Advances in diagnosis, treatment and palliation of cholangiocarcinoma: 1990-2009
Bibliographic record
Abstract
Several advances in diagnosis, treatment and palliation of cholangiocarcinoma (CC) have occurred in the last decades. A multidisciplinary approach to this disease is therefore recommended. CC is a relatively rare tumor and the main risk factors are: chronic inflammation, genetic predisposition and congenital abnormalities of the biliary tree. While the incidence of intra-hepatic CC is increasing, the incidence of extra-hepatic CC is trending down. The only curative treatment for CC is surgical resection with negative margins. Liver transplantation has been proposed only for selected patients with hilar CC that cannot be resected who have no metastatic disease after a period of neoadjuvant chemo-radiation therapy. Magnetic resonance imaging/magnetic resonance cholangiopancreatography, positron emission tomography scan, endoscopic ultrasound and computed tomography scans are the most frequently used modalities for diagnosis and tumor staging. Adjuvant therapy, palliative chemotherapy and radiotherapy have been relatively ineffective for inoperable CC. For most of these patients biliary stenting provides effective palliation. Photodynamic therapy is an emerging palliative treatment that seems to provide pain relief, improve biliary patency and increase survival. The clinical utility of other emerging therapies such as transarterial chemoembolization, hepatic arterial chemoinfusion and high intensity intraductal ultrasound needs further study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".