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Updated: Mar 31, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Interaction between a single exposure and age in cohort-based hazard rate models impacted the statistical
Shizue Izumi1, Ritsu Sakata2, Michiko Yamada3
1Faculty of Engineering, Department of Computer Science and Intelligent Systems, Oita University, 700 Dannoharu, Oita 870-1192, Japan.
Objective:
Statistical interaction between a single, instantaneous exposure and attained age (age during follow-up; attained age = age at exposure + time since exposure) is used in risk analyses to assess potential effect modification by unmeasured factors correlated with age. However, the impact of such interaction on the statistical distribution of age-at-onset of outcome (disease or death) is infrequently assessed. We therefore explored the impact of such interaction on the shape of the onset-age distribution.
Study Design And Setting:
We use for illustration age-at-onset of radiation-related early menopause in a cohort of female Japanese Atomic Bomb Survivors. The statistical distribution of age-at-onset was derived from a parametric hazard rate model fit to the data, assuming an underlying Gaussian onset-age distribution among nonexposed women.
Results:
Commonly used forms of exposure-by-age (attained age) interaction led to unnatural estimates of the age-specific rate function and unreasonable estimates of the onset-age distribution among exposed women, including positive risk of menopause before menarche.
Conclusion:
We recommend that researchers examine the distribution of age-at-onset and exposure-age interaction when conducting risk analyses. To distinguish this from potential etiologic interaction between exposure and unmeasured factors represented by age as a surrogate, richer models or additional data may be required.
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