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Development and Validation of a Prognostic Nomogram in Lung Cancer With Obstructive Sleep Apnea Syndrome
Wei Liu1, Ling Zhou2, Dong Zhao1
1Department of Respiratory and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, China.
Frontiers in Medicine
|April 4, 2022
Summary
This study developed a nomogram to predict survival in lung cancer patients with obstructive sleep apnea (OSA). The model accurately identifies key prognostic factors, aiding personalized treatment decisions for better patient outcomes.
Area of Science:
- Oncology
- Pulmonology
- Medical Statistics
Background:
- Obstructive sleep apnea (OSA) is increasingly recognized as a comorbidity in lung cancer patients.
- Accurate prognostic assessment is crucial for guiding treatment strategies in this complex patient population.
- Existing prognostic models may not adequately incorporate the impact of OSA on lung cancer outcomes.
Purpose of the Study:
- To develop and validate a nomogram for predicting the survival rate of lung cancer patients with obstructive sleep apnea (OSA).
- To identify independent prognostic factors influencing survival in lung cancer patients with OSA.
- To assess the clinical utility of the nomogram in guiding individualized treatment decisions.
Main Methods:
- A nomogram was developed using a cohort of 90 lung cancer patients with OSA and validated in a separate cohort of 38 patients.
- Cox hazard analysis was employed to identify significant prognostic factors, including age, apnea-hypopnea index (AHI), tumor-node-metastasis (TNM) stage, cancer type, body mass index (BMI), and oxygen desaturation index (ODI4).
- Model accuracy was evaluated using discrimination (c-index, ROC curves) and calibration, with decision curve analysis (DCA) assessing clinical benefit.
Main Results:
- Significant differences in various parameters (e.g., AHI, TNM, LSpO2, T90%, TS90%, ODI4) were observed between lung cancer patients with and without OSA.
- The established nomogram, incorporating age, AHI, TNM, cancer type, BMI, and ODI4, demonstrated good accuracy with a c-index of 0.802.
- The nomogram showed strong predictive performance for 1-, 3-, and 5-year survival rates (AUCs ranging from 0.801 to 0.867) and good calibration, with DCA indicating clinical utility.
Conclusions:
- The developed nomogram serves as a reliable tool for predicting prognosis in lung cancer patients with OSA.
- The identified prognostic factors highlight the significant impact of OSA on lung cancer outcomes.
- This nomogram can aid clinicians in making informed, individualized treatment decisions for improved patient management.
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