| Title: | Quantifying the versatility of routinely measured prognostic factors |
| Journal: | Diagnostic and Prognostic Research |
| Published: | 4 Dec 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41340068/ |
| DOI: | https://doi.org/10.1186/s41512-025-00206-7 |
| URL: | https://link.springer.com/content/pdf/10.1186/s41512-025-00206-7.pdf |
Publication 16737
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Abstract
BackgroundSome prognostic factors (PF) are "versatile" insofar as they predict diverse health outcomes (age is an exemplar par excellence). In this study, we sought to quantify the versatility of commonly measured PFs.MethodsParticipants from the UKB (UK biobank) study were followed from enrolment until the date of outcome or censoring. Over 800 incident adverse outcomes were considered, based on a unique 3-digit ICD code (A00, A01, A02, etc.). Twenty-four routine PFs - including renal, liver function and blood count biomarkers - featured in this analysis. Cox regression was used to determine the association between each PF with time to each outcome event. The number of statistically significant associations, direction of the association (positive/negative) and the median log hazard ratio (LHR) were determined for each PF. Data were visualised using Volcano plots.ResultsThe analysis included up to 502,408 UKB participants followed for 12.4 years. PFs with the greatest number of statistically significant associations were age (563/836; median LHR: 0.47), waist-hip ratio (530/836; LHR: 0.37) and hand-grip strength (416/836; LHR: 0.27). Conversely, PFs with the lowest number of significant associations were diastolic blood pressure (138/835; LHR: 0.11) and total protein (138/835; LHR: 0.11). Positive correlation was observed between the number of events a PF was associated with and the average effect size for those associations.ConclusionA wide spectrum exists between the most and least versatile PFs. In addition to age, waist-hip ratio and handgrip strength exhibit high versatility. Understanding PF versatility has implications for optimising the development/performance of prognostic models.</p>
2 Authors
- Hamish Innes
- Philip J Johnson
1 Application
| Application ID | Title |
|---|---|
| 8764 | The epidemiology of liver disease in a population-based cohort. |
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