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Dietary Habits and Daily Routines as Prognostic Factors in Endometrial Cancer: A Machine Learning Approach.

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Area of Science:

  • Oncology
  • Epidemiology
  • Lifestyle Medicine

Background:

  • Endometrial cancer (EC) incidence is rising globally, linked to increased life expectancy and obesity.
  • Modifiable lifestyle factors may influence EC progression and patient survival.

Purpose of the Study:

  • To investigate the impact of dietary habits and daily routines on endometrial cancer recurrence and survival.
  • To identify specific lifestyle variables associated with improved or worsened EC outcomes.

Main Methods:

  • Utilized a Random Survival Forest (RSF) approach for multivariable survival analysis.
  • Analyzed data from 481 women who underwent hysterectomy for EC.
  • Collected data via extensive questionnaires on diet and daily routines.

Main Results:

  • Consumption of sugar-sweetened beverages and fried potatoes correlated with increased EC recurrence and mortality risk.
  • Regular physical activity was associated with a decreased risk of death in EC patients.
  • RSF identified significant lifestyle-related risk and protective factors.

Conclusions:

  • Random Survival Forest is an effective method for analyzing complex survival data in endometrial cancer.
  • Specific dietary choices (sugar-sweetened beverages, fried potatoes) and physical activity levels are crucial for EC patient outcomes.