Prognostic Factors and Treatment Outcomes in Gallbladder Cancer Patients Undergoing Curative Surgery: A Multicenter Retrospective Cohort Study
Bibliographic record
Abstract
Background: Gallbladder cancer (GBC) is a highly aggressive malignancy often diagnosed at an advanced stage due to its asymptomatic onset. Despite surgery being the only potentially curative option, recurrence and poor prognosis remain common, especially in advanced-stage diseases. There is limited consensus regarding the extent of lymphadenectomy, hepatic resection, and the role of adjuvant therapies. Identifying prognostic factors and optimizing treatment strategies are critical for improving outcomes. This multicenter retrospective study was conducted to evaluate the clinical and pathological predictors of survival and recurrence in GBC patients that underwent radical surgery and to assess the potential benefit of adjuvant therapies in advanced stages. Methods: This was a retrospective cohort study of GBC patients who underwent curative-intent resection for GBC between 2010 and 2022 at two tertiary medical centers in China. The baseline characteristics, surgical data, pathology, adjuvant therapy, and follow-up outcomes were analyzed. The survival outcomes were assessed using Kaplan–Meier methods and Cox regression models. Subgroup analyses were conducted to explore the impact of postoperative adjuvant chemotherapy, period of surgical treatment, and extent of resection. Multiple imputation was used to address missing data. Results: The 5-year overall survival (OS) rate was 57.4%. Independent predictors of a poorer OS included CA19-9 > 30 U/mL (HR = 1.861, p = 0.003), poor/moderate-to-poor differentiation (HR = 2.134, p = 0.004), T3–T4 stage (HR = 2.685, p = 0.001), N1–N2 stage (HR = 2.217, p = 0.002), M1 stage (HR = 2.308, p = 0.001), and a high CAN score (HR = 1.875, p = 0.009). Adjuvant chemotherapy improved the OS in the stage III–IV patients (24.8 vs. 17.3 months, p = 0.036), though the DFS improvement was not significant (p = 0.133). No survival difference was observed between the segment IVb + V resection and wedge resection in the T2b patients. The patients treated after 2017 had a better OS (p = 0.024), possibly due to improved surgical techniques and perioperative care. Conclusions: Radical surgery remains critical for GBC. Accurate staging and tailored perioperative strategies, including chemotherapy, may improve outcomes, though further prospective studies are needed to validate these findings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".