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Record W4317951417 · doi:10.1158/1538-7755.disp22-b096

Abstract B096: Food insecurity and receipt of Supplemental Nutrition Assistance Program (SNAP) benefits among income-eligible US pediatric acute lymphoblastic leukemia patients enrolled on a multi-center clinical trial

2023· article· en· W4317951417 on OpenAlexaff
Rahela Aziz‐Bose, Yael Flamand, Puja J. Umaretiya, Lenka Ilcisin, Ariana Valenzuela, Peter D. Cole, Lisa Gennarini, Justine M. Kahn, Kara M. Kelly, Bruno Michon, Thai-Hoa Tran, Jennifer Welch, Lewis B. Silverman, Kira Bona

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2023
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsInstitute for Research in Immunology and CancerCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsMedicineReceiptSupplemental Nutrition Assistance ProgramMcNemar's testPediatric cancerFamily medicineClinical trialPovertyGerontologyPediatricsCancerFood insecurityInternal medicineFood security

Abstract

fetched live from OpenAlex

Abstract Background Food insecurity (FI) is an adverse social determinant of health (SDoH) prevalent among pediatric cancer patients and associated with poorer health outcomes in general pediatrics. Receipt of federal SNAP benefits reduces FI in general pediatrics, and is thus a marker of appropriate resource support to mitigate adverse SDoH. Dana-Farber Cancer Institute (DFCI) Acute Lymphoblastic Leukemia (ALL) Consortium Trial 16-001 is the first pediatric oncology clinical trial to prospectively collect parent-reported SDoH, including income, SNAP receipt, and FI. We investigated whether income-eligible pediatric ALL families were successfully receiving SNAP benefits, and whether SNAP receipt was associated with FI. Methods Secondary analysis of children aged 1-17 years with de novo ALL enrolled on the DFCI 16-001-embedded SDoH cohort study at 6 US centers from 2017-2022. We utilized parent-reported SDoH data at diagnosis (T0) and 6-mos (T1) into therapy to identify families as (1) SNAP-eligible, proxied as household income <130% Federal Poverty Level based on federal guidelines; and (2) food insecure, based on validated 2-item screen. McNemar’s test compared SNAP receipt at T0 vs T1 among those eligible at both timepoints. Associations between SNAP eligibility, SNAP receipt, and FI were evaluated with chi-square tests. Results At T0, among 262 evaluable families, 21% reported FI. A total of 20% (n=53) were SNAP-eligible, of whom 60% (n=32) reported FI and 53% (n=28) were receiving SNAP. Among 28 SNAP-recipient families, 61% reported FI. Similarly, at T1, among 223 evaluable families, 25% reported FI. A total of 28% (n=62) were SNAP-eligible, of whom 58% (n=36) reported FI and 58% (n=36) were receiving SNAP. Among 36 SNAP-recipient families, 56% reported FI. A significantly higher proportion of the 33 families SNAP-eligible at both T0 and T1 were receiving SNAP at T1 (70%) compared to T0 (52%) (p=0.034). Among eligible families, SNAP receipt was not associated with lower odds of FI at T0 (OR 1.03, p=0.96) or T1 (OR 0.83, p=0.73). Discussion FI, a well-defined adverse SDoH associated with inferior health outcomes, is highly prevalent among a trial-enrolled pediatric ALL population. Despite care delivery at highly resourced centers with dedicated staff to address social needs, a substantial proportion of likely eligible families (as proxied by income) were not receiving SNAP benefits 6-mos into therapy. Further, receipt of SNAP was inadequate to ameliorate FI in this cohort, with ~60% of SNAP recipients reporting concurrent FI both at T0 and T1. Ensuring successful connection of eligible families to existing benefits is an essential first step. However, high rates of FI among SNAP recipients indicate that resource navigation, though necessary, is not sufficient to address FI for this population. These data provide immediate targets for health equity interventions—including systematic benefits navigation, direct resource provision, and policy-based approaches for benefits augmentation—to address adverse SDoH and improve cancer outcomes. Citation Format: Rahela Aziz-Bose, Yael Flamand, Puja J. Umaretiya, Lenka Ilcisin, Ariana Valenzuela, Peter D. Cole, Lisa M. Gennarini, Justine M. Kahn, Kara M. Kelly, Bruno Michon, Thai-Hoa Tran, Jennifer J. G. Welch, Lewis B. Silverman, Kira Bona. Food insecurity and receipt of Supplemental Nutrition Assistance Program (SNAP) benefits among income-eligible US pediatric acute lymphoblastic leukemia patients enrolled on a multi-center clinical trial [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr B096.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.083
GPT teacher head0.417
Teacher spread0.334 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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