Validity of ankylosing spondylitis diagnoses in The Health Improvement Network

Background/PurposeBecause ankylosing spondylitis (AS) is uncommon, large medical record databases offer important opportunities for pharmacoepidemiologic research. However, the validity of AS diagnoses recorded by a general practitioner (GP) is unknown. We assessed the validity of algorithms for identifying AS in The Health Improvement Network (THIN). MethodsTHIN is a database of GP records for over 10 million persons in the UK. In 2014, we administered a questionnaire to GPs of 100 adults for whom an AS diagnosis had been recorded. As high positive predictive value (PPV) is critically important in AS research, we sought to determine the PPV of an AS diagnostic code relative to the GP's clinical impression as the gold standard. Other AS algorithms included: more than one AS diagnostic code, prescription of a nonsteroidal anti-inflammatory drug (NSAID), disease modifying anti-rheumatic drug (DMARD) or biologic. ResultsIn 61 of 85 returned questionnaires, the GP's clinical impression confirmed AS yielding an overall PPV of 72%. PPV was 89% for two AS codes >7days apart, and was 86% for an AS code plus a DMARD/biologic. Sensitivity was reduced with algorithms requiring two AS codes (64%) and a DMARD/biologic prescription (30%). Algorithms requiring prescription of an NSAID, or the absence of OA or RA had lower PPV (71-75%) and higher sensitivity (95-98%). ConclusionAn AS identification algorithm of two AS diagnoses separated by >7days provided the highest PPV. This algorithm should be used for pharmacoepidemiologic studies in THIN. Copyright (c) 2016 John Wiley & Sons, Ltd.