MétaCan
Menu
Back to cohort
Record W2794323096 · doi:10.2147/ott.s158171

Role of palliative resection of the primary pancreatic neuroendocrine tumor in patients with unresectable metastatic liver disease: a systematic review and meta-analysis

2018· review· en· W2794323096 on OpenAlexaff
Bo Zhou, Canyang Zhan, Yuan Ding, Sheng Yan, Shusen Zheng

Bibliographic record

VenueOncoTargets and Therapy · 2018
Typereview
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsPancreas Centre (Canada)
FundersScience and Technology Department of Zhejiang ProvinceDepartment of Education of Zhejiang Province
KeywordsMedicineMeta-analysisNeuroendocrine tumorsSystematic reviewRandomized controlled trialPrimary tumorInternal medicineOdds ratioMEDLINEOncologySurgeryCancerMetastasis

Abstract

fetched live from OpenAlex

Background: Treatment for pancreatic neuroendocrine tumors (PNETs) in patients with unresectable metastatic liver disease has long been a controversial issue. This systematic review aims to summarize the existing evidence concerning the value of primary tumor resection in this group of patients. Methods: A systematic review of the literature and a meta-analysis were performed. The PubMed and Cochrane databases were searched to identify articles that compared palliative primary tumor resection and nonsurgical regimens in patients with PNETs and unresectable liver metastases. Relevant articles were identified in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The primary outcome was overall survival. The included studies were evaluated for heterogeneity and publication bias. Results: Overall, 10 studies were included in the analysis. No randomized controlled trials (RCTs) were identified. These studies included 1,226 patients who underwent a resection of the primary tumor and 1,623 patients who did not undergo surgery. The median overall survival was 36–137 and 13.2–65 months in the surgical and nonsurgical groups, respectively, and the 5-year overall survival rate was 35.7–83 and 5.4%–50%, respectively, in these two groups. The meta-analysis demonstrated that there was no significant difference in liver tumor burden (odds ratio [OR] =1.51, 95% CI: 0.59–3.89, P =0.39) or tumor grade (OR =2.88, 95% CI: 0.92–9.04, P =0.07) among patients who underwent surgery and nonsurgical therapy. Furthermore, patients who underwent an aggressive surgical approach appeared to have a higher tumor grade. However, the meta-analysis demonstrated that patients who underwent primary tumor resection had better overall survival ( P <0.001), with a pooled hazard ratio of 0.36 (95% CI: 0.30–0.45). No publication bias was detected. Conclusion: This meta-analysis demonstrates that the palliative resection of the primary tumor in patients with PNETs and unresectable liver metastases can increase survival, although a bias toward a more aggressive surgical approach in patients with better performance status, less advanced disease, or a tumor located in the body or tail of the pancreas appears likely. RCTs with longer follow-up periods are required to confirm the advantages of palliative primary tumor resection for PNETs. Keywords: pancreatic neuroendocrine tumors, surgery, liver metastases, prognosis

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.033
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0160.038
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.041
GPT teacher head0.334
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations34
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueOncoTargets and TherapySame topicNeuroendocrine Tumor Research AdvancesFrench-language works237,207