Intended for healthcare professionals

Editorials

Primary prevention of coronary heart disease

BMJ 2002; 325 doi: https://doi.org/10.1136/bmj.325.7355.56 (Published 13 July 2002) Cite this as: BMJ 2002;325:56

Unevaluated screening inhibits informed consent

  1. Peter Brindle, Wellcome training fellow in health services research (peter.brindle{at}bristol.ac.uk),
  2. Tom Fahey, professor of primary health care
  1. Department of Social Medicine, University of Bristol, Bristol BS8 2PR
  2. Tayside Centre for General Practice, University of Dundee, Dundee DD2 4AD

    Papers p 78

    Population screening for individuals at high risk of getting coronary heart disease is an explicit objective in primary care. The national service framework for coronary heart disease recommends that general practitioners and primary healthcare teams should identify all people at significant risk of cardiovascular disease, but who have not yet developed symptoms, and offer them appropriate advice and treatment to reduce their risk.1 In contrast to the current policy of maximising participation, Marteau and Kinmonth in this issue suggest that helping individuals to become involved in making informed choices may increase their motivation to make changes.2

    When the introduction of a national screening programme is being considered, a proper scientific evaluation should occur. Wilson and Jungner's criteria are a yardstick against which a screening programme can be judged (see box).3 Apart from the recognition that coronary heart disease is an important health problem little evidence exists that any of the other criteria are adequately met.

    The “significant risk of cardiovascular disease” to which the national service framework refers equates to a risk of coronary heart disease of more than 30% over 10 years. It is advocated that risk assessment should be performed by using one of several clinical decisions aids that are based on a Framingham risk equation.4 Although mortality due to coronary heart disease has declined considerably since the 1970s, and evidence has shown that the Framingham risk equation overestimates risk in populations of low prevalence of coronary heart disease, we do not know the sensitivity and specificity of this equation in a British population. 5 6 Further, the collection of the necessary information about risk factors is inadequate and user accuracy only moderate even when all the information is present. Wide variation also exists between the clinical decision aids with respect to the numbers of individuals identified as being at high risk. 7 8

    The Wilson-Jungner criteria for appraising the validity of a screening programme

    1. The condition being screened for should be an important health problem

    2. The natural history of the condition should be well understood

    3. There should be a detectable early stage

    4. Treatment at an early stage should be of more benefit than at a later stage

    5. A suitable test should be devised for the early stage

    6. The test should be acceptable

    7. Intervals for repeating the test should be determined

    8. Adequate health service provision should be made for the extra clinical workload resulting from screening

    9. The risks, both physical and psychological, should be less than the benefits

    10. The costs should be balanced against the benefits

    Even if the Framingham equation is assumed to be accurate, an estimated 3.4% of the population aged between 35 and 69 years would be identified as having a risk of coronary heart disease of greater than 30% over 10 years. Moreover, the threshold of 15% for consideration of treatment with aspirin and antihypertensives would entail identifying and treating 25% of the population.9 Only very few patients' records contain all the necessary data on risk factors, and this reflects that primary care is struggling with the workload associated with identifying the patients at high risk.7 More conservative and practicable approaches have been suggested, which entail restricting the measuring of total and high density lipoprotein cholesterol to patients who are among the 5% of the population (based only on their age, sex, smoking, and blood pressure) with a risk of 30% or more over 10 years.10 As yet, no consensus has been reached.

    Difficulties in risk assessment aside, once an estimate has been made of a patient's risk of coronary heart disease, a dialogue needs to be started between clinician and patient to enable an informed decision about possible interventions. The language used by the clinician—for example, the use of words such as “rare” or “probable”—and the way in which numerical data are presented can strongly influence the decisions that patients make.11 Framing effects—the description of similar degrees of risk in different ways—can further complicate informed decision making. For example, presenting information in terms of relative risk or as absolute risk can influence clinicians' decision making, but the effect on patients is unknown.11 The clinical decision aids that the national service framework advocates present only absolute risk and do not include information about the possible risk reductions that could be expected from interventions.

    The presence of the national service framework has undoubtedly resulted in concentrating the efforts of primary care practitioners on the prevention of coronary heart disease. Risk assessment combining multiple risk factors is preferable to focusing on arbitrary thresholds of single risk factors. But practical issues remain concerning the estimation of risk of coronary heart disease and sharing the decisions on treatment with patients. These difficulties, combined with the disappointing results of the trials of multiple risk factor interventions, question how informed the clinician or the patient can be.12 Until scientific evaluation catches up with political expediency, the goal of involving patients in making genuinely informed choices about coronary heart disease screening seems a long way off.

    References

    1. 1.
    2. 2.
    3. 3.
    4. 4.
    5. 5.
    6. 6.
    7. 7.
    8. 8.
    9. 9.
    10. 10.
    11. 11.
    12. 12.
    View Abstract

    Log in

    Log in through your institution

    Subscribe

    * For online subscription