Abstract A083: Higher incidence of rare ovarian tumors in West Africa
Bibliographic record
Abstract
Abstract There is considerable regional variation in the incidences of ovarian cancer (OC); Europe and North America have the highest rate of 10.1 and 8.7 per 100,000 respectively whereas Japan and developing countries present with lowest incidences. Recent studies showed that West and East Africa women have high proportion of non-epithelial ovarian cancer, 30% and 39.5% from West and East Africa women respectively compared to 14%, 12%, 3% and 4.12% from US Born Black, Caribbean Born Black, US Born white and Alberta women, respectively. Africa women with epithelial ovarian cancer (EOC) presented at a lower age group; median age of 52.5 years compared with 59 years and above for the other group of women. The objective of the study was to evaluate a large cohort of OC tumors from West Africa, Nigeria to determine the patients’ demographics, the diagnostic accuracy and the tumor histotypes with the aim at identifying opportunities to improve the OC diagnosis in Africa and long-term goal of reduction in mortality and morbidity associated with the disease condition. This is a multi-centered retrospective study of OC involving 19 tertiary health institutions in West Africa, Nigeria over a period of 3 years (2017-2019). The histological records were accessed with the retrieval of patients’ demographics, original diagnosis and formalin fixed paraffin embedded (FFPE) tissue blocks of the corresponding patients. The FFPEs were sent to the collaborating institution, Division of Gynecological Oncology, Miller School of Medicine, University of Miami, Florida for further diagnostic appraisal. All FFPEs were sectioned, stained with hematoxylin and eosin (H&E) and reviewed by two pathologists. Immunohistochemistry (IHC) was performed on cases in which the morphology features were not diagnostic. A total of 422 FFPE ovarian tissue blocks were reviewed, corresponding to 377 patients. 238 (63.1%) of the cases fulfilled criteria for inclusion such as documentation of original diagnosis, presence of tumor on the slides, and interpretable morphologic features. 95 (39.9%) cases had some changes in their diagnosis. 5 cases (2.1%) had a complete change from malignant tumor to benign or borderline. IHC was required to perform differential diagnosis in 42 (44.2%) while the remaining 55 (56.8%) cases were made after histological secondary review. Epithelial ovarian cancer was 48.3% (115) of cases while non-epithelial ovarian cancer cases were 41 (36.4%) and other malignancies such as sarcoma, metastasis and hematological neoplasm accounted for the remaining 60 (25.2%) with 35 (58.3%) of the cases being metastatic tumors to the ovary. Our findings confirmed that West African women have a lower percentage of EOC compared to East Africa and North America women. We further demonstrated that secondary review of surgical pathology cases in a sub-specialized academic center and the use of ancillary techniques such as IHC may improve the diagnosis accuracy of OC in a low resource country. There would be need to incorporate this into the management of OC in low resource countries. Citation Format: Ayodele Joshua Omotoso. Higher incidence of rare ovarian tumors in West Africa [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A083.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".