Intrahepatic Cholangiocarcinoma: Evaluating the burden on hospitals, prognostic factors for early recurrence, and safety of a new treatment option
Bibliographic record
Abstract
Background: The incidence of intrahepatic cholangiocarcinoma (iCCA) is rising in North America and the low 5-year overall survival rate of 10% is concerning. Through a series of projects, this thesis aims to address comprehensive issues related to poor iCCA outcomes, such as high rates of unresectable cases, high early recurrence rates after curative resection, and a lack of established neoadjuvant chemotherapy treatments.Methods: This thesis consisted of four projects each exploring a different aspect of iCCA care. Project One analyzed iCCA-related hospitalizations under the Department of Medicine or Intensive Care Unit (ICU) across 28 hospitals in Ontario using the GEMINI database. Project Two reviewed and meta-analyzed prognostic factors for early recurrence after iCCA resection. Project Three explored the associations between preoperative biomarkers and early recurrence using a landmark survival analysis and single-center data. Project Four studied neoadjuvant chemotherapy safety in resected iCCA patients using propensity-score matching and American College of Surgeons-National Surgical Quality Improvement Program database. Results: Through our research, we identified the rising number of iCCA-related, medical and ICU service hospitalizations (from 385 in 2016 to 420 in 2021, p=0.005) in Ontario. However, we also observed a decrease in the hospital length of stay (mean of 10 days, standard deviation (SD): 12 in 2016 to 9 days, SD: 8 in 2021, p=0.04). Additionally, our findings have helped define early recurrence as recurrence occurring within 12 months of surgery and identify those at risk for early recurrence after curative resection (multiple tumors, vascular invasions, lymph node metastasis, positive-margin resections, and high (>4.3) neutrophil-to-lymphocyte-ratio). Furthermore, we have demonstrated the short-term safety of neoadjuvant chemotherapy on patients undergoing iCCA resection. Conclusion: To improve the quality of iCCA patient care, multidisciplinary care patterns need to be re-evaluated, those at risk for early recurrence after curative surgery should be identified and provided with neoadjuvant or adjuvant chemotherapy with intensified follow-ups, and neoadjuvant chemotherapy clinical trials should be supported along with shifting practice towards its use for localized or locally advanced iCCAs. Overall, our research has contributed to the improvement of iCCA patient care at various treatment stages, with actionable recommendations for healthcare professionals.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".