Gastrointestinal Adverse Effects of Immunotherapeutic Agents: A Systematic Review
Bibliographic record
Abstract
The utilization of immunotherapy is increasing to the point of becoming the fifth pillar of management alongside surgical intervention, chemotherapy, radiotherapy and targeted therapy. However, gastrointestinal adverse effects and toxicities have been frequently cited with its use. As per literature, the most common adverse effect of immune checkpoint inhibitors is watery and non-bloody diarrhea. Adoptive cell therapy can lead to delayed, on-target but off-tumor adverse effects which are unknown and may be life-threatening. The use of anti-angiogenic monoclonal antibodies can lead to bowel perforations, whereas epidermal growth factor receptor inhibitors and anti-HER2 agents are frequently associated with diarrhea. Minimal adverse effects have been associated with therapeutic cancer vaccines; however, additional studies are needed to determine their efficacy and potential toxicities. To provide an in-depth review of the gastrointestinal side effects of immunotherapeutic agents, we performed a thorough literature search using multiple online search engines such as PubMed, Google Scholar and Ovid MEDLINE, along with a review of the guidelines from the United States Food and Drug Administration (FDA) and the Cancer Research Institute on immunotherapy. In this systematic review, we detail the gastrointestinal adverse effects of immunotherapy and describe their management. With the advent of newer immunotherapeutic agents and the consistent approval of current agents by FDA for a wide spectrum of cancers, it is vital for physicians to familiarize themselves with their adverse effects for prompt diagnosis and early intervention to decrease adverse outcomes.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".