Background and objectives: It has been argued that the binary framework frequently adopted to analyse test accuracy does not represent the clinical reality of diagnostic practice, and the recognition of an intermediate category of test result could make the utility of diagnostic tests more transparent. The objective of this thesis is to explore the value of moving away from the binary framework when evaluating and interpreting quantitative diagnostic tests. Methods: This thesis starts with an overview of the key arguments against dichotomising quantitative test results and a summary of some of the alternative methods proposed. Four distinct studies are then reported: 1) a systematic review of the methods currently used to evaluate the accuracy of quantitative cancer biomarkers, 2) a survey of GPs exploring preferences for threshold guidance 3) an evaluation of existing methods for identifying an intermediate range of test values, and 4) an assessment of the feasibility of applying these methods to the results of a meta-analysis. Results: The binary framework remains the most common method for evaluating the accuracy of quantitative tests, despite the survey of GPs indicating that a single threshold interpretation is less helpful than identifying rule-in and rule-out thresholds. Existing methods for identifying an intermediate range of values require some adaptation to incorporate the cost trade-offs relating to different outcomes but, given complete reporting at the primary research, could be applied to the results of a meta-analysis. Conclusion: The 2 x 2 diagnostic framework frequently fails to capture many of the realities and complexities of clinical research questions. Standardised methods that facilitate complete reporting of test accuracy in primary diagnostic accuracy studies are required to allow for greater flexibility when producing threshold recommendations further down the evidence pathway.