Publications by authors named "James D Best"

70 Publications

Letter to the Editor Regarding "Public Health Approaches to Type 2 Diabetes Prevention: The US National Diabetes Prevention Program and Beyond".

Authors:
James A Dunbar Vincent Versace Edward Janus Tiina Laatikainen Erkki Vartiainen Pilvikki Absetz James D Best Craig Bennett

Curr Diab Rep 2019 11 20;19(11):130. Epub 2019 Nov 20.

Diabetes Victoria, Melbourne, Australia.

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http://dx.doi.org/10.1007/s11892-019-1262-yDOI Listing
November 2019

Results of the first recorded evaluation of a national gestational diabetes mellitus register: Challenges in screening, registration, and follow-up for diabetes risk.

Authors:
Douglas I R Boyle Vincent L Versace James A Dunbar Wendy Scheil Edward Janus Jeremy J N Oats Timothy Skinner Sophy Shih Sharleen O'Reilly Ken Sikaris Liza Kelsall Paddy A Phillips James D Best

PLoS One 2018 8;13(8):e0200832. Epub 2018 Aug 8.

Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.

Objective: Gestational Diabetes Mellitus (GDM) increases the risk of type 2 diabetes. A register can be used to follow-up high risk women for early intervention to prevent progression to type 2 diabetes. We evaluate the performance of the world's first national gestational diabetes register.

Research Design And Methods: Observational study that used data linkage to merge: (1) pathology data from the Australian states of Victoria (VIC) and South Australia (SA); (2) birth records from the Consultative Council on Obstetric and Paediatric Mortality and Morbidity (CCOPMM, VIC) and the South Australian Perinatal Statistics Collection (SAPSC, SA); (3) GDM and type 2 diabetes register data from the National Gestational Diabetes Register (NGDR). All pregnancies registered on CCOPMM and SAPSC for 2012 and 2013 were included-other data back to 2008 were used to support the analyses. Rates of screening for GDM, rates of registration on the NGDR, and rates of follow-up laboratory screening for type 2 diabetes are reported.

Results: Estimated GDM screening rates were 86% in SA and 97% in VIC. Rates of registration on the NGDR ranged from 73% in SA (2013) to 91% in VIC (2013). During the study period rates of screening at six weeks postpartum ranged from 43% in SA (2012) to 58% in VIC (2013). There was little evidence of recall letters resulting in screening 12 months follow-up.

Conclusions: GDM Screening and NGDR registration was effective in Australia. Recall by mail-out to young mothers and their GP's for type 2 diabetes follow-up testing proved ineffective.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0200832PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6082534PMC
February 2019

Transient epigenomic changes during pregnancy and early postpartum in women with and without type 2 diabetes.

Authors:
Agnes A Michalczyk Edward D Janus Alisha Judge Peter R Ebeling James D Best Michael J Ackland Dino Asproloupos James A Dunbar M Leigh Ackland

Epigenomics 2018 04 21;10(4):419-431. Epub 2018 Mar 21.

Centre for Cellular & Molecular Biology, School of Life & Environmental Sciences, Deakin University, Burwood, Victoria 3125, Australia.

Aim: To investigate epigenomic changes in pregnancy and early postpartum in women with and without type 2 diabetes.

Methods: Dimethylation of histones H3K4, H3K9, H3K27, H3K36 and H3K79 was measured in white blood cells of women at 30 weeks pregnancy, at 8-10 and 20 weeks postpartum and in never-pregnant women.

Results: Dimethylation levels of all five histones were different between women in pregnancy and early postpartum compared with never-pregnant women and were different between women with and without type 2 diabetes.

Conclusion: Histone methylation changes are transient in pregnancy and early postpartum and may represent normal physiological responses to hormones. Different epigenomic profiles in women with type 2 diabetes mellitus may correlate with hormonal responses, leading to high risk pregnancy outcomes.
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http://dx.doi.org/10.2217/epi-2017-0129DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5925439PMC
April 2018

Effect of fenofibrate on uric acid and gout in type 2 diabetes: a post-hoc analysis of the randomised, controlled FIELD study.

Authors:
Boris Waldman Jean-Claude Ansquer David R Sullivan Alicia J Jenkins Neil McGill Luke Buizen Timothy M E Davis James D Best Liping Li Michael D Feher Christelle Foucher Y Antero Kesaniemi Jeffrey Flack Michael C d'Emden Russell S Scott John Hedley Val Gebski Anthony C Keech

Lancet Diabetes Endocrinol 2018 04 26;6(4):310-318. Epub 2018 Feb 26.

National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia. Electronic address:

Background: Gout is a painful disorder and is common in type 2 diabetes. Fenofibrate lowers uric acid and reduces gout attacks in small, short-term studies. Whether fenofibrate produces sustained reductions in uric acid and gout attacks is unknown.

Methods: In the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial, participants aged 50-75 years with type 2 diabetes were randomly assigned to receive either co-micronised fenofibrate 200 mg once per day or matching placebo for a median of 5 years follow-up. We did a post-hoc analysis of recorded on-study gout attacks and plasma uric acid concentrations according to treatment allocation. The outcomes of this analysis were change in uric acid concentrations and risk of on-study gout attacks. The FIELD study is registered with ISRCTN, number ISRCTN64783481.

Findings: Between Feb 23, 1998, and Nov 3, 2000, 9795 patients were randomly assigned to fenofibrate (n=4895) or placebo (n=4900) in the FIELD study. Uric acid concentrations fell by 20·2% (95% CI 19·9-20·5) during the 6-week active fenofibrate run-in period immediately pre-randomisation (a reduction of 0·06 mmol/L or 1 mg/dL) and remained -20·1% (18·5-21·7, p<0·0001) lower in patients taking fenofibrate than in those on placebo in a random subset re-measured at 1 year. With placebo allocation, there were 151 (3%) first gout events over 5 years, compared with 81 (2%) among those allocated fenofibrate (HR with treatment 0·54, 95% CI 0·41-0·70; p<0·0001). In the placebo group, the cumulative proportion of patients with first gout events was 7·7% in patients with baseline uric acid concentration higher than 0·36 mmol/L and 13·9% in those with baseline uric acid concentration higher than 0·42 mmol/L, compared with 3·4% and 5·7%, respectively, in the fenofibrate group. Risk reductions were similar among men and women and those with dyslipidaemia, on diuretics, and with elevated uric acid concentrations. For participants with elevated baseline uric acid concentrations despite taking allopurinol at study entry, there was no heterogeneity of the treatment effect of fenofibrate on gout risk. Taking account of all gout events, fenofibrate treatment halved the risk (HR 0·48, 95% CI 0·37-0·60; p<0·0001) compared with placebo.

Interpretation: Fenofibrate lowered uric acid concentrations by 20%, and almost halved first on-study gout events over 5 years of treatment. Fenofibrate could be a useful adjunct for preventing gout in diabetes.

Funding: None.
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http://dx.doi.org/10.1016/S2213-8587(18)30029-9DOI Listing
April 2018

Baseline Circulating FGF21 Concentrations and Increase after Fenofibrate Treatment Predict More Rapid Glycemic Progression in Type 2 Diabetes: Results from the FIELD Study.

