Мы используем файлы cookie.
Продолжая использовать сайт, вы даете свое согласие на работу с этими файлами.
Number needed to harm
Другие языки:

    Number needed to harm

    Подписчиков: 0, рейтинг: 0
    Illustration of two groups: one exposed to a risk factor, and one unexposed. Exposed group has larger risk of adverse outcome (NNH = 4).
    Group exposed to a risk factor (left) has increased risk of an adverse outcome (black) compared to the unexposed group (right). 4 individuals need to be exposed for 1 adverse outcome to occur (NNH = 4).

    In medicine, the number needed to harm (NNH) is an epidemiological measure that indicates how many persons on average need to be exposed to a risk factor over a specific period to cause harm in an average of one person who would not otherwise have been harmed. It is defined as the inverse of the absolute risk increase, and computed as , where is the incidence in the treated (exposed) group, and is the incidence in the control (unexposed) group. Intuitively, the lower the number needed to harm, the worse the risk factor, with 1 meaning that every exposed person is harmed.

    NNH is similar to number needed to treat (NNT), where NNT usually refers to a positive therapeutic result and NNH to a detrimental effect or risk factor. A combined measure, the number needed to treat for an additional beneficial or harmful outcome (NNTB/H), is also used.

    Relevance

    The NNH is an important measure in evidence-based medicine and helps physicians decide whether it is prudent to proceed with a particular treatment which may expose the patient to harms while providing therapeutic benefits. If a clinical endpoint is devastating enough without the drug (e.g. death, heart attack), drugs with a low NNH may still be indicated in particular situations if the NNT is smaller than the NNH. However, there are several important problems with the NNH, involving bias and lack of reliable confidence intervals, as well as difficulties in excluding the possibility of no difference between two treatments or groups.

    Numerical example

    Example of risk increase
    Quantity Experimental group (E) Control group (C) Total
    Events (E) EE = 75 CE = 100 175
    Non-events (N) EN = 75 CN = 150 225
    Total subjects (S) ES = EE + EN = 150 CS = CE + CN = 250 400
    Event rate (ER) EER = EE / ES = 0.5, or 50% CER = CE / CS = 0.4, or 40%
    Variable Abbr. Formula Value
    Absolute risk increase ARI EERCER 0.1, or 10%
    Number needed to harm NNH 1 / (EERCER) 10
    Relative risk (risk ratio) RR EER / CER 1.25
    Relative risk increase RRI (EERCER) / CER, or RR − 1 0.25, or 25%
    Attributable fraction among the exposed AFe (EERCER) / EER 0.2
    Odds ratio OR (EE / EN) / (CE / CN) 1.5

    Новое сообщение