Survival of stage <scp>III</scp> non‐seminoma testis cancer patients versus simulated controls, according to race/ethnicity
Bibliographic record
Abstract
BACKGROUND: It is unknown whether 5-year overall survival (OS) differs and to what extent between the American Joint Committee on Cancer stage III non-seminoma testicular germ cell tumor (NS-TGCT) patients and simulated age-matched male population-based controls, according to race/ethnicity groups. METHODS: We identified newly diagnosed (2004-2014) stage III NS-TGCT patients within the Surveillance Epidemiology and End Results database 2004-2019. For each case, we simulated an age-matched male control (Monte Carlo simulation), relying on Social Security Administration (SSA) Life Tables with 5 years of follow-up. We compared OS rates between stage III NS-TGCT patients and simulated age-matched male population-based controls, according to race/ethnicity groups (Caucasian, Hispanic, Asian/Pacific Islander and African American). Both, cancer-specific mortality (CSM) and other-cause mortality (OCM) were computed. RESULTS: Of 2054 stage III NS-TGCT patients, 60% were Caucasians versus 33% Hispanics versus 4% Asians/Pacific Islanders versus 3% African Americans. The 5-year OS difference between stage III NS-TGCT patients versus simulated age-matched male population-based controls was highest in Asians/Pacific Islanders (64 vs. 99%, Δ = 35%), followed by African Americans (66 vs. 97%, Δ = 31%), Hispanics (72 vs. 99%, Δ = 27%), and Caucasians (76 vs. 98%, Δ = 22%). The 5-year CSM rate was highest in Asians/Pacific Islanders (32%), followed by African Americans (26%), Hispanics (25%), and Caucasians (20%). The 5-year OCM rate was highest in African Americans (8%), followed by Caucasians (4%), Asians/Pacific Islanders (4%), and Hispanics (2%). CONCLUSION: Relative to SSA Life Tables, the highest 5-year OS disadvantage applied to stage III NS-TGCT Asian/Pacific Islander race/ethnicity group, followed by African American, Hispanic and Caucasian, in that order.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".