Background: Use of tumor necrosis factor inhibitors (TNFi) in patients with a history of cancer remains a clinical dilemma.Objective: To investigate whether TNFi treatment in rheumatoid arthritis (RA) is associated with increased risk for cancer recurrence.Design: Population-based cohort study based on linkage of nationwide registers.Setting: Sweden.Participants: Patients with RA who started TNFi treatment between 2001 and 2015, after being diagnosed with cancer, and matched patients with RA and a history of the same cancer who had never received biologics.Measurements: The primary outcome was the first recurrence of cancer. Adjusted Cox proportional hazards models were used to estimate hazard ratios (HRs), taking into account time, cancer type, and whether the cancer was invasive or in situ (or tumor, node, metastasis [TNM] classification system stage in a subset of patients).Results: Among 467 patients who started TNFi treatment (mean time after cancer diagnosis, 7.9 years), 42 had cancer recurrences (9.0%; mean follow-up, 5.3 years); among 2164 matched patients with the same cancer history, 155 had recurrences (7.2%; mean follow-up, 4.3 years) (HR, 1.06 [95% CI, 0.73 to 1.54). Hazard ratios were close to 1 in analyses of patient subsets matched on cancer stage or with similar time from index cancer diagnosis to the start of TNFi treatment, as well as in unmatched analyses. Several CIs had upper limits close to 2.Limitation: The outcome algorithm was partly nonvalidated, and channeling bias was possible if patients with a better index cancer prognosis were more likely to receive TNFi.Conclusion: The findings suggest that TNFi treatment is not associated with increased risk for cancer recurrence in patients with RA, although meaningful risk increases could not be ruled out completely.Primary Funding Source: ALF (an agreement in Stockholm County Council concerning medical education and research in health and medical care), the Swedish Cancer Society, the Swedish Foundation for Strategic Research, and the Swedish Research Council.
Aged Algorithms