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In recent years, the importance of describing mortality at the limits of the life span has led to a number of relevant and controversial studies. Whereas considerable efforts have been devoted to collecting data and estimating models on the oldest-old individuals, the testing of statistical confidence about the conclusions of analyses at extreme ages has been largely neglected. How certain can we be in saying that the risk of dying increases, levels out, or, paradoxically, decreases over age 105? Can we recognize particular mortality age patterns at such high ages? In this paper, it is shown that very little can be confidently asserted about mortality at extreme ages. Instead of analyzing actual data, we perform a series of simulation studies mimicking actual scenarios from controlled mechanisms. Our findings are thus robust with respect to factors such as particular observation schemes, heterogeneity, and data quality issues. Given the sample sizes currently available and the levels of mortality experienced in present populations, we show that before age 110, only a Gompertzian increase of mortality may be detected. Afterwards a plateau will be regularly recognized as the most suitable pattern, regardless of the complexity of the true underlying mortality.