Authors:
Kwok-Leung Ong Rachel O'Connell Andrzej S Januszewski Alicia J Jenkins Aimin Xu David R Sullivan Philip J Barter Russell S Scott Marja-Riitta Taskinen Boris Waldman Peter G Colman James D Best John R Simes Kerry-Anne Rye Anthony C Keech

Clin Chem 2017 Jul 12;63(7):1261-1270. Epub 2017 Jun 12.

Lipid Research Group, School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia.

Background: It is not known whether circulating fibroblast growth factor 21 (FGF21) concentrations are associated with glycemic progression in patients with established type 2 diabetes. This study reports this relationship in type 2 diabetes patients participating in the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial.

Methods: Plasma FGF21 was quantified in 9697 study participants. Among patients with lifestyle-only glucose control measures at baseline, glycemic progression was defined as the initiation of oral hypoglycemic agents or insulin therapy. We assessed the relationship of FGF21 concentrations with glycohemoglobin (Hb A), the homeostasis model assessment of β-cell function (HOMA-B) and insulin resistance (HOMA-IR), and glycemic progression.

Results: Among 2584 patients with lifestyle-only glycemic therapy at baseline, plasma FGF21 concentrations were positively associated with HOMA-IR (5.1% increase per 100% increase in FGF21 concentrations). Patients with higher baseline plasma FGF21 concentrations had higher risk of glycemic progression over a 5-year period ( = 0.02), but the association was not significant after further adjusting for alanine aminotransferase (ALT) enzyme activity. During the fenofibrate active run-in phase, higher tertiles of fenofibrate-induced increase in FGF21 concentrations were associated with higher risk of glycemic progression (adjusted hazards ratio = 1.09 and 1.18 for tertiles 2 and 3, respectively, for trend = 0.01), even after adjusting for ALT enzyme activity. This association was statistically significant in the fenofibrate group only ( = 0.01).

Conclusions: Higher baseline and fenofibrate-induced increase in FGF21 concentrations predict more rapid glycemic progression in type 2 diabetes patients. This association may be partly explained by hepatic function.
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http://dx.doi.org/10.1373/clinchem.2016.270876DOI Listing
July 2017

Clinical outcomes associated with albuminuria in central Australia: a cohort study.

Authors:
Rebecca Ritte Joanne Luke Craig Nelson Alex Brown Kerin O'Dea Alicia Jenkins James D Best Robyn McDermott Mark Daniel Kevin Rowley

BMC Nephrol 2016 08 5;17(1):113. Epub 2016 Aug 5.

Onemda Group, Indigenous Health Equity Unit, Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, VIC, Melbourne, 3010, Australia.

Background: Chronic kidney disease (CKD) and end-stage-kidney disease (ESKD) continue to be under-diagnosed and a major burden for Aboriginal communities in central Australia. The aim of this study was to examine the risk of poor clinical outcomes associated with elevated albumin-to-creatinine ratio (ACR) among Aboriginal people in central Australia.

Methods: Cox proportional hazards models were used to estimate the risk of end stage kidney disease (ESKD), dialysis, CVD (cardiovascular disease) and mortality associated with participants' baseline albuminuria reading from a 10-year cohort study of Aboriginal people (n = 623) from three communities in central Australia. Predictors of progression of albuminuria were also examined in the context of the Kidney Health Australia (KHA) Risk Matrix.

Results: A baseline ACR level of ≥3.5 mg/mmol was associated with an almost 10-fold increased risk of ESKD (95%CI 2.07-43.8) and a 15-fold risk of dialysis (95%CI 1.89-121). Albuminuria ≥3.5 mg/mmol was also associated with a borderline 63 % increased risk of CVD (95%CI 0.98-2.71). No significant association was observed with mortality from all-causes or chronic disease. Diabetes and a waist-to-hip ratio ≥0.90 independently predicted a two-fold increased risk of a progression to higher ACR levels.

Conclusions: A single measure of moderately increased albuminuria was a strong predictor of renal failure in this population. A single spot urine ACR analysis in conjunction with the KHA Risk Matrix may be a useful and efficient strategy to screen for risk of CKD and progression to dialysis in remote communities. A focus on individuals with diabetes and/or central obesity for strategies to avoid increases in albuminuria may also prevent future CKD and CVD complications.
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http://dx.doi.org/10.1186/s12882-016-0328-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4974695PMC
August 2016

Mothers after Gestational Diabetes in Australia (MAGDA): A Randomised Controlled Trial of a Postnatal Diabetes Prevention Program.

Authors:
Sharleen L O'Reilly James A Dunbar Vincent Versace Edward Janus James D Best Rob Carter Jeremy J N Oats Timothy Skinner Michael Ackland Paddy A Phillips Peter R Ebeling John Reynolds Sophy T F Shih Virginia Hagger Michael Coates Carol Wildey

PLoS Med 2016 Jul 26;13(7):e1002092. Epub 2016 Jul 26.

Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.

Background: Gestational diabetes mellitus (GDM) is an increasingly prevalent risk factor for type 2 diabetes. We evaluated the effectiveness of a group-based lifestyle modification program in mothers with prior GDM within their first postnatal year.

Methods And Findings: In this study, 573 women were randomised to either the intervention (n = 284) or usual care (n = 289). At baseline, 10% had impaired glucose tolerance and 2% impaired fasting glucose. The diabetes prevention intervention comprised one individual session, five group sessions, and two telephone sessions. Primary outcomes were changes in diabetes risk factors (weight, waist circumference, and fasting blood glucose), and secondary outcomes included achievement of lifestyle modification goals and changes in depression score and cardiovascular disease risk factors. The mean changes (intention-to-treat [ITT] analysis) over 12 mo were as follows: -0.23 kg body weight in intervention group (95% CI -0.89, 0.43) compared with +0.72 kg in usual care group (95% CI 0.09, 1.35) (change difference -0.95 kg, 95% CI -1.87, -0.04; group by treatment interaction p = 0.04); -2.24 cm waist measurement in intervention group (95% CI -3.01, -1.42) compared with -1.74 cm in usual care group (95% CI -2.52, -0.96) (change difference -0.50 cm, 95% CI -1.63, 0.63; group by treatment interaction p = 0.389); and +0.18 mmol/l fasting blood glucose in intervention group (95% CI 0.11, 0.24) compared with +0.22 mmol/l in usual care group (95% CI 0.16, 0.29) (change difference -0.05 mmol/l, 95% CI -0.14, 0.05; group by treatment interaction p = 0.331). Only 10% of women attended all sessions, 53% attended one individual and at least one group session, and 34% attended no sessions. Loss to follow-up was 27% and 21% for the intervention and control groups, respectively, primarily due to subsequent pregnancies. Study limitations include low exposure to the full intervention and glucose metabolism profiles being near normal at baseline.

Conclusions: Although a 1-kg weight difference has the potential to be significant for reducing diabetes risk, the level of engagement during the first postnatal year was low. Further research is needed to improve engagement, including participant involvement in study design; it is potentially more effective to implement annual diabetes screening until women develop prediabetes before offering an intervention.

Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12610000338066.
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http://dx.doi.org/10.1371/journal.pmed.1002092DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4961439PMC
July 2016

Epigenetic Markers to Predict Conversion From Gestational Diabetes to Type 2 Diabetes.

