How to Read a Paper: The Basics of Evidence-Based Medicine by Trisha Greenhalgh Page A
Authors: Trisha Greenhalgh
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outcome, but the diagnosis of ‘caseness’ and the decision as to when the individual became a case.
A good example of this occurred a few years ago when legal action was brought against the manufacturers of the whooping cough (pertussis) vaccine, which was alleged to have caused neurological damage in a number of infants [12]. In order to answer the question ‘Did the vaccine cause brain damage?’, a case–control study had been undertaken in which a ‘case’ was defined as an infant who, previously well, had exhibited fits or other signs suggestive of brain damage within 1 week of receiving the vaccine. A control was an infant of the same age and sex taken from the same immunisation register, who had received immunisation and who may or may not have developed symptoms at some stage.
New onset of features of brain damage in apparently normal babies is extremely rare, but it does happen, and the link with recent immunisation could conceivably be coincidental. Furthermore, heightened public anxiety about the issue could have biased the recall of parents and health professionals so that infants whose neurological symptoms predated, or occurred some time after, the administration of pertussis vaccine, might be wrongly classified as cases. The judge in the court case ruled that misclassification of three such infants as ‘cases’ rather than controls led to the overestimation of the harm attributable to whooping cough vaccine by a factor of three [12]. Although this ruling has subsequently been challenged, the principle stands—that assignment of ‘caseness’ in a case–control study must be performed rigorously and objectively if systematic bias is to be avoided.
Was assessment ‘blind’?
Even the most rigorous attempt to achieve a comparable control group will be wasted effort if the people who assess outcome (e.g. those who judge whether someone is still clinically in heart failure, or who say whether an X-ray is ‘improved’ from last time) know which group the patient they are assessing was allocated to. If you believe that the evaluation of clinical signs and the interpretation of diagnostic tests such as ECGs and X-rays is 100% objective, you haven't been in the game very long [13].
The chapter ‘The Clinical Examination’ in Sackett and colleagues' book ‘Clinical epidemiology: a basic science for clinical medicine’ [14] provides substantial evidence that when examining patients, doctors find what they expect and hope to find. It is rare for two competent clinicians to reach complete agreement for any given aspect of the physical examination or interpretation of any diagnostic test. The level of agreement beyond chance between two observers can be expressed mathematically as the Kappa score, with a score of 1.0 indicating perfect agreement. Kappa scores for specialists in the field assessing the height of a patient's jugular venous pressure, classifying diabetic retinopathy from retinal photographs and interpreting a mammogram X-ray, were, respectively, 0.42, 0.55 and 0.67 [14].
This digression into clinical disagreement should have persuaded you that efforts to keep assessors ‘blind’ (or to avoid offence to the visually impaired, masked ), to the group allocation of their patients are far from superfluous. If, for example, I knew that a patient had been randomised to an active drug to lower blood pressure rather than to a placebo, I might be more likely to re-check a reading that was surprisingly high. This is an example of performance bias , which, along with other pitfalls for the unblinded assessor, are listed in Figure 4.1 .
An excellent example of controlling for bias by adequate ‘blinding’ was published in the Lancet a few years ago [15]. Majeed and colleagues performed an RCT that demonstrated, in contrast with the findings of several previous studies, that the recovery time (days in hospital, days off work and time to resume full activity) after laparoscopic removal of the
A good example of this occurred a few years ago when legal action was brought against the manufacturers of the whooping cough (pertussis) vaccine, which was alleged to have caused neurological damage in a number of infants [12]. In order to answer the question ‘Did the vaccine cause brain damage?’, a case–control study had been undertaken in which a ‘case’ was defined as an infant who, previously well, had exhibited fits or other signs suggestive of brain damage within 1 week of receiving the vaccine. A control was an infant of the same age and sex taken from the same immunisation register, who had received immunisation and who may or may not have developed symptoms at some stage.
New onset of features of brain damage in apparently normal babies is extremely rare, but it does happen, and the link with recent immunisation could conceivably be coincidental. Furthermore, heightened public anxiety about the issue could have biased the recall of parents and health professionals so that infants whose neurological symptoms predated, or occurred some time after, the administration of pertussis vaccine, might be wrongly classified as cases. The judge in the court case ruled that misclassification of three such infants as ‘cases’ rather than controls led to the overestimation of the harm attributable to whooping cough vaccine by a factor of three [12]. Although this ruling has subsequently been challenged, the principle stands—that assignment of ‘caseness’ in a case–control study must be performed rigorously and objectively if systematic bias is to be avoided.
Was assessment ‘blind’?
Even the most rigorous attempt to achieve a comparable control group will be wasted effort if the people who assess outcome (e.g. those who judge whether someone is still clinically in heart failure, or who say whether an X-ray is ‘improved’ from last time) know which group the patient they are assessing was allocated to. If you believe that the evaluation of clinical signs and the interpretation of diagnostic tests such as ECGs and X-rays is 100% objective, you haven't been in the game very long [13].
The chapter ‘The Clinical Examination’ in Sackett and colleagues' book ‘Clinical epidemiology: a basic science for clinical medicine’ [14] provides substantial evidence that when examining patients, doctors find what they expect and hope to find. It is rare for two competent clinicians to reach complete agreement for any given aspect of the physical examination or interpretation of any diagnostic test. The level of agreement beyond chance between two observers can be expressed mathematically as the Kappa score, with a score of 1.0 indicating perfect agreement. Kappa scores for specialists in the field assessing the height of a patient's jugular venous pressure, classifying diabetic retinopathy from retinal photographs and interpreting a mammogram X-ray, were, respectively, 0.42, 0.55 and 0.67 [14].
This digression into clinical disagreement should have persuaded you that efforts to keep assessors ‘blind’ (or to avoid offence to the visually impaired, masked ), to the group allocation of their patients are far from superfluous. If, for example, I knew that a patient had been randomised to an active drug to lower blood pressure rather than to a placebo, I might be more likely to re-check a reading that was surprisingly high. This is an example of performance bias , which, along with other pitfalls for the unblinded assessor, are listed in Figure 4.1 .
An excellent example of controlling for bias by adequate ‘blinding’ was published in the Lancet a few years ago [15]. Majeed and colleagues performed an RCT that demonstrated, in contrast with the findings of several previous studies, that the recovery time (days in hospital, days off work and time to resume full activity) after laparoscopic removal of the
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