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Record W4403315336 · doi:10.3389/fonc.2024.1417630

Microvascular invasion is associated with poor prognosis in renal cell carcinoma: a retrospective cohort study and meta-analysis

2024· review· en· W4403315336 on OpenAlexaboutno aff
Jinbin Xu, Yiyuan Tan, Shuntian Gao, Wei‐Jen Lee, Yuedian Ye, Gengguo Deng, Zhansen Huang, Xiaoming Li, Li Jiang, Samun Cheong, Jinming Di

Bibliographic record

VenueFrontiers in Oncology · 2024
Typereview
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsnot available
FundersSouthern Medical UniversitySun Yat-sen UniversityNational Natural Science Foundation of China
KeywordsRenal cell carcinomaMedicineRetrospective cohort studyOncologyInternal medicineCohort

Abstract

fetched live from OpenAlex

Background This retrospective cohort study and meta-analysis aims to explore the association between microvascular invasion (MVI) and clinicopathologiccal features, as well as survival outcomes of patients with renal cell carcinoma (RCC). Material and methods The retrospective cohort study included 30 RCC patients with positive MVI and another 75 patients with negative MVI as controls. Clinicopathological features and follow-up data were compiled. The meta-analysis conducted searches on PubMed, Cochrane Library, Web of Science, Embase, and WanFang Data from the beginning to 30 September 2023, for comparative studies relevant to MVI patients. The Newcastle-Ottawa Scale and Egger Test were used to assess the risk of biases and certainty of evidence in the included studies. Results The cohort study showed that MVI was associated with advanced primary tumor stage, high pathological grades, high tumor size, high clinical symptoms and lymph node invasion (P <0.05). Kaplan-Meier analyses demonstrated MVI was associated with worse CSS rates when compared to MVI negative group (P <0.05). However, in the multivariate analysis it was not presented as an independent predictor of cancer survival mortality (P >0.05). The meta-analysis part included 11 cohort studies. The results confirmed that patients with MVI positive had worse 12 and 60 mo CSS rates (HR12mo = 0.86, 95%CI 0.80–0.92; HR60mo = 0.63, 95% CI 0.55–0.72; P < 0.00001). Moreover, the meta-analysis also confirmed that MVI group was associated with higher rate of advanced tumor stage, pathological grades, tumor size diameter, higher rate of clinical symptoms and lymph node invasion (P <0.05). Conclusions The presence of MVI in renal cell carcinoma patients is linked to poorer survival outcomes and worse clinicopathological features. In spite of this, it does not seem to be an independent predictor for cancer survival mortality in renal cell carcinoma. Systematic review registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023470640 , identifier CRD42023470640.

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)0.011
metaresearch head score (Gemma)0.019
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: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.030
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.053
GPT teacher head0.321
Teacher spread0.268 · 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
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

Citations4
Published2024
Admission routes1
Has abstractyes

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