Authors:
Agnes A Michalczyk James A Dunbar Edward D Janus James D Best Peter R Ebeling Michael J Ackland Dino Asproloupos M Leigh Ackland

J Clin Endocrinol Metab 2016 06 5;101(6):2396-404. Epub 2016 Apr 5.

Centre for Cellular and Molecular Biology (A.A.M., M.L.A.), School of Life and Environmental Sciences, Deakin University, Burwood, Victoria, Australia 3125; Deakin Population Health Strategic Research Centre (J.A.D., D.A.), Faculty of Health, Deakin University, Burwood, Victoria, Australia 3125; University of Melbourne (E.D.J.) Western Centre for Health Research and Education, Western Health, St Albans, Victoria, Australia 3021; Lee Kong Chian School of Medicine (J.D.B.), Singapore, 308232; Faculty of Medicine, Nursing and Health Sciences (P.R.E.), Monash University, Victoria, Australia 3168; and Department of Health & Human Services (M.J.A.), Victoria, Australia 3000.

Context: Lifestyle factors mediate epigenetic changes that can cause chronic diseases. Although animal and laboratory studies link epigenetic changes to diabetes, epigenetic information in women with gestational diabetes (GDM) and type 2 diabetes is lacking.

Objective: This study sought to measure epigenetic markers across pregnancy and early postpartum and identify markers that could be used as predictors for conversion from GDM to type 2 diabetes.

Design: Global histone H3 dimethylation was measured in white blood cells at three time points: 30 wk gestation, 8-10 wk postpartum, and 20 wk postpartum, from four groups of women with and without diabetes.

Setting And Participants: A total of 39 participants (six to nine in each group) were recruited including: nondiabetic women; women with GDM who developed postpartum type 2 diabetes; women with GDM without postpartum type 2 diabetes; and women with type 2 diabetes.

Main Outcome Measure: Percentages of dimethylation of H3 histones relative to total H3 histone methylation were compared between diabetic/nondiabetic groups using appropriate comparative statistics.

Results: H3K27 dimethylation was 50-60% lower at 8-10 and 20 wk postpartum in women with GDM who developed type 2 diabetes, compared with nondiabetic women. H3K4 dimethylation was 75% lower at 8-10 wk postpartum in women with GDM who subsequently developed type 2 diabetes compared with women who had GDM who did not.

Conclusions: The percentage of dimethylation of histones H3K27 and H3K4 varied with diabetic state and has the potential as a predictive tool to identify women who will convert from GDM to type 2 diabetes.
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http://dx.doi.org/10.1210/jc.2015-4206DOI Listing
June 2016

Challenges of diabetes prevention in the real world: results and lessons from the Melbourne Diabetes Prevention Study.

Authors:
James A Dunbar Andrea L Hernan Edward D Janus Erkki Vartiainen Tiina Laatikainen Vincent L Versace John Reynolds James D Best Timothy C Skinner Sharleen L O'Reilly Kevin P Mc Namara Elizabeth Stewart Michael Coates Catherine M Bennett Rob Carter

BMJ Open Diabetes Res Care 2015 1;3(1):e000131. Epub 2015 Oct 1.

Faculty of Health, Deakin Health Economics , Deakin University, Melbourne Burwood Campus , Burwood, Victoria , Australia.

Objective: To assess effectiveness and implementability of the public health programme Life! Taking action on diabetes in Australian people at risk of developing type 2 diabetes.

Research Design And Methods: Melbourne Diabetes Prevention Study (MDPS) was a unique study assessing effectiveness of Life! that used a randomized controlled trial design. Intervention participants with AUSDRISK score ≥15 received 1 individual and 5 structured 90 min group sessions. Controls received usual care. Outcome measures were obtained for all participants at baseline and 12 months and, additionally, for intervention participants at 3 months. Per protocol set (PPS) and intention to treat (ITT) analyses were performed.

Results: PPS analyses were considered more informative from our study. In PPS analyses, intervention participants significantly improved in weight (-1.13 kg, p=0.016), waist circumference (-1.35 cm, p=0.044), systolic (-5.2 mm Hg, p=0.028) and diastolic blood pressure (-3.2 mm Hg, p=0.030) compared with controls. Based on observed weight change, estimated risk of developing diabetes reduced by 9.6% in the intervention and increased by 3.3% in control participants. Absolute 5-year cardiovascular disease (CVD) risk reduced significantly for intervention participants by 0.97 percentage points from 9.35% (10.4% relative risk reduction). In control participants, the risk increased by 0.11 percentage points (1.3% relative risk increase). The net effect for the change in CVD risk was -1.08 percentage points of absolute risk (p=0.013).

Conclusions: MDPS effectively reduced the risk of diabetes and CVD, but the intervention effect on weight and waist reduction was modest due to the challenges in recruiting high-risk individuals and the abbreviated intervention.
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http://dx.doi.org/10.1136/bmjdrc-2015-000131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4597415PMC
October 2015

Erratum to: Favourable effects of fenofibrate on lipids and cardiovascular disease in women with type 2 diabetes: results from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study.

Authors:
Michael C d'Emden Alicia J Jenkins Liping Li Diana Zannino Kristy P Mann James D Best Bronwyn G A Stuckey Kris Park Juha Saltevo Anthony C Keech

Diabetologia 2015 Sep;58(9):2200

Endocrine Research Unit, Royal Brisbane Hospital, Brisbane, QLD, Australia.

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http://dx.doi.org/10.1007/s00125-015-3693-6DOI Listing
September 2015

Comment on O'Connor et Al. Randomized trial of telephone outreach to improve medication adherence and metabolic control in adults with diabetes. Diabetes care 2014;37:3317-3324.

Authors:
Irene D Blackberry John S Furler James D Best Doris Young

Diabetes Care 2015 Mar;38(3):e45

Department of General Practice, University of Melbourne, Carlton, Victoria, Australia.

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http://dx.doi.org/10.2337/dc14-2599DOI Listing
March 2015

An exploratory trial of basal and prandial insulin initiation and titration for type 2 diabetes in primary care with adjunct retrospective continuous glucose monitoring: INITIATION study.

Authors:
Irene D Blackberry John S Furler Louise E Ginnivan Jo-Anne Manski-Nankervis Alicia Jenkins Neale Cohen James D Best Doris Young Danny Liew Glenn Ward David N O'Neal

Diabetes Res Clin Pract 2014 Nov 8;106(2):247-55. Epub 2014 Sep 8.

Department of Medicine, St Vincent's Hospital, The University of Melbourne, Level 4, Clinical Sciences Building, 29 Regent St Fitzroy, Melbourne, VIC 3065, Australia. Electronic address:

Aims: To evaluate basal and prandial insulin initiation and titration in people with type 2 diabetes mellitus (T2DM) in primary care and to explore the feasibility of retrospective-continuous glucose monitoring (r-CGM) in guiding insulin dosing. The new model of care features General Practitioners (GPs) and Practice Nurses (PNs) working in an expanded role, with Credentialed Diabetes Educator - Registered Nurse (CDE-RN) support.

