O’Dea, Patrick Gethin, Ryan Guthrie, CSBP futurefarm 14. Claying affects potassium nutrition in barley, Stephen Loss, David Phelps, Tim O’Dea, Patrick Gethin, Ryan Guthrie, Lisa Leaver, CSBP futurefarm 15. Nitrogen and potassium improve oaten hay quality, Stephen Loss, Tim O’Dea, Patrick Gethin, Ryan Guthrie, Lisa Leaver, CSBP futurefarm AGRONOMY 16. Agronomic responses of new wheat varieties in the northern wheatbelt, Darshan Sharma and Wal Anderson, Agriculture Western Australia 17. Wheat agronomy research on the south coast, Mohammad Amjad and Wal Anderson, Agriculture Western Australia 18. Influence of sowing date on wheat yield and quality in the south coast environment, Mohammad Amjadand Wal Anderson, Agriculture Western Australia 19. More profit from durum, Md.Shahajahan Miyan and Wal Anderson, Agriculture Western Australia 20. Enhancing recommendations of flowering and yield in wheat, JamesFisher1, Senthold Asseng2, Bill Bowden1 and Michael Robertson3 ,1AgricultureWestern Australia, 2CSIRO Plant Industry, 3CSIRO Sustainable Ecosystems 21. When and where to grow oats, Glenn McDonald, Agriculture Western Australia 22. Managing Gaidner barley for quality, Kevin Young and Blakely Paynter, Agriculture Western Australia PESTS AND DISEASES 23. Strategies for leaf disease management in wheat, Jatinderpal Bhathal1, Cameron Weeks2, Kith Jayasena1 and Robert Loughman1 ,1Agriculture Western Australia. 2Mingenew-Irwin Group Inc 24. Strategies for leaf disease management in malting barley, K. Jayasena1, Q. Knight2 and R. Loughman1, 1Agriculture Western Australia, 2IAMA Agribusiness 25. Cereal disease diagnostics, Dominie Wright and Nichole Burges, Agriculture Western Australia 26. The big rust: Did you get your money back!! Peter Burgess, Agritech Crop Research 27. Jockey – winning the race against disease in wheat, Lisa-Jane Blacklow, Rob Hulme and Rob Giffith, Aventis CropScience 28. Distribution and incidence of aphids and barley yellow dwarf virus in over-summering grasses in WA wheatbelt, Jenny Hawkes and Roger Jones, CLIMA and Agriculture Western Australia 29. Further developments in forecasting aphid and virus risk in cereals, Debbie Thackray, Jenny Hawkes and Roger Jones, Agriculture Western Australia and Centre for Legumes in Mediterranean Agriculture 30. Effect of root lesion nematodes on wheat yields in Western Australia, S. B. Sharma, S. Kelly and R. Loughman, Crop Improvement Institute, Agriculture Western Australia 31. Rotational crops and varieties for management of root lesion nematodes in Western Australia, S.B. Sharma, S. Kelly and R. Loughman, Crop Improvement Institute, Agriculture Western Australia WEEDS 32. Phenoxy herbicide tolerance of wheat, Peter Newman and Dave Nicholson, Agriculture Western Australia 33. Tolerance of wheat to phenoxy herbicides,Harmohinder S. Dhammu, Terry Piper and Mario F. D\u27Antuono, Agriculture Western Australia 34. Herbicide tolerance of durum wheats, Harmohinder S. Dhammu, Terry Piper and David Nicholson, Agriculture Western Australia 35. Herbicide tolerance of new wheats, Harmohinder S. Dhammu, Terry Piper and David F. Nicholson, Agriculture Western Australia BREEDING 36. Towards molecular breeding of barley: construction of a molecular genetic map, Mehmet Cakir1, Nick Galwey1, David Poulsen2, Garry Ablett3, Reg Lance4, Rob Potter5 and Peter Langridge6,1Plant Sciences, Faculty of Agriculture, UWA, 2Queensland Department of Primary Industries, Qld, 3Centre for Plant Conservation Genetics Southern Cross University, Lismore NSW, 5SABC Murdoch University, WA, 6Department of Plant Science University of Adelaide, Glen Osmond SA 37. Toward molecular breeding of barley: Identifying markers linked to genes for quantitative traits, Mehmet Cakir1, Nick Galwey1, David Poulsen2, Reg Lance3, Garry Ablett4, Greg Platz2, Joe Panozzo5, Barbara Read6, David Moody5, Andy Barr7 and Peter Langridge7 , 1Plant Sciences, Faculty of Agriculture, UWA, 2Queensland Department of Primary Industries, Warwick, QLD,3Agriculture Western Australia, 4Centre for Plant Conservation Genetics, Southern Cross University, Lismore NSW, 5VIDA Private Bag 260, Horsham VIC, 6NSW Dept. of Agriculture, Wagga Wagga NSW, 7Department of Plant Science, University of Adelaide, Glen Osmond SA 38. Can we improve grain yield by breeding for greater early vigour in wheat? Tina Botwright1, Tony Condon1, Robin Wilson2 and Iain Barclay2, 1CSIRO Plant Industry, 2Agriculture Western Australia MARKETING AND QUALITY 39. The Crop Improvement Royalty, Howard Carr, Agriculture Western Australia 40. GrainGuardÔ - The development of a protection plan for the wheat industry, Greg Shea, Agriculture Western Australia CLIMATE 41. Rainfall – what happened in 2000 and the prospects for 2001, Ian Foster, Agriculture Western Australia 42. Software for climate management issues, David Tennant,Agriculture Western Australia CONTRIBUTING AUTHOR CONTACT DETAIL

