Objective: To develop and validate a mortality risk model for patients with
resected stage I non-small cell bronchogenic carcinoma (NSCBC).
Patients and method: Tumors from 798 patients with diagnoses of NSCBC were
resected and classified in stage I. The Kaplan-Meier method and Cox's propo
rtional hazard model were used to analyze the influence of clinical and pat
hologic variables on survival.
Results: Univariate analysis revealed that age (p=0.0461), symptoms (p=0.03
83), histology (p=0.0489) and tumor size (p=0.0002) and invasion (p=0.0010)
affected survival. Size (p=0.0000) and age (p=0.0269) were entered into mu
ltivariate analysis.
Each patient's risk was estimated by applying the regression equation deriv
ed from multivariate analysis; the mean was 1.47 +/-0.31 (range 0.68 to 2.9
2). The series was divided into three groups by degree of risk (low, interm
ediate and high), establishing the cutoff points at 1.16 and 1.78 (standard
deviation of the mean). Five-year survival rates were 85%, 62% and 46%, re
spectively (p=0.0000).
To validate the model's predictive capacity, the series was divided randoml
y into two groups: the study group with 403 patients and the validation gro
up with 395.
Age (p=0.0295), symptoms (p=0.0396), tumor size (p=0.0010) and invasion (p=
0.0010) affected survival in the univariate analysis. Size (p=0.0000) and a
ge (p=0.0358) were entered into Cox's model. Mean risk was 1.94 +/-0.36 (ra
nge 0.98 to 3.32). The series was divided into three risk groups, with cut-
off points established at 1.58 and 2.30. Five year survival rates were 90%,
62% and 46% for the low, intermediate and high risk groups, respectively (
p=0.0000). The same model proved able to identify risk when applied to the
validation group, in which five-year survival rates were 78%, 61% and 48%,
respectively (p=0.0000).
Conclusion: Risk models can identify patient subgroups, potentially influen
ced by co-adjuvant treatment, as well as facilitate comparison of patient s
eries.