The relationship between immune-related adverse events during ipilimumab monotherapy and survival outcomes among melanoma patients: A systematic review
Bibliographic record
Abstract
BackgroundIpilimumab disinhibits immune system activity which results in the elimination of malignant cells. An unintended consequence of ipilimumab therapy is off-target immune-related adverse events (irAEs). It has therefore been proposed that the incidence of irAEs is a manifestation of treatment effectiveness. The objective of this systematic review is to examine the relationship between irAEs and survivability among melanoma patients administered ipilimumab monotherapy.MethodsA comprehensive search was conducted across several databases which yielded a total of 2381 studies. Clinical trials and prospective studies administering ipilimumab monotherapy to melanoma patients were included. Furthermore, there was no restriction placed on publication date. After screening, five studies were included for data extraction. The primary outcome of median overall survival (OS) and the secondary outcome of OS hazard ratio were extracted from the included studies.ResultsBased on qualitative analysis of the included studies, there seemed to be an association between the occurrence of non-lethal irAEs and improved survival outcomes among melanoma patients administered ipilimumab monotherapy. With that being said, the poorer survivability among patients who experienced high-grade irAEs may be the result of subsequent treatment discontinuation. Potential confounders such as corticosteroid use should be accounted for. Finally, landmark analyses may be conducted to account for immortal time bias.ConclusionsThe findings from this systematic review provide evidence suggesting that the incidence of irAEs is a marker of an improved anti-tumor response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".