Gender differences in symptoms experienced by advanced cancer patients: a literature review
Bibliographic record
Abstract
INTRODUCTION: Advanced cancer patients are multi-symptomatic and require attentive palliative care. As gender differences are apparent in multiple aspect of everyday life, this literature review aims to determine the gender differences seen in the population of advanced cancer patients and the symptoms that they experience. METHODS: A literature review was conducted using the OvidSP Medline database from 1946 to November 2012. Randomized, prospective or retrospective cohort studies on advanced cancer patients who were undergoing any type of palliative treatments (palliative radiation, chemotherapy) or those in which palliative treatments have failed (antalgic treatment) were included. The patient population, tools/questionnaire used and gender differences in symptoms found statistically or qualitatively significant in the respective studies were extracted. RESULTS: Of the 163 studies resulting from the literature search, nineteen publications were identified. Gender differences in multiple symptoms were discovered. Gender differences were commonly found in symptoms of emotional changes, fatigue, gastrointestinal symptoms (nausea, vomiting, and diarrhea) anxiety, tension, sleep problems and pain. CONCLUSION: At present, gender differences seen in the symptoms experienced by advanced cancer patients continues to be inconclusive. Further study investigating gender differences in the symptoms experienced by advanced cancer patients as the primary endpoint is recommended.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| 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) | 0.003 | 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".