Medical Statistics. David Machin. Читать онлайн. Newlib. NEWLIB.NET

Автор: David Machin
Издательство: John Wiley & Sons Limited
Серия:
Жанр произведения: Медицина
Год издания: 0
isbn: 9781119423652
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would have to treat nine patients with corn plasters in order to expect one extra patient (compared to scalpel treatment) to have their corn resolved at a three‐month follow‐up.

       Issues with NNT – Always Consider all the Risks

Scenario P Test P Control P TestPControl NNT RRTest/Control ORTest/Control
1 0.1001 0.0001 0.1 10 1001 1112
2 0.101 0.001 0.1 10 101 112
3 0.11 0.01 0.1 10 11 12
4 0.15 0.05 0.1 10 3 3
5 0.2 0.1 0.1 10 2 2
6 0.6 0.5 0.1 10 1.2 2
7 0.9 0.8 0.1 10 1.1 2

      Without stating the direction of the effect, the alternative treatment, the treatment period, and the follow‐up period, information in terms of NNTs is uninterpretable. Thus when quoting an NNT one should always give the basic information about which treatments are compared, the treatment period, the follow‐up period, and the direction of the effect.

      Example – Importance of Considering both Absolute Risk and Relative Risk

      Women of reproductive age not using the combined oral contraceptive pill have a risk of deep vein thrombosis (DVT) of about 2 per 10 000 women per year (Stegeman et al. 2013). Use of combined oral contraceptives increases the risk of DVT compared with non‐use by a relative risk of 4 to 8 per 10 000 women per year, which would seem a large extra risk. However, the absolute increase in risk is 8/10 000 – 2/10 000 = 6/10 000 = 0.0006, or an additional 6 women with DVTs in 10 000 years of exposure. This increased risk is very small and hence may be considered worth taking, when balanced against other factors such as cost or convenience. Also, it is worth mentioning that a pregnant woman has a risk of a DVT of about 11 per 10 000 per year (Kourlaba et al. 2016); so the risk of DVT if you are pregnant is greater than the risk of a DVT when using the contraceptive pill, of 8 per 10 000 per year. Thus when one reads in the newspapers about a new risk to health that has been discovered, often only the relative risk is quoted, but one should ask about the baseline risk or incidence of the outcome (given you are not exposed to the risk factor) and the ARD, which may be negligible. If you are at very low risk, then you will remain at very low risk even when exposed to a hazard, unless the relative risk for the hazard is enormous!

       Summarising Binary Data – Odds and Odds Ratios

      A further method of summarising the results is to use the odds of an event rather than the probability. The odds of an event are defined as the ratio of the probability of occurrence of the event to the probability of non‐occurrence, that is, p/(1−p).

      Using the notation of Table 3.3 we can see that the odds of a positive outcome for the test group relative to the odds of a positive outcome for control group, the odds ratio (OR), is:

equation

      The odds ratio (OR) from Table 3.3 is

      What does an odds ratio of less than 1 mean? There is a negative association between exposure and outcome (people in the exposed group less likely to experience outcome of interest). What does an odds ratio of more than 1 mean? There is a positive association between the exposure and outcome (people in the exposed group more likely to experience the outcome of interest).

      Example – Summarising Results from a Clinical Trial– Corn Plasters: Odds Ratio

      From Table 3.4, the odds of the corn resolving by three‐months in the plaster group is 0.337/(1 − 0.337) = 0.508; whilst the odds of resolution in the scalpel group is 0.213/(1 − 0.213) = 0.270. Thus, the odds ratio for the corn resolving by three months in the plaster compared to the scalpel treated group is 0.508/0.270 = 1.88. You can also calculate the odds ratio