OBJECTIVE: To identify predictors of rheumatic immune-related adverse events (irAEs) following immune checkpoint inhibitor (ICI) treatment for cancer. METHODS: We performed a case-control study to predict the occurrence of rheumatic irAEs in cancer patients who initiated ICI treatment at Mass General Brigham and the Dana-Farber Cancer Institute between 2011 and 2020. We screened for the presence of rheumatic irAEs by reviewing the medical records of patients evaluated by rheumatologists or those prescribed nonglucocorticoid immunomodulatory drugs after the time of ICI initiation (baseline). Review of medical records confirmed the presence of rheumatic irAEs and the indications necessitating immunomodulatory drug treatment. Controls were defined as patients who did not experience rheumatic irAEs, did not have preexisting rheumatic disease, did not have a clinical evaluation by a rheumatologist after ICI treatment, did not receive an immunomodulatory drug after ICI, did not receive systemic glucocorticoids after ICI, and survived at least 6 months after the initial ICI treatment. We used logistic regression to estimate the odds ratios (ORs) (with 95% confidence intervals [95% CIs]) for the risk of a rheumatic irAE in the presence of various baseline predictors. RESULTS: A total of 8,028 ICI recipients were identified (mean age 65.5 years, 43.1% female, 31.8% with lung cancer). After ICI initiation, 404 patients (5.0%) were evaluated by rheumatologists, and 475 patients (5.9%) received an immunomodulatory drug to treat any irAEs. There were 226 confirmed rheumatic irAE cases (2.8%) and 118 de novo inflammatory arthritis cases (1.5%). Rheumatic diseases (either preexisting rheumatic diseases or rheumatic irAEs) were a common indication for immunomodulatory drug use (27.9%). Baseline predictors of rheumatic irAEs included melanoma (multivariable OR 4.06 [95% CI 2.54-6.51]) and genitourinary (GU) cancer (OR 2.22 [95% CI 1.39-3.54]), both relative to patients with lung cancer; combination ICI treatment (OR 2.35 [95% CI 1.48-3.74]), relative to patients receiving programmed death 1 inhibitor monotherapy; autoimmune disease (OR 2.04 [95% CI 1.45-2.85]) and recent glucocorticoid use (OR 2.13 [95% CI 1.51-2.98]), relative to patients not receiving a glucocorticoid, compared to the 2,312 controls without rheumatic irAEs. Predictors of de novo inflammatory arthritis were similar to those of rheumatic irAEs. CONCLUSION: We identified novel predictors of rheumatic irAE development in cancer patients, including baseline presence of melanoma, baseline presence of GU tract cancer, preexisting autoimmune disease, receiving or having received combination ICI treatment, and receiving or having received glucocorticoids. The proportion of cancer patients experiencing rheumatic irAEs may be even higher than was reported in the present study, since we used stringent criteria to identify cases of rheumatic irAEs. Our findings could be used to identify cancer patients at risk of developing rheumatic irAEs and de novo inflammatory arthritis and may help further elucidate the pathogenesis of rheumatic irAEs in patients with cancer who are receiving ICI treatment.
OBJECTIVE: To identify predictors of rheumatic immune-related adverse events (irAEs) following immune checkpoint inhibitor (ICI) treatment for cancer. METHODS: We performed a case-control study to predict the occurrence of rheumatic irAEs in cancer patients who initiated ICI treatment at Mass General Brigham and the Dana-Farber Cancer Institute between 2011 and 2020. We screened for the presence of rheumatic irAEs by reviewing the medical records of patients evaluated by rheumatologists or those prescribed nonglucocorticoid immunomodulatory drugs after the time of ICI initiation (baseline). Review of medical records confirmed the presence of rheumatic irAEs and the indications necessitating immunomodulatory drug treatment. Controls were defined as patients who did not experience rheumatic irAEs, did not have preexisting rheumatic disease, did not have a clinical evaluation by a rheumatologist after ICI treatment, did not receive an immunomodulatory drug after ICI, did not receive systemic glucocorticoids after ICI, and survived at least 6 months after the initial ICI treatment. We used logistic regression to estimate the odds ratios (ORs) (with 95% confidence intervals [95% CIs]) for the risk of a rheumatic irAE in the presence of various baseline predictors. RESULTS: A total of 8,028 ICI recipients were identified (mean age 65.5 years, 43.1% female, 31.8% with lung cancer). After ICI initiation, 404 patients (5.0%) were evaluated by rheumatologists, and 475 patients (5.9%) received an immunomodulatory drug to treat any irAEs. There were 226 confirmed rheumatic irAE cases (2.8%) and 118 de novo inflammatory arthritis cases (1.5%). Rheumatic diseases (either preexisting rheumatic diseases or rheumatic irAEs) were a common indication for immunomodulatory drug use (27.9%). Baseline predictors of rheumatic irAEs included melanoma (multivariable OR 4.06 [95% CI 2.54-6.51]) and genitourinary (GU) cancer (OR 2.22 [95% CI 1.39-3.54]), both relative to patients with lung cancer; combination ICI treatment (OR 2.35 [95% CI 1.48-3.74]), relative to patients receiving programmed death 1 inhibitor monotherapy; autoimmune disease (OR 2.04 [95% CI 1.45-2.85]) and recent glucocorticoid use (OR 2.13 [95% CI 1.51-2.98]), relative to patients not receiving a glucocorticoid, compared to the 2,312 controls without rheumatic irAEs. Predictors of de novo inflammatory arthritis were similar to those of rheumatic irAEs. CONCLUSION: We identified novel predictors of rheumatic irAE development in cancer patients, including baseline presence of melanoma, baseline presence of GU tract cancer, preexisting autoimmune disease, receiving or having received combination ICI treatment, and receiving or having received glucocorticoids. The proportion of cancer patients experiencing rheumatic irAEs may be even higher than was reported in the present study, since we used stringent criteria to identify cases of rheumatic irAEs. Our findings could be used to identify cancer patients at risk of developing rheumatic irAEs and de novo inflammatory arthritis and may help further elucidate the pathogenesis of rheumatic irAEs in patients with cancer who are receiving ICI treatment.
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