An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk
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: Competing risks arise when subjects are exposed to multiple mutually exclusive failure events, and the occurrence of one failure hinders the occurrence of other failure events. In the presence of competing risks, it is important to use methods accounting for competing events because failure to account for these events might result in misleading inferences. METHODS AND OBJECTIVE: Using data from a multisite retrospective observational longitudinal study done in Ethiopia, we performed sensitivity analyses using Fine-Gray model, Cause-specific Cox (Cox-CSH) model, Cause-specific Accelerated Failure Time (CS-AFT) model, accounting for death as a competing risk to determine baseline covariates that are associated with a composite of unfavourable retention in care outcomes in people living with Human Immune Virus who were on both Isoniazid preventive therapy (IPT) and antiretroviral therapy (ART). Non-cause specific (non-CSH) model that does not account for competing risk was also performed. The composite outcome comprises of loss to follow-up, stopped treatment and death. Age, World Health Organisation (WHO) stage, gender, and CD4 count were the considered baseline covariates. RESULTS: We included 3578 patients in our analysis. WHO stage III-or-IV was significantly associated with the composite of unfavourable outcomes, Sub-hazard ratio (SHR) = 1.31, 95% confidence interval (CI):1.04-1.65 for the sub-distribution hazard model, hazard ratio [HR] = 1.31, 95% CI:1.05-1.65, for the Cox-CSH model, and HR = 0.81, 95% CI:0.69-0.96, for the CS-AFT model. Gender and WHO stage were found to be significantly associated with the composite of unfavourable outcomes, HR = 1.56, 95% CI:1.27-1.90, HR = 1.28, 95% CI: 1.06-1.55 for males and WHO stage III-or-IV, respectively for the non-CSH model. CONCLUSIONS: Results show that WHO stage III-or-IV is significantly associated with unfavourable outcomes. The results from competing risk models were consistent. However, results obtained from the non-CSH model were inconsistent with those obtained from competing risk analysis models.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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