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Record W3040746161 · doi:10.1002/cam4.3241

Body mass index trajectories and prostate cancer risk: Results from the EPICAP study

2020· article· en· W3040746161 on OpenAlexfundno aff
Céline Lavalette, E Cordina Duverger, Fanny Artaud, Xavier Rébillard, Pierre‐Jean Lamy, Brigitte Trétarre, Sylvie Cénée, F. Ménégaux

Bibliographic record

VenueCancer Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsnot available
FundersAgence Nationale de Sécurité Sanitaire de l’Alimentation, de l’Environnement et du TravailFondation de FranceLigue Contre le CancerInstitute of Cancer ResearchInstitut National de la Santé et de la Recherche Médicale
KeywordsProstate cancerBody mass indexOverweightMedicineObesityProstateCancerEpidemiologyOncologyInternal medicineGynecology

Abstract

fetched live from OpenAlex

Elevated body mass index (BMI) has been inconsistently associated with prostate cancer occurrence but it has been suggested that life course adulthood obesity may be associated with an increased risk of prostate cancer. However, few studies have investigated lifetime BMI and prostate cancer risk. We analyzed life course BMI trajectories on prostate cancer risk based on data from the Epidemiological study of Prostate Cancer (EPICAP). We included in our analyses 781 incident prostate cancer cases and 829 controls frequency matched by age. Participants were asked about their weight every decade from age 20 to two years before reference date. BMI trajectories were determined using group-based trajectory modeling to identify groups of men with similar patterns of BMI changes. We identified five BMI trajectories groups. Men with a normal BMI at age 20 developing overweight or obesity during adulthood were at increased risk of aggressive prostate cancer compared to men who maintained a normal BMI. Our results suggest that BMI trajectories resulting in overweight or obesity during adulthood are associated with an increased risk of aggressive prostate cancer, particularly in never smokers, emphasizing the importance of maintaining a healthy BMI throughout adulthood.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.319
Teacher spread0.287 · 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.

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

Citations27
Published2020
Admission routes1
Has abstractyes

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