Trends of Ovarian Cancer Incidence by Histotype and Race/Ethnicity in the United States 1992–2019
Bibliographic record
Abstract
The effect of risk factors on ovarian cancer differs by histotype, and the prevalence of such risk factors varies by race/ethnicity. It is not clear how ovarian cancer incidence has changed over time by histotype and race/ethnicity. We used the Surveillance, Epidemiology, and End Results Program (SEER-12) 1992–2019 data to examine the trend of ovarian cancer incidence for three histotypes (high-grade serous N = 19,691, endometrioid N = 3,212, and clear cell N = 3,275) and four racial/ethnic groups (Asian/Pacific Islander, Hispanic, non-Hispanic Black, and non-Hispanic White). Joinpoint and age-period-cohort analyses were conducted to analyze ovarian cancer incidence trends. High-grade serous cancer was the most common histotype, but its incidence has significantly decreased over time for all racial/ethnic groups; the decrease was largest for non-Hispanic White women (average annual percent change AAPC during 2010–2019 = −6.1; 95% confidence interval (CI), −8.0 to −4.2). Conversely, clear cell cancer was most common in the Asian/Pacific Islanders, and its incidence has increased over time, particularly among Hispanic and Asian/Pacific Islander women (AAPC during 2010–2019 = 2.8; 95% CI, 0.8 to 4.7, and AAPC = 1.5; 95% CI, 0.7 to 2.2, respectively). Endometrioid cancer incidence has decreased in non-Hispanic White but increased in Hispanic women (AAPC during 2010–2019 = −1.3; 95% CI, −1.9 to −0.8, and AAPC = 3.6; 95% CI, 1.0 to 6.3, respectively). The differential incidence trends by histotype and race/ethnicity underscore the need to monitor incidence and risk factor trends across different groups and develop targeted preventive interventions to reduce the burden of ovarian cancer and disparity by race/ethnicity. Significance: During 1992–2019, high-grade serous ovarian cancer incidence has decreased while clear cell cancer incidence has increased regardless of race/ethnicity. Endometrioid cancer incidence has decreased in non-Hispanic White but increased in Hispanic women. Differential ovarian cancer incidence trends highlight the need for targeted preventive interventions by histotype and race/ethnicity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".