PSA, stage, grade and prostate cancer specific mortality in Asian American patients relative to Caucasians according to the United States Census Bureau race definitions
Bibliographic record
Abstract
BACKGROUND: The United States Census Bureau recommends distinguishing between "Asians" vs. "Native Hawaiians or Other Pacific Islanders" (NHOPI). We tested for prognostic differences according to this stratification in patients with prostate cancer (PCa) of all stages. METHODS: Descriptive statistics, time-trend analyses, Kaplan-Meier plots and multivariate Cox regression models were used to test for differences at diagnosis, as well as for cancer specific mortality (CSM) according to the Census Bureau's definition in either non-metastatic or metastatic patients vs. 1:4 propensity score (PS)-matched Caucasian controls, identified within the Surveillance, Epidemiology and End Results database (2004-2016). RESULTS: Of all 380,705 PCa patients, NHOPI accounted for 1877 (0.5%) vs. 23,343 (6.1%) remaining Asians vs. 93.4% Caucasians. NHOPI invariably harbored worse PCa characteristics at diagnosis. The rates of PSA ≥ 20 ng/ml, Gleason ≥ 8, T3/T4, N1- and M1 stages were highest for NHOPI, followed by Asians, followed by Caucasians (PSA ≥ 20: 18.4 vs. 14.8 vs. 10.2%, Gleason ≥ 8: 24.9 vs. 22.1, vs. 15.9%, T3/T4: 5.5 vs. 4.2 vs. 3.5%, N1: 4.4 vs. 2.8, vs. 2.7%, M1: 8.3 vs. 4.9 vs. 3.9%). Despite the worst PCa characteristics at diagnosis, NHOPI did not exhibit worse CSM than Caucasians. Moreover, despite worse PCa characteristics, Asians exhibited more favorable CSM than Caucasians in comparisons that focussed on non-metastatic and on metastatic patients. CONCLUSIONS: Our observations corroborate the validity of the distinction between NHOPI and Asian patients according to the Census Bureau's recommendation, since these two groups show differences in PSA, grade and stage characteristics at diagnosis in addition to exhibiting differences in CSM even after PS matching and multivariate adjustment.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".