Background Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of multiple cancers. However, these promising therapies may also cause immune-related adverse events (irAEs) in a substantial proportion of patients. These autoimmune phenomena may affect almost any organ system and may occur at almost any point in therapy. In some instances, these toxicities are life-threatening and potentially permanent. Diverse clinical presentation and unpredictable timing further complicate their anticipation and diagnosis. Content To improve patient safety and selection for ICI use, biomarkers for irAE diagnosis and prediction are under development. Clinicians may use traditional laboratory markers such as routine chemistries, creatinine clearance, thyroid function tests, and serum cortisol/adrenocorticotrophic hormone to monitor for specific irAEs, but noted aberrations may not necessarily represent an immune-mediated etiology. Novel biomarkers have the potential to be more specific to assist in the diagnosis of irAEs. The prediction of irAEs is more challenging. Apart from a history of autoimmune disease, no other clinical parameters are routinely used to project risk. Biomarker candidates under investigation for irAE diagnosis and prediction include blood cell analysis, chemokines/cytokines, autoantibodies, and genetic predisposition, such as human leukocyte antigen haplotype. Among other emerging candidates are immune-cell subsets, T-cell repertoire, fecal microbiome, tumor genomics, and radiomic characterization. Summary Several conventional laboratory indexes of end-organ dysfunction are currently in routine clinical use for irAE monitoring and diagnosis. Novel biomarkers for the prediction and diagnosis of these irAEs, which primarily characterize patient immune function, represent an area of active investigation.

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Immune-related adverse events (irAE) may affect almost any organ system and occur at any point during treatment with immune checkpoint inhibitors (ICI). We present a patient with advanced lung cancer receiving antiprogrammed death 1 checkpoint inhibitor who developed a delayed-onset visual irAE treated with corticosteroids. Through assessment of longitudinal biospecimens, we analyzed serial autoantibodies, cytokines, and cellular populations. Months after ICI initiation and preceding clinical toxicity, the patient developed broad increases in cytokines (most notably interleukin-6 (IL-6), interferon-γ (IFNγ), C-X-C motif chemokine ligand 2 (CXCL2), and C–C motif chemokine ligand 17 (CCL17)), autoantibodies (including anti-angiotensin receptor, α-actin, and amyloid), CD8 T cells, and plasmablasts. Such changes were not observed in healthy controls and ICI-treated patients without irAE. Administration of corticosteroids resulted in immediate and profound decreases in cytokines, autoantibodies, and inflammatory cells. This case highlights the potential for late-onset changes in humoral and cellular immunity in patients receiving ICI. It also demonstrates the biologic effects of corticosteroids on these parameters. Application of humoral and cellular immune biomarkers across ICI populations may inform toxicity monitoring and management.

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Background With the expansion of non–small cell lung cancer (NSCLC) screening methods, the percentage of cases with early‐stage NSCLC is anticipated to increase. Yet it remains unclear how the type and case volume of the health care facility at which treatment occurs may affect surgery selection and overall survival for cases with early‐stage NSCLC. Methods A total of 332,175 cases with the American Joint Committee on Cancer (AJCC) TNM stage I and stage II NSCLC who were reported to the National Cancer Data Base (NCDB) by 1302 facilities were studied. Facility type was characterized in the NCDB as community cancer program (CCP), comprehensive community cancer program (CCCP), academic/research program (ARP), or integrated network cancer program (INCP). Each facility type was dichotomized further into high‐volume or low‐volume groups based on the case volume. Multivariate Cox proportional hazard models, the logistic regression model, and propensity score matching were used to evaluate differences in survival and surgery selection among facilities according to type and volume. Results Cases from ARPs were found to have the longest survival (median, 16.4 months) and highest surgery rate (74.8%), whereas those from CCPs had the shortest survival (median, 9.7 months) and the lowest surgery rate (60.8%). The difference persisted when adjusted by potential confounders. For cases treated at CCPs, CCCPs, and ARPs, high‐volume facilities had better survival outcomes than low‐volume facilities. In facilities with better survival outcomes, surgery was performed for a greater percentage of cases compared with facilities with worse outcomes. Conclusions For cases with early‐stage NSCLC, both facility type and case volume influence surgery selection and clinical outcome. Higher surgery rates are observed in facilities with better survival outcomes.