Prevalence of immune-related adverse events (irAEs) and association with symptom distress score by Edmonton Symptom Assessment System (ESAS) in solid cancer patients receiving immune checkpoint inhibitor (ICI) therapy.
Bibliographic record
Abstract
e23191 Background: Immune-related adverse events (irAEs) after immunotherapy are unique and unpredictable, differing from chemotherapy or targeted therapy. The impact of irAEs during treatment on symptom distress and quality of life of the patients remains unclear. We hypothesized that irAEs affect the patient-report outcomes, as assessed by the Edmonton Symptom Assessment System (ESAS). This study aimed to evaluate the association between irAEs and ESAS. Methods: We conducted a retrospective study of patients diagnosed with solid cancer who received immune checkpoint inhibitor (ICI) therapy from December 2021-August 2024 at MedPark hospital, Thailand. Patients’ health status was routinely evaluated at each visit using ESAS. Baseline clinical characteristics and irAEs were collected. The ESAS score was calculated to a total symptom distress score (TSDS) based on the sum of the first nine physical and psychosocial symptoms. TSDS was collected before ICI treatment (baseline) and after ICI treatment at three time points (4, 8, and 12 weeks post-treatment). The outcome measures were the prevalence of irAEs and post-treatment TSDS compared to baseline TSDS in both irAEs and non-irAEs groups. Results: A total of 39 patients (24 women,15 men) were analyzed.The mean age was 59.1 years (range 33-88). Lung cancer was the most common diagnosis (28.2%) followed by breast cancer (17.9%). All grades of irAEs were evidenced in 48.7%, with a median time to irAEs onset of 8.8 weeks (interquartile range: 4.9-12.6 weeks). The most common irAEs was hypothyroid (20.5%). Grade ≥3 irAEs occurred in 7.7% of patients, including two cases of pneumonitis and one case of hepatitis. Baseline TSDS was 12.63 in the irAEs group and 11.9 in the non-irAEs group. Post-treatment TSDS showed slight improvement (decreased scores) compared to baseline in both groups, with a mean difference of -0.48 (SD,10.9; p = 0.788); -0.31 in irAEs group and -0.63 in non-irAEs group. Compared to baseline, the mean differences of post-treatment TSDS in the irAEs and non-irAEs groups were 1.07 vs 1.26, -2.29 vs -3.79, and -1.57 vs 0.84 at 4, 8 and 12weeks, respectively. Conclusions: irAEs were experienced by nearly half of the patients undergoing ICI therapy. The presence of irAEs did not significant change ESAS score during ICI treatment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".