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Record W3047462357 · doi:10.1158/1538-7445.pedca19-b66

Abstract B66: Nutritional intakes are associated with HDL-cholesterol levels in survivors of childhood acute lymphoblastic leukemia

2020· article· en· W3047462357 on OpenAlexaffabout
Sophia Morel, Devendra Amre, Emma Teasdale, Caroline Laverdière, Daniel Sinnett, Émile Lévy, Valérie Marcil

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsDyslipidemiaMedicineCholesterolPopulationInternal medicineMicronutrientBody mass indexLogistic regressionLipid profileEndocrinologyPediatricsEnvironmental healthObesityPathology

Abstract

fetched live from OpenAlex

Abstract Background: Survivors of childhood acute lymphoblastic leukemia (cALL) are at high risk of developing dyslipidemia (high LDL-cholesterol, high triglycerides, or low HDL-cholesterol). Studies showed that, similarly to the general population, cALL survivors do not respect dietary guidelines. However, whether nutritional intakes affect the lipid profile of this high-risk population remains unknown. This study aims to examine the associations between macro- and micronutrients and the presence of dyslipidemia in children and young adult survivors of cALL. Methods: Participants (n=247) survivors of cALL were recruited as part of the PETALE study at Sainte-Justine University Health Center (49.4% boys; median age: 21.7 yrs, range: 8.5-41.0 yrs; median time since diagnosis: 15.2 yrs, range: 5.4-28.2 yrs). Nutritional data were collected using a validated food frequency questionnaire (FFQ) comprising 190 items. Fasting blood was used to determine participants’ lipid profile by enzymatic reactions. Multivariable logistic regression models were fitted to evaluate the associations between intakes of macro- and micronutrients and dyslipidemia. The model included the following covariables: body mass index, age at diagnosis, age at diagnosis2, sex, and total energy intake. Results: Despite their young age, 41.3% of cALL survivors had dyslipidemia defined by having at least one abnormal lipid value. Specifically, 12.2% had high triglycerides and 17.4% high LDL-cholesterol and 23.1% low HDL-cholesterol. Our analysis revealed that having low HDL-cholesterol was associated with higher intakes in several nutrients (3rd vs. 1st tertile). They were proteins [odd ratio (OR): 0.27, 95%CI: 0.08-0.92, P<0.05], zinc (OR: 0.26, 95%CI: 0.08-0.84, P<0.05), copper (OR: 0.34, 95%CI: 0.12-0.99, P<0.05), selenium (OR: 0.17, 95%CI: 0.05-0.59, P<0.01), niacin (OR: 0.25, 95%CI: 0.08-0.84, P<0.05), riboflavin (OR: 0.24, 95%CI: 0.07-0.84, P<0.05), and vitamin B12 (OR: 0.35, 95%CI: 0.13-0.90, P<0.05). Conclusion: Our study shows the potential protective role of specific macro- and micronutrients on HDL-cholesterol levels in cALL survivors. These results stress the importance of deepening our understanding of the impact of nutrition in the development of dyslipidemia after cancer treatment. Nutritional strategies could be a valuable approach to prevent long-term cardiometabolic complications in cALL survivors. Citation Format: Sophia Morel, Devendra Amre, Emma Teasdale, Caroline Laverdière, Daniel Sinnett, Emile Levy, Valérie Marcil. Nutritional intakes are associated with HDL-cholesterol levels in survivors of childhood acute lymphoblastic leukemia [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B66.

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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)0.000
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0040.000

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 head0.131
GPT teacher head0.404
Teacher spread0.273 · 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
Published2020
Admission routes2
Has abstractyes

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