Methods: Insulin-naïve T2DM patients (HbA1c >7.5% [>58 mmol/mol] despite maximal oral therapy) from 22 general practices in Victoria, Australia commenced insulin glargine, with glulisine added as required. Each was randomised to receive r-CGM or self-monitoring of blood glucose (SMBG). Glycaemic control (HbA1c) was benchmarked against specialist ambulatory patients referred for insulin initiation.

Results: Ninety-two patients mean age (range) 59 (28-77) years; 40% female; mean (SD) diabetes duration 10.5 (6.1) years participated. HbA1c decreased from (median (IQR)) 9.9 (8.8, 11.2)%; 85 (73, 99) mmol/mol to 7.3 (6.9, 7.8)%; 56 (52, 62) mmol/mol at 24 weeks (p < 0.0001). Comparing r-CGM (n = 46) with SMBG (n = 42), there were no differences in major hypoglycaemia (p=0.17) or ΔHbA1c (p = 0.31). More r-CGM than SMBG participants commenced glulisine (26/48 vs. 7/44; p < 0.001). Results were comparable to 82 benchmark patients, with similar low rates of major hypoglycaemia (2/89 vs. 0/82; p = 0.17) and less loss to follow up in the INITIATION group (3/92 vs. 14/82; p = 0.002).

Conclusions: Insulin initiation and titration for T2DM patients in primary care was safe and improved HbA1c with low rates of major hypoglycaemia. CDE-RNs were effective in a new consultant role. r-CGM use in primary care was feasible and enhanced post-prandial hyperglycaemia recognition. Trial registration ACTRN12610000797077.
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http://dx.doi.org/10.1016/j.diabres.2014.08.011DOI Listing
November 2014

Favourable effects of fenofibrate on lipids and cardiovascular disease in women with type 2 diabetes: results from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study.

Authors:
Michael C d'Emden Alicia J Jenkins Liping Li Diana Zannino Kristy P Mann James D Best Bronwyn G A Stuckey Kris Park Juha Saltevo Anthony C Keech

Diabetologia 2014 Nov 23;57(11):2296-303. Epub 2014 Aug 23.

Endocrine Research Unit, Royal Brisbane Hospital, Brisbane, QLD, Australia.

Aims/hypothesis: In the double-blind placebo-controlled Fenofibrate Intervention and Event Lowering in Diabetes trial (n = 9,795), fenofibrate reduced major cardiovascular events in type 2 diabetes. Sex-related differences in fenofibrate response could be clinically relevant and were pre-specified analyses.

Methods: Women (n = 3,657) and men (n = 6,138) with type 2 diabetes not using statins were assigned fenofibrate (200 mg/day) or placebo for 5 years. Effects on lipoproteins and total cardiovascular events were evaluated by sex.

Results: Baseline total, LDL-, HDL- and non-HDL cholesterol and apolipoproteins A-I and B differed between sexes, and these and triacylglycerol levels improved with fenofibrate in both sexes (all p < 0.001). Fenofibrate reduced total, LDL- and non-HDL cholesterol and apolipoprotein B more in women (all p < 0.001), independent of menopausal status and statin uptake. Adjusted for covariates, fenofibrate reduced total cardiovascular outcomes (cardiovascular death, fatal and non-fatal stroke and carotid and coronary revascularisation) by 30% in women (95% CI 8%, 46%; p = 0.008) and 13% in men (95% CI -1%, 24%; p = 0.07) with no treatment-by-sex interaction (p > 0.1). In patients with high triacylglycerol levels and low HDL-cholesterol, fenofibrate reduced total cardiovascular outcomes by 30% (95% CI -7%, 54%) in women and 24% (95% CI 2%, 42%) in men, with no treatment-by-sex interaction (p > 0.1).

Conclusions/interpretation: Fenofibrate improved the lipoprotein profile more in women than men. Cardiovascular event reductions with fenofibrate were consistently similar in women and men, both overall and among those with low HDL-cholesterol and high triacylglycerol levels. These data provide reassurance about fenofibrate efficacy in women and men. Both sexes with type 2 diabetes should be considered for fenofibrate therapy for cardioprotection.
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http://dx.doi.org/10.1007/s00125-014-3344-3DOI Listing
November 2014

Mothers After Gestational Diabetes in Australia Diabetes Prevention Program (MAGDA-DPP) post-natal intervention: an update to the study protocol for a randomized controlled trial.

Authors:
Sophy T F Shih Nathalie Davis-Lameloise Edward D Janus Carol Wildey Vincent L Versace Virginia Hagger Dino Asproloupos Sharleen L O'Reilly Paddy A Phillips Michael Ackland Timothy Skinner Jeremy Oats Rob Carter James D Best James A Dunbar

Trials 2014 Jun 30;15:259. Epub 2014 Jun 30.

Greater Green Triangle University Department of Rural Health, Flinders University, PO Box 423, 3280 Warrnambool, VIC, Australia.

Background: The Mothers After Gestational Diabetes in Australia Diabetes Prevention Program (MAGDA-DPP) is a randomized controlled trial (RCT) that aims to assess the effectiveness of a structured diabetes prevention intervention for women who had gestational diabetes.

Methods/design: The original protocol was published in Trials (http://www.trialsjournal.com/content/14/1/339). This update reports on an additional exclusion criterion and change in first eligibility screening to provide greater clarity. The new exclusion criterion "surgical or medical intervention to treat obesity" has been added to the original protocol. The risks of developing diabetes will be affected by any medical or surgical intervention as its impact on obesity will alter the outcomes being assessed by MAGDA-DPP. The screening procedures have also been updated to reflect the current recruitment operation. The first eligibility screening is now taking place either during or after pregnancy, depending on recruitment strategy.

Trial Registration: Australian New Zealand Clinical Trials Registry ANZCTRN 12610000338066.
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http://dx.doi.org/10.1186/1745-6215-15-259DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4083860PMC
June 2014

An exploratory trial of insulin initiation and titration among patients with type 2 diabetes in the primary care setting with retrospective continuous glucose monitoring as an adjunct: INITIATION study protocol.

Authors:
Irene D Blackberry John S Furler Louise E Ginnivan Hanan Derraz Alicia Jenkins Neale Cohen James D Best Doris Young Danny Liew Glenn Ward Jo-Anne Manski-Nankervis David N O'Neal

BMC Fam Pract 2014 May 3;15:82. Epub 2014 May 3.

General Practice and Primary Health Care Academic Centre, The University of Melbourne, 200 Berkeley St, Carlton 3053, Australia.

Background: Insulin initiation and titration in primary care is necessary to respond to the growing epidemic of type 2 diabetes (T2D). The INITIATION study aims to evaluate the impact of implementing a new model of care with Primary Care Physician and Practice Nurse (PN) teams supported by a Credentialed Diabetes Educator-Registered Nurse (CDE-RN) and endocrinologist in initiating and titrating basal and prandial insulin for T2D patients in the Australian healthcare system over 24 weeks. This study also explores the feasibility and efficacy of retrospective continuous glucose monitoring (r-CGM) in comparison with self-monitoring of blood glucose (SMBG) among people with T2D in primary care.

Methods/design: The study employs a before and after design with a nested exploratory trial of SMBG and r-CGM. A total of 102 insulin naïve T2D patients with a glycated haemoglobin (HbA1c) level of >7.5% in the previous 6 months while treated with maximal oral therapy will be recruited and screened from 22 primary care practices in Melbourne, Australia. All patients will be commenced on a basal insulin regimen following randomization into one of the two blood glucose monitoring arms, with intensification to a "basal plus" regimen if required. The outcomes of the new model of care will be benchmarked with data collected over the same period from a specialist setting in Melbourne, Australia.

