To support clinical researchers, librarians and informationists may need search filters for particular tasks. Development of filters typically depends on a “gold standard” dataset. This paper describes generalizable methods for creating a gold standard to support future filter development and evaluation using oral squamous cell carcinoma (OSCC) as a case study. OSCC is the most common malignancy affecting the oral cavity. Investigation of biomarkers with potential prognostic utility is an active area of research in OSCC. The methods discussed here should be useful for designing quality search filters in similar domains.

The authors searched MEDLINE for prognostic studies of OSCC, developed annotation guidelines for screeners, ran three calibration trials before annotating the remaining body of citations, and measured inter-annotator agreement (IAA).

We retrieved 1,818 citations. After calibration, we screened the remaining citations (n = 1,767; 97.2%); IAA was substantial (kappa = 0.76). The dataset has 497 (27.3%) citations representing OSCC studies of potential prognostic biomarkers.

The gold standard dataset is likely to be high quality and useful for future development and evaluation of filters for OSCC studies of potential prognostic biomarkers.