Abstract A02: Pediatric ovarian cancer in the United States: Incidence trends over four decades
Bibliographic record
Abstract
Abstract Objectives: Ovarian cancer is rare in children, accounting for 1% of childhood cancers. However, it is the most common cancer of the female genital tract in adolescents. Due to the rarity of the disease and the histologic and prognostic differences between pediatric and adult cases, there is a paucity of data describing incidence trends of pediatric ovarian cancer in the United States. It is unknown whether pediatric ovarian cancer has increased in incidence over time. The aim of the current study was to examine incidence and trends in pediatric ovarian cancer in the last four decades in the United States. Methods: We queried the Surveillance, Epidemiology, and End Results 9 database from 1975-2016 for age-adjusted ovarian cancer incidence rates for pediatric cases, aged 0 to 19 years. We used Joinpoint regression analyses to examine incidence trends stratified by race (white, blacks, and others, which included Hispanics, American Indians/Alaskan Natives, and Asian Pacific Islanders), histology (carcinoma, germ cell tumor, others), and age groups (0-14, and 15-19 years). Results: There were 897 pediatric ovarian cancer cases in the study. Whites accounted for 71.3% of tumors, and 75.6% of tumors were germ cell. Overall, there was a 46% increase in the incidence of pediatric ovarian tumors in (12.59 per 100,000 in 1975 vs. 18.38 per 100,000 in 2016). Average annual percent change (AAPC) was 0.9 (p < 0.05), and APC from 1975 to 1977 was 5.1 (p = 0.5), from 1977 to 2006 APC was 0.5 (p < 0.05), and from 2006 to 2016, APC was 1.3 (p < 0.05). There was an upward trend in tumor incidence in all racial groups, and age-adjusted incidence rate was highest among whites (18.95 per 100,000). Among whites, APC changed significantly between 1981 and 2016 (APC = 0.8, p < 0.05); however, among blacks, APC increased between 1997 and 2016 (APC = 1.3, p < 0.05); and among other races, it increased between 1975 and 1997 (APC=1.1, p<0.05) and between 2000 and 2016 (APC = 1.9 p < 0.05). Conclusions: In the past four decades, there has been a steady increase in the age-adjusted incidence rate of pediatric ovarian tumors, and while overall incidence is highest among whites, there has been a sharp increase in incidence among blacks and other minority populations, especially in the last two decades. This surveillance information may be relevant to issues germane to survivors of pediatric cancers, such as oncofertility issues. Citation Format: Kara M. Christopher, Eric Adjei Boakye, Justin M. Barnes, Matthew C. Simpson, Brittany J. Kline, Katherine Mass, Theresa L. Schwartz, Shannon Grabosch, Nosayaba Osazuwa-Peters. Pediatric ovarian cancer in the United States: Incidence trends over four decades [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 A02.
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 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 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".