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One of the difficulties in measuring patient-relevant outcomes is that they may be ‘composite’ outcomes and include items that are not readily amenable to objective measurement. They are likely to include a measure of a clinical effect, adverse effects, and change in quality of life and may need to be individualised for each treatment. In this situation the following types of outcomes should be considered:
• all-cause mortality;
• cause-specific mortality;
• changes in morbidity, subdivided according to type—for example, hospital admission or nursing home requirements;
• side-effects of treatment—including adverse reactions to drug therapies —and co-interventions that may be necessitated by the primary treatment; and
• disease-specific outcomes—including disease-specific quality-of-life measures.
Emphasis should be given to studies that measure clinical or patient-relevant outcomes. Guideline developers should seek the advice of experts and patient- support groups in determining what the most appropriate outcomes are. Many clinical trials and studies do not consider all the outcomes, beneficial and harmful, that are relevant to patients with a particular condition and to those who care for them. Clinical endpoints—such as a small change in blood cholesterol in a ‘low- risk’ patient—may not be as relevant as the side-effects of a particular treatment. Equally, a condition that impairs the social functioning of a person might be very effectively alleviated by a new intervention. Formal quality-of-life measures such as the SF-36 often do not capture the information that is of real importance in assessing the potential impact or value of a new technology.
2.2.3 The strength of the evidence
The strength of the evidence depends on the magnitude of the treatment effect seen in the clinical studies. It also depends on how confident we are of the observed effect—in other words, the size of the confidence interval—and the extent to which the findings have been reproduced across a series of studies.
Strength of evidence is important for two main reasons. Strong effects are less likely than weak effects to be the result of bias in the studies: they are more likely to be real. And strong effects are more likely to be clinically important.
2.3 Using evidence in making recommendations for treatment
Evidence is necessary, but not sufficient, when making recommendations for treatment. Taking the evidence—of whatever level, quality, relevance or strength—and turning it into a clinically useful recommendation depends on the judgment, experience and good sense of the guideline developers.
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