The impact of primary sclerosing cholangitis or inflammatory bowel disease on cholangiocarcinoma phenotype, therapy, and survival
Bibliographic record
Abstract
Abstract Background and Aim Primary sclerosing cholangitis (PSC), with or without inflammatory bowel disease (IBD), confers the risk of cholangiocarcinoma. Isolated IBD may be an independent risk factor for cholangiocarcinoma. We sought to compare cholangiocarcinoma phenotype and outcomes between patients with PSC, IBD, and neither. Methods Patients with malignancy were separated into cohorts by the presence of PSC and IBD. Data regarding demographics, clinical presentation, therapeutic regimens, and survival were collected. Statistical analysis was carried out using GraphPad and R‐Studio. Results Of 946 patients, 22 had PSC, and 18 had isolated IBD. PSC and IBD patients were younger than controls ( P < 0.001, P = 0.01). Cholangiocarcinoma prevalence was estimated at 0.01% for IBD patients, 0.6% for PSC patients, and 0.002% for all other patients. All cohorts most often presented at stage 4. PSC patients presented more often at stage 3 ( P = 0.04) and with perihilar disease ( P = 0.001). Patients with PSC or IBD received less chemotherapy ( P = 0.004, 0.01). Median overall survivals were 15 months (PSC), 11 months (IBD), and 10 months (controls) ( P = 0.79). Patients with intrahepatic tumors had longer survival ( P < 0.001). Curative intent resection improved survival in all cohorts ( P < 0.001). Multivariate regression identified resection as a predictor of improved survival. Extrahepatic, perihilar, gallbladder, and unspecified biliary tumors were predictors of death. Conclusions Cholangiocarcinoma presents at a late stage and portends dismal survival regardless of PSC or IBD status. Survival was dependent on tumor location and surgical resection. These data suggest that efforts should focus on developing protocols that are able to detect and treat cholangiocarcinoma in high‐risk populations (PSC) at an early stage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".