African American vs Caucasian race/ethnicity in adrenocortical carcinoma patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In some primaries, African American race/ethnicity predisposes to higher stage and worse survival. We tested for differences in cancer-specific mortality (CSM) and other-cause mortality (OCM) in patients with adrenocortical carcinoma (ACC) according to African American vs Caucasian race/ethnicity. We hypothesized that African Americans present with higher tumor stage and grade, do not receive the same treatment, and experience worse oncological outcomes than Caucasians. Within Surveillance, Epidemiology, and End Results database, we identified 1016 ACC patients: 123 (12.1%) African Americans vs 893 (87.9%) Caucasians. Propensity score matching (PSM) (age, sex, marital status, grade, T, N, and M stages, and treatment type), Poisson-smoothed cumulative incidence plots, and competing risk regression (CRR) were used. Compared to Caucasians, African Americans were more frequently unmarried (56.9% vs 35.5%, P < 0.001). No clinically meaningful or statistically significant differences were observed for age, grade, T, N, and M stages, as well as treatment type (all P > 0.05). After PSM (1:4), 123 African Americans and 492 Caucasians remained and were included in CRR analysis. In multivariable CRR models, CSM and OCM rates were not different between the two race/ethnicities (hazard ratio: 0.84, P = 0.3). In African Americans, 5-year CSM rates were 31.2% and 75.3% in European Network for the Study of Adrenal Tumors (ENSAT) stages I-II and III-IV, respectively vs 32.9% and 75.4% in Caucasians. Overall 5-year OCM rates were 11.0% vs 10.1% in respectively African Americans and Caucasians. Unlike other primaries, in ACC, African American race/ethnicity is not associated with higher disease stage at initial diagnosis or worse survival.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it