Kulig Michael, Perleth Matthias, Langer Gero, Meerpohl Joerg J, Gartlehner Gerald, Kaminski-Hartenthaler Angela, Schünemann Holger J
Abteilung Fachberatung Medizin, Gemeinsamer Bundesausschuss, Berlin.
Z Evid Fortbild Qual Gesundhwes. 2012;106(9):677-88. doi: 10.1016/j.zefq.2012.10.016. Epub 2012 Nov 3.
GRADE suggests that examination of 95% confidence intervals (CIs) provides the optimal primary approach to decisions regarding imprecision. For practice guidelines, rating down the quality of evidence (i.e., confidence in estimates of effect) is required when clinical action would differ if the upper versus the lower boundary of the CI represented the truth. An exception to this rule occurs when an effect is large, and consideration of CIs alone suggests a robust effect, but the total sample size is not large and the number of events is small. Under these circumstances, one should consider rating down for imprecision. To inform this decision, one can calculate the number of patients required for an adequately powered individual trial (termed the "optimal information size" or OIS). For continuous variables, we suggest a similar process, initially considering the upper and lower limits of the CI, and subsequently calculating an OIS. Systematic reviews require a somewhat different approach. If the 95% CI excludes a relative risk (RR) of 1.0 and the total number of events or patients exceeds the OIS criterion, precision is adequate. If the 95% CI includes appreciable benefit or harm (we suggest a RR of under 0.75 or over 1.25 as a rough guide) rating down for imprecision may be appropriate even if OIS criteria are met.
GRADE建议，检查95%置信区间（CI）是针对不精确性做出决策的最佳主要方法。对于实践指南，如果CI的上限与下限代表真实情况时临床行动会有所不同，则需要降低证据质量等级（即对效应估计的置信度）。当效应很大，仅考虑CI表明效应稳健，但总样本量不大且事件数量较少时，此规则有一个例外情况。在这种情况下，应考虑因不精确性而降低等级。为辅助做出此决策，可以计算一项效能充足的个体试验所需的患者数量（称为“最佳信息量”或OIS）。对于连续变量，我们建议采用类似的流程，首先考虑CI的上限和下限，随后计算OIS。系统评价需要采用略有不同的方法。如果95%CI排除相对危险度（RR）为1.0，且事件或患者总数超过OIS标准，则精确性是足够的。如果95%CI包含明显的获益或危害（我们建议以RR低于0.75或高于1.25作为大致指导），即使满足OIS标准，因不精确性而降低等级可能也是合适的。