Discussion: This article describes the study protocol and insulin treatment algorithm employed in the first study to explore r-CGM use among T2D in primary care. Findings from the INITIATION study will inform development of a larger randomized controlled trial.

Trial Registration: ACTRN12610000797077.
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http://dx.doi.org/10.1186/1471-2296-15-82DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4037429PMC
May 2014

Plasma semicarbazide-sensitive amine oxidase activity in type 1 diabetes is related to vascular and renal function but not to glycaemia.

Authors:
Andrzej S Januszewski Nick Mason Connie S Karschimkus Kevin G Rowley James D Best David N O'Neal Alicia J Jenkins

Diab Vasc Dis Res 2014 Jul 22;11(4):262-269. Epub 2014 May 22.

NHMRC Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia Department of Medicine, St Vincent's Hospital, University of Melbourne, Melbourne, Australia.

Purpose: Associations of semicarbazide-sensitive amine oxidase (SSAO) activity with renal and vascular function, oxidative stress, glycaemia and diabetes complications were determined.

Methods: Plasma SSAO activity in 94 type 1 diabetes (T1DM) patients, including 34 with microvascular complications T1DM CX[+], and in 96 healthy subjects (CON) was measured by production of benzaldehyde using high-performance liquid chromatography (HPLC).

Results: SSAO activity (mean ± SD) was greater in T1DM than in CON (1049 ± 294 vs 749 ± 204 mU/L; p < 0.00001) and was higher in T1DM CX[+] vs complication-free DM subjects (1148 ± 313 mU/L vs 982 ± 269 mU/L; p = 0.01). In T1DM, SSAO activity correlated with renal dysfunction [estimated glomerular filtration rate (eGFR): r = -0.44; p = 0.0001; cystatin C: r = 0.47; p = 0.0001] and markers of inflammation [soluble vascular cell adhesion molecule-1 (sVCAM-1): r = 0.41, p = 0.0001; soluble intercellular adhesion molecule-1 (sICAM-1): r = 0.33, p = 0.002] and was inversely related to small artery elasticity (SAE) (r = -0.23, p = 0.03). In CON, SSAO activity correlated with HbA1c (r = 0.26; p = 0.02).

Conclusion: In T1DM, SSAO activity correlates with renal dysfunction, but not with glycaemia, and may promote vascular inflammation and be a therapeutic target.
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http://dx.doi.org/10.1177/1479164114532963DOI Listing
July 2014

Reversing social disadvantage in secondary prevention of coronary heart disease.

Authors:
Michael V Jelinek John D Santamaria James D Best David R Thompson Andrew M Tonkin Margarite J Vale

Int J Cardiol 2014 Feb 24;171(3):346-50. Epub 2013 Dec 24.

The University of Melbourne, Department of Medicine, St Vincent's Hospital, Melbourne, Australia.

Background: To compare and contrast the coronary heart disease (CHD) risk factors of lower socio-economic status public hospital patients with those of privately insured CHD patients before and after six months of telephone delivered coaching using The COACH Program.

Methods: A retrospective observational study which contrasts the lifestyle and biomedical coronary risk factor status of 2256 public hospital patients with the same risk factors of 3278 patients who had private health insurance. All patients received an average of 5 coach sessions over 6 months.

Results: The public hospital patients were four years younger and had multiple measures confirming their lower socio-economic status than their private hospital counterparts. At entry to the program, the public hospital patients had worse risk factor levels than the privately insured patients for total and LDL-cholesterol, triglycerides, fasting glucose, smoking and physical activity levels (P<0.0001) but better status for systolic and diastolic blood pressures and alcohol intake. At exit from the program, many of these differences had diminished or disappeared. The public hospital patients had greater improvements in their risk factor status for total and LDL-cholesterol, fasting glucose, body weight, smoking status and physical activity level than did the privately insured patients (P<0.05).

Conclusions: This paper demonstrates that a program of initiating contact with patients with CHD, identifying treatment gaps in their management and coaching to achieve guideline recommended risk factor targets can help reduce health inequalities in such patients and thus benefit all patients in the context of ongoing secondary prevention.
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http://dx.doi.org/10.1016/j.ijcard.2013.12.022DOI Listing
February 2014

Scaling up diabetes prevention in Victoria, Australia: policy development, implementation, and evaluation.

Authors:
James A Dunbar Abirami Jayawardena Greg Johnson Karen Roger Amy Timoshanko Vincent L Versace Jane Shill Benjamin Philpot Erkki Vartiainen Tiina Laatikainen James D Best Edward D Janus

Diabetes Care 2014 Apr 6;37(4):934-42. Epub 2013 Dec 6.

Corresponding author: James A. Dunbar,

OBJECTIVE The Australian lifestyle intervention program Life! is only the second reported, large-scale diabetes prevention program. This article describes the genesis and the successful establishment of Life! and its key outcomes for participants and implementation. RESEARCH DESIGN AND METHODS Life!, a behavior-change intervention, comprises six group sessions over 8 months. The Victorian Department of Health funded Diabetes Australia-Victoria to implement the program. Experience of the Greater Green Triangle diabetes prevention implementation trial was used for intervention design, workforce development, training, and infrastructure. Clinical and anthropometric data from participants, used for program evaluation, were recorded on a central database. RESULTS Life! has a statewide workforce of 302 trained facilitators within 137 organizations. Over 29,000 Victorians showed interest in Life!, and 15,000 individuals have been referred to the program. In total, 8,412 participants commenced a Life! program between October 2007 and June 2011, and 37% of the original participants completed the 8-month program. Participants completing sessions 1 to 5 lost an average of 1.4 kg weight (P < 0.001) and waist circumference of 2.5 cm (P < 0.001). Those completing six sessions lost an average of 2.4 kg weight (P < 0.001) and waist circumference of 3.8 cm (P < 0.001). The weight loss of 2.4 kg represents 2.7% of participants' starting body weight. CONCLUSIONS The impact of Life! is attributable to applying available evidence for the system's design of the intervention and collaboration between policy makers, implementers, and evaluators using the principles of continuous quality improvement to support successful, large-scale recruitment and implementation.
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http://dx.doi.org/10.2337/dc12-2647DOI Listing
April 2014

Response to the Letter by Kawada et al. regarding the manuscript entitled "The metabolic syndrome and CVD outcomes for a central Australian cohort".

Authors:
Joanne N Luke Alex Brown Mark Daniel Kerin O'Dea James D Best Alicia J Jenkins Zhiqiang Wang Robyn A McDermott Zaimin Wang Kevin G Rowley

Diabetes Res Clin Pract 2013 Nov 1;102(2):e22-3. Epub 2013 Oct 1.

The University of Melbourne, Australia. Electronic address:

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http://dx.doi.org/10.1016/j.diabres.2013.08.013DOI Listing
November 2013

Mothers After Gestational Diabetes in Australia Diabetes Prevention Program (MAGDA-DPP) post-natal intervention: study protocol for a randomized controlled trial.

