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Record W4414923677 · doi:10.1158/2159-8290.cd-25-1244

Association between Medicaid Expansion and 5-Year Survival among Individuals Diagnosed with Cancer

2025· article· en· W4414923677 on OpenAlexaff
Elizabeth J. Schafer, Christopher J. Johnson, Fábio Ynoe de Moraes, Xuesong Han, Jingxuan Zhao, Ahmedin Jemal

Bibliographic record

VenueCancer Discovery · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsQueen's University
FundersNational Center for Chronic Disease Prevention and Health PromotionNational Cancer InstituteCenters for Disease Control and Prevention
KeywordsMedicaidCancerAssociation (psychology)Cancer survivalOverall survival

Abstract

fetched live from OpenAlex

Medicaid expansion is associated with improvements in access to early detection and treatment services, and 2-year overall survival (OS) among individuals with cancer. However, the association with improvements in longer-term survival remains understudied. A difference-in-differences (DD) approach was used to examine changes in 5-year cause-specific survival and OS following Medicaid expansion. A total of 1,423,983 cancer cases diagnosed between 2007 and 2008 and 2014 and 2015 among adults 18 to 59 years of age residing in 26 expansion and 12 non-expansion states were included. Improvements in cause-specific survival were significantly greater in expansion states among individuals residing in rural [DD: 2.55 percentage point (ppt); 95% confidence interval (CI), 0.23-4.86] and high-poverty communities (DD: 1.54 ppt; 95% CI, 0.30-2.77), non-Hispanic White individuals (DD: 0.37 ppt; 95% CI, 0.05-0.70), and those with pancreatic (DD: 2.60 ppt; 95% CI, 0.86-4.34), lung (DD: 1.32 ppt; 95% CI, 0.30-2.34), and colorectal cancers (DD: 1.31 ppt; 95% CI, 0.26-2.37). Results were similar for OS. These findings underscore the importance of Medicaid expansion in mitigating disparities in survival outcomes. SIGNIFICANCE: Improvements in 5-year cause-specific survival and OS were greater in Medicaid expansion than non-expansion states among individuals residing in rural and high-poverty communities and among individuals diagnosed with cancers that generally have a worse prognosis, emphasizing the importance of Medicaid expansion in mitigating disparities in survival outcomes. See related commentary by Paskett, p. 2404.

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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.043
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.030
GPT teacher head0.282
Teacher spread0.252 · 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 teacher head, 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

Citations2
Published2025
Admission routes1
Has abstractyes

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