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Record W3003873186 · doi:10.1016/j.hpb.2020.01.001

Neoadjuvant chemotherapy for primary resectable pancreatic cancer: a systematic review and meta-analysis

2020· review· en· W3003873186 on OpenAlexaboutno aff
Mao Ye, Qi Zhang, Yiwen Chen, Qihan Fu, Xiang Li, Xueli Bai, Tingbo Liang

Bibliographic record

VenueHPB · 2020
Typereview
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsnot available
FundersScience and Technology Program of Zhejiang ProvinceMedical Scientific Research Foundation of Zhejiang Province, ChinaNational Natural Science Foundation of China
KeywordsMedicineMeta-analysisOncologyChemotherapyPancreatic cancerInternal medicineNeoadjuvant therapyCancerBreast cancer

Abstract

fetched live from OpenAlex

BACKGROUND: Preoperative chemotherapy has shown benefits for locally advanced and borderline resectable pancreatic cancer. Neoadjuvant chemotherapy (NAC) has also been attempted in resectable pancreatic cancer (RPC); however, its role remains controversial. This study aimed to compare the clinical difference between NAC and upfront resection (UR) in RPC. METHODS: Electronic databases including PubMed, Embase, Medline, Web of Science, ClinicalTrials.gov, and Cochrane Central Register of Controlled Trials were searched for relevant articles from inception to February 2019 that addressed the overall survival in patients with RPC treated with or without NAC to identify eligible studies. Eleven studies were included in the final meta-analysis. The quality assessment of the included studies was based on the Newcastle-Ottawa quality scale. Data of the unresectable rate, R0 resection rate, and positive lymph node rate were also extracted in each study for further analysis. Pooled hazard ratio (HR), odds ratio (OR), and 95% confidence intervals (CIs) were calculated to assess the strength of the association. RESULTS: A total of eleven studies (eight cohort studies and three randomized controlled trials) involving 9773 patients were included. Ten of the eleven studies followed the "intention-to-treat" principle. NAC was found to be significantly associated with a higher R0 resection rate (P < 0.0001; OR = 2.62, 95% CI 1.70-4.03) and increased negative lymph node rate (P < 0.00001; OR = 0.34, 95% CI 0.31-0.37). However, compared with the UR group, NAC was related to a lower surgical resection rate (P = 0.0004; OR = 2.18, 95% CI 1.41-3.37). Overall, the NAC group exhibited no benefits in terms of overall survival compared with that in the UR group (P = 0.10; HR = 0.86, 95% CI 0.73-1.03). In the subgroup analysis, however, patients who received gemcitabine-based regimen as the NAC strategy had more favorable overall survival than that in the UR group (P = 0.04; HR = 0.75, 95% CI 0.57-0.99). CONCLUSIONS: NAC may be associated with a lower resection rate; however, it is associated with an increased R0 resection rate and lymph node negative rate. Although overall survival was similar in patients with or without NAC, gemcitabine-based NAC might provide longer overall survival. Further large-volume, randomized controlled trials are needed to validate the improved prognosis of patients undergoing NAC.

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)0.010
metaresearch head score (Gemma)0.022
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 score0.017
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0170.036
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.142
GPT teacher head0.437
Teacher spread0.295 · 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

Citations82
Published2020
Admission routes1
Has abstractyes

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