Pemigatinib in the Real-World Management of Cholangiocarcinoma Through a Canadian Patient Support Program
Bibliographic record
Abstract
BACKGROUND: rearrangements/fusions. This retrospective study aimed to characterize the real-world management and outcomes of patients with CCA receiving pemigatinib through a Canadian patient support program (PSP). METHODS: We evaluated a multi-centre case series of Canadian patients who were prescribed pemigatinib between September 2021 and January 2023 for eligible CCA diagnoses and enrolled in the PSP. The retrospective study data included demographic and disease-, treatment-, and outcome-related information, and these were collected using a survey of prescribing physicians. RESULTS: Of the 26 patients who initiated pemigatinib in the PSP, we received survey responses for 18 (69%). Their median age was 57 years, 67% were female, 61% had stage IV disease, and 83% had intrahepatic CCA. Prior to pemigatinib, a partial hepatectomy was performed in 44% of the patients, and 66% of the patients received 2-4 prior lines of systemic therapy. All patients were treated with platinum-based regimens as the first-line treatment for unresectable/metastatic disease. The median follow-up time on pemigatinib was 12.6 (range: 2.3-28.4) months, and their median real-world progression-free survival (rwPFS) was 12.1 months (95% CI 7.2-NR). The physician-assessed objective response and disease control rates were 56% and 89%, respectively. For the nine patients who discontinued pemigatinib, the median treatment duration was 10.6 months (range: 0.8-21.7). Disease progression was the most common reason for discontinuation (89%). None discontinued due to adverse events. CONCLUSIONS: Objective response rates, disease control rates, and a PFS comparable to that in the phase 2 FIGHT-202 trial was reported with pemigatinib use in this Canadian PSP cohort.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".