MétaCan
Menu
← Back to cohort
Record W4389229669 · doi:10.1182/blood-2023-178401

Trends of Obesity over Time and Its Prognostic Significance in Children and Adolescents with Newly-Diagnosed Acute Lymphoblastic Leukemia in Canada: A Population-Based Study

2023· article· en· W4389229669 on OpenAlexaffabout
Samuel Sassine, Marie‐Claude Pelland‐Marcotte, André Ilinca, Uma H. Athale, Henrique Bittencourt, Lynette Bowes, Josée Brossard, Sara J. Israels, J. Chorostecki Donna, Ketan Kulkarni, Sarah McKillop, Meera Rayar, Roona Sinha, Tony H. Truong, Catherine Vézina, Laura Wheaton, Alexandra P. Zorzi, Lillian Sung, Thai Hoa Tran

Bibliographic record

VenueBlood · 2023
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsHospital for Sick ChildrenLondon Health Sciences CentreMcMaster UniversityConcordia UniversityIzaak Walton Killam Health CentreStollery Children's HospitalAlberta Children's HospitalBC Children's HospitalKingston Health Sciences CentreMcGill UniversityChildren's Hospital of Eastern OntarioCentre Hospitalier Universitaire Sainte-JustineUniversité de SherbrookeCancerCare Manitoba
Fundersnot available
KeywordsMedicinePediatricsBody mass indexObesityPopulationIncidence (geometry)Retrospective cohort studyCancerCohortChildhood obesityCancer registryInternal medicineOverweightEnvironmental health

Abstract

fetched live from OpenAlex

Introduction Childhood obesity can result in a variety of adverse health outcomes and it has been associated with inferior survival in children and adolescents with acute lymphoblastic leukemia (ALL). With the rising incidence of childhood obesity in Canada, we seek to assess the prevalence of obesity and its prognostic significance in children and adolescents with newly-diagnosed ALL in Canada. Methods We conducted a retrospective cohort study using the Cancer in Young People in Canada (CYP-C) database, a national population-based pediatric surveillance program collecting in-depth clinical data from all cancer patients <15 years old before 2015 and <19 years old after 2015 in Canada. This study included patients aged 2 to 18 years old with newly-diagnosed ALL and treated at one of the 17 pediatric oncology centers across Canada from January 1, 2001 to December 31, 2020. Obese patients were defined as patients with a body mass index (BMI) at or greater than the 95 th age and sex-adjusted percentile as per the Centers for Disease Control & Prevention (CDC). Patients <2 years old were excluded given no BMI data could be derived from CDC growth charts. The main outcomes were event-free survival (EFS) and overall survival (OS). EFS was defined as time from ALL diagnosis to first event (relapse or death). OS was defined as time from ALL diagnosis to death from any cause. Patients without an event were censored at date of last contact. Predictors of obesity were explored using logistic regression. Univariate and multivariable Cox proportional hazards models were used to compare EFS and OS between patients with and without obesity. Results A total of 3458 ALL patients were included. The median BMI was 16.4 kg/m 2 (interquartile range (IQR): 15.2-18.1 kg/m 2). Eleven percent of children were obese at the time of ALL diagnosis. The prevalence of obesity significantly increased over time compared to that at ALL diagnosis: 18.9% at 1 year (p<0.0001), 25.8% at 2 years (p<0.0001), 23.3% at 3 years (p<0.0001), 21.8 % at 4 years (p<0.0001) and 20% at 5 years (p<0.0001). The prevalence of obesity did not vary according to age at diagnosis, gender, neighborhood income quintile (NIQ), ALL immunophenotype and treatment era ( Table 1). Non-Caucasian race (odds ratio (OR): 1.35 [95% confidence interval (CI) 1.09 -1.67]; p=0.005), presenting white blood cell (WBC) ≥ 50 x 10 9/L (OR: 1.38 [1.07 - 1.77]; p=0.01) and central nervous disease (CNS) disease (OR: 1.44 [1.10 - 1.88]; p=0.009) were significantly associated with increased risk of obesity at diagnosis. The 5-year EFS of obese patients at ALL diagnosis were significantly inferior to those of non-obese patients (85.3% vs. 90.6%; p=0.0008) ( Figure 1). The 5-year OS was 90.4% for obese vs. 94.9% for non-obese patients at diagnosis (p=0.003). The causes of death in the entire cohort were 1) related to disease (73.5%); 2) related to treatment toxicities (15.6%); and 3) due to other causes (10.9%). In univariate analysis, obese patients at ALL diagnosis had a higher risk for worse EFS (Hazard Ratio (HR) 1.76, 95% CI 1.34 - 2.32, p<0.0001)and OS (HR 1.99, 95% CI 1.41- 2.81, p<0.0001) compared to non-obese patients. In addition, age ≥ 10 years old at diagnosis, CNS disease, presenting WBC count ≥ 50x10 9/L, non-favorable cytogenetics and treatment era before 2010 were also significantly associated with worse EFS and OS in univariate analyses. In multivariable models controlling for patients' age at diagnosis, gender, presenting WBC, CNS status, NIQ, ethnicity, treatment era and ALL immunophenotype, obesity at ALL diagnosis retained independent significance with a HR of 1.67, 95% CI 1.26-2.21, p=0.0004 for EFS and a HR of 1.83, 95% CI 1.29-2.61, p=0.0008 for OS. Conclusion In this population-based study of children and adolescents with ALL in Canada, obesity was found in 11% of patients at ALL diagnosis, peaked at 2 years and remained significantly increased at 5 years from initial diagnosis. Patients with higher risk features such as WBC ≥ 50 x 10 9/L and CNS disease were more likely to be obese at diagnosis. Nevertheless, obesity at ALL diagnosis remained independently associated with inferior EFS and OS even after adjustment for these high-risk features. More mechanistic studies are needed to better understand the relationship between obesity and outcome to inform future trial designs.

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)0.000
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 score0.029
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.007
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.008
GPT teacher head0.241
Teacher spread0.232 · 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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueBlood→Same topicChildhood Cancer Survivors' Quality of Life→French-language works237,207→