SynthesisJournal of pharmacokinetics and pharmacodynamics2022
Estimation of time to progression and post progression survival using joint modeling of summary level OS and PFS data with an ordinary differential equation model.
Synthesis in Journal of pharmacokinetics and pharmacodynamics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Leveraging data-driven risk-adapted surveillance strategies after disease progression in locally advanced rectal cancer.BMC cancer · 2026Article
- Integration of Time-Varying Pharmacometric Modeling With Cox Regression for Time-to-Event Analysis in NONMEM.CPT: pharmacometrics & systems pharmacology · 2026Article
- Predicting tumor dynamics in treated patients from patient-derived-xenograft mouse models: a translational model-based approach.Journal of pharmacokinetics and pharmacodynamics · 2025Article
- A multistate platform model for time-to-event endpoints in oncology clinical trials.CPT: pharmacometrics & systems pharmacology · 2024Article
- Model-based prediction of progression-free survival for combination therapies in oncology.CPT: pharmacometrics & systems pharmacology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
measures such as progression-free survival (PFS) and overall survival (OS) are commonly reported in literature for oncology trials, while time to progression (TTP) and post progression survival (PPS) are not usually reported. A time-variant transition hazard model was developed using an ordinary differential equation (ODE) model to estimate TTP and PPS from summary level PFS and OS. The model was applied to published data from immune checkpoint inhibitor trials for non-small cell lung cancer (NSCLC) in a meta-analysis framework. This model-based method was able to robustly estimate TTP and PPS from summary level OS and PFS data, provided a quantitative approach for understanding the patterns of disease progression across different treatments through the time-variant disease progression rate function, and provided a summary of how different treatments affect TTP and PPS. The proposed method can be generalized to characterize and quantify multiple time-to-event endpoints jointly in oncology trials and improve our understanding of disease prognostics for different treatments.
Indexed as
Identifiers
35870059What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.