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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and validation of a nomogram to pediatric postoperative pulmonary complications following thoracic
Lei Wang1, Ting Xiao1, Zhen Du1
1Department of Anesthesiology, the Affiliated Children's Hospital Of Xiangya School of Medicine, Central South University (Hunan children's hospital), Yuhua District, 86 Ziyuan Road, Changsha, Hunan, China.
Insights
A new nomogram accurately predicts postoperative pulmonary complications in children undergoing thoracic surgery with one-lung ventilation. This tool uses four key factors for early risk assessment and improved patient outcomes.
Area of Science:
- Pediatric Thoracic Surgery
- Pulmonary Complications
- Medical Nomograms
Background:
- Children have distinct respiratory anatomy and physiology, increasing their risk of postoperative pulmonary complications after thoracic surgery requiring one-lung ventilation.
- Existing methods for predicting these complications in pediatric patients are limited.
Purpose of the Study:
- To develop and validate a predictive nomogram for postoperative pulmonary complications in children undergoing thoracic surgery with one-lung ventilation.
- To identify easily accessible perioperative variables that can predict these complications.
Main Methods:
- A cohort of 361 children undergoing thoracic surgery with one-lung ventilation was divided into training (80%) and validation (20%) groups.
- A nomogram was developed using logistic regression and validated for its discriminative ability and calibration.
- Predictive factors were selected using univariate analysis and the least absolute shrinkage and selection operator regression model.
Main Results:
- The nomogram incorporated four key predictors: preoperative neutrophil-to-lymphocyte ratio, intraoperative ventilation mode, maximum peak airway pressure, and minimum oxygenation index.
- The nomogram demonstrated strong predictive performance with C-indices of 0.909 in the training cohort and 0.871 in the validation cohort.
- Calibration curves indicated good agreement between predicted and observed complication rates.
Conclusions:
- The developed nomogram offers excellent predictive accuracy for pediatric postoperative pulmonary complications following one-lung ventilation.
- This tool enables early risk stratification and facilitates targeted interventions to enhance patient outcomes.
- The nomogram utilizes objective and readily available perioperative factors for clinical application.
Background:
Since the respiratory anatomy and physiology of children differ from those of adults, they are more susceptible to postoperative pulmonary complications after thoracic surgery that requires one-lung ventilation. Hypothesizing that the incidence of postoperative pulmonary complications could be predicted using easily accessible perioperative variables, we aimed to develop a nomogram specifically for children receiving thoracic surgery with one-lung ventilation.
Methods:
A total of 361 children undergoing thoracic surgery with one-lung ventilation were randomly assigned to two groups: a training cohort (80%) and a validation cohort (20%). The training cohort was utilized to develop a nomogram, whereas the validation cohort was used to assess its performance. The outcome of this study was the incidence of postoperative pulmonary complications. Univariate analysis and the least absolute shrinkage and selection operator regression model were applied to select the most relevant prognostic predictors. Multivariable logistic regression was used to develop a nomogram based on the selected prediction factors. Internal validation was conducted to evaluate its performance. The C-index and calibration plots were used to assess its discriminative ability and calibration.
Results:
Among the included patients, 109 (30.2%) presented postoperative pulmonary complications. Four predictive factors were ultimately selected to develop the nomogram. They were preoperative neutrophil-to-lymphocyte ratio, intraoperative ventilation mode, maximum peak airway pressure and minimum oxygenation index during one-lung ventilation. By incorporating these factors, the nomogram demonstrated strong C-indices of 0.909 (95% confidence interval (CI) [0.809-0.82]) and 0.871 (95% CI [0.795-0.945]) in the training and validation cohorts, respectively, along with well-matched calibration curves.
Conclusion:
The nomogram, based on four objective and easily assessed factors, demonstrates excellent predictive performance for pediatric postoperative pulmonary complications after one-lung ventilation, enabling early risk assessment and targeted interventions to improve patient outcomes.
Trial Registration:
This study is registered at the Chinese Clinical Trial Registry (Registration number: ChiCTR2300072042, Date of Registration: 1/6/2023).
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