ArticleJCO clinical cancer informatics2023
Correlation Between Early Trends of a Prognostic Biomarker and Overall Survival in Non-Small-Cell Lung Cancer Clinical Trials.
Article in JCO clinical cancer informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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
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Who cites it
2 citing papers in PubMed.
- Large language models forecast patient health trajectories enabling digital twins.NPJ digital medicine · 2025Article
- Gene Expression Profiling Identifies CAV1, CD44, and TFRC as Potential Diagnostic Markers and Therapeutic Targets for Multiple Myeloma.Cell biochemistry and biophysics · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeOverall survival (OS) is the primary end point in phase III oncology trials. Given low success rates, surrogate end points, such as progression-free survival or objective response rate, are used in early go/no-go decision making. Here, we investigate whether early trends of OS prognostic biomarkers, such as the ROPRO and DeepROPRO, can also be used for this purpose.
methodsUsing real-world data, we emulated a series of 12 advanced non-small-cell lung cancer (aNSCLC) clinical trials, originally conducted by six different sponsors and evaluated four different mechanisms, in a total of 19,920 individuals. We evaluated early trends (until 6 months) of the OS biomarker alongside early OS within the joint model (JM) framework. Study-level estimates of early OS and ROPRO trends were correlated against the actual final OS hazard ratios (HRs).
resultsWe observed a strong correlation between the JM estimates and final OS HR at 3 months (adjusted
conclusionWe describe a pipeline to predict trial OS HRs using emulated aNSCLC studies and their early OS and OS biomarker trends. The method has the potential to accelerate and improve decision making in drug development.
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