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Updated: Sep 12, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Projecting individualized probabilities of lifetime all-cancer risk
Neel M Butala1,2, Noor Al-Hammadi3, Asiri Ediriwickrema4
1Department of Medicine, University of Colorado School of Medicine, Aurora, CO.
Introduction:
Technological advances and direct-to-consumer marketing have unearthed significant organic demand from patients for cancer screening and prevention. However, in the absence of strong data or guidelines, physicians have minimal support on how to approach patients in clinical practice.
Methods:
We projected individualized probabilities of 10-year and lifetime cancer risk across a population as well as potential improvement with healthy behaviors in the UK Biobank.
Results:
A total of 118 distinct variables were included across 38 cancer-specific models. The distribution of lifetime cancer risk had a rightward skew and wide variation for both men and women. The median lifetime cancer risk was 29.5% for men (interquartile range (IQR) 8.4%) and 21.0% for women (IQR 8.8%). If all modifiable risk factors were set to the ideal state, this decreased to 20.5% for men (IQR 3.9%) and 16.5% for women (IQR 4.9%). There was considerable overlap between age groups, with men aged 50-59 at the 90th percentile having greater risk (11.9%) than men aged 60-70 at the 25th percentile (11.8%), and women aged 40-49 at the 90th percentile having greater risk (7.4%) than women aged 50-59 at the 60th percentile (6.8%) and women aged 60-70 at the 20th percentile (7.3%).
Conclusions:
Lifetime cancer risk varies widely across the UK Biobank cohort, but this risk decreases substantially with healthy behaviors. There was considerable overlap in 10-year cancer risk between age groups, suggesting that future multicancer screening guidelines should account for more than age and sex as more evidence becomes available in the future.
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