Peto’s method (Yusuf 1985) can only be used to pool odds ratios. It uses an inverse variance approach but utilizes an approximate method of estimating the log odds ratio, and uses different weights. An alternative way of viewing the Peto method is as a sum of ‘O – E’ statistics. Here, O is the observed number of events and E is an expected number of events in the experimental intervention group of each study.
The approximation used in the computation of the log odds ratio works well when intervention effects are small (odds ratios are close to one), events are not particularly common and the studies have similar numbers in experimental and control groups. In other situations it has been shown to give biased answers. As these criteria are not always fulfilled, Peto’s method is not recommended as a default approach for meta-analysis.
Corrections for zero cell counts are not necessary when using Peto’s method. Perhaps for this reason, this method performs well when events are very rare (Bradburn 2007) (see Chapter 16, Section 16.9). Also, Peto’s method can be used to combine studies with dichotomous outcome data with studies using time-to-event analyses where log-rank tests have been used (see Section 9.4.9).