Major adverse cardiac event risk prediction model incorporating baseline Cardiac disease, Hypertension, and Logarithmic Left anterior descending coronary artery radiation dose in lung cancer (CHyLL)
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: In patients with locally advanced non-small cell lung cancer (LA-NSCLC) post-radiotherapy, mean heart dose (MHD) and the percent of left anterior descending (LAD) coronary artery receiving ≥15 Gy (LADV15) are associated with major adverse cardiac events (MACE). We developed a MACE prediction model in this population. MATERIALS AND METHODS: Total 701 patients with LA-NSCLC treated with curative-intent radiotherapy reviewed, split by diagnosis date into "development" (n = 500) and later (n = 201) "test" cohorts. Development patients were analyzed using a multivariable Cox-proportional hazard model with backward elimination scheme (Bonferroni-adjusted α = 0.025). Potential predictors were selected a priori: age, coronary heart disease (CHD), Framingham Risk, hypertension, MHD, LADV15, intensity modulated radiotherapy use, and CHD and LADV15 interaction (CHD:LADV15). Cardiac doses as quadratic, square root, and logarithmic (ln[X + 1]) forms were explored. Models were internally validated with bootstrapping. RESULTS: Final model incorporated CHD, Hypertension, Logarithmic LADV15, and CHD*ln[LADV15 + 1] (CHyLL; β coefficients: 5.51, 1.28, 1.48, -1.36; all p < 0.025; bootstrapping c-index: 0.80; test cohort c-index: 0.76). Possible risk score range: 0-8.11. MACE incidence was 6.8% and 23.6% at 48 months (p = 0.041), and survival rates were 51.6% and 35.0% (p = 0.099), in the low-risk (score <5.00) and high-risk (score ≥5) test groups, respectively. Using the model, calculated LADV15 constraints for patients without CHD were 11.3% and 28.3% for those with and without hypertension, respectively, to remain low-risk. CONCLUSIONS: Pre-existing CHD, hypertension, and LADV15 were important factors in predicting MACE after radiotherapy. CHyLL has the potential to estimate personalized LADV15 constraints based on cardiac risk factors and acceptable MACE thresholds.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".