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Plant health is increasingly threatened by abiotic and biotic stressors linked to anthropogenic global change. These stressors are frequently studied in isolation. However, they might have non-additive (antagonistic or synergistic) interactive effects that affect plant communities in unexpected ways. We conducted a global meta-analysis to summarize existing evidence on the joint effects of climate change (drought and warming) and biotic attack (pathogens) on plant performance. We also investigated the effect of drought and warming on pathogen performance, as this information is crucial for a mechanistic interpretation of potential indirect effects of climate change on plant performance mediated by pathogens. The final databases included 1230 pairwise cases extracted from 117 recently published scientific articles (from 2006) on a global scale. We found that the combined negative effects of drought and pathogens on plant growth were lower than expected based on their main effects, supporting the existence of antagonistic interactions. Thus, the larger the magnitude of the drought, the lower the pathogen capacity to limit plant growth. On the other hand, the combination of warming and pathogens caused larger plant damage than expected, supporting the existence of synergistic interactions. Our results on the effects of drought and warming on pathogens revealed a limitation of their growth rates and abundance in vitro but an improvement under natural conditions, where multiple factors operate across the microbiome. Further research on the impact of climate change on traits explicitly defining the infective ability of pathogens would enhance the assessment of its indirect effects on plants. The evaluated plant and pathogen responses were conditioned by the intensity of drought or warming and by moderator categorical variables defining the pathosystems. Overall, our findings reveal the need to incorporate the joint effect of climatic and biotic components of global change into predictive models of plant performance to identify non-additive interactions.