How do the Australian guidelines for lipid-lowering drugs perform in practice? Cardiovascular disease risk in the AusDiab Study, 1999–2000

Lei Chen, Sophie L Rogers, Stephen Colagiuri, Dominique A Cadilhac, Timothy H Mathew, Andrew N Boyden, Anna Peeters, Dianna J Magliano, Jonathan E Shaw, Paul Z Zimmet and Andrew M Tonkin
Med J Aust 2008; 189 (6): 319-322. || doi: 10.5694/j.1326-5377.2008.tb02049.x
Published online: 15 September 2008


Objective: To determine how well the current Pharmaceutical Benefits Scheme (PBS) eligibility criteria for subsidy of lipid-lowering drugs compare with current national guidelines for determining the population at high risk of developing cardiovascular disease (CVD).

Design and participants: Analyses of the population-based, cross-sectional Australian Diabetes, Obesity and Lifestyle (AusDiab) study, conducted in 1999–2000. The 1991 Framingham risk prediction equation was used to compute 5-year risk of developing first-time CVD in 8286 participants aged 30–74 years with neither CVD nor diabetes. Based on the National Heart Foundation of Australia and Cardiac Society of Australia and New Zealand guidelines, people with either 5-year CVD risk ≥ 15% or with 5-year CVD risk of 10%–< 15% and the metabolic syndrome were defined as having estimated high absolute CVD risk.

Main outcome measures: 5-year CVD risk; estimated population with high CVD risk.

Results: Among participants without prevalent CVD or diabetes, 7.9% of men and 1.5% of women had a 5-year CVD risk ≥ 15%. Of the estimated residential Australian population in 2000 aged 30–74 years without CVD or diabetes, 717 000 people were considered to be at high absolute CVD risk. Among the high-risk AusDiab participants without CVD or diabetes, only 16.9% of men and 15.4% of women were being treated with lipid-lowering drugs. Of the 9.6% of participants free of CVD and diabetes who were untreated but eligible for subsidy under PBS criteria, only 27.4% had an estimated high absolute CVD risk.

Conclusion: Strategies for CVD prevention using lipid-lowering medications can be improved by adoption of the absolute-risk approach.

The 2004–2005 National Health Survey showed that 3.8% of the Australian population had at least one of the four major manifestations of cardiovascular disease (CVD): coronary heart disease (CHD), stroke, peripheral vascular disease, and heart failure.1 These four common manifestations of CVD accounted for 30.4% of Australian deaths in 2005.2

Diabetes substantially increases cardiovascular risk, and people with diabetes are generally regarded as having CHD risk equivalence.3 As the population-attributable risk of CVD related to other risk factors such as dyslipidaemia and elevated blood pressure is very high, accurate identification of asymptomatic people without diabetes who are nevertheless at high risk of developing CVD events should inform the most effective use of preventive therapies.

Traditionally, treatment decisions for modifiable risk factors have been based on single risk factor thresholds for cholesterol or blood pressure. However, the relationship between risk factors and CVD outcomes is continuous, and estimating an individual’s “absolute risk” of future CVD events based on the intensity and integrated effects of multiple independent risk factors is a more efficient and cost-effective strategy.4 This approach has been recommended in several clinical practice guidelines.3,5-7

The updated National Heart Foundation of Australia and Cardiac Society of Australia and New Zealand (NHFA/CSANZ) Position statement on lipid management — 2005 suggests that, in addition to those with CVD, diabetes, chronic kidney disease, familial hypercholesterolaemia, or an Aboriginal or Torres Strait Islander background, people with either a 5-year CVD risk ≥ 15% (using the 1991 Framingham risk prediction equation) or with a 5-year CVD risk of 10%–< 15% and the metabolic syndrome or a family history of premature CHD should also be considered at high risk.5 These criteria are yet to be adopted in guidelines governing eligibility for subsidy of lipid-lowering drugs under the Pharmaceutical Benefits Scheme (PBS),8 which is still determined primarily by cholesterol levels.

We applied the high-risk definition as adapted from the NHFA/CSANZ position statement on lipid management5 to determine population estimates of people with high CVD risk based on participants in the Australian Diabetes, Obesity and Lifestyle (AusDiab) study, the most recent population-based, biomedical risk factor survey in Australia.9 We also examined the proportion of people with high CVD risk who were untreated but eligible for subsidy of lipid-lowering drugs under the PBS.

