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Peer-reviewedCC BYFrontiers in pharmacology

Ensemble signal detection reveals target-specific temporal risk of hypokalemia after immune checkpoint inhibition: a translational pharmacology framework

  • Shengwang Chen1
  • Ziyi Dai2
  • Zihan Guo3
  • Ziyi Li2
  • Ruiqi Liu4
  • Xuewen Jiang5
5 affiliations
  1. 1Department of Neurosurgery, The Third Hospital of Xiamen , , ,
  2. 2The Second Clinical College of China Medical University , ,
  3. 3Dalian Medical University , ,
  4. 4The First Clinical College of China Medical University , ,
  5. 5Department of Neurosurgery, Xiamen Xinglin Hospital , ,
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Abstract

Introduction: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, but traditional pharmacovigilance lacks a translational computational framework capable of resolving target-specific nonlinear temporal risks of adverse events such as hypokalemia.

Methods: We integrated 3,243 ICI-related hypokalemia reports from the FDA Adverse Event Reporting System (FAERS) and VigiBase (2014–2024). An ensemble signal-detection strategy cross-validated four disproportionality algorithms (Reporting Odds Ratio [ROR], Proportional Reporting Ratio [PRR], Empirical Bayesian Geometric Mean [EBGM], and Information Component [IC]). Flexible nonlinear survival analysis was performed using restricted cubic spline (RCS) Cox regression to model time-to-event dynamics.

Results: Programmed Death-Ligand 1 (PD-L1) inhibitors triggered the strongest signal (ROR = 3.20, 95% CI: 2.95–3.48), with ultra-early onset (median 23 days) and the highest case fatality rate (23.7%). An asymmetric biphasic mortality pattern showed a nadir at 60 days: early-onset (≤30 days) hypokalemia peaked at a hazard ratio (HR) of ∼1.9, whereas late-onset (>90 days) risk gradually rose to HR ∼1.8 within 350 days. Programmed Death-1 (PD-1) inhibitors significantly increased severe hypokalemia risk (odds ratio [OR] = 28.32), with male predominance across PD-1 and CTLA-4 subgroups.

Discussion: This interpretable ensemble framework reveals target-specific temporal toxicity signatures from multi-source real-world data, providing a computationally grounded translational pharmacology foundation for precision electrolyte monitoring and mechanism-informed safety prediction.

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Cite

BibTeXRIS
BibTeX
@article{chen2026ensemble,
  title = {{Ensemble signal detection reveals target-specific temporal risk of hypokalemia after immune checkpoint inhibition: a translational pharmacology framework}},
  author = {Shengwang Chen and Ziyi Dai and Zihan Guo and Ziyi Li and Ruiqi Liu and Xuewen Jiang},
  journal = {Frontiers in pharmacology},
  year = {2026},
  month = oct,
  doi = {10.3389/fphar.2026.1960328},
  url = {https://europepmc.org/article/PMC/PMC13668552},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Ensemble signal detection reveals target-specific temporal risk of hypokalemia after immune checkpoint inhibition: a translational pharmacology framework
AU  - Shengwang Chen
AU  - Ziyi Dai
AU  - Zihan Guo
AU  - Ziyi Li
AU  - Ruiqi Liu
AU  - Xuewen Jiang
PY  - 2026
DA  - 2026/10/01
JO  - Frontiers in pharmacology
DO  - 10.3389/fphar.2026.1960328
UR  - https://europepmc.org/article/PMC/PMC13668552
AB  - Introduction: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, but traditional pharmacovigilance lacks a translational computational framework capable of resolving target-specific nonlinear temporal risks of adverse events such as hypokalemia.  Methods: We integrated 3,243 ICI-related hypokalemia reports from the FDA Adverse Event Reporting System (FAERS) and VigiBase (2014–2024). An ensemble signal-detection strategy cross-validated four disproportionality algorithms (Reporting Odds Ratio [ROR], Proportional Reporting Ratio [PRR], Empirical Bayesian Geometric Mean [EBGM], and Information Component [IC]). Flexible nonlinear survival analysis was performed using restricted cubic spline (RCS) Cox regression to model time-to-event dynamics.  Results: Programmed Death-Ligand 1 (PD-L1) inhibitors triggered the strongest signal (ROR = 3.20, 95% CI: 2.95–3.48), with ultra-early onset (median 23 days) and the highest case fatality rate (23.7%). An asymmetric biphasic mortality pattern showed a nadir at 60 days: early-onset (≤30 days) hypokalemia peaked at a hazard ratio (HR) of ∼1.9, whereas late-onset (>90 days) risk gradually rose to HR ∼1.8 within 350 days. Programmed Death-1 (PD-1) inhibitors significantly increased severe hypokalemia risk (odds ratio [OR] = 28.32), with male predominance across PD-1 and CTLA-4 subgroups.  Discussion: This interpretable ensemble framework reveals target-specific temporal toxicity signatures from multi-source real-world data, providing a computationally grounded translational pharmacology foundation for precision electrolyte monitoring and mechanism-informed safety prediction.
SN  - 1663-9812
ER  -