Bone Metastases from Intrahepatic Cholangiocarcinoma Confer Worse Prognosis
Bibliographic record
Abstract
Background: Metastatic intrahepatic cholangiocarcinoma still has a dismal prognosis. The aim of our study was to investigate the prognostic role of bone metastases in patients affected by intrahepatic cholangiocarcinoma. Methods: A total of 186 metastatic intrahepatic cholangiocarcinoma patients were retrospectively reviewed. Clinicopathologic and survival data were collected and reviewed, in particular overall survival, progression-free survival after first-line treatment and time from end of first-line therapy to cancer death. Results: Around 11% of intrahepatic cholangiocarcinoma patients developed bone metastases. This subgroup of patients showed no differences in progression-free survival to first-line chemotherapy but had a shorter median overall survival of 4 months compared to the group with liver involvement only (p = 0.03). If treated, the outcome for ECOG PS 2 patients with bone metastases was worse in comparison to patients with liver involvement only with poor performance status (p = 0.003). The presence of bone metastases, poor performance status and no subsequent second-line treatment was associated with a worse outcome in multivariate analysis. Conclusions: Patients with intrahepatic carcinoma and bone metastases with poor ECOG performance status might be treated with best supportive care and not active chemotherapy treatment, the decisions which have to be shared with patients.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".