Race/ethnic differences in AD survival in US Alzheimer's Disease Centers
Bibliographic record
Abstract
OBJECTIVE: Survival after Alzheimer disease (AD) is poorly understood for patients of diverse race/ethnic groups. We examined whether nonwhite AD patients (African American, Latino, Asian, American Indian) had different rates of survival compared with white AD patients. METHODS: The National Alzheimer's Coordinating Center (NACC) cataloged data from more than 30 Alzheimer's Disease Centers in the United States from 1984 to 2005. Patients aged 65 years or older with a diagnosis of possible/probable AD were included (n = 30,916). Survival was calculated using Cox proportional hazards models with a primary outcome of time to death. Secondary outcomes of this study were neuropathologic characteristics on an autopsied subsample (n = 3,017). RESULTS: The 30,916 AD patients in the NACC were followed up for 2.4 +/- 2.9 years (mean age 77.6 +/- 6.5 years; 65% women; 19% nonwhite [12% African American, 4% Latino, 1.5% Asian, 0.5% American Indian, and 1% other]). Median survival was 4.8 years. African American and Latino AD patients had a lower adjusted hazard for mortality compared with white AD patients (African American hazard ratio [HR] 0.85, 95% CI 0.74 to 0.96; Latino HR 0.57, 95% CI 0.46 to 0.69). Asians and American Indians had similar adjusted hazards for mortality compared with white AD patients (p > 0.10 for both). African American and Latino autopsied AD patients had similar neuropathologic characteristics compared with white AD patients with similar clinical severity. CONCLUSIONS: African American and Latino Alzheimer disease (AD) patients may have longer survival compared with white AD patients. Neuropathology findings did not explain survival differences by race. Determining the underlying factors behind survival differences may lead to longer survival for AD patients of all race/ethnic backgrounds.
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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 | 0.000 |
| 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".