This study aimed to predict patient responses to the DAFNE diabetes education program based on baseline characteristics and assess the cost-effectiveness of providing DAFNE only to predicted responders. Regression models found baseline HbA1c, fear of hypoglycemia, thoughts on diabetes seriousness, BMI, and gender predictive of HbA1c change after DAFNE. However, integrating these models into an economic simulation found providing DAFNE only to predicted responders generated fewer health benefits at higher costs than current practice, making it not a cost-effective approach.

1. The Cost-Effectiveness of Providing DAFNE to
Subgroups of Predicted Responders
J Kruger1, A Brennan1, P Thokala1, S Heller2
on behalf of the DAFNE Research Group
1 School of Health and Related Research (ScHARR), University of
Sheffield, Sheffield
2 Academic Unit of Diabetes, Endocrinology and Metabolism,
School of Medicine and Biomedical Sciences, University of
Sheffield, Sheffield
Introduction
The Dose Adjustment for Normal Eating (DAFNE) course is a structured education programme for adult patients with Type 1 diabetes. DAFNE has been found to
improve glycosylated haemoglobin (HbA1c) levels in UK Type 1 diabetes patients1 and a cost-effectiveness modelling analysis concluded that DAFNE was cost-
effective from the NHS perspective2. This analysis assumed that HbA1c benefit experienced by patients receiving DAFNE was homogeneous, however it has been
found that HbA1c response to DAFNE is highly variable between patients. Although some patients do experience significant HbA1c reductions after DAFNE, other
patients experience a worsening of HbA1c
1,3 and some find it difficult to maintain initial HbA1c improvements4. Targeting DAFNE to only those patients that are
expected to benefit may improve the cost-effectiveness of the intervention.
This study aims to explore statistical modelling methodologies to predict individual clinical responses to DAFNE from psychosocial characteristics and incorporate
psychosocial predictors into an economic simulation model to investigate the cost-effectiveness of providing DAFNE to subgroups of predicted responders.
Methods
Data from the National Institute for Health Research (NIHR) DAFNE Research
Programme were used to support all analyses*. In the psychosocial sub-study of
the NIHR DAFNE Research Programme demographic, psychosocial and clinical
data were collected from 262 patients at baseline and 3-, 6-, and 12-months after
DAFNE.
Three regression models were used to investigate the relationships between
patients’ baseline demographic and psychosocial characteristics and 12-month
HbA1c response to DAFNE:
The regression prediction models were integrated with a patient level simulation
model of Type 1 diabetes. The integrated model was used to compare provision of
DAFNE only to those patients who were predicted from their baseline
characteristics to experience a 12-month HbA1c reduction of at least 0.5% with
current practice. The model estimated costs and quality-adjusted life-years
(QALYs) over a 50-year time horizon from an NHS perspective. Costs and QALYs
were discounted at a rate of 3.5%.
Conclusions
The results suggest that screening patients prior to offering them DAFNE and
providing the intervention only to predicted responders is not cost-effective.
The adapted health economic model offers the opportunity to investigate
research questions about the cost-effectiveness of DAFNE that could not be
assessed using previously published cost-effectiveness models of Type 1
diabetes. The model could be used to evaluate and compare future
developments of the DAFNE intervention.
Results
Baseline HbA1c, baseline fear of hypoglycaemia5, baseline thoughts about diabetes
seriousness6, BMI and gender were found to be significantly predictive (p<0.05) of
12-month HbA1c change after DAFNE. The adjusted R2 of prediction model A was
0.534 and of prediction model B was 0.054. Prediction model C correctly
categorised 86.6% of non-responders and 35.2% of responders.
The results suggest that providing DAFNE only to a subgroup of predicted
responders generates fewer QALYs for higher costs and is therefore dominated by
current practice (see Figure 1). The results were insensitive to the treatment
response prediction model used and to alternative model assumptions tested in
one-way sensitivity-analysis.
References
1. DAFNE Study Group, Training in flexible, intensive insulin management to enable dietary freedom in
people with type 1 diabetes: dose adjustment for normal eating (DAFNE) randomised controlled trial.
British Medical Journal 2002;325:746-749.
2. Shearer A., Bagust A, Sanderson D, Heller S, Roberts S. Effectiveness of flexible intensive insulin
management to enable dietary freedom in people with type1 diabetes in the UK. Diabetic Medicine
2004;21:460–467.
3. DAFNE NIHR Research Group. Personal communication: Unpublished data. 2006.
4. Speight J, Amiel S, Bradley C, Heller S, Oliver L, Roberts S, et al. Long-term biomedical and
psychosocial outcomes following DAFNE (Dose Adjustment For Normal Eating) structured education
to promote intensive insulin therapy in adults with sub-optimally controlled Type 1 diabetes. Diabetes
Research and Clinical Practice 2010;89:22-9.
5. Cox D, Irvine A, Gonder-Frederick L, Nowacek G, Butterfield J. Fear of hypoglycemia: quantification,
validation, and utilization. Diabetes Care 1987;10(5):617-21.
6. Hampson S, Glasgow R, Toobert D. Personal Models of Diabetes and Their Relations to Self-Care
Activities. Health Psychology 1990;9(5):632-46.
* This study was funded by the NIHR. This poster presents independent research commissioned by the NIHR under Improving
management of Type 1 diabetes in the UK: the DAFNE programme as a research test-bed. The views expressed in this poster
are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.
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Prediction model A
Prediction model B
Prediction model C
Figure 1: The cost-effectiveness of providing DAFNE only to
predicted responders vs. current practice
Acknowledgements
We would like to thank our collaborators Dr Debbie Cooke and Dr Marie Clark at
University College London and Dr Rod Bond at University of Sussex for sharing
data and preliminary research findings from the psychosocial sub-study of the
NIHR DAFNE Research Programme.
Prediction
model
Definition of treatment
response
Statistical analysis
method
A 12-month HbA1c value Multiple linear
regression
B Change in HbA1c from
baseline to 12-months
Multiple linear
regression
C Probability of responding to
DAFNE (reduction of at
least 0.5% by 12 months)
Logistic regression