AusDiab study

The baseline AusDiab study recruited 11 247 adults (5048 men, 6199 women; 55.3% of those who completed an initial household interview) aged 25 years or over from 42 randomly selected census collector districts across Australia in 1999–2000.9 The study was approved by the Ethics Committee of the International Diabetes Institute and the Monash University Standing Committee on Ethics in Research involving Humans. Written informed consent was obtained from all participants.

Estimation of absolute CVD risk

The 1991 Framingham risk prediction equation for CVD was used to compute participants’ 5-year risk of developing a first CVD event.10 This multivariable equation uses age, sex, smoking status, blood pressure, total and high-density lipoprotein (HDL) cholesterol levels, presence of diabetes, and electrocardiogram (ECG) evidence of left ventricular hypertrophy (LVH) to predict risk of a CVD event within 4–12 years. CVD is defined as including myocardial infarction, angina pectoris, coronary insufficiency, CHD death, stroke, congestive heart failure, and peripheral vascular disease.


Of the 11 247 AusDiab participants, 9832 were aged 30–74 years, reflecting the age range in the Framingham cohort from which the risk prediction equation was developed.10 We excluded participants who were pregnant (46), had unclassified diabetes status (132), or who were missing data for blood pressure, total and HDL cholesterol (42) or smoking status (178), which are required for calculation of risk using the Framingham equation. Some participants fell into more than one exclusion category. Of the remaining 9526 participants (4312 men, 5214 women), 1240 had previous CVD (angina, CHD or stroke) or diabetes (self-reported or diagnosed at survey).


A standard 12-lead ECG was performed in participants aged over 40 years and in younger participants who requested it. LVH was diagnosed according to the Minnesota code 3-1.11 Participants lacking data for LVH were assumed not to have it. Glomerular filtration rate (GFR) was calculated with the Cockcroft–Gault formula, including a correction factor of 0.85 for women and adjustment for body surface area. Impaired GFR was defined as estimated GFR < 60 mL/min/1.73 m2. There were 64 participants lacking GFR data.


Characteristics of the AusDiab study participants aged 30–74 years are shown in Box 1. Compared with women, men had higher levels of systolic and diastolic blood pressure, lower levels of HDL cholesterol and higher prevalence of self-reported CVD and diabetes (all P < 0.05). Men were also more likely to smoke and use lipid-lowering therapy than women (both P < 0.05). In the AusDiab participants aged over 40 years who did not have prevalent CVD, LVH was present in 4.9% of men and 1.6% of women. There were 2143 participants without data for LVH who were all assumed not to have it; 83.2% of them were aged less than 40 years.

Use of lipid-lowering therapy in people at high CVD risk

Among the AusDiab participants aged 30–74 years, 39.0% of people with prevalent CVD (41.9% of men, 34.9% of women) and 24.4% of people with either known or newly diagnosed diabetes (24.6% of men, 24.1% of women) reported being treated with lipid-lowering drugs — much lower than the proportions eligible for such medications (ie, 100% of those with CVD and 83.6% of those with diabetes, under the PBS guidelines8). Of the people with known diabetes, only 34.8% (38.4% of men, 29.6% of women) were being treated with lipid-lowering drugs.

Among the participants with neither CVD nor diabetes but with an estimated high CVD risk, 16.9% of men and 15.4% of women were being treated with lipid-lowering drugs, including 16.5% of men and 27.9% of women with a 5-year CVD risk ≥ 15%, and 17.7% of men and 8.2% of women with a 5-year CVD risk of 10%–< 15% and the metabolic syndrome.

Among all participants free of CVD and diabetes, 4.8% (4.9% of men, 4.7% of women) reported being treated with lipid-lowering drugs. Despite being treated, 44.2% of these men and 13.1% of the women were still assessed to be at high absolute CVD risk based on their risk factor levels.

In contrast, 9.6% of people who were untreated and without CVD and diabetes met the PBS criteria for eligibility for subsidy of therapy based on their abnormal lipid levels (Box 3). Among this subgroup, only 13.4% had a 5-year CVD risk ≥ 15%, and 27.4% had an estimated high absolute CVD risk.


