Identification of Demographic and Clinical Characteristics, Differentially Expressed Genes, and Differentially Perturbed Pathways Associated with Chemotherapy-Induced Nausea
Bibliographic record
Abstract
Despite advancements in antiemetic prophylaxis, chemotherapy-induced nausea (CIN) continues to be a significant clinical problem. Between 30% to 60% of oncology patients experience CIN. While a number of demographic and clinical characteristics are established risk factors CIN, these phenotype risk factors do not explain all of the variance in the occurrence of CIN. The purposes of this dissertation research were to: perform a systematic review of the literature on the associations between single nucleotide polymorphisms (SNPs) in candidate genes and the occurrence of CIN; determine additional risk factors associated with the occurrence of CIN; and determine additional molecular mechanisms associated with the occurrence of CIN. Sixteen studies evaluated for associations between genomic markers and the occurrence and/or severity of chemotherapy-induced nausea and vomiting (CINV). Candidate genes in the major mechanistic pathways for CINV (i.e., serotonin receptor pathway, drug transport pathway and/or drug metabolism) were evaluated for associations with the occurrence and severity of CINV. In brief, none of the SNPs in these mechanistic pathways were associated with CIN occurrence. Demographic and clinical risk factors were evaluated for their associations with CIN occurrence. In addition, the impact of concurrent symptoms, stress associated with cancer and its treatment, as well as quality of life (QOL) outcomes on the occurrence of CIN were investigated in patients prior to their next dose of chemotherapy (CTX). Modifiable risk factors identified in this study include: having child-care responsibilities; poorer functional status; and higher levels of depression, sleep disturbance, evening fatigue, perceived stress, and intrusive thoughts and feelings. Patients who reported CIN experienced decrements in QOL outcomes.Because findings regarding associations between mechanistically-based candidate genes and CIN occurrence were inconclusive, a hypothesis-generating study was undertaken to uncover novel mechanisms associated with CIN occurrence. Findings from this dissertation research suggest that a number of differentially expressed genes and perturbed pathways in the gut-brain axis are associated with the occurrence of CIN. CTX-induced changes in the GBA that may contribute to the occurrence of CIN include: mucosal inflammation and disruption of the gut microbiome. This dissertation concludes with implications for clinical practice and directions for future research.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".