An Aggressive Surgical Approach Leads to Improved Survival in Patients With Gallbladder Cancer
Bibliographic record
Abstract
OBJECTIVE: To determine if an aggressive surgical approach, with an increase in R0 resections, has resulted in improved survival for patients with gallbladder cancer. SUMMARY BACKGROUND DATA: Many physicians express a relatively nihilistic approach to the treatment of gallbladder cancer; consensus among surgeons regarding the indications for a radical surgical approach has not been reached. METHODS: A retrospective review of all patients with gallbladder cancer admitted during the past 12 years was conducted. Ninety-nine patients were identified. Cases treated during the 12-year period 1990 to 2002 were divided into 2 time-period (TP) cohorts, those treated in the first 6 years (TP1, N = 35) and those treated in the last 6 years (TP2, N = 64). RESULTS: Disease stratification by stage and other demographic features were similar in the 2 time periods. An operation with curative intent was performed on 38 patients. Nine (26%) R0 resections were performed in TP1 and 24 (38%) in TP2. The number of liver resections, as well as the frequency of extrahepatic biliary resections, was greater in TP2 (P < 0.04). In both time periods, an R0 resection was associated with improved survival (P < 0.02 TP1, P < 0.0001 TP2). Overall survival of all patients in TP2 was significantly greater than in TP1 (P < 0.03), with a median survival of 9 months in TP1 and 17 months in TP2. The median 5-year survival in TP1 was 7%, and 35% in TP2. The surgical mortality rate for the entire cohort was 2%, with a 49% morbidity rate. CONCLUSIONS: A margin-negative, R0 resection leads to improved survival in patients with gallbladder cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".