Examples of bias due to missing outcomes in a randomized trial and how to report on trials with missing outcomes
| Scenario | Treatment group, no. (%) of events | Estimated treatment effect,* RR | What to report: characteristics of participants included in the analysis | ||
|---|---|---|---|---|---|
| Treatment | Placebo | Treatment, no. (%) of participants | Placebo, no. (%) of participants | ||
| Scenario 1: no missing outcomes | |||||
| Women | 40/500 (8) | 50/500 (10) | 500/1000 (50) | 500/1000 (50) | |
| Men | 120/500 (24) | 150/500 (30) | 500/1000 (50) | 500/1000 (50) | |
| Total | 160/1000 (16) | 200/1000 (20) | 0.80 | ||
| Scenario 2: 25% missing outcomes (all women from treatment group) | |||||
| Women | – | 50/500 (10) | 0/500 (0) | 500/1000 (50) | |
| Men | 120/500 (24) | 150/500 (30) | 500/500 (100) | 500/1000 (50) | |
| Total | 120/500 (24) | 200/1000 (20) | 1.20 | ||
| Scenario 3: 25% missing outcomes that affect both treatment groups in a different way | |||||
| Women | 20/250 (8) | 50/500 (10) | 250/750 (33) | 500/750 (67) | |
| Men | 120/500 (24) | 75/250 (30) | 500/750 (67) | 250/750 (33) | |
| Total | 140/750 (19) | 125/750 (17) | 1.12 | ||
Note: RR = risk ratio.
↵* In all scenarios, the estimated treatment effect is unbiased if stratified by sex. In scenario 2, the estimated treatment effect (RR) for men is 0.8 ([120/500]/[150/500]); the RR for women cannot be estimated. In scenario 3, the RR for men and women is the same (RR 0.8; men: RR = [120/500]/[75/250]; women: RR = [20/250]/[50/500]).