Background: Measures that reflect patients’ assessment of their health are of increasing importance as outcome measures in randomised controlled trials. The methodological approach used in the pre-validation development of new instruments (item generation, item reduction and question formatting) should be robust and transparent. The totality of the content of existing PRO instruments for a specific condition provides a valuable resource (pool of items) that can be utilised to develop new instruments. Such ‘top down’ approaches are common, but the explicit pre-validation methods are often poorly reported. This paper presents a systematic and generalisable 5-step prevalidation PRO instrument methodology. Methods: The method is illustrated using the example of the Aberdeen Glaucoma Questionnaire (AGQ). The five steps are: 1) Generation of a pool of items; 2) Item de-duplication (three phases); 3) Item reduction (two phases); 4) Assessment of the remaining items’ content coverage against a pre-existing theoretical framework appropriate to the objectives of the instrument and the target population (e.g. ICF); and 5) qualitative exploration of the target populations’ views of the new instrument and the items it contains. Results: The AGQ ‘item pool’ contained 725 items. Three de-duplication phases resulted in reduction of 91, 225 and 48 items respectively. The item reduction phases discarded 70 items and 208 items respectively. The draft AGQ contained 83 items with good content coverage. The qualitative exploration (’think aloud’ study) resulted in removal of a further 15 items and refinement to the wording of others. The resultant draft AGQ contained 68 items. Conclusions: This study presents a novel methodology for developing a PRO instrument, based on three sources: literature reporting what is important to patient; theoretically coherent framework; and patients’ experience of completing the instrument. By systematically accounting for all items dropped after the item generation phase, our method ensures that the AGQ is developed in a transparent, replicable manner and is fit for validation. We recommend this method to enhance the likelihood that new PRO instruments will be appropriate to the research context in which they are used, acceptable to research participants and likely to generate valid data.