Work

Development of a nomogram to predict the need for more than one Nuss bar in pectus excavatum

Year: 2026

Type: article

Abstract: Dear Editor,Figure 1.: (A) Nomogram predicting the need for more than one Nuss bar. (B) Calibration curve showing good agreement between predicted and observed probabilities, indicating excellent model fit and robust predictive performance. Pectus excavatum (PE), the most common congenital deformity of the anterior chest wall, leads to abnormal thoracic morphology and varying degrees of cardiopulmonary impairment[1]. It also exerts a significant psychosocial impact, particularly among children and adolescents[2]. The Nuss procedure has become the standard treatment for PE; however, achieving optimal individualized correction remains a major surgical challenge, particularly in determining whether to place a single or multiple Nuss bars[3]. Currently, this decision relies primarily on the surgeon’s subjective assessment of preoperative imaging, lacking objective and quantitative tools for guidance. Such subjectivity may result in overcorrection or undercorrection, especially in low-volume centers or less-experienced hands, thereby affecting outcomes and increasing the risk of reoperation. This study aimed to develop and validate a nomogram model based on clinical and radiological parameters to predict the required number of Nuss bars in patients with PE, providing a quantitative and intuitive tool to support preoperative decision-making. This study adheres to the Transparency In The reporting of Artificial INtelligence (TITAN) Guidelines 2025 for transparency and integrity in the use of artificial intelligence in research and publication[4]. Patients who underwent the Nuss procedure for PE at our institution between 2020 and 2023 were retrospectively reviewed, excluding those without preoperative computed tomography (CT) at our hospital or lost to follow-up. The number of Nuss bars was jointly determined by two senior pediatric thoracic surgeons after comprehensive evaluation. Clinical variables included age, height, weight, and body mass index (BMI). Radiological parameters were derived from quantitative CT measurements: sternovertebral distance (SVD), Haller index (HI), asymmetry index (AI), correction index (CI), and flatness index (FI). All measurements were performed at the level of maximal sternal depression. SVD was the shortest sternum-to-vertebra distance; HI and CI assessed deformity severity. AI quantified asymmetry from left–right hemithorax diameter differences. FI was the transverse-to-longitudinal diameter ratio, indicating chest flatness (Supplemental Digital Content Figure 1, available at: https://links.lww.com/JS9/G813). Continuous variables were expressed as mean ± standard deviation, and intergroup comparisons were conducted using independent-samples t-tests. To construct the predictive model, least absolute shrinkage and selection operator (LASSO) regression was first applied to all candidate variables to avoid multicollinearity and identify the most informative predictors[5]. The penalty parameter λ was selected using 10-fold cross-validation based on the minimum-λ criterion. Subsequently, Firth’s penalized logistic regression was used to develop the final model, minimizing bias due to the limited sample size and outcome imbalance. Based on this model, a nomogram was constructed to visually estimate the probability of requiring dual Nuss bars. Model discrimination was evaluated using the receiver operating characteristic curve and the area under the curve (AUC). Model calibration was internally validated using 1000 bootstrap resamples to obtain the bias-corrected AUC, and calibration performance was visualized using calibration plots generated with the rms package[6]. A total of 64 patients were included in the final analysis, comprising 46 patients who received a single Nuss bar and 18 who received dual bars. No complications attributable to the number of bars occurred in any patient, and all patients reported satisfaction with both the therapeutic outcomes and overall treatment cost. Differences were observed between the two groups (Table 1), particularly in age, height, weight, and CI (P < 0.05). Table 1 - Baseline characteristics and group comparison Variable Total (n = 64) One Nuss bar (n = 48) Dual Nuss bars (n = 16) P-value Age (days) 4535.30 ± 1016.18 4266.81 ± 990.67 5340.75 ± 582.38 <0.001 Height (cm) 156.72 ± 17.17 151.79 ± 16.15 171.50 ± 10.50 <0.001 Weight (kg) 39.78 ± 11.59 36.89 ± 11.35 47.66 ± 8.23 <0.001 BMI 15.71 ± 2.15 15.56 ± 2.09 16.17 ± 2.33 0.33 SVD (mm) 61.50 ± 14.63 63.28 ± 13.54 56.17 ± 16.88 0.09 HI 3.85 ± 1.57 3.50 ± 0.70 4.89 ± 2.70 0.06 CI 0.28 ± 0.12 0.26 ± 0.09 0.36 ± 0.16 0.02 AI 1.00 ± 0.06 1.00 ± 0.05 0.98 ± 0.07 0.21 FI 1.66 ± 0.15 1.64 ± 0.13 1.73 ± 0.20 0.06 BMI = body mass index; SVD = sternovertebral distance; HI = Haller index; CI = correction index; AI = asymmetry index; FI = flatness index.Values are presented as mean ± standard deviation. P-values were derived from independent t-tests for continuous variables. LASSO regression identified five key predictors – age, height, SVD, HI, and CI – for inclusion in the final model (Fig. 1A). The original model achieved an AUC of 0.915. After Firth correction and bootstrap internal validation, the bias-corrected AUC was 0.875, demonstrating excellent discriminative performance. The calibration curve showed strong agreement between predicted and observed probabilities, with the bias-corrected curve nearly overlapping the ideal line, indicating good model fit and robust predictive performance (Fig. 1B). The resulting nomogram visually illustrates the contribution of each variable to the prediction, providing a quantitative reference for preoperative assessment. This study established a nomogram model capable of predicting the need for dual Nuss bars in patients with PE based on basic clinical data and preoperative CT parameters. The model offers practical, noninvasive, and cost-effective advantages, assisting surgeons in preoperative decision-making, reducing subjectivity, and optimizing corrective outcomes. The findings of this study are subject to several limitations. Our sample size is limited, and the cohort exclusively comprised pediatric patients (none of whom required more than two bars). Although most PE repairs are performed in childhood, these characteristics may restrict the model’s applicability to adult populations. Therefore, future multicenter studies are warranted to validate and generalize this nomogram and to determine whether its clinical application can lead to measurable improvements in patient outcomes.

Source: International Journal of Surgery

DOI: 10.1097/js9.0000000000004917

Authors: Xiaosong Huang, Jiajun Chen, Huijiao Xu, Wenying Liu, Siyu Pu

Institutions: Sichuan University, West China Second University Hospital of Sichuan University

Language: English

Topic: Pectus Deformity Diagnosis and Treatment

Subfield: Surgery

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,450