Authors:
Sophy T F Shih Nathalie Davis-Lameloise Edward D Janus Carol Wildey Vincent L Versace Virginia Hagger Dino Asproloupos Sharleen O'Reilly Paddy A Phillips Michael Ackland Timothy Skinner Jeremy Oats Rob Carter James D Best James A Dunbar

Trials 2013 Oct 17;14:339. Epub 2013 Oct 17.

Greater Green Triangle University Department of Rural Health, Flinders University, PO Box 423, Warrnambool VIC 3280, Australia.

Background: Gestational diabetes mellitus (GDM) is defined as glucose intolerance with its onset or first recognition during pregnancy. Post-GDM women have a life-time risk exceeding 70% of developing type 2 diabetes mellitus (T2DM). Lifestyle modifications reduce the incidence of T2DM by up to 58% for high-risk individuals.

Methods/design: The Mothers After Gestational Diabetes in Australia Diabetes Prevention Program (MAGDA-DPP) is a randomized controlled trial aiming to assess the effectiveness of a structured diabetes prevention intervention for post-GDM women. This trial has an intervention group participating in a diabetes prevention program (DPP), and a control group receiving usual care from their general practitioners during the same time period. The 12-month intervention comprises an individual session followed by five group sessions at two-week intervals, and two follow-up telephone calls. A total of 574 women will be recruited, with 287 in each arm. The women will undergo blood tests, anthropometric measurements, and self-reported health status, diet, physical activity, quality of life, depression, risk perception and healthcare service usage, at baseline and 12 months. At completion, primary outcome (changes in diabetes risk) and secondary outcome (changes in psychosocial and quality of life measurements and in cardiovascular disease risk factors) will be assessed in both groups.

Discussion: This study aims to show whether MAGDA-DPP leads to a reduction in diabetes risk for post-GDM women. The characteristics that predict intervention completion and improvement in clinical and behavioral measures will be useful for further development of DPPs for this population.

Trial Registration: Australian New Zealand Clinical Trials Registry ANZCTRN 12610000338066.
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http://dx.doi.org/10.1186/1745-6215-14-339DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3853589PMC
October 2013

Effectiveness of general practice based, practice nurse led telephone coaching on glycaemic control of type 2 diabetes: the Patient Engagement and Coaching for Health (PEACH) pragmatic cluster randomised controlled trial.

Authors:
Irene D Blackberry John S Furler James D Best Patty Chondros Margarite Vale Christine Walker Trisha Dunning Leonie Segal James Dunbar Ralph Audehm Danny Liew Doris Young

BMJ 2013 Sep 18;347:f5272. Epub 2013 Sep 18.

General Practice and Primary Health Care Academic Centre, University of Melbourne, 200 Berkeley St, Carlton, VIC 3053, Australia.

Objective: To evaluate the effectiveness of goal focused telephone coaching by practice nurses in improving glycaemic control in patients with type 2 diabetes in Australia.

Design: Prospective, cluster randomised controlled trial, with general practices as the unit of randomisation.

Setting: General practices in Victoria, Australia.

Participants: 59 of 69 general practices that agreed to participate recruited sufficient patients and were randomised. Of 829 patients with type 2 diabetes (glycated haemoglobin (HbA1c) >7.5% in the past 12 months) who were assessed for eligibility, 473 (236 from 30 intervention practices and 237 from 29 control practices) agreed to participate.

Intervention: Practice nurses from intervention practices received two days of training in a telephone coaching programme, which aimed to deliver eight telephone and one face to face coaching episodes per patient.

Main Outcome Measures: The primary end point was mean absolute change in HbA1c between baseline and 18 months in the intervention group compared with the control group.

Results: The intervention and control patients were similar at baseline. None of the practices dropped out over the study period; however, patient attrition rates were 5% in each group (11/236 and 11/237 in the intervention and control group, respectively). The median number of coaching sessions received by the 236 intervention patients was 3 (interquartile range 1-5), of which 25% (58/236) did not receive any coaching sessions. At 18 months' follow-up the effect on glycaemic control did not differ significantly (mean difference 0.02, 95% confidence interval -0.20 to 0.24, P=0.84) between the intervention and control groups, adjusted for HbA1c measured at baseline and the clustering. Other biochemical and clinical outcomes were similar in both groups.

Conclusions: A practice nurse led telephone coaching intervention implemented in the real world primary care setting produced comparable outcomes to usual primary care in Australia. The addition of a goal focused coaching role onto the ongoing generalist role of a practice nurse without prescribing rights was found to be ineffective.

Trial Registration: Current Controlled Trials ISRCTN50662837.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3776648PMC
http://dx.doi.org/10.1136/bmj.f5272DOI Listing
September 2013

The metabolic syndrome and CVD outcomes for a central Australian cohort.

Authors:
Joanne N Luke Alex Brown Mark Daniel Kerin O'Dea James D Best Alicia J Jenkins Zhiqiang Wang Robyn A McDermott Zaimin Wang Kevin G Rowley

Diabetes Res Clin Pract 2013 Jun 26;100(3):e70-3. Epub 2013 Mar 26.

Onemda VicHealth Koori Health Unit, The University of Melbourne, 4/207 Bourerie Street, Carlton South, 3053, Victoria, Australia.

We investigated if the metabolic syndrome (MetS) and its component risk factors predict cardiovascular disease (CVD) for Aboriginal people from central Australia. WHO (HR 2.83), NCEP (1.80) and IDF (2.47) definitions of the MetS all had positive associations with CVD, however offered little above individual MetS components for hyperglycaemia.
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http://dx.doi.org/10.1016/j.diabres.2013.03.020DOI Listing
June 2013

Scaling-up from an implementation trial to state-wide coverage: results from the preliminary Melbourne Diabetes Prevention Study.

Authors:
Edward D Janus James D Best Nathalie Davis-Lameloise Benjamin Philpot Andrea Hernan Catherine M Bennett Sharleen O'Reilly Rob Carter Erkki Vartiainen James A Dunbar

Trials 2012 Aug 28;13:152. Epub 2012 Aug 28.

Greater Green Triangle University Department of Rural Health, Flinders University and Deakin University, PO Box 423, Warrnambool, VIC 3280, Australia.

Background: The successful Greater Green Triangle Diabetes Prevention Program (GGT DPP), a small implementation trial, has been scaled-up to the Victorian state-wide 'Life!' programme with over 10,000 individuals enrolled. The Melbourne Diabetes Prevention Study (MDPS) is an evaluation of the translation from the GGT DPP to the Life! programme. We report results from the preliminary phase (pMDPS) of this evaluation.

Methods: The pMDPS is a randomised controlled trial with 92 individuals aged 50 to 75 at high risk of developing type 2 diabetes randomised to Life! or usual care. Intervention consisted of six structured 90-minute group sessions: five fortnightly sessions and the final session at 8 months. Participants underwent anthropometric and laboratory tests at baseline and 12 months, and provided self-reported psychosocial, dietary, and physical activity measures. Intervention group participants additionally underwent these tests at 3 months. Paired t tests were used to analyse within-group changes over time. Chi-square tests were used to analyse differences between groups in goals met at 12 months. Differences between groups for changes over time were tested with generalised estimating equations and analysis of covariance.

