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Record W2569754686

Prostate Cancer as a Metabolic Disease - Is Prostate Cancer Diagnosis Associated with Worse Cardiovascular Outcomes?

2014· dissertation· en· W2569754686 on OpenAlexaboutno aff
Bimal Bhindi

Bibliographic record

VenueTSpace (University of Toronto) · 2014
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProstate cancerConfoundingMetabolic syndromeDiseaseInternal medicineCancerPopulationOncologySelection biasCancer registryObesityPathologyEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Metabolic syndrome (MetS) and prostate cancer (PC) share several risk factors. In addition to increased cardiovascular risk, there is evidence that men with MetS have an increased PC risk. Given that both diseases develop over decades, PC diagnosis may precede the onset of MetS, and may be an early indicator of cardiovascular risk. We sought to determine if PC diagnosis is associated with increased risk of subsequent cardiovascular event. In our population-based study using administrative databases, men with PC identified using the Ontario Cancer Registry were hard-matched and propensity score-matched to men without PC diagnosis identified using the Registered Persons Database. Competing risks analyses were performed to compare risk of cardiovascular events. Contrary to our hypothesis, men with PC were less likely to experience a cardiovascular event compared to men without PC (sub-distributional HR=0.92, 95%CI=0.88-0.96). The difference was not clinically significant. Selection bias and confounding may explain this unexpected result.

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 score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.006
GPT teacher head0.241
Teacher spread0.234 · 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".

Quick stats

Citations4
Published2014
Admission routes1
Has abstractyes

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