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Record W2326286020 · doi:10.1158/1538-7445.am2012-4505

Abstract 4505: Polymorphisms in <i>vascular endothelial growth factor</i> (<i>VEGF</i>) and associated receptors as prognostic and predictive factors in advanced solid tumors

2012· article· en· W2326286020 on OpenAlexaff
Lawson Eng, Eitan Amir, Abul Kalam Azad, Steven Habbous, Anke H. Maitland‐van der Zee, Sevtap Savas, Helen Mackay, Geoffrey Liu

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsMemorial University of NewfoundlandPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsBevacizumabAngiogenesisVascular endothelial growth factorMedicineOncologyInternal medicineVascular endothelial growth factor ACancer researchCancerVEGF receptorsChemotherapy

Abstract

fetched live from OpenAlex

Abstract Introduction: Angiogenesis is an important host factor that is utilized by cancer cells to both grow and metastasize. In an attempt to halt the progression of cancer growth, new agents, such as bevacizumab, have been developed to target VEGF. Host genetic variability in the VEGF pathway may influence angiogenesis-dependent signalling during cancer development, cancer biology and therefore may impact on sensitivity to various therapies and survival. Here, we conducted a systematic review of the predictive and prognostic significance of polymorphisms in VEGF and VEGF receptor (VEGFR) and their isoforms. Materials and Methods: We performed a literature search of PubMed in July 2011 using the keywords and MeSH terms: {“angiogenesis,” “VEGF,” “VEGFR1,” “FLT1,” “KDR,” “VEGFR2,” “VEGFA,” “VEGFB,” “bevacizumab”} and “cancer” and “polymorphism”. Eligible studies were those comparing wild-type and variant polymorphisms and reporting one or more of the following outcomes: overall survival (OS), progression free survival, time to progression, time to recurrence, disease free survival, response rate or drug toxicities. Meta-analysis was performed for studies reporting identical outcome data for pre-specified polymorphisms. Results: We identified 44 prognostic studies and 12 predictive studies. There was marked inter and intra-disease site heterogeneity in the effect of polymorphisms on both outcome and response to therapy. Meta-analysis was possible for six polymorphisms (VEGF +936C>T, VEGF –460T>C, VEGF +405G>C, VEGF –1154G>A, VEGF –2578C>A and VEGF –634G>C) each of which reported the effect of wild-type and variant forms on OS. VEGF –634G>C showed a statistically significant improvement in OS (HR: 0.75, 95% CI: 0.57-0.98, p=0.03). There were non-significant associations between VEGF +936C>T with worse OS and VEGF +405G>C with improved survival (HR: 1.38, 95% CI: 0.96-1.97, p=0.08 and HR: 0.85, 95% CI: 0.72-1.01, p=0.07, respectively). There were no significant differences between homozygosity and heterozygosity for these polymorphisms. Conclusions: VEGF –634G>C appears to predict for improved outcome while VEGF +936C>T and +405G>C both show non-significant associations with outcome. These polymorphisms should be investigated in prospective studies to ensure standardization of measurement and reporting. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4505. doi:1538-7445.AM2012-4505

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)0.009
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.008
Bibliometrics0.0080.012
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.328
Teacher spread0.302 · 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 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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