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Updated: Oct 11, 2025
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A prognostic nomogram based on a new classification of combined micropapillary and solid components for stage IA
Wuhao Huang1, Hua Zhang1, Zhiwei Zhang1,2
1Department of Lung Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin Lung Cancer Center, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Background:
We aimed to develop a prognostic nomogram based on a new classification of combined micropapillary and solid components in pathological stage IA invasive lung adenocarcinoma (LUAD).
Methods:
According to the total proportion of solid and micropapillary components (TPSM), the X-tile software was applied to classify patients into the following three groups: TPSM-low (TPSM-L), TPSM-middle (TPSM-M), and TPSM-high (TPSM-H). The postoperative survival was compared among the three groups. The multivariate Cox regression analysis was performed to identify independent prognostic factors for survival. According to these factors, a nomogram model was developed to provide a personalized prognostic evaluation.
Results:
A total of 595 patients with pathological stage IA invasive LUAD were included in our study. The 5-year disease-free survival and overall survival rates in patients with TPSM-H and TPSM-M were significantly lower than those with TPSM-L. The multivariate Cox regression analysis revealed that the TPSM classification was an independent prognostic factor for survival. According to TPSM classification, we developed a nomogram model which had good calibration and reliable discrimination ability to evaluate survival.
Conclusions:
The nomogram based on the combination of micropapillary and solid components has good prognostic value in predicting postoperative recurrence and survival of patients with pathological stage IA invasive LUAD.
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