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Record W3093380089 · doi:10.1016/j.euros.2020.08.008

Fibroblast Growth Factor Receptor 3 Mutation as a Prognostic Indicator in Patients with Urothelial Carcinoma: A Systematic Review and Meta-analysis

2020· review· en· W3093380089 on OpenAlexaff
Sidra Khalid, Bassam Basulaiman, Jeffrey Emack, Christopher M. Booth, Ignacio Durán, Andrew Robinson, David M. Berman, Martin Smoragiewicz, Eitan Amir, Francisco Vera-Badillo

Bibliographic record

VenueEuropean Urology Open Science · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFibroblast Growth Factor Research
Canadian institutionsUniversity of TorontoSunnybrook Health Science CentrePrincess Margaret Cancer CentreUniversity of OttawaQueen's University
Fundersnot available
KeywordsFibroblast growth factor receptor 3Hazard ratioOncologyMedicineInternal medicineMeta-analysisCarcinogenesisCarcinomaBladder cancerProportional hazards modelUrothelial carcinomaCancer researchCancerConfidence intervalFibroblast growth factorReceptor

Abstract

fetched live from OpenAlex

Fibroblast growth factor receptor 3 (FGFR3) mutations have been implicated in urothelial tumorigenesis. FGFR3 inhibitors are being explored in clinical trials. We aimed to study the association between FGFR3 mutations and survival in urothelial carcinoma. We performed a systematic literature search of PubMed, Cochrane, Ovid, and Web of Science from January 1985 to October 2018. The search terms were as follows: targeted therapies, FGFR and its subtypes, urothelial, bladder, and cancer. We included case-control or cohort studies of FGFR3 mutations in urothelial carcinoma. We included studies reporting hazard ratios (HRs) and 95% confidence intervals (CIs) for outcomes comparing FGFR3 mutations with FGFR3 wild type. Two reviewers performed article selection. We assessed heterogeneity among study-specific HRs using I2 statistic. We used a random effect model to obtain HR and 95% CI for event-free survival (EFS), composed of recurrence-free and progression-free survival. Statistical tests were two sided. Eleven studies (seven retrospective and four prospective) comprising 2162 patients were included. Analysis was performed for two groups. The first group included 1651 patients with non–muscle-invasive (NMI) urothelial carcinomas (886 [53.6%] had FGFR3 mutations). Compared with FGFR3 wild type, FGFR3 mutation did not influence EFS (HR = 0.99, CI = 0.77–1.28, p = 0.96). There was no significant heterogeneity (I2 = 25%). The second group included 511 patients with NMI and muscle-invasive (MI) urothelial carcinomas (151 [30%] had FGFR3 mutations). FGFR3 mutation was not prognostic (HR = 1.54, CI = 0.41–5.81, p = 0.52). There was heterogeneity (I2 = 91%). There is no association between FGFR3 mutation and EFS in NMI urothelial carcinoma, and in NMI and MI urothelial carcinoma groups. Fibroblast growth factor receptor 3 (FGFR3) mutation is not associated with a worse survival outcome in urothelial carcinoma. This is important as FGFR inhibitors are emerging as a new treatment option.

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)0.024
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.024
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.025
Bibliometrics0.0080.011
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
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 head0.034
GPT teacher head0.313
Teacher spread0.280 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

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