S3196 Analyzing Trends in Upper Gastrointestinal Tract Cancer Mortality Rates in the United States From 1999-2020
Bibliographic record
Abstract
Introduction: Gastrointestinal (GI) cancers account for approximately a quarter of global cancer cases, with one-third occurring in the upper tract (esophagus, stomach, duodenum). Their shared etiology warrants a collective mortality trend analysis to identify vulnerable populations. This study analyzes mortality trends in upper GI cancer mortality in the United States from 1999-2020. Methods: We utilized death certificate data from the CDC WONDER database spanning 1999-2020, focusing on upper GI tract cancers using ICD-10 codes: C15.0-C15.5, C15.8-C15.9, C16.0-C16.6, C16.8-C16.9, and C17.0. Age-adjusted mortality rates (AAMRs) per 100,000 population were calculated and stratified by sex, race/ethnicity, age group, geographic region, and urbanization. Joinpoint regression analysis identified statistically significant changes in temporal trends, expressed as Average Annual Percent Change (AAPC). Results: A total of 559,403 deaths from upper GI cancers were recorded in the U.S. from 1999 to 2020, with an overall decline in mortality (AAPC -1.58%). Men exhibited a substantially higher mortality rate than women (mean AAMR 33.93 vs 11.42) and a slower decline in rates (AAPC -1.62% vs -1.96%). Non-Hispanic (NH) Black individuals had the highest AAMRs (21.6) but also experienced the steepest decline (AAPC -3.51%). Other racial/ethnic groups had the following AAMRs: NH American Indian/Alaska Native (79.5), NH Asian/Pacific Islander (22.21), Hispanic (20.86), and NH White (20.43). Regionally, the Northeast had the highest burden (AAMR 22.8) but also the greatest decline (AAPC -2.02%), while the Midwest saw the slowest decrease (AAPC -1.15%). Urban areas had higher AAMRs in 1999 (25.92) compared to rural areas (23.34) but experienced a sharper decline (AAPC -1.74% vs -0.80%), resulting in lower mortality in urban areas by 2020 (20.1 vs 21.45). State-level analysis showed the District of Columbia (AAMR 28.62), Alaska (25.51), Rhode Island (24.29), Maine (24.16), Massachusetts (23.93), and Louisiana (23.81) ranked in the top 90th percentile for mortality burden. Conclusion: This study found a sustained decline in upper GI cancer mortality, reflecting advancements in preventative medicine, screening modalities, and targeted treatment. However, persistent disparities remain among men, African Americans, and rural populations. This highlights the need for tailored public health approaches and healthcare reforms to better reach high-risk groups and enhance outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".