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Early prediction of neonatal chronic lung disease: a comparison of three scoring methods
B A Yoder1, M U Anwar, R H Clark
1Department of Pediatrics, Wilford Hall Medical Center, Lackland Air Force Base, San Antonio, Texas 52636-02, USA. yoder_b@whmc-lafb.af.mil
Insights
A new Respiratory Failure Score (RFS) accurately predicts neonatal chronic lung disease (CLD) in high-risk infants. This simple method improves early patient selection for clinical trials investigating CLD prevention therapies.
Area of Science:
- Neonatology
- Pediatric Pulmonology
- Clinical Trial Design
Background:
- Neonatal chronic lung disease (CLD) poses significant challenges, necessitating effective early identification of high-risk infants for intervention trials.
- Existing predictive models for CLD, such as the Sinkin and Ryan models, require validation in diverse populations.
- Optimizing patient selection is crucial for the success of clinical trials evaluating postnatal therapies for CLD.
Purpose of the Study:
- To develop and validate a simple clinical scoring system, the Respiratory Failure Score (RFS), for early prediction of neonatal CLD.
- To compare the predictive performance of the RFS with established Sinkin and Ryan models in distinct infant populations.
- To enhance the efficiency of clinical trials by improving the selection of high-risk infants for early intervention.
Main Methods:
- A prospective cohort study was conducted involving infants born at <32 weeks gestation.
- A Respiratory Failure Score (RFS) was developed using logistic regression, identifying gestation, birth weight, and RFS as key predictors.
- The RFS, Sinkin, and Ryan models were retrospectively and prospectively compared using receiver operating characteristic (ROC) curves in multiple study groups.
Main Results:
- The RFS, incorporating gestation and birth weight, demonstrated strong predictive capability for neonatal CLD.
- All evaluated models (RFS, Sinkin, Ryan) showed similar performance across different study populations.
- The RFS, assessed at 72 hours of age, exhibited the largest area under the ROC curve, indicating superior predictive accuracy for CLD at 36 weeks postconceptional age.
Conclusions:
- The RFS is a reliable and simple method for the early prediction of neonatal CLD in preterm infants.
- Implementing the RFS can significantly improve the selection of infants for early prevention trials, thereby optimizing research outcomes.
- This validated scoring system offers a valuable tool for clinicians and researchers focused on mitigating the impact of CLD.
Abstract:
A variety of postnatal therapies have been and will be evaluated for prevention or treatment of neonatal chronic lung disease (CLD). A simple method for early selection of the highest risk infants would optimize intervention trials. Our study compared a clinical scoring system for predicting neonatal CLD (defined at 36 weeks postconceptional age) with previous regression models developed by Sinkin et al. (Sinkin model) [Pediatrics 1990;86:728-736] and Ryan et al. (Ryan model) [Eur J Pediatr 1996;668-671] in two distinct populations. A respiratory failure score (RFS) was prospectively developed for infants at <32 weeks of gestation admitted to the Wilford Hall Medical Center from January 1990-December 1992. Logistic regression modeling identified three independent predictors of CLD: gestation, birth weight, and RFS. Applying a modified RFS score (to include gestation and birth weight), the RFS, Sinkin, and Ryan models were compared among high-risk infants admitted to Wilford Hall from January 1993-December 1995, and to Crawford Long Hospital (Atlanta, GA) from January 1993-December 1994. Predictive values, sensitivity, specificity, and receiver operating characteristic (ROC) curves were determined for the primary outcome variable: CLD at 36 weeks of corrected gestation. Of 248 infants at <32 weeks admitted to Wilford Hall, 220 survived >7 days. Thirty of 31 (97%) infants diagnosed with CLD were <29 weeks or < or =1,000 g at birth. Despite important demographic and treatment differences between the study populations, similar ROC curves were found for each scoring method when individually evaluated among the three study groups. The RFS method at 72 h demonstrated the greatest area under the ROC curve for prediction of neonatal CLD in the groups as a whole. Application of the RFS method for early prediction of neonatal CLD at age 72 h should improve patient selection for early prevention trials.
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