Systematic review of health-related quality of life (HRQoL) issues associated with gastric cancer: capturing cross-cultural differences
Bibliographic record
Abstract
The treatment landscape for gastric cancer (GC) is constantly evolving with therapies affecting all aspects of health-related quality of life (HRQoL) which need careful monitoring. While there are HRQoL measures designed specifically to capture issues relevant to patients with GC, these might be outdated and only relevant to patients in westernised cultures. This review identifies the patient-reported measures used to assess HRQoL of patients with GC and compares the HRQoL measures used across cultures including East Asia, where GC is more prevalent. We conducted a systematic review of publications between January 2001 and January 2021. A total of 267 papers were identified; the majority (66%) of studies involved patients from East Asian countries. Out of the 24 HRQoL questionnaires captured, the European Organisation for Research and Treatment of Cancer Core Cancer measure (QLQ-C30) was the most widely used (60% of all studies and 62% of those involving patients from East Asian countries), followed by its gastric cancer-specific module (QLQ-STO22, 34% of all studies and 41% from East Asia). Eight questionnaires were developed within East Asian countries and, of the 20 studies including bespoke questions, 16 were from East Asia. There were six qualitative studies. HRQoL issues captured include diarrhoea, constipation, reflux, abdominal pain and abdominal fulness or bloating, difficulty swallowing, restricted eating, and weight loss. Psychosocial issues related to these problems were also assessed. Issues relating to the compatibility of some of the westernised measures within East Asian cultures were highlighted.
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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 | 0.015 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".