Effects of serotonergic drugs on immune checkpoint inhibitor response: a pooled analysis of individual patient data from four Canadian Cancer Trials Group (CCTG) trials
Bibliographic record
Abstract
Immune checkpoint inhibitors (ICIs) are used to treat various cancers. Serotonin receptors are expressed by immune cells. In preclinical models, serotonergic drugs affect T-cell cytokine production, proliferation and apoptosis. Interactions between clinical serotonergic drug use and dual ICI treatment remain unknown. Individual patient data were pooled from 4 Canadian Cancer Trials Group (CCTG) trials of patients treated with dual ICI ± chemotherapy (n = 684). Serotonergic drug use was correlated with clinicopathologic characteristics, best overall response (BOR)/iBOR per RECIST 1.1/iRECIST, progression-free survival (PFS)/iPFS, overall survival (OS) and immune-related adverse events (irAEs) using Cochran – Mantel – Haenszel and log-rank tests. Eighty-three (12%) patients used serotonergic drugs at baseline and 118 (17%) at any time on trial. By multivariate analysis, serotonergic drug use at baseline was significantly associated with decreased iBOR (p = 0.04), but not PFS (p = 0.21), iPFS (p = 0.28), OS (p = 0.30) or incidence of grade 1/2 or 3/4 irAE (p = 0.85 and 0.99 respectively). Results were not significantly different with serotonergic drug use at any time on trial. Use of serotonergic drugs did not impact PFS or OS in patients treated with dual ICI ± chemotherapy. This study supports the safe use of serotonergic drugs in the context of dual ICI therapy. Immune checkpoint inhibitors (ICIs) are a type of therapy that harnesses a patient’s own immune system to treat various cancers. Serotonin is a hormone that helps regulate mood, sleep, appetite and other cognitive functions. Serotonin receptors are expressed by immune cells. Drugs that affect serotonin levels may play a role in regulating immune cell function. It is not clear whether drugs that affect serotonin levels affect how well ICIs work. This study looked at clinical trial data from four Canadian Cancer Trials Group (CCTG) trials of patients treated with ICI ± chemotherapy (n=684) and aimed to correlate serotonergic drug use with patient and disease characteristics, response to treatment, and progression-free and overall survival, and ICI-related side effects. This study found that the use of drugs that affect serotonin levels did not significantly affect progression-free or overall survival of patients being treated with ICI±chemotherapy. Therefore, this study supports the safe use of serotonergic drugs in the context of dual ICI therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".