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Updated: Oct 21, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
[Factors influencing the survival prognosis in older adults]
Hisanori Otsubo1,2, Tsuyoshi Suda3, Yuri Ota4
1Department of Rehabilitation, Kanazawa Municipal Hospital.
Aim:
The present study examined the predictive factors for the survival prognosis in older adults.
Methods:
The subjects were 431 patients (75-99 years old) who visited our hospital between April 2016 and March 2019. Multivariate analyses were conducted to clarify the survival prognosis (P <0.05).
Results:
In a Cox regression analysis, the significant factors for the survival were the age (hazard ratio [HR] 1.050, 95% confidence interval [CI] 1.014-1.087), Charlson comorbidity index (CCI) (low vs. medium: HR 0.106, 95% CI 0.032-0.353; low vs. high: HR 0.244, 95% CI 0.150-0.398; low vs. very high: HR 0.514, 95% CI 0.326-0.809), pre-hospitalized gait (HR 1.861, 95% CI 1.158-2.988), sitting at discharge (HR 0.429, 95% CI 0.277-0.663), subcutaneous adipose tissue index (SATI) (HR 0.988, 95% CI 0.979-0.997) and modified controlling nutritional status (m-CONUT) (normal vs. light: HR 0.114, 95% CI 0.042-0.311; normal vs. moderate: HR 0.235, 95% CI 0.110-0.502; normal vs. severe: HR 0.351, 95% CI 0.166-0.741). In decision tree analyses, the significant factors for the 1-year survival were a CCI of low >medium >high-very high, body mass index of >20.7 kg/m2, m-CONUT of normal-light >moderate-severe and sitting at discharge, and those for the 2-year survival were sitting at discharge, a SATI of >43.9 cm2m-2, a CCI of low-medium >high-very high, male
Conclusions:
High SATI and body mass index values appeared to be associated with better survival outcomes.
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