Pyoderma Gangrenosum: A Retrospective Cohort Study of Comorbidities and Therapies in Over 65,000 Patients in the TriNetX Database

Background: Pyoderma gangrenosum (PG) is a rare neutrophilic dermatosis associated with systemic inflammatory diseases and malignancy. Although biologic therapies demonstrate efficacy in PG, the extent of their real-world use remains incompletely characterized. Additionally, the temporal relationship between PG and associated comorbidities remains poorly defined. Objectives: To examine the temporal relationship between PG diagnosis and associated comorbidities and to describe treatment sequencing and duration of therapies in a large retrospective cohort of PG cases. Methods: A retrospective analysis of the TriNetX electronic health record network was performed. Cases of PG were identified using ICD-10 codes up to July 30, 2025. Comorbidities diagnosed within 10 years before and after PG diagnosis were analyzed using McNemar's test with odds ratios. Treatment duration and switching between therapies were assessed using survival analysis with log-rank testing. Results: A total of 65,501 PG cases were identified. Malignancies were more frequently recorded prior to PG diagnosis, while inflammatory conditions including hidradenitis suppurativa, inflammatory bowel disease and inflammatory arthropathies were more frequently recorded following diagnosis. Antibiotics and corticosteroids were the most commonly recorded first-line therapies, while only 2.2% of cases were recorded as receiving immunomodulatory therapies initially. The longest median duration of therapy was observed with infliximab (median 185 days), followed by methotrexate (125 days). Conclusions: Comorbidity patterns differed before and after PG diagnosis in this large retrospective database analysis. Inflammatory comorbidities were more frequently recorded following PG diagnosis. The uptake of immunomodulatory therapy was low during the study period. These findings should be interpreted cautiously, given the limitations of retrospective database studies and potential diagnostic misclassification, and are best considered hypothesis-generating.