Association of Laparoscopic Surgery with Improved Perioperative and Survival Outcomes in Patients with Resectable Intrahepatic Cholangiocarcinoma: A Systematic Review and Meta-Analysis from Propensity-Score Matched Studies
Bibliographic record
Abstract
BACKGROUND: Recent studies have associated laparoscopic surgery with better overall survival (OS) in patients with hepatocellular carcinoma (HCC) and colorectal liver metastasis (CRLM). The potential benefits of laparoscopic liver resection (LLR) over open liver resection (OLR) have not been demonstrated in patients with intrahepatic cholangiocarcinoma (iCC). METHODS: A systematic review of the PubMed, EMBASE, and Web of Science databases was performed to search studies comparing OS and perioperative outcome for patients with resectable iCC. Propensity-score matched (PSM) studies published from database inception to May 1, 2022 were eligible. A frequentist, patient-level, one-stage meta-analysis was performed to analyze the differences in OS between LLR and OLR. Second, intraoperative, postoperative, and oncological outcomes were compared between the two approaches by using a random-effects DerSimonian-Laird model. RESULTS: Six PSM studies involving data from 1.042 patients (530 OLR vs. 512 LLR) were included. LLR in patients with resectable iCC was found to significantly decrease the hazard of death (stratified hazard ratio [HR]: 0.795 [95% confidence interval [CI]: 0.638-0.992]) compared with OLR. Moreover, LLR appears to be significantly associated with a decrease in intraoperative bleeding (- 161.47 ml [95% CI - 237.26 to - 85.69 ml]) and transfusion (OR = 0.41 [95% CI 0.26-0.69]), as well as with a shorter hospital stay (- 3.16 days [95% CI - 4.98 to - 1.34]) and a lower rate of major (Clavien-Dindo ≥III) complications (OR = 0.60 [95% CI 0.39-0.93]). CONCLUSIONS: This large meta-analysis of PSM studies shows that LLR in patients with resectable iCC is associated with improved perioperative outcomes and, being conservative, yields similar OS outcomes compared with OLR.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.024 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".