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Record W2953981166

Insulin-like growth factors and risk of kidney cancer in men

2013· article· en· W2953981166 on OpenAlexaff
Jacqueline M. Major, Michaël Pollak, K. Snyder, Jarmo Virtamo, Demetrius Albanes

Bibliographic record

VenueSTM:n Hallinnonalan avoin julkaisuarkisto (Julkari) · 2013
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineRenal functionKidney cancerInternal medicineOdds ratioCancerProspective cohort studyRisk factorKidneyEndocrinologyCohort studyConfidence interval
DOInot available

Abstract

fetched live from OpenAlex

Insulin-like growth factor-I (IGF-I) has been shown to increase kidney growth, glomerular filtration rate, and renal function. In the prospective Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) study of 29 133 Finnish male smokers aged 50–69 years, serum concentrations of IGF were measured in samples collected in 1985–1988. A total of 100 men with kidney cancer diagnosed ⩾5 years after blood collection through 1997 were compared with a subcohort of 400 men; logistic regression models were used to estimate the risk of developing kidney cancer. Men with IGF-I levels >113 ng ml−1 were 59% less likely to develop kidney cancer than men with levels ⩽113 ng ml−1 (odds ratio=0.41; 95% confidence interval=0.23–0.75). The IGF binding protein-3 (IGFBP-3) levels did not alter the association. No association was observed between IGFBP-3, or molar ratio of IGF-I/IGFBP-3, and kidney cancer. Low serum IGF-I levels in this cohort of older middle-aged male smokers are associated with increased kidney cancer risk, independent of IGFBP-3.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.266
Teacher spread0.253 · 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.

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

Citations2
Published2013
Admission routes1
Has abstractyes

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