Modern Methods of Clinical Investigation (1990) / Chapter Skim
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10. Should We Change the Rules for Evaluating Medical Technologies?
10. Should We Change the Rules for Evaluating Medical Technologies?
Pages 117-134
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From page 117... ...
They range from simply asking experts (pure clinical judgment) to conducting multiple randomized controlled trials, with anecdotes, clinical series, data bases, nonrandomized controlled trials, and case-control studies in between.
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From page 118... ...
. We can require dozens of randomized controlled trials to demonstrate that a drug is effective for a particular indication, and leave it to pure clinical judgment to determine its effectiveness for other indications.
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From page 119... ...
This uncertainty can be displayed in terms of confidence intervals or probability distributions. For this particular example, Me 95 percent confidence intervals for the estimated effect of We technology range from 0.2 -0.4 I J 1~ I I -0.2 ~ 0 0.2 0.4 DIFFERENCE IN PROBABILITY FIGURE 10.1 Results of randomized controlled clinical trial of hypothetical treatment for heart attacks.
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From page 120... ...
To people who interpret statistical significance rigidly, there is even a big difference between a range of uncertainty of_5.2 percent and _4.9 percent (see Figure 10.4~.
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From page 121... ...
Stated another way, if all the results could be taken at face value, randomized controlled trials, case for case, would not provide any more precise or certain information than designs that are considered less rigorous, such as non-randomized controlled trials, case-control studies, comparisons of clinical series, or analyses of data bases. Consider, for example, two studies of breast cancer screening in women over age 50.
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From page 122... ...
(1~. After seven years of follow-up, there were 71 breast cancer deaths in the group offered screening and 76 breast cancer deaths in the control group.
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From page 123... ...
, 162 women matched by year of birth who have not died of breast cancer (the controls) , and retrospective ascertainment of which women had been screened.
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From page 124... ...
Patient selection bias exists when patients in the two groups to be compared (e.g., the control and treated groups of a controlled trial) differ in ways that could affect the outcome of interest.
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From page 125... ...
Data bases can be subject to the same problem, depending on the accuracy with which the data elements were coded. With respect to external validity, randomized controlled trials are sensitive to population biases, because the recruitment process and admission criteria often result in a narrowly defined set of patient indications.
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From page 126... ...
Someone who believes in only the most rigorous randomized controlled trials (what we might call a "strict constructionist") might say the potential biases of data bases (or case-control studies, or non-randomized controlled trials)
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From page 127... ...
Consider the implications of different points of view. To insist on seeing randomized controlled trial "proof" of effectiveness before approving a technology, and to not allow case-control studies, non-randomized controlled trials, analysis of data bases, or comparisons of clinical series (call this the "strict constructionist approach")
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From page 128... ...
Is there really any reason to believe there is something inherent about drugs versus procedures that makes multiple randomized controlled trials necessary for drugs, but clinical series and clinical judgment best for procedures? It is difficult to argue that the status quo is the appropriate choice.
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From page 129... ...
The hallmark of the flexible but firm approach is that it uses formal techniques (e.g., statistical models of biases) to incorporate focused subjective judgments (not global clinical impressions)
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From page 130... ...
Adjustment for these assumptions delivers the estimated effect of breast cancer screening in the circumstances of interest shown in Figure 10.6. The randomized controlled trial taken at face value is included in the figure for comparison (dashed line)
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From page 131... ...
breast cancer screening in the circumstances of interest is shown in Figure 10.7, which includes for comparison the study's results taken at face value, and the two distributions derived from the randomized controlled trial. This example could be made richer by incorporating uncertainty about any of the estimates of biases, by considering other potential biases that might affect the studies, by introducing and adjusting five other controlled studies of breast cancer screening for this age group (9-13)
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From page 132... ...
To 0.5 ODDS RATIO FIGURE 10.7 Probability distributions for Swedish randomized controlled clinical trial taken at face value and adjusted for biases (see text) and for DOM case-control study taken at face value and adjusted for biases (see text)
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From page 133... ...
For the people who produce the evidence, adoption of a new approach could either decrease or increase the research burden, depending on the current standard that must be met. Compared with the rigorous approach, it should be faster and simpler to gather evidence, because a wider variety of designs can be chosen from, and most of the new options are logistically simpler than the randomized controlled trial.
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From page 134... ...
Current results of the breast cancer screening randomized trial: The Health Insurance Plan (HIP) of Greater New York Study.
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