Results: Intervention participants significantly improved at 12 months in mean body mass index (-0.98 kg/m(2), standard error (SE) = 0.26), weight (-2.65 kg, SE = 0.72), waist circumference (-7.45 cm, SE = 1.15), and systolic blood pressure (-3.18 mmHg, SE = 1.26), increased high-density lipoprotein-cholesterol (0.07 mmol/l, SE = 0.03), reduced energy from total (-2.00%, SE = 0.78) and saturated fat (-1.54%, SE = 0.41), and increased fibre intake (1.98 g/1,000 kcal energy, SE = 0.47). In controls, oral glucose at 2 hours deteriorated (0.59 mmol/l, SE = 0.27). Only waist circumference reduced significantly (-4.02 cm, SE = 0.95).Intervention participants significantly outperformed controls over 12 months for body mass index and fibre intake. After baseline adjustment, they also showed greater weight loss and reduced saturated fat versus total energy intake.At least 5% weight loss was achieved by 32% of intervention participants versus 0% controls.

Conclusions: pMDPS results indicate that scaling-up from implementation trial to state-wide programme is possible. The system design for Life! was fit for purpose of scaling-up from efficacy to effectiveness.

Trial Registration: Australian and New Zealand Clinical Trials Registry ACTRN12609000507280.
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http://dx.doi.org/10.1186/1745-6215-13-152DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3502588PMC
August 2012

Glycemic control over 5 years in 4,900 people with type 2 diabetes: real-world diabetes therapy in a clinical trial cohort.

Authors:
James D Best Paul L Drury Timothy M E Davis Marja-Riitta Taskinen Y Antero Kesäniemi Russell Scott Christopher Pardy Merryn Voysey Anthony C Keech

Diabetes Care 2012 May 19;35(5):1165-70. Epub 2012 Mar 19.

Department of Medicine, University of Melbourne Medical School, St. Vincent’s Hospital, Melbourne, Victoria, Australia.

Objective: Glycemic control in type 2 diabetes generally worsens over time, requiring intensification of therapy. The Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial provided the opportunity to observe glycemic control in a real-world setting. We assessed the adequacy of metformin, sulfonylureas, and insulin to maintain glycemic control and their effects on weight.

Research Design And Methods: Diabetes control was measured at baseline and yearly for a median of 5 years in the 4,900 patients from the nonintervention arm of this study allocated to placebo.

Results: Median HbA(1c) was 6.9% at baseline and increased by an average of 0.22% over 5 years (P < 0.001). Median weight was 86.3 kg at baseline and decreased by 0.4 kg over 5 years (P = 0.002). Baseline therapy was lifestyle measures only in 27%, oral agents without insulin in 59%, and insulin in 14% (7% also taking oral agents). Over 5 years, insulin use increased to 32% (21% also taking oral agents). Use of oral agents remained similar at 56%. Only 2% of patients at baseline and 4% after 5 years were taking oral agents other than metformin or sulfonylureas. Initiation of insulin therapy in 855 patients produced a sustained reduction of HbA(1c) from a median of 8.2 to 7.7%, with a weight gain of 4.6 kg over 5 years.

Conclusions: With intensification of traditional therapies, glycemic control deteriorated very little over 5 years in a large cohort of type 2 diabetes. However, the requirement for insulin therapy doubled, at the expense of significant weight gain and risk of hypoglycemia.
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http://dx.doi.org/10.2337/dc11-1307DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3329812PMC
May 2012

Exploring clinical predictors of cardiovascular disease in a central Australian Aboriginal cohort.

Authors:
Joanne N Luke Alex D Brown Laima Brazionis Kerin O'Dea James D Best Robyn A McDermott Zaimin Wang Zhiqiang Wang Kevin G Rowley

Eur J Prev Cardiol 2013 Apr 24;20(2):246-53. Epub 2012 Jan 24.

Onemda VicHealth Koori Health Unit, Centre for Health and Society, School of Population Health, University of Melbourne, Australia.

Introduction: For Aboriginal populations, predicting individuals at risk of cardiovascular disease (CVD) is difficult due to limitations and inaccuracy in existing risk-prediction algorithms. We examined conventional and novel risk factors associated with insulin resistance and the metabolic syndrome and assessed their relationships with subsequent CVD events.

Design: Longitudinal cohort.

Methods: Aboriginal people (n = 739) from Central Australia completed population-based risk-factor surveys in 1995 and were followed up in 2005. Principal components analysis (PCA), regression and univariate analyses (using ROC defined cut-off points) were used to identify useful clinical predictors of primary CVD.

Results: PCA yielded five components: (1) lipids and liver function; (2) insulin resistance; (3) blood pressure and kidney function; (4) glucose tolerance; and (5) anti-inflammatory (low fibrinogen, high HDL cholesterol). Components 2, 3 and 4, and age were significant independent predictors of incident CVD, and smoking approached significance. In univariate analysis fasting glucose ≥ 4.8 mmol/l, total:HDL cholesterol ratio ≥ 5.7, non-HDL cholesterol ≥ 4.3 mmol/l, gamma-glutamyl transferase ≥ 70 U/l, albumin creatinine ratio ≥ 5.7 mg/mmol, systolic blood pressure ≥ 120 mmHg and diastolic blood pressure ≥ 70 mmHg were useful predictors of CVD. The co-occurrence of three or more risk variables (fasting glucose ≥ 4.8 mmol/l, total:HDL cholesterol ratio ≥ 5.7, blood pressure (systolic ≥ 120 mmHg; diastolic ≥ 70 mmHg; albumin:creatinine ratio ≥ 5.7 mg/mmol and smoking) had sensitivity of 82.0% and specificity of 59.9% for predicting incident CVD.

Conclusion: Age is the strongest predictor of CVD for this population. For clinical identification of individuals at high risk, screening for the combination of three or more of hyperglycaemia, dyslipidaemia, hypertension, albuminuria and smoking may prove a useful and efficient strategy.
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http://dx.doi.org/10.1177/2047487312437713DOI Listing
April 2013

An algorithm guiding patient responses to real-time-continuous glucose monitoring improves quality of life.

Authors:
Alicia J Jenkins Balasubramanian Krishnamurthy James D Best Fergus J Cameron Peter G Colman Peter S Hamblin Michele A O'Connell Christine Rodda Helena Teede David N O'Neal

Diabetes Technol Ther 2011 Feb;13(2):105-9

University of Melbourne Department of Medicine, St. Vincent's Hospital, Fitzroy, Australia.

Objective: This study evaluated the impact on quality of life (QoL) of an algorithm guiding the responses of continuous subcutaneous insulin infusion (CSII)-treated type 1 diabetes (T1D) patients using real-time (RT)-continuous glucose monitoring (CGM).

Research Design And Methods: Sixty CSII-treated T1D participants (13-70 years old, glycosylated hemoglobin [HbA1c] ≤ 9.5%), including adult and adolescent subgroups, were randomized in age-, gender-, and HbA1c-matched pairs. Phase 1 was an open 16-week multicenter randomized controlled trial; Group A received CSII/RT-CGM with the algorithm, and Group B received CSII/RT-CGM without algorithm. Phase 2 was the 16-32-week follow-up study; Group A returned to usual care (CSII without RT-CGM), and Group B was provided with algorithm at 16 weeks. QoL was assessed by DQOL (adults) and DQOLY (adolescents) questionnaires at baseline, 16 weeks, and 32 weeks. Higher scores (range 1-5) indicate poorer QoL. Analysis was by analysis of variance (between group for baseline-16 weeks) and paired two-tailed t tests (within group for baseline and 32 weeks) with significance at P < 0.05.

