Moreover, the combination of age, UICC stage, and serum CEA level as predictors of overall survival is shown in Table 5.
The estimation covariates should be added to the equations in Stage 2 as predictors because they are directly related to the outcome, adding them prevents the omitted variables problem.
Likewise, combination of UICC stage, age and serum CEA level as predictors of overall survival showed that the poorer the prognostic factors involved, the poorer the overall survival rate.
A Cox proportionatal hazards model identified both pathologic tumor and nodal stage as independent predictors of disease-free survival.
For example, a study done in Singapore [ 16] looked at the incorporation of a Comprehensive Geriatric Assessment (CGA) scale in the management of Asian elderly cancer patients, and identified age, poor performance status, abnormal albumin level, abnormal geriatric depression scale, high malnutrition risk and advanced disease stage as independent predictors of overall survival.
These findings are in agreement with a SEER-based study of EPSCC (1973 2006) where age ≥50 years, tumor size ≥5 cm, regional stage, and distant stage were identified as predictors of survival in multivariate analysis [ 8].
The validation results clearly demonstrated the added benefit of pN stage as a predictor of cancer-specific mortality.
Those definitely going abroad were defined as the reference category (excluding those unsure about migration plans) with degree stage as the predictor variable.
Tumour stage as a predictor variable was excluded from the multivariate survival models since, if time between presentation and treatment is an important factor for survival, then its effect would be via more advanced disease stage.
Interestingly, our study confirms TNM stage and VPI as predictors of OS, while stage and LVI emerged as risk factors for shortened time to relapse.