We have shown that policy measures encouraging use of lipid-lowering therapies based largely on cholesterol levels directs treatment away from those who are at higher risk and have most to gain from such treatment. This accords with other analyses, which have shown that the 10% of individuals with highest risk-factor levels for physiological variables such as cholesterol account for only 20%–30% of the total number of cases of ischaemic heart disease, stroke and diabetes.14

To our knowledge, this study is the first to describe population estimates of people with high CVD risk in a contemporary Australian population. The NHFA/CSANZ position statement on lipid management suggests a “threshold” of 15% 5-year CVD risk for drug treatment in those without known CVD or diabetes.5 We estimated that 717 000 Australians aged 30–74 years reached this threshold. However, more than 80% of people in this high-risk population were not being treated with lipid-lowering medication, indicating that current primary prevention of CVD is suboptimal. Our finding that 13% of women and 44% of men with neither CVD nor diabetes who were already being treated with lipid-lowering medications were still assessed to be at high CVD risk strongly suggests that their treatment may have been inadequate.

According to the PBS criteria, nearly 10% of people who were untreated and without prevalent CVD or diabetes were eligible for subsidy of lipid-lowering drugs. However, more than 70% of these people were not estimated to be at high absolute CVD risk as defined by the NHFA/CSANZ position statement. Similar results were also found in an earlier Australian study, which showed that of patients deemed suitable for lipid-lowering drugs by PBS guidelines, 63% had a 10-year risk of CHD of less than 20%.15 These findings favour using absolute or “global” risk assessment to determine who should receive drug therapies for primary prevention.

There are some limitations to our analyses. People who did not have ECG results were assumed not to have LVH, thereby possibly underestimating the high-risk distributions. However, LVH on ECG is very uncommon, found in less than 5% of people in this study who were aged over 40 years and free of CVD and diabetes. Lack of information on family history of premature CHD and familial hypercholesterolaemia might also have led to underestimation of risk. Finally, because the AusDiab study was conducted in 1999–2000, data on reported use of lipid-lowering medication might not reflect current clinical practice.

Several other aspects need to be considered. Prediction equations or risk scores derived from the Framingham Heart Study are the most widely used to assess CVD risk, and their validity in Australians has been confirmed in the Busselton and Dubbo studies.16,17 Both the Busselton and Dubbo groups have developed multivariate risk equations, but these have some limitations for general use. The prediction algorithm derived from the Busselton Health Study only allows estimation of risk of hospitalisation or death due to CHD within the next 10 years.18 The CVD risk prediction equation from the Dubbo Study is only applicable to older Australians aged 60–79 years.17 Contemporary population-specific risk prediction equations for future CVD or CHD events need to be further developed and validated.

Despite these limitations and considerations, our findings can inform health policy and clinical practice. As the greatest absolute risk reduction results from treatment of those at highest risk, we propose that criteria to support use of lipid-lowering medications in those without manifest CVD or diabetes should be revised.

Received 16 December 2007, accepted 18 June 2008

  • Lei Chen1
  • Sophie L Rogers2
  • Stephen Colagiuri3
  • Dominique A Cadilhac4
  • Timothy H Mathew5
  • Andrew N Boyden6
  • Anna Peeters1
  • Dianna J Magliano7
  • Jonathan E Shaw7
  • Paul Z Zimmet7
  • Andrew M Tonkin1

  • 1 Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC.
  • 2 Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC.
  • 3 Institute of Obesity, Nutrition and Exercise, University of Sydney, Sydney, NSW.
  • 4 Public Health Division, National Stroke Research Institute, Melbourne, VIC.
  • 5 Kidney Health Australia, Adelaide, SA.
  • 6 National Heart Foundation of Australia, Canberra, ACT.
  • 7 Baker IDI Heart and Diabetes Institute, Melbourne, VIC.


The work described here was partly supported by a grant from the Commonwealth Department of Health and Aged Care. Lei Chen is supported by an Australian Postgraduate Award scholarship. We are grateful to the following for their support of the AusDiab study: the Commonwealth Department of Health and Aged Care, Abbott Australasia, Alphapharm, AstraZeneca, Aventis, Bristol-Myers Squibb, Eli Lilly, GlaxoSmithKline, Janssen-Cilag, Merck Lipha, Merck Sharp & Dohme, Novartis, Novo Nordisk, Pharmacia and Upjohn, Pfizer, Roche Diagnostics, Sanofi Synthelabo, Servier, BioRad, HITECH Pathology, the Australian Kidney Foundation, Diabetes Australia, Diabetes Australia (Northern Territory), Queensland Health, South Australian Department of Human Services, Tasmanian Department of Health and Human Services, Territory Health Services, Victorian Department of Human Services, and Health Department of Western Australia. For their invaluable contribution to AusDiab set-up and field activities, we are grateful to A Allman, B Atkins, S Bennett, S Chadban, S Colagiuri, M de Courten, M Dalton, M D’Embden, D Dunstan, T Dwyer, D Jolley, I Kemp, P Magnus, J Mathews, D McCarty, A Meehan, K O’Dea, P Phillips, P Popplewell, C Reid, A Stewart, R Tapp, H Taylor, T Welborn and F Wilson.

