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Record W4405528316 · doi:10.1007/s44178-024-00133-5

The correlation between uveal melanoma and iris nevus

2024· article· en· W4405528316 on OpenAlexaff
Yuhang Yang, Jingting Luo, Zhaoxun Feng, Yang Li, Wenbin Wei, Yueming Liu

Bibliographic record

VenueHolistic Integrative Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsUniversity of Ottawa
FundersCapital Health Research and Development of Special FundBeijing Dongcheng District People's GovernmentBeijing Municipal Administration of HospitalsNatural Science Foundation of Beijing MunicipalityBeijing Science and Technology Planning ProjectBeijing Municipal Commission of EducationNational Natural Science Foundation of China
KeywordsMedicineIRIS (biosensor)NevusDermatologyProportional hazards modelUnivariate analysisMelanomaMultivariate analysisInternal medicineOphthalmologyBiometrics

Abstract

fetched live from OpenAlex

Abstract Purpose To investigate the impact of iris nevus on the incidence and prognosis of uveal melanoma (UM). Methods A retrospective cohort study was conducted involving 1128 UM cases and 4356 healthy controls. Participants were categorized based on iris nevus presence and grade: grade 0 (no iris nevus), grade 1 (single iris nevus), grade 2 (multiple iris nevi), and grade 3 (partial or complete darkening of the iris). Propensity matching score method was employed to control for age and sex differences, while the χ 2 test was used to compare the existence rate and grade of iris nevus between groups. Univariate ANOVA evaluated differences among various iris nevus grades, the Kaplan–Meier method analyzed the prognosis of patients with different iris nevus grades, and multivariate Cox proportional risk regression analysis was conducted to evaluate the relationship between clinical data and prognosis. Results A total of 5484 subjects were analyzed. UM patients exhibited a higher prevalence and grade of iris nevus (all P < 0.001) after propensity matching. Patients with iris nevus in the affected eye did not show a worse prognosis (P = 0.414). However, those with partial or complete iris darkening or multiple nevi had a poorer prognosis compared to those with a single or no iris nevus (all P < 0.05). Iris nevus presence and grade in the healthy eye had no prognostic impact (P = 0.726 and P = 0.825, respectively). The multivariate COX proportional risk model showed that tumor diameter (P < 0.001), age (P = 0.020), and grade of iris nevus in the affected eye (P = 0.009) were independent risk factors for a worse prognosis. LSD analysis revealed that patients with partial or complete darkening of the iris had larger tumor diameters than those without iris nevus (P = 0.013), single nevus (P = 0.015), and multiple nevus (P = 0.023). Discussion Our findings indicate a higher proportion and grade of iris nevus in UM patients compared to controls, and a worse prognosis for UM patients with higher-grade iris nevi in the affected eye.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.370
Teacher spread0.333 · 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
Published2024
Admission routes1
Has abstractyes

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