This report by Salonikiou et al. tests a metric described as 'maximum tolerable rate of progression to avoid visual impairment' (maxTRoP_VI) and a similar metric for blindness (maxTRoP_BL) that may be applied to patients with open-angle glaucoma (OAG). This is an interesting concept and fits with the objective of glaucoma treatment to maintain lifelong preservation of visual function and related quality of life. Using data from a population- based cross-sectional study of 5000 randomly selected people aged 60+ years in an urban area of northern Greece (The Thessaloniki Eye Study), the authors were able to obtain visual field data for 123 study participants with Open Angle Glaucoma, OAG). A strength of using population-based data is that the risk of selection bias is reduced which may occur when using clinical trial data and convenience samples of clinic-based patients which are not representative of the natural history of all persons affected by OAG in a population (half or more of those identified in population based studies being unaware they have OAG). Using a statistical model that requires age, sex and MD of the visual field at presentation as input values, each participant's life expectancy was calculated based on life expectancy tables. Their software tool then calculated the maxTRoP_VI and maxTRoP_BL, which are essentially the rates of progression which would not lead to visual impairment and blindness, respectively, until the very end of each participant's expected lifetime. There have been relatively few attempts to model visual field progression using cross-sectional data. Notably Broman et al. developed a model that calculates OAG incidence from age-specific prevalence using cross-sectional survey data to estimate the average rate of progression for an individual with OAG,1 based on an approach suggested by Leske et al.2 Since OAG does not spontaneously disappear and produces either stable or worsening damage, the increment in prevalence at each succeeding age in a cross sectional study is a measure of the number of new cases added (incidence). Broman et al. modeled OAG visual field progression using age-specific damage data from nine large population-based studies, (392 subjects in the European dataset). They were able to estimate the proportion of all OAG patients expected to become bilaterally blind (30 dB MD loss in both worse and better eye. By contrast, this study by Salonikiou et al. does not describe the equation that underlies the calculator and therefore it is unclear as to how rates of progression were calculated in this rather smaller sample of Europeans with OAG. While Broman et al. used a threshold of vision function that is much more severe (30dB MD loss), Salonikiou et al. additionally used the thresholds of −14dB and −12dB in better or worse eyes. Mean Deviation, a summary measure of visual field damage, is likely to encompass a much wider range of disability when these less severe thresholds are reached, than when considering a 'blindness' cut-off, and therefore one has to be cautious in conflating 'visual impairment' defined by an MD threshold with 'visual impairment' defined by a visual acuity threshold, a more common usage of the term (e.g. as defined by the World Health Organisation). Salonikiou et al. report that 70% of those with OAG would become visually impaired (Using −12 dB as threshold for visual impairment) at rates of progression as slow as −1 dB/year. More than 70% would have a maximum tolerable rate of progression to avoid blindness during their expected lifetime of slower than −2 dB/year. The authors therefore argue that being complacent about an eye that appears to have a slower rate of progression may not be appropriate. Certainly their findings do not contradict the importance of excluding a rate of progression of−2 dB/year, as was recommended by Chauhan et al.3 Although there are clearly limitations in this approach that assumes linearity of the rate of change in the visual field over time and the issue of ocular co-pathology that may affect the visual field, these findings do raise an interesting discussion about how best to individualize our approach to measuring progression and the need to find better more practical tools.