Construction and validation of a Nomogram model for postoperative early recurrence in patients with non-small cell lung cancer

CHEN Chunyu; ZHOU Jing; LIU Guyue; YU Jie; GU Jiangkui

doi:10.7619/jcmp.20232467

Journal of Clinical Medicine in Practice > 2023 > 27(24): 7-13. > DOI: 10.7619/jcmp.20232467

CHEN Chunyu, ZHOU Jing, LIU Guyue, YU Jie, GU Jiangkui. Construction and validation of a Nomogram model for postoperative early recurrence in patients with non-small cell lung cancer[J]. Journal of Clinical Medicine in Practice, 2023, 27(24): 7-13. DOI: 10.7619/jcmp.20232467

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Construction and validation of a Nomogram model for postoperative early recurrence in patients with non-small cell lung cancer

1.
Department of Thoracic and Cardiac Surgery, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, Anhui, 236000
2.
Department of Thoracic and Cardiac Surgery, Fuyang City People's Hospital Affiliated to Anhui Medical University, Fuyang, Anhui, 236000

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Received Date: August 02, 2023
Revised Date: November 20, 2023
Available Online: January 04, 2024

Graphical Abstract

Abstract

Abstract

Objective
To explore the risk factors of postoperative early recurrence in patients with non-small cell lung cancer (NSCLC) and establish a new Nomogram model.
Methods
The clinicopathological materials of 236 NSCLC patients with surgical resection in Fuyang Hospital Affiliated to Anhui Medical University and Fuyang City People's Hospital Affiliated to Anhui Medical University from January to August 2021 were retrospectively analyzed, and all the patients were randomly divided into a modeling group (n=165) and a validation group (n=71) with a ratio of 7 to 3. The independent risk factors of postoperative recurrence for NSCLC patients were determined by the univariate and multivariate Cox regression analyses, and a Nomogram model was constructed. The consistency index (C-index), calibration curve and receiver operating characteristics (ROC) curve were used to evaluate the predictive ability of the Nomogram model.
Results
The early recurrence rate of 236 NSCLC patients after surgery was 17.4% (41/236). Univariate and multivariate Cox analyses indicated that lymph node metastasis (HR=2.342, 95%CI, 1.214 to 4.517, P=0.011), pleural invasion (HR=2.738, 95%CI, 1.443 to 5.196, P=0.002), vascular invasion (HR=3.526, 95%CI, 1.802 to 6.899, P < 0.001) and serum D-dimer level (HR=3.656, 95%CI, 1.265 to 10.561, P=0.017) were the independent predictors of early recurrence and metastasis for NSCLC patients. Based on the above four variables, a Nomogram model was constructed, and the resul showed that the C-index of this model in the modeling group and validation group were 0.769 (95%CI, 0.661 to 0.879) and 0.790 (95%CI, 0.682 to 0.897) respectively; the area under the curve (AUC) of this model in predicting recurrence free survival (RFS) for patients in the modeling group at 1 year and 2 years was 0.817 and 0.792 respectively, while the AUC for patients in the validation group at 1 year and 2 years was 0.782 and 0.771 respectively. The calibration curve indicated that the predicted probability of this model was consistent with the actual recurrence risk in both groups.
Conclusion
This Nomogram model has good predictive value for early postoperative recurrence of NSCLC, and is of great significance for assisting clinical doctors in accurately identifying high-risk recurrence populations.
- non-small cell lung cancer,
- recurrence,
- Nomogram model,
- predictive value,
- risk factors,
- validation

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References (36)

References

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Construction and validation of a Nomogram model for postoperative early recurrence in patients with non-small cell lung cancer

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