Safety evaluation of afatinib in patients with a history of interstitial lung disease using data from an administrative claims database in Japan.

introductionAfatinib, an epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), is an effective treatment agent for lung cancer with uncommon epidermal growth factor receptor (EGFR) mutations. EGFR-TKIs should be administered with caution in patients with a history of interstitial lung disease (ILD); however, such patients are often excluded from clinical trials, and evidence on afatinib safety in this population remains limited.

aimTo exploratorily evaluate the safety profile of afatinib in patients with a history of ILD using an administrative claims database and investigate whether severe ILD events occur uniformly across patient backgrounds or cluster within specific patient profiles.

methodWe analyzed data of patients who received afatinib between May 1, 2014 and November 30, 2020 from the administrative claims database provided by Medical Data Vision Co., Ltd. Severe ILD was defined using two claims-based operational definitions: (1) a broader primary definition combining ILD diagnostic codes and high-dose intravenous corticosteroid administration; (2) a stricter definition requiring intravenous methylprednisolone for sensitivity analysis. Classification and Regression Trees (CART) were used to exploratorily identify patient profiles associated with severe ILD.

resultsAmong 2,174 patients treated with afatinib, 12.3% (267/2,174) had a history of ILD. Using the primary definition, severe ILD occurred in 6.0% (16/267) of these patients, whereas 3.4% (9/267) met the stricter definition. Although CART analyses yielded different split variables and cutoff values across the two definitions, both consistently indicated that severe ILD events were concentrated within specific patient profiles rather than being uniformly distributed across the population.

conclusionIn patients with a history of ILD, the incidence of severe ILD following afatinib treatment was clarified. CART-derived findings should be interpreted as exploratory signals suggesting clustering of severe ILD events within particular patient profiles. However, as severe ILD was identified using claims-based operational definitions, outcome misclassification cannot be excluded despite sensitivity analyses. Further studies are warranted to validate these findings in independent real-world datasets with richer clinical detail and to support more precise stratification of severe ILD occurrence.