Targeted literature review of the global burden of gastric cancer
Bibliographic record
Abstract
Gastric cancer (GC) and gastroesophageal junction cancers (GEJCs) are the third leading cause of cancer-related death worldwide. Although several studies have evaluated the epidemiology and management of GC and GEJC, to our knowledge, no global estimates of the economic burden of GC and GEJC have yet been reported. This targeted literature review was conducted to summarise the epidemiology and management of GC and GEJC and to estimate its global economic and humanistic burden. The incidence of GC and GEJC is highest in Eastern Asia, several South and Central American countries and Central and Eastern Europe and lowest in North America and Africa. Prognosis is generally poor; the global 5-year survival rate is 5%-10% in advanced stages. Patients with GC and GEJC have more severe symptoms compared with patients with other cancers, and health-related quality of life (HRQoL) worsens as the disease progresses. Given the rapid progression of GC and GEJC at advanced stages, chemotherapy, despite its toxicity, improves HRQoL compared with best supportive care. The costs of GC/GEJC are generally higher than for other cancers; in the US, the average annual cost per patient between 1998 and 2003 was 46,501 USD, compared with 29,609 USD and 35,672 USD for colorectal and lung cancer, respectively. Based on the 2012 incidence data and average costs per patient, estimates of the annual financial burden of GC and GEJC revealed great regional differences. Japan and Iran had the highest (8,492 million USD) and lowest (27 million USD) costs for 2017, respectively, while the estimate for the US was 3,171 million USD. The overall annual cost of GC and GEJC estimated for 2017 in a geographic area including Europe (France, Germany, Italy, Spain and the UK), Asia (Iran, Japan and China), North America (Canada and the US) and Australia was 20.6 billion USD.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".