Results: Withdrawals left 28 of 30 patients in Group A and 27 of 30 patients in Group B at 32 weeks. In Phase 1, QoL in Group A (2.16 [0.44] baseline to 1.86 [0.40] at 16 weeks) improved compared with Group B (2.03 [0.47] to 2.03 [0.50]) (P = 0.002). Change in QoL correlated with changes in HbA1c (R = 0.36; P = 0.007). In Phase 2, Group A QoL was better at 32 weeks compared with baseline (2.16 [0.44] vs. 2.02 [0.43]) (P = 0.04) but was not in Group B (2.03 [0.47] vs. 1.99 [0.51]) (P = not significant).

Conclusions: An algorithm guiding CSII-treated T1D responses to RT-CGM improved QoL, which persisted post-RT-CGM withdrawal. Algorithm provision at RT-CGM initiation was required to benefit QoL.
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http://dx.doi.org/10.1089/dia.2010.0139DOI Listing
February 2011

For love or money? Changing the way GPs are paid to provide diabetes care.

Authors:
Doris Young Anthony Scott James D Best

Med J Aust 2010 Jul;193(2):67-8

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http://dx.doi.org/10.5694/j.1326-5377.2010.tb03798.xDOI Listing
July 2010

Evaluation of an algorithm to guide patients with type 1 diabetes treated with continuous subcutaneous insulin infusion on how to respond to real-time continuous glucose levels: a randomized controlled trial.

Authors:
Alicia J Jenkins Balasubramanium Krishnamurthy James D Best Fergus J Cameron Peter G Colman Steven Farish Peter S Hamblin Michele A O'Connell Christine Rodda Kevin Rowley Helena Teede David N O'Neal

Diabetes Care 2010 Jun 9;33(6):1242-8. Epub 2010 Mar 9.

Department of Medicine, The University of Melbourne, St Vincent's Hospital, Fitzroy, Victoria, Australia.

Objective: To evaluate an algorithm guiding responses of continuous subcutaneous insulin infusion (CSII)-treated type 1 diabetic patients using real-time continuous glucose monitoring (RT-CGM).

Research Design And Methods: Sixty CSII-treated type 1 diabetic participants (aged 13-70 years, including adult and adolescent subgroups, with A1C
Results: In phase 1, after withdrawals 29 of 30 subjects were left in group A and 28 of 30 subjects were left in group B. The change in target glucose time did not differ between groups. A1C fell (mean 7.9% [95% CI 7.7-8.2to 7.6% [7.2-8.0]; P < 0.03) in group A but not in group B (7.8% [7.5-8.1] to 7.7 [7.3-8.0]; NS) with no difference between groups. More subjects in group A achieved A1C
Conclusions: Early but not late algorithm provision to type 1 diabetic patients using CSII/RT-CGM did not increase the target glucose time but increased achievement of A1C
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http://dx.doi.org/10.2337/dc09-1481DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2875432PMC
June 2010

A novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials.

Authors:
John Simes Merryn Voysey Rachel O'Connell Paul Glasziou James D Best Russell Scott Christopher Pardy Karen Byth David R Sullivan Christian Ehnholm Anthony Keech

PLoS One 2010 Jan 8;5(1):e8580. Epub 2010 Jan 8.

National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, Australia.

Background: When rates of uptake of other drugs differ between treatment arms in long-term trials, the true benefit or harm of the treatment may be underestimated. Methods to allow for such contamination have often been limited by failing to preserve the randomization comparisons. In the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study, patients were randomized to fenofibrate or placebo, but during the trial many started additional drugs, particularly statins, more so in the placebo group. The effects of fenofibrate estimated by intention-to-treat were likely to have been attenuated. We aimed to quantify this effect and to develop a method for use in other long-term trials.

Methodology/principal Findings: We applied efficacies of statins and other cardiovascular drugs from meta-analyses of randomized trials to adjust the effect of fenofibrate in a penalized Cox model. We assumed that future cardiovascular disease events were reduced by an average of 24% by statins, and 20% by a first other major cardiovascular drug. We applied these estimates to each patient who took these drugs for the period they were on them. We also adjusted the analysis by the rate of discontinuing fenofibrate. Among 4,900 placebo patients, average statin use was 16% over five years. Among 4,895 assigned fenofibrate, statin use was 8% and nonuse of fenofibrate was 10%. In placebo patients, use of cardiovascular drugs was 1% to 3% higher. Before adjustment, fenofibrate was associated with an 11% reduction in coronary events (coronary heart disease death or myocardial infarction) (P = 0.16) and an 11% reduction in cardiovascular disease events (P = 0.04). After adjustment, the effects of fenofibrate on coronary events and cardiovascular disease events were 16% (P = 0.06) and 15% (P = 0.008), respectively.

Conclusions/significance: This novel application of a penalized Cox model for adjustment of a trial estimate of treatment efficacy incorporates evidence-based estimates for other therapies, preserves comparisons between the randomized groups, and is applicable to other long-term trials. In the FIELD study example, the effects of fenofibrate on the risks of coronary heart disease and cardiovascular disease events were underestimated by up to one-third in the original analysis.

Trial Registration: Controlled-Trials.com ISRCTN64783481.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0008580PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2798963PMC
January 2010

What does it cost to establish a practice-nurses-led clinical trial in general practice?

Authors:
Irene D Blackberry John S Furler Doris Young James D Best

Med J Aust 2009 Nov;191(9):492-5

Department of General Practice, University of Melbourne, Melbourne, VIC, Australia.

Objective: To describe the processes and costs of engaging practice nurses (PNs) to establish a cluster randomised controlled trial (RCT) to study type 2 diabetes in general practice.

Design, Setting And Participants: Descriptive study of the processes and costs of engaging PNs from 59 general practices in Victoria that were participating in the Patient Engagement And Coaching for Health (PEACH) study, prior to practices being randomly assigned in the cluster RCT.

Main Outcome Measures: Estimated direct research costs and personnel costs for establishing a general practice-based research project involving PNs (eg, costs for approaching Victorian Divisions of General Practice and the Australian Practice Nurses Association; practice and patient recruitment; research project establishment at general practices; and PNs' training, support and engagement during the study establishment period).

Results: The estimated cost to establish our PN-led general practice-based cluster RCT was over $110 000, with an average cost of $2000 per practice. Direct research and personnel costs were considerably higher than anticipated. Lack of research skills among PNs required intensive hands-on support from the research team.

Conclusions: It is feasible to undertake a PN-led, general practice-based clinical trial in diabetes care. Future research funding needs to account for recruitment costs, including the need to build PN research capacity, and to overcome the inherent difficulties of engaging practices in complex intervention trials in primary care.

Trial Registration: International Standard Randomised Controlled Trial Number Register ISRCTN50662837.
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http://dx.doi.org/10.5694/j.1326-5377.2009.tb02911.xDOI Listing
November 2009