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16. 1025MO First-in-human (FIH) phase I study of RO7122290 (RO), a novel FAP-targeted 4-1BB agonist, administered as single agent and in combination with atezolizumab (ATZ) to patients with advanced solid tumours

Author

Melero, I., Sanmamed, M.F., Calvo, E., Moreno, I., Moreno, V., Guerrero, T.C. Hernandez, Martinez-Garcia, M., Rodriguez-Vida, A., Tabernero, J., Pedrazzoli, A.B. Azaro, Spanggaard, I., Rohrberg, K.S., Guarin, E., Nueesch, E., Chesne, E., Ceppi, M., Sweere, U., McIntyre, C., Lichtenegger, F.S., and Krieter, O.

Published
2020
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17. The effects of exclusions of patients from the analysis in randomised controlled trials: Meta-epidemiological study

Author

Nüesch, E, Trelle, S, Reichenbach, S, Rutjes, AWS, Bürgi, E, Scherer, M, Altman, DG, and Jüni, P

Abstract

Objective: To examine whether exclusions of patients from the analysis of randomized trials are associated with biased estimates of treatment effects and higher heterogeneity between trials. Design: Meta-epidemiological study based on a collection of meta-analyses of randomised trials. Data sources: 14 meta-analyses including 167 trials that compared therapeutic interventions with placebo or non-intervention control in patients with osteoarthritis of the hip or knee and used patient reported pain as an outcome. Methods: Effect sizes were calculated from differences in means of pain intensity between groups at the end of follow-up, divided by the pooled standard deviation. Trials were combined by using random effects meta-analysis. Estimates of treatment effects were compared between trials with and trials without exclusions from the analysis, and the impact of restricting meta-analyses to trials without exclusions was assessed. Results: 39 trials (23 %) had included all patients in the analysis. In 128 trials (77 %) some patients were excluded from the analysis. Effect sizes from trials with exclusions tended to be more beneficial than those from trials without exclusions (difference -0.13, 95 %-confidence interval -0.29 to 0.04). However, estimates of bias between individual meta-analyses varied considerably (2=0.07). Tests of interaction between exclusions from the analysis and estimates of treatment effects were positive in five meta-analyses. Stratified analyses indicated that differences in effect sizes between trials with and trials without exclusions were more pronounced in meta-analyses with high between trial heterogeneity, in meta-analyses with large estimated treatment benefits, and in meta-analyses of complementary medicine. Restriction of meta-analyses to trials without exclusions resulted in smaller estimated treatment benefits, larger P values, and considerable decreases in between trial heterogeneity. Conclusion: Exclusions of patients from the analysis in randomised trials often result in biased estimates of treatment effects, but the extent and direction of bias is unpredictable. Results from intention to treat analyses should always be described in reports of randomised trials. In systematic reviews, the influence of exclusions from the analysis on estimated treatment effects should routinely be assessed.

Published
2016

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