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Record W4212847032 · doi:10.3390/curroncol29020102

The Prognostic Effect of Multidisciplinary Team Intervention in Patients with Advanced Gastric Cancer

2022· article· en· W4212847032 on OpenAlexvenueno aff
Yuanyuan Xiang, Cuncan Deng, Han-Yuan Liu, Zichong Kuo, Changhua Zhang, Yulong He

Bibliographic record

VenueCurrent Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMultivariate analysisInternal medicineProportional hazards modelCancerOverall survivalSurvival analysisIntervention (counseling)

Abstract

fetched live from OpenAlex

Background: The effect of multidisciplinary team intervention (MDT) on the prognosis of advanced gastric cancer (GC) is still controversial. This study aims to analyze the effect of MDTs on the overall survival time of advanced gastric cancer patients. Methods: Patients with advanced GC who underwent surgical treatment between 2007 and 2014 were included in the study. They were divided into two groups; the MDT group received MDT treatment and the non-MDT group received conventional treatment. The Kaplan-Meier method was used to compare the overall survival (OS) of the two groups. The prognostic factors of advanced GC were evaluated by multivariate Cox regression analysis. Results: 394 patients were included in our study. Kaplan-Meier survival analysis showed that the prognosis of advanced GC patients with who underwent MDT intervention was better than those without (3-year OS of 55.6% vs. 46.1%, p = 0.005), Multivariate analysis indicated that MDT intervention could reduce mortality (HR = 0.493, p < 0.001). Conclusions: MDT intervention is an effective measure that improves the survival of patients with advanced GC.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.371
Teacher spread0.346 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations27
Published2022
Admission routes1
Has abstractyes

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