Feasibility and validity of The Health Improvement Network database of primary care electronic health records to identify and characterise patients with small cell lung cancer in the United Kingdom

BACKGROUND: Epidemiological research on small cell lung cancer (SCLC) is limited and based on cancer registry data. We evaluated the feasibility and validity of using primary care electronic health records (The Health Improvement Network [THIN]) in the UK to identify and characterise SCLC. METHODS: We searched THIN records of individuals aged 18–89 years between 2000 and 2014 for a first diagnostic code suggestive of lung cancer (group 1) or small cell cancer (SCC; group 2) and for text strings among free text comments to identify and characterise incident SCLC cases. We validated our case identification strategy by manual review of patient EHRs, including free text comments, for a random sample of 400 individuals initially detected with a diagnostic code (300 from group 1 and 100 from group 2). RESULTS: Twenty five thousand two hundred fourty one individuals had a code for lung cancer (n = 24,508 [97.1%]) or SCC (733 [2.9%]). Following free-text searches, there were 3530 incident SCLC cases (2956 from group 1; 574 from group 2) corresponding to an incidence rate of 1.01 per 10,000 person-years. In the validation exercise, SCLC confirmation rates were 99% (group 1) and 85% (group 2). Mean age at diagnosis among confirmed cases was 68.5 years; staging information was present in 63.5% of cases of whom 17.8% had limited disease and 82.2% had extensive disease. The majority (84.5%) had a recorded symptom suggestive of lung cancer; chest infection was the most common (18%) followed by cough (15.8%) and chest/abdominal/back pain (15.2%). The first year crude mortality rates was 9.9 per 100 person-months (95% confidence interval [CI] 9.5–10.4), was higher among men and those aged 80 years and above. A total of 144 (37.8%) confirmed cases had metastases recorded. Median survival among the whole study cohort was 7.37 months. CONCLUSIONS: Our SCLC case identification method appears to be valid and could potentially be adapted to identify other cancer types. However, complete characterisation of staging requires information from additional data sources including cancer registries. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-019-5305-1) contains supplementary material, which is available to authorized users.