ArticleCPT: pharmacometrics & systems pharmacology2022
Performance of Cox proportional hazard models on recovering the ground truth of confounded exposure-response relationships for large-molecule oncology drugs.
Article in CPT: pharmacometrics & systems pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Dynamic Prediction of Clinical Endpoints in Survival Analysis With Machine and Deep Learning: A Systematic Review and Regulatory Perspective.CPT: pharmacometrics & systems pharmacology · 2026Pooled it
- Skipping a pillar does not make for strong foundations: Pharmacokinetic-pharmacodynamic reasoning behind the shape of dose-response relationships in oncology.CPT: pharmacometrics & systems pharmacology · 2023Pooled it
- Association Between Health Insurance Type and Survival Outcomes: Insight Into the Impact of Socioeconomic Disparities in the Postoperative Outcomes of Abdominal Aortic Aneurysm in Korea.Journal of Korean medical science · 2025Article
- A prognostic framework for predicting lung signet ring cell carcinoma via a machine learning based cox proportional hazard model.Journal of cancer research and clinical oncology · 2024Article
- Rare oncology therapeutics: review of clinical pharmacology package of drug approvals (2019-2023) by US FDA, best practices and recommendations.Journal of pharmacokinetics and pharmacodynamics · 2023Review
- A multistate modeling and simulation framework to learn dose-response of oncology drugs: Application to bintrafusp alfa in non-small cell lung cancer.CPT: pharmacometrics & systems pharmacology · 2023Article
- Applying interpretable machine learning workflow to evaluate exposure-response relationships for large-molecule oncology drugs.CPT: pharmacometrics & systems pharmacology · 2022Article
- Performance of Cox proportional hazard models on recovering the ground truth of confounded exposure-response relationships for large-molecule oncology drugs.CPT: pharmacometrics & systems pharmacology · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A Cox proportional hazard (CoxPH) model is conventionally used to assess exposure-response (E-R), but its performance to uncover the ground truth when only one dose level of data is available has not been systematically evaluated. We established a simulation workflow to generate realistic E-R datasets to assess the performance of the CoxPH model in recovering the E-R ground truth in various scenarios, considering two potential reasons for the confounded E-R relationship. We found that at high doses, when the pharmacological effects are largely saturated, missing important confounders is the major reason for inferring false-positive E-R relationships. At low doses, when a positive E-R slope is the ground truth, either missing important confounders or mis-specifying the interactions can lead to inaccurate estimates of the E-R slope. This work constructed a simulation workflow generally applicable to clinical datasets to generate clinically relevant simulations and provide an in-depth interpretation on the E-R relationships with confounders inferred by the conventional CoxPH model.
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