RNA interference (RNAi) has opened promising avenues to better understand gene function. Though many RNAi screens report on the identification of genes, very few, if any, have been further studied and validated. Data discrepancy is emerging as one of RNAi main pitfalls. We reasoned that a systematic analysis of lethality-based screens, since they score for cell death, would examine the extent of hit discordance at inter-screen level. To this end, we developed a methodology for literature mining and overlap analysis of several screens using both siRNA and shRNA flavors, and obtained 64 gene lists censoring an initial list of 7,430 nominated genes. We further performed a comparative analysis first at a global level followed by hit re-assessment under much more stringent conditions. To our surprise, none of the hits overlapped across the board even for PLK1, which emerged as a strong candidate in siRNA screens; but only marginally in the shRNA ones. Furthermore, EIF5B emerges as the most common hit only in the shRNA screens. A highly unusual and unprecedented result was the observation that 5,269 out of 6,664 nominated genes (~80%) in the shRNA screens were exclusive to the pooled format, raising concerns as to the merits of pooled screens which qualify hits based on relative depletions, possibly due to multiple integrations per cell, data deconvolution or inaccuracies in intracellular processing causing off-target effects. Without golden standards in place, we would encourage the community to pay more attention to RNAi screening data analysis practices, bearing in mind that it is combinatorial in nature and one active siRNA duplex or shRNA hairpin per gene does not suffice credible hit nomination. Finally, we also would like to caution interpretation of pooled shRNA screening outcomes.