{"doi":"10.3390/cancers17091399","title":"Outcomes for Medicaid Patients with Colorectal Cancer Are Improved in Affluent Neighborhoods, but Disparities Persist","abstract":"Background: Socioeconomic status (SES) significantly influences outcomes in colorectal cancer (CRC) patients, with those from low-SES backgrounds facing worse prognoses. However, living in an affluent neighborhood may mitigate some of these disparities through environmental advantages. This study investigates whether Medicaid-insured CRC patients, as a proxy for low individual SES, experience better outcomes when residing in high-SES neighborhoods. Methods: Using the National Cancer Database, we examined Medicaid CRC patients, stratifying them by neighborhood SES indicators: median household income and education level. Patients in the highest and lowest quartiles of income and education were compared. Medicaid patients from the highest-SES neighborhoods were compared to the general population. Multivariable regression models analyzed 30- and 90-day postoperative mortality, overall survival (OS), and time from diagnosis to treatment initiation and surgery. Results: CRC patients in high-income neighborhoods began treatment earlier (coefficient −1.847, p = 0.015) and exhibited improved OS (HR 0.810, p < 0.001) compared to those in low-income neighborhoods, irrespective of education level. Similarly, patients in high-education neighborhoods started treatment sooner (coefficient −3.926, p < 0.001) and had better OS (HR 0.897, p < 0.001). No differences were observed in time to surgery or postoperative mortality. Despite these advantages, Medicaid patients in high-income (HR 1.130, p < 0.001) and high-education (HR 1.209, p = 0.002) areas still had worse OS compared to non-Medicaid patients. Conclusions: Higher neighborhood SES is associated with a significant survival benefit for Medicaid CRC patients, but these patients still lag behind their non-Medicaid counterparts. Understanding the mechanisms by which neighborhood SES influences cancer outcomes could inform targeted interventions to close the survival gap.","journal":"Cancers","year":2025,"id":543863,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9594,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1268473,"name":"Mohamad El Moheb","orcid":"0000-0002-1897-2145","position":1,"is_corresponding":false},{"id":334149,"name":"Chengli Shen","orcid":"0000-0003-4731-2872","position":2,"is_corresponding":false},{"id":1404743,"name":"Susan J. Kim","orcid":null,"position":3,"is_corresponding":false},{"id":399988,"name":"Russell G. Witt","orcid":"0000-0003-3747-8633","position":4,"is_corresponding":false},{"id":474952,"name":"Samantha M. Ruff","orcid":"0000-0001-5275-6705","position":5,"is_corresponding":false},{"id":242172,"name":"Allan Tsung","orcid":"0000-0002-3916-8965","position":6,"is_corresponding":false},{"id":233297,"name":"Kaelyn C. Cummins","orcid":"0009-0006-6962-9802","position":0,"is_corresponding":true}],"reference_count":45,"raw_metadata":null,"created_at":"2026-07-19T02:53:08.338070Z","pmid":"40361326","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}