External Validation of International Risk-Prediction Models of IgA Nephropathy in an Asian-Caucasian Cohort
Bibliographic record
Abstract
INTRODUCTION: Two prediction models for IgA nephropathy (IgAN) using clinical variables and the Oxford MEST scores were developed and validated in 2 multiethnic cohorts. Additional external validation is required. METHODS: ) for model fit, and calibration plots for model calibration. Baseline survival function was also evaluated. RESULTS: was higher than reported. Survival curves in the subgroups (<16th, ∼16th to <50th, ∼50th to <84th, and ≥84th percentiles of linear predictor) were well separated. Most of the predictor variables, including hazard ratio, predicted 5-year risk, and eGFR decline slope, were worse with risk increasing. The baseline survival function was comparable in our cohort and the reported cohorts. The calibration was acceptable for the full model without race. However, the risk probability over 3 years was overestimated in the full model with race included. CONCLUSION: The prediction models showed good performance on personalized risk assessment, which may be used as drug-specific, precision-medicine approaches to treatment decisionmaking.
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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 | 0.001 |
| 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 | 0.001 |
| 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".