Abstract A05: Incidence and trends in head and neck cancer among United States’ pediatric, adolescent, and young adult population
Bibliographic record
Abstract
Abstract Objectives: In 2009, there were 48,010 new cases of head and neck cancer in the United States. A decade later, it is projected that there will be 65,410 new cases in 2019, a 36% increase in new cases of the disease. While this number represents the general head and neck cancer population in the United States, only a few studies have described incidence and trends in head and neck cancer in the pediatric, adolescent, and young adult population—individuals who may have to live with the effects of cancer treatment due to a younger than average age of diagnosis. This study aimed to estimate head and neck cancer incidence and trends in the United States’ pediatric, adolescent, and young adult population. Methods: Using the Surveillance, Epidemiology, and End Results (SEER) 9 database from 1975-2016, we analyzed age-adjusted head and neck cancer incidence rates for pediatric cases (aged 0 to 14 years) and young adult cases (aged 15-39 years). We used Joinpoint regression analyses to examine incidence trends stratified by sex (male, female), race (white, blacks, and Others), and age groups (0-14, and 15-39 years). Results: There were 424 pediatric HNC cases and 6,936 adolescent and young adult cases in the study. Whites accounted for 70.6% of cancers, and 57.6% of cancers occurred in males. Overall, there was a 14.7% decrease in the incidence of HNC (1.32 per 100,000 in 1975 vs. 1.12 per 100,000 in 2016). For pediatric cases, there was a 51.2% decrease in incidence of HNC (0.18 per 100,000 in 1975 vs. 0.09 per 100,000 in 2016); in young adults, there was a 12.8% decrease in incidence of HNC (2.01 per 100,000 in 1975 vs. 1.75 per 100,000 in 2016). While there was overall decrease in incidence, we found differences based on sex. Among young adult males, the annual percent change (APC) from 1975 to 2016 was -0.46 (p < 0.05) while among young adult females, it significantly increased by 0.50 (p < 0.05). This difference in young adult male vs. female head and neck cancer incidence may have been driven by race: as stratified by race, the APC for white young adult males was -0.29 (ns) while white females had an APC of 0.55 (p < 0.05); and among black young adults, APC for males was -2.24 (p < 0.05) and APC for females was -0.82 (p < 0.05). Conclusions: Among pediatric, adolescent, and young adults in the United States, head and neck cancer has decreased markedly in all groups in the last four decades, except among white female adolescents and young adults where there has been a significant increase in the time period of the study. As this trend differs from the adult head and neck cancer population, it is critical that further investigations provide more insight into the epidemiology of head and neck cancer among white adolescent and young adult females. Note: This abstract was not presented at the conference. Citation Format: Nosayaba Osazuwa-Peters, Kara M. Christopher, Matthew C. Simpson, Premal B. Desai, Rebecca L. Rohde, Sai D. Challapalli, Adnan S. Hussaini, Neelima Panth, Eric Adjei Boakye. Incidence and trends in head and neck cancer among United States’ pediatric, adolescent, and young adult population [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A05.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".