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Co-Occurrence Patterns and Prognostic Implications of Immune-Related Adverse Events From Immune Checkpoint Inhibitors
abstract
This abstract is available on the publisher's site.
Access this abstract now Full Text Available for ClinicalKey SubscribersBACKGROUND
Understanding co-occurrence patterns and prognostic implications of immune-related adverse events is crucial for immunotherapy management. However, previous studies have been limited by sample size and generalisability. In this study, we leveraged a multi-institutional cohort and a population-level database to investigate co-occurrence patterns of and survival outcomes after multi-organ immune-related adverse events among recipients of immune checkpoint inhibitors.
METHODS
In this retrospective study, we identified individuals who received immune checkpoint inhibitors between May 31, 2015, and June 29, 2022, from the Massachusetts General Hospital, Brigham and Women's Hospital, and Dana-Farber Cancer Institute (Boston, MA, USA; MGBD cohort), and between April 30, 2010, and Oct 11, 2021, from the independent US population-based TriNetX network. We identified recipients from all datasets using medication codes and names of seven common immune checkpoint inhibitors, and patients were excluded from our analysis if they had incomplete information (eg, diagnosis and medication records) or if they initiated immune checkpoint inhibitor therapy after Oct 11, 2021. Eligible patients from the MGBD cohort were then propensity score matched with recipients of immune checkpoint inhibitors from the TriNetX database (1:2) based on demographic, cancer, and immune checkpoint inhibitor characteristics to facilitate cohort comparability. We applied immune-related adverse event identification rules to identify patients who did and did not have immune-related adverse events in the matched cohorts. To reduce the likelihood of false positives, patients diagnosed with suspected immune-related adverse events within 3 months after chemotherapy were excluded. We performed pairwise correlation analyses, non-negative matrix factorisation, and hierarchical clustering to identify co-occurrence patterns in the MGBD cohort. We conducted landmark overall survival analyses for patient clusters based on predominant immune-related adverse event factors and calculated accompanying hazard ratios (HRs) and 95% CIs, focusing on the 6-month landmark time for primary analyses. We validated our findings using the TriNetX cohort.
FINDINGS
We identified 15 246 recipients of immune checkpoint inhibitors from MGBD and 50 503 from TriNetX, of whom 13 086 from MGBD and 26 172 from TriNetX were included in our propensity score-matched cohort. Median follow-up durations were 317 days (IQR 113-712) in patients from MGBD and 249 days (91-616) in patients from TriNetX. After applying immune-related adverse event identification rules, 8704 recipients of immune checkpoint inhibitors were retained from MGBD, of whom 3284 (37·7%) had and 5420 (62·3%) did not have immune-related adverse events, and 18 162 recipients were retained from TriNetX, of whom 5538 (30·5%) had and 12 624 (69·5%) did not have immune-related adverse events. In both cohorts, positive pairwise correlations of immune-related adverse events were commonly observed. Co-occurring immune-related adverse events were decomposed into seven factors across organs, revealing seven distinct patient clusters (endocrine, cutaneous, respiratory, gastrointestinal, hepatic, musculoskeletal, and neurological). In the MGBD cohort, the patient clusters that predominantly had endocrine (HR 0·53 [95% CI 0·40-0·70], p<0·0001) and cutaneous (0·61 [0·46-0·81], p=0·0007) immune-related adverse events had favourable overall survival outcomes at the 6-month landmark timepoint, while the other clusters either had unfavourable (respiratory: 1·60 [1·25-2·03], p=0·0001) or neutral survival outcomes (gastrointestinal: 0·86 [0·67-1·10], p=0·23; musculoskeletal: 0·97 [0·78-1·21], p=0·78; hepatic: 1·20 [0·91-1·59], p=0·19; and neurological: 1·30 [0·97-1·74], p=0·074). Similar results were found in the TriNetX cohort (endocrine: HR 0·75 [95% CI 0·60-0·93], p=0·0078; cutaneous: 0·62 [0·48-0·82], p=0·0007; respiratory: 1·21 [1·00-1·46], p=0·044), except for the neurological cluster having unfavourable (rather than neutral) survival outcomes (1·30 [1·06-1·59], p=0·013).
INTERPRETATION
Reliably identifying the immune-related adverse event cluster to which a patient belongs can provide valuable clinical information for prognosticating outcomes of immunotherapy. These insights can be leveraged to counsel patients on the clinical impact of their individual constellation of immune-related adverse events and ultimately develop more personalised surveillance and mitigation strategies.
FUNDING
US National Institutes of Health.
Additional Info
Disclosure statements are available on the authors' profiles:
Multi-organ immune-related adverse events from immune checkpoint inhibitors and their downstream implications: a retrospective multicohort study
Lancet Oncol 2024 Jul 15;[EPub Ahead of Print], G Wan, W Chen, S Khattab, K Roster, N Nguyen, B Yan, A Rajeh, J Seo, H Rashdan, L Zubiri, MJ Hadfield, S Demehri, KH Yu, W Lotter, A Gusev, NR LeBoeuf, KL Reynolds, SG Kwatra, YR SemenovFrom MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.
Using two large US cohorts of patients treated with immune checkpoint inhibitors (ICIs) in the metastatic setting in several cancer types between 2015 and 2022, Wan and colleagues analyzed the co-occurrence patterns of immune-related adverse events (irAEs) and their impact on survival. The vast majority of patients received single-agent PD-1/PD-L1 immunotherapy, with only approximately 1% treated with an anti–CTLA-4 monoclonal antibody and approximately 10% with doublet immunotherapy. The study demonstrated that one-third of the patients had an irAE, the majority being grade 2, which is consistent with the established anti–PD-1 therapy toxicity profile. Patterns of toxicity were grouped in seven organ-based clusters. Endocrine and cutaneous clusters were the most frequent in both cohorts and were associated with better survival. On the contrary, the respiratory and neurological clusters were associated with a poorer outcome. In addition, the respiratory cluster was the most complex and associated with several multi-organ toxicities. The better outcomes in the endocrine and cutaneous clusters suggest that the less frequent use of systemic immunosuppressive therapy in these patients could be an explanation. However, further analyses showed that the use of glucocorticoids for toxicity management did not impact the outcomes.
Despite its retrospective nature, this large study elegantly portrayed the landscape of irAEs and their co-occurrence patterns. Nonetheless, it essentially includes patients with advanced cancer treated with anti–PD-1/PD-L1 immunotherapy. Although not used in many tumor types, the combination of anti–CTLA-4 and anti–PD-1 agents presents a higher rate and grade of toxicity, and the co-occurrence patterns of irAEs in this setting are an important piece of information. Moreover, new immunotherapies are emerging (new ICIs, bispecific antibodies, cancer vaccines, and adoptive cell therapy), used alone or in combinations, which potentially may increase the rate of multiple irAEs and combined toxicities. Future studies need to address these new therapies in other patient populations.
Inherent to the nature of the study, translational biological data were not included in this analysis. These might indeed help define some potential predictive biomarkers of the co-occurrence patterns of irAEs.
Overall, this large effort should be saluted, as it brings important information to help stratify patient risk. In addition, this research sets the basis for prospective studies analyzing irAEs and their patterns of co-occurrence in a broader population, including new immunotherapies, and defining the needed predictive biomarkers of toxicity.