Competing interests:

Andrew Tonkin has received speaker fees from AstraZeneca, Bristol-Myers Squibb, Merck Sharp & Dohme, Pfizer and Schering-Plough, and travel assistance from Pfizer and Schering-Plough.

  • 1. Australian Bureau of Statistics. National Health Survey: summary of results, 2004–05. Canberra: ABS, 2006. (ABS Cat. No. 4364.0.) (accessed Jul 2008).
  • 2. Australian Bureau of Statistics. Causes of death, Australia, 2005. Canberra: ABS, 2007. (ABS Cat. No. 3303.0.) (accessed Jul 2008).
  • 3. Grundy SM, Cleeman JI, Merz CN, et al. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines. Circulation 2004; 110: 227-239.
  • 4. Murray CJL, Lauer JA, Hutubessy RCW, et al. Effectiveness and costs of interventions to lower systolic blood pressure and cholesterol: a global and regional analysis on reduction of cardiovascular-disease risk. Lancet 2003; 361: 717-725.
  • 5. Tonkin A, Barter P, Best J, et al; National Heart Foundation of Australia and the Cardiac Society of Australia and New Zealand. Position statement on lipid management — 2005. Heart Lung Circ 2005; 14: 275-291.
  • 6. British Cardiac Society, British Hypertension Society, Diabetes UK, et al. JBS 2: Joint British Societies’ guidelines on prevention of cardiovascular disease in clinical practice. Heart 2005; 91 Suppl 5: v1-v52.
  • 7. New Zealand Guidelines Group. Best practice evidence-based guideline: the assessment and management of cardiovascular risk. Wellington: NZGG, 2003. (accessed Jul 2008).
  • 8. Australian Government Department of Health and Ageing. PBS-eligibility criteria for lipid lowering drugs: fact sheet. Canberra: DHA, 2006. (accessed Jul 2008).
  • 9. Dunstan DW, Zimmet PZ, Welborn TA, et al. The Australian Diabetes, Obesity and Lifestyle Study (AusDiab) — methods and response rates. Diabetes Res Clin Pract 2002; 57: 119-129.
  • 10. Anderson KM, Odell PM, Wilson PWF, Kannel WB. Cardiovascular disease risk profiles. Am Heart J 1991; 121: 293-298.
  • 11. Rose GA, Blackburn H. Cardiovascular survey methods. Geneva: World Health Organization, 1968.
  • 12. Alberti KG, Zimmet P, Shaw J; IDF Epidemiology Task Force Consensus Group. The metabolic syndrome — a new worldwide definition. Lancet 2005; 366: 1059-1062.
  • 13. Australian Bureau of Statistics. Population by age and sex, Australian states and territories, Jun 1997 to Jun 2002. Canberra: ABS, 2003. (ABS Cat. No. 3201.0.) 20to%20Jun%202002?OpenDocument (accessed Jul 2008).
  • 14. Law MR, Wald NJ. Risk factor thresholds: their existence under scrutiny. BMJ 2002; 324: 1570-1576.
  • 15. Forge BH, Briganti EM. Lipid lowering and coronary heart disease risk: how appropriate are the national guidelines? Med J Aust 2001; 175: 471-475.
  • 16. Knuiman MW, Vu HT. Prediction of coronary heart disease mortality in Busselton, Western Australia: an evaluation of the Framingham, national health epidemiologic follow up study, and WHO ERICA risk scores. J Epidemiol Community Health 1997; 51: 515-519.
  • 17. Simons LA, Simons J, Friedlander Y, et al. Risk functions for prediction of cardiovascular disease in elderly Australians: the Dubbo Study. Med J Aust 2003; 178: 113-116. <MJA full text>
  • 18. Knuiman MW, Vu HT, Bartholomew HC. Multivariate risk estimation for coronary heart disease: the Busselton Health Study. Aust N Z J Public Health 1998; 22: 747-753.


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