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Record W2111311540 · doi:10.1093/jnci/djm155

Fruits, Vegetables, and Colon Cancer Risk in a Pooled Analysis of 14 Cohort Studies

2007· article· en· W2111311540 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2007
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of TorontoUniversité de Montréal
FundersNational Cancer Institute
KeywordsColorectal cancerMedicineCohortPooled analysisCohort studyEnvironmental healthCancerOncologyInternal medicineMeta-analysis

Abstract

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BACKGROUND: Fruit and vegetable intakes have been associated with a reduced risk of colon cancer; however, in more recent studies associations have been less consistent. Statistical power to examine associations by colon site has been limited in previous studies. METHODS: Fruit and vegetable intakes in relation to colon cancer risk were examined in the Pooling Project of Prospective Studies of Diet and Cancer. Relative risks (RRs) and 95% confidence intervals (CIs) were estimated separately in 14 studies using Cox proportional hazards model and then pooled using a random-effects model. Intakes of total fruits and vegetables, total fruits, and total vegetables were categorized according to quintiles and absolute cutpoints. Analyses were conducted for colon cancer overall and for proximal and distal colon cancer separately. All statistical tests were two-sided. RESULTS: Among 756,217 men and women followed for up to 6 to 20 years, depending on the study, 5838 were diagnosed with colon cancer. The pooled multivariable RRs (95% CIs) of colon cancer for the highest versus lowest quintiles of intake were 0.91 (0.82 to 1.01, P(trend) = .19) for total fruits and vegetables, 0.93 (0.85 to 1.02, P(trend) = .28) for total fruits, and 0.94 (0.86 to 1.02, P(trend) = .17) for total vegetables. Similar results were observed when intakes were categorized by identical absolute cut points across studies (pooled multivariable RR = 0.90, 95% CI = 0.77 to 1.05 for 800 or more versus <200 g/day of total fruits and vegetables, P(trend) = .06). The age-standardized incidence rates of colon cancer for these two intake categories were 54 and 61 per 100,000 person-years, respectively. When analyzed by colon site, the pooled multivariable RRs (95% CIs) comparing total fruit and vegetable intakes of 800 or more versus less than 200 g/day were 0.74 (0.57 to 0.95, P(trend) = .02) for distal colon cancers and 1.02 (0.82 to 1.27, P(trend) = .57) for proximal colon cancers. Similar site-specific associations were observed for total fruits and total vegetables. CONCLUSION: Fruit and vegetable intakes were not strongly associated with colon cancer risk overall but may be associated with a lower risk of distal colon cancer.

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.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.036
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.046
GPT teacher head0.371
Teacher spread0.326 · 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