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Abstract B13: Adherence to cancer-specific prevention recommendations reduces risk of cancer in participants in Alberta's Tomorrow Project, Alberta, Canada

2017· article· en· W2623925690 on OpenAlexaffabout
Jianyi Xu, Jennifer E. Vena, Heather K. Whelan, Paula J. Robson

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2017
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineCancer preventionEnvironmental healthCancerPopulationCohortRandom digit dialingProspective cohort studyCohort studyGerontologyRed meatInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract Background: The World Cancer Research Fund (WCRF) and the American Institute for Cancer Research (AICR) published specific recommendations on food and nutrition, physical activity, body composition, and other modifiable risk factors in 2007 with the aim of reducing risk for cancer. However, inconsistent results have been reported regarding the impact of following these recommendations on cancer incidence and cancer mortality. Further, the impact of adhering to cancer-specific recommendations issued by WCRF/AICR has not been evaluated in a Canadian population. Objective: The objective of this study was to estimate the association between adherence to cancer-specific prevention recommendations and subsequent cancer risk in a prospective Canadian cohort; Alberta's Tomorrow Project (ATP). Design: ATP is a large population-based cohort of 55,000 adults who will be followed for up to 50 years to study the etiology of cancer and chronic disease, providing information that will help establish targeted prevention strategies. In the present study, 25,100 adult Albertans (35-69 years) with no previous diagnosis of cancer were recruited into ATP from 2001 to 2009 by random digit dialing. Self-administered questionnaires (Health and Lifestyle Questionnaire, Canadian Diet History Questionnaire (past year food frequency questionnaire), and Past Year Total Physical Activity Questionnaire) were used to collect participants' health and lifestyle information. A composite score was constructed to reflect each participant's overall adherence to seven WCRF/AICR personal recommendations, including body fatness, physical activity, consumption of fruits and vegetables, consumption of red meat, alcoholic drinks, dietary supplements intake, and tobacco exposure (including second hand smoke). Incidence cancer cases (excluding non-melanoma skin cancer) were identified through linkage with the Alberta Cancer Registry in 2015. Multivariable Cox proportional hazard regression models were employed to assess the association (HRs and 95% CIs) between the adherence composite score and risk of developing cancer. Results: Over a median of 10.0 years (252,120 person-years) follow-up, 1,709 participants developed cancer. After adjustment for potential confounding covariates, participants who were most adherent to WCRF/AICR recommendations (composite score: 4-7) were 19% (HR 0.81, 95% CI: 0.71-0.91) less likely to develop cancer when compared to those who were least adherent to the same recommendations (composite score: 0-2). Each unit increase in the composite score corresponded to an 8% (HR 0.92, 95% CI: 0.88-0.96) reduction in risk of developing cancer. When stratified by sex, the associations remained significant for women, but not for men. Conclusions: Adherence to cancer-specific prevention recommendations may reduce the risk of developing cancer. The adherence composite score constructed in this study may serve as a surrogate lifestyle indictor for predicting those at high risk of developing cancer. Future work should focus on assessing contribution of each component of the overall risk reduction within the total score. Disclosure: This study was supported by Alberta Cancer Foundation, the Alberta Cancer Prevention Legacy Fund, and the Canadian Partnership Against Cancer. Citation Format: Jian-Yi Xu, Jennifer E Vena, Heather K Whelan, Paula J Robson. Adherence to cancer-specific prevention recommendations reduces risk of cancer in participants in Alberta's Tomorrow Project, Alberta, Canada. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B13.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.020
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
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 head0.124
GPT teacher head0.435
Teacher spread0.311 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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