Hispanic<i>vs.</i>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
BACKGROUND/AIM: In primaries other than adrenocortical carcinoma (ACC), Hispanic race/ethnicity may predispose to higher stage at initial diagnosis and may result in worse survival. We tested the association between Hispanic race/ethnicity and cancer specific mortality (CSM) in ACC patients in addition to testing for differences in other-cause mortality (OCM) rates between Hispanics and Caucasians. PATIENTS AND METHODS: Within Surveillance, Epidemiology, and End Results database (2004-2018), we identified 1,060 ACC patients: 167 (15.8%) Hispanics vs. 893 (84.2%) Caucasians. Propensity score matching (age, sex, grade, T, N and M stages, treatment types), cumulative incidence plots Poisson-smoothing and competing risk regression (CRR) were used. RESULTS: Compared to Caucasians, Hispanics were younger (51 vs. 57 years, p<0.001) and presented higher rates of T3-4 primary tumor stage (52.7% vs. 42.8%, p=0.007). No other statistically significant differences were observed for grade, lymph node invasion, distant metastases, European Network for the Study of Adrenal Tumors (ENSAT) stage and treatment type (p>0.05 in all cases). After matching (1:3), 167 Hispanics and 501 Caucasians remained and were included in CRR analyses. In Hispanics, five-year CSM rates were 38.0% and 78.8% in respectively ENSAT stages I-II and III-IV vs. 34.1% and 74.4% in Caucasians. Overall, five-year OCM rates were 10.7% vs. 9.0% in Hispanics and Caucasians, respectively. In multivariable CRR models, Hispanic race/ethnicity was not an independent predictor for higher CSM (hazard ratio=1.18, p=0.2). CONCLUSION: In ACC, relative to Caucasians, Hispanic race/ethnicity is associated with lower age at initial diagnosis, but not with higher tumor stage or survival disadvantage.
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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 | 0.001 |
| 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) | 0.003 | 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 it