Global patterns of hepatocellular carcinoma management from diagnosis to death: the <scp>BRIDGE</scp> Study
Bibliographic record
Abstract
BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) is the second most common cause of cancer deaths worldwide. The global HCC BRIDGE study was a multiregional, large-scale, longitudinal cohort study undertaken to improve understanding of real-life management of patients with HCC, from diagnosis to death. METHODS: Data were collected retrospectively from January 2005 to September 2012 by chart reviews of eligible patients newly diagnosed with HCC at participating institutions. RESULTS: Forty-two sites in 14 countries contributed final data for 18 031 patients. Asia accounted for 67% of patients, Europe for 20% and North America for 13%. As expected, the most common risk factor was hepatitis C virus in North America, Europe and Japan, and hepatitis B virus in China, South Korea and Taiwan. The most common Barcelona Clinic Liver Cancer stage at diagnosis was C in North America, Europe, China and South Korea, and A in Taiwan and Japan. Across all stages, first HCC treatment was most frequently transarterial chemoembolization in North America, Europe, China and South Korea, percutaneous ethanol injection or radiofrequency ablation in Japan and resection in Taiwan. Survival from first HCC treatment varied significantly by region, with median overall survival not reached for Taiwan and 60, 33, 31, 24 and 23 months for Japan, North America, South Korea, Europe and China respectively (P < 0.0001). CONCLUSIONS: Initial results from the BRIDGE study confirm previously reported regional trends in patient demographic characteristics and HCC risk factors, document the heterogeneity of treatment approaches across regions/countries and underscore the need for earlier HCC diagnosis worldwide.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".