Treatment Delays in the Hispanic Population With Renal Cell Carcinoma: An Analysis of Over 150,000 Patients Using the National Cancer Database
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
INTRODUCTION: Disparities have been documented in the outcomes of various cancers (eg, lung, colorectal, breast) among the Hispanic population compared with non-Hispanic White (NHW) patients. However, little is known about disparities in renal cell carcinoma (RCC) management despite worse outcomes for those with delays in treatment. The aim of this study was to investigate the disparities in (1) RCC presentation and (2) the time to treatment initiation between Hispanic and NHW patients. METHODS: We conducted a comparative analysis using National Cancer Database data from 2004 to 2020 to evaluate disparities in RCC presentation and time to treatment initiation between Hispanic and NHW patients. To minimize inherent differences between the 2 groups, we used 1:1 greedy caliper propensity score matching. RESULTS: = .027). CONCLUSIONS: Our data indicate that Hispanic patients often present with more advanced stages of RCC and are likely to experience delays in treatment. This study underscores significant disparities in the presentation and care of RCC between Hispanic and NHW patients, highlighting the need for targeted interventions to address these inequalities.
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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 | 0.000 | 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 | 0.000 |
| 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 it