Objective To elicit a range of values for sensitivity, specificity and other measures of performance in screening for oral cancer and precancer. Method A literature search which included three databases was conducted. Strict inclusion criteria were applied. Values for sensitivity (Sn) and specificity (Sp), from seven investigations, were expressed as a receiver operator characteristic (ROC) curve. Meta-analysis of the combined results was used to produce a summary operator characteristic (SROC) curve. Results The pooled weighted value of Sn from the seven studies was 0.796. From the SROC, the corresponding value of Sp at this level of Sn was 0.977 (95% CI 0.941, 0.991). When Sp was held at 0.977, the corresponding value of Sn from the SROC was 0.796 (95% CI 0.594, 0.912). Conclusions The reports selected for eventual inclusion revealed a high level of heterogeneity with respect to the location of investigations, prevalence of lesions, the personnel used and other factors. The meta-analysis indicated that overall the studies had high discriminatory ability. The estimates of Sn and Sp, and values obtained for other measures of screening performance, were considered suitable for input to a simulation model in assessing the likely cost-utility of a variety of screening scenarios in further planned research.During the past decade, there has been mounting interest in the possibility of instituting screening programmes for oral cancer and precancer. Although a disease of relatively low incidence, oral cancer has high morbidity and mortality and appears to fulfil many of the criteria of a disease suitable for screening population groups at risk. Nevertheless, it would be difficult to envisage the formal acceptance of population screening for oral cancer as a part of health policy without its likely costs and benefits, as well as its feasibility and suitability, having been evaluated. The best evidence of the efficacy of a clinical intervention is provided by a randomised controlled trial (RCT), this being the 'gold standard' for evaluations of effectiveness. However, the cost and logistical difficulties of organising and managing a trial of screening for such a relatively uncommon disease would be formidable. A feasible alternative in such circumstances is the use of simulation modelling. This technique synthesises and analyses data collected from multiple sources, including the literature, and is capable of generating valid cost-effectiveness data. Simulation modelling has the added advantage that by the means of sensitivity analysis, it enables a range of screening scenarios to be examined relatively cheaply and the optimum approach identified. However RCT would allow at the most only a very few programmes to be evaluated and compared simultaneously and would be extremely costly to mount.The use of a simple model to simulate opportunistic screening of patients at risk of oral cancer in general dental practice and provide a tentative determination of the health gain screening might achieve, together with its cost-effec...