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK

Risk factors for Coronavirus disease 2019 (Covid-19) death in a population cohort study from the Western Cape province, South Africa

Risk factors for coronavirus disease 2019 (COVID-19) death in sub-Saharan Africa and the effects of human immunodeficiency virus (HIV) and tuberculosis on COVID-19 outcomes are unknown. We conducted a population cohort study using linked data from adults attending public-sector health facilities in the Western Cape, South Africa. We used Cox proportional hazards models, adjusted for age, sex, location, and comorbidities, to examine the associations between HIV, tuberculosis, and COVID-19 death from 1 March to 9 June 2020 among (1) public-sector “active patients” (≥1 visit in the 3 years before March 2020); (2) laboratory-diagnosed COVID-19 cases; and (3) hospitalized COVID-19 cases. We calculated the standardized mortality ratio (SMR) for COVID-19, comparing adults living with and without HIV using modeled population estimates.Among 3 460 932 patients (16% living with HIV), 22 308 were diagnosed with COVID-19, of whom 625 died. COVID19 death was associated with male sex, increasing age, diabetes, hypertension, and chronic kidney disease. HIV was associated with COVID-19 mortality (adjusted hazard ratio [aHR], 2.14; 95% confidence interval [CI], 1.70–2.70), with similar risks across strata of viral loads and immunosuppression. Current and previous diagnoses of tuberculosis were associated with COVID-19 death (aHR, 2.70 [95% CI, 1.81–4.04] and 1.51 [95% CI, 1.18–1.93], respectively). The SMR for COVID-19 death associated with HIV was 2.39 (95% CI, 1.96–2.86); population attributable fraction 8.5% (95% CI, 6.1–11.1)

Correlation of mutation status and survival with predominant histologic subtype according to the new IASLC/ATS/ERS lung adenocarcinoma classification in stage III (N2) patients

IntroductionWe investigated the relationship between predominant subtype, according to the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society International Multidisciplinary Lung Adenocarcinoma Classification; mutation status; and patient outcome in stage III (N2) lung adenocarcinoma.MethodsWe identified 69 patients with stage III (N2) lung adenocarcinoma operated on with curative intent between 1993 and 2011 who had adequate tumor tissue for molecular analysis and adequate follow-up time for survival analysis. DNA was isolated and tested for mutations using Sequenom's OncoCarta Panel (v1.0; Sequenom, San Diego, CA).ResultsThe majority of tumors were acinar (26 of 69 tumors; 38%), solid (24 of 69 tumors; 35%), and micropapillary predominant (13 of 69 tumors; 19%) subtypes. EGFR and KRAS mutations were identified in 17 of 59 tumors (29%) and 13 of 59 tumors (22%), respectively. EGFR mutations occurred most often in acinar (11 of 25 tumors; 44%) and micropapillary predominant tumors (five of 13 tumors; 38%) (p = 0.009), whereas KRAS mutations occurred most often in solid predominant tumors (nine of 21 tumors; 43%) (p = 0.016). Patients with acinar predominant tumors had significantly improved overall survival compared with those with non-acinar predominant tumors (hazard ratio: 0.45; 95% confidence interval: 0.22–0.91; p = 0.026), which remained significant after adjustment for EGFR status, T-stage, sex, and age. Patients with EGFR-mutant micropapillary predominant tumors had similar survival to those with EGFR-mutant acinar predominant tumors. The predominant subtype in the primary tumor was most often seen in the N2 node in micropapillary and solid predominant tumors but not in acinar predominant tumors.ConclusionsThe predominant subtype in the primary tumor was associated with overall survival in resected stage III (N2) lung adenocarcinoma and was independent of mutation status. Histologic subtyping provides important prognostic information and potentially molecular correlates

Serum amyloid P ameliorates radiation-induced oral mucositis and fibrosis

Purpose: To evaluate the effect of the anti-fibrotic protein serum amyloid P (SAP) on radiation-induced oral mucositis (OM) and fibrosis in a hamster cheek-pouch model. Experimental Design: Hamsters received a single dose of radiation (40 Gy) to the left everted cheek pouch to induce significant OM. The protective therapeutic potential of SAP was evaluated using varying dosing regimens. The extent of OM was measured using a validated six-point scoring scheme ranging from 0 (normal tissue, no mucositis) to 5 (complete ulceration). Fibrotic remodeling was also visualized histologically and quantified at later time points using collagen gene expression. Results: SAP treatment attenuated the profile of radiation-induced oral mucositis by delaying the time of onset, reducing the peak value, and enhancing the resolution of injury. The peak mucositis score was reduced by approximately 0.5 grade in SAP-treated animals. The number of animal days with a score of ≥ 3 was reduced by 48% in the SAP-treated group, compared with the saline control group (P < 0.01). SAP also inhibited the extent of tissue remodeling and decreased radiation-induced increases in myofibroblast number. Attenuated collagen deposition and gene expression was also observed in the cheek pouches of hamsters treated with SAP at both 16 and 28 days post-radiation. Conclusions: SAP treatment significantly attenuated radiation-induced injury. In particular, SAP attenuated the severity of OM and inhibited pathogenic remodeling. This suggests that SAP may be a useful therapy for the palliation of side effects observed during treatment for head and neck cancer.Medicine, Faculty ofNon UBCAnesthesiology, Pharmacology and Therapeutics, Department ofReviewedFacult