Impact of Residing in Below Median Household Income Districts on Outcomes in Patients with Advanced Barrett’s Esophagus
Bibliographic record
Abstract
Abstract Background Barrett’s esophagus (BE) is a premalignant condition to esophageal adenocarcinoma (EAC). Low socioeconomic (SES) status adversely impacts care and outcomes in patients with EAC, but this has not been evaluated in BE. As the treatment of BE is similarly intensive, we aimed to evaluate the effect of SES on achieving complete eradication of intestinal metaplasia (CE-IM), dysplasia (CE-D) and development of invasive EAC. Methods Our study was a retrospective cohort study. Consecutive patients between January 1, 2010, to December 31, 2018, referred for BE-associated high-grade dysplasia or intramucosal adenocarcinoma were included. Pre, intra and post-procedural data were collected. Household income data was collected from the 2016 census based on postal code region. Patients were divided into income groups relative to the 2016 median household income in Ontario. Multivariate regression was performed for outcomes of interest. Results Four hundred and fifty-nine patients were included. Rate of CE-IM was similar between income groups. Fifty-five per cent (n = 144/264) versus 65% (n = 48/264) in the below and above-income groups achieved CE-D, respectively, P = 0.02. Eighteen per cent (n = 48/264) versus 11% (n = 22/195) were found to have invasive EAC during their treatment course in below and above-income groups, respectively, P = 0.04. Residing in a below-median-income district was associated with developing invasive EAC (Odds Ratio, [OR] 1.84, 95% confidence interval [CI] 1.01 to 3.35) and failure to achieve CE-D (OR 0.64, 95% CI 0.42 to 0.97). Conclusions Residing in low-income districts is associated with worse outcomes in patients with advanced BE. Further research is needed to guide future initiatives to address the potential impact of SES barriers in the optimal care of BE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".