Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Randomized Controlled Trial
. 2022 Aug 3;20(1):249.
doi: 10.1186/s12957-022-02716-w.

Construction and validation of a nomogram for predicting prolonged air leak after minimally invasive pulmonary resection

Rongyang Li  1 , Mengchao Xue  1 , Zheng Ma  1 , Chenghao Qu  1 , Kun Wang  1 , Yu Zhang  1 , Weiming Yue  1 , Huiying Zhang  1 , Hui Tian  2
Affiliations
Randomized Controlled Trial

Construction and validation of a nomogram for predicting prolonged air leak after minimally invasive pulmonary resection

Rongyang Li et al. World J Surg Oncol. .

Abstract

Background: Prolonged air leak (PAL) remains one of the most frequent postoperative complications after pulmonary resection. This study aimed to develop a predictive nomogram to estimate the risk of PAL for individual patients after minimally invasive pulmonary resection.

Methods: Patients who underwent minimally invasive pulmonary resection for either benign or malignant lung tumors between January 2020 and December 2021 were included. All eligible patients were randomly assigned to the training cohort or validation cohort at a 3:1 ratio. Univariate and multivariate logistic regression were performed to identify independent risk factors. All independent risk factors were incorporated to establish a predictive model and nomogram, and a web-based dynamic nomogram was then built based on the logistic regression model. Nomogram discrimination was assessed using the receiver operating characteristic (ROC) curve. The calibration power was evaluated using the Hosmer-Lemeshow test and calibration curves. The nomogram was also evaluated for clinical utility by the decision curve analysis (DCA).

Results: A total of 2213 patients were finally enrolled in this study, among whom, 341 cases (15.4%) were confirmed to have PAL. The following eight independent risk factors were identified through logistic regression: age, body mass index (BMI), smoking history, percentage of the predicted value for forced expiratory volume in 1 second (FEV1% predicted), surgical procedure, surgical range, operation side, operation duration. The area under the ROC curve (AUC) was 0.7315 [95% confidence interval (CI): 0.6979-0.7651] for the training cohort and 0.7325 (95% CI: 0.6743-0.7906) for the validation cohort. The P values of the Hosmer-Lemeshow test were 0.388 and 0.577 for the training and validation cohorts, respectively, with well-fitted calibration curves. The DCA demonstrated that the nomogram was clinically useful. An operation interface on a web page ( https://lirongyangql.shinyapps.io/PAL_DynNom/ ) was built to improve the clinical utility of the nomogram.

Conclusion: The nomogram achieved good predictive performance for PAL after minimally invasive pulmonary resection. Patients at high risk of PAL could be identified using this nomogram, and thus some preventive measures could be adopted in advance.

Keywords: Minimally invasive pulmonary resection; Nomogram; Predictive model; Prolonged air leak; Risk factor.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Flow diagram of patient selection through the study. PAL, prolonged air leak
Fig. 2
Fig. 2
A nomogram for prediction of PAL risk after minimally invasive pulmonary resection. Draw a vertical line from the corresponding axis of each variable to the points axis to acquire the point of this variable. Make a summation of the points for each variable to yield a total score, and the probability of PAL could be estimated by projecting the total score to the lower total point axis. BMI, body mass index; FEV1, forced expiratory volume in one second; PAL, prolonged air leak
Fig. 3
Fig. 3
ROC curves of the nomogram for predicting PAL in the training and validation cohorts. ROC, receiver operating characteristic; AUC, areas under the ROC curve; PAL, prolonged air leak
Fig. 4
Fig. 4
Calibration curves of the prediction nomogram in the training cohort (A) and validation cohort (B). The x-axis represents the nomogram-predicted probability, and the y-axis represents the actual probability of PAL. The black pointed line represents the ideal curve, the red solid line represents the apparent curve (non-correction), and the blue solid line represents the bias-correction curve by bootstrapping (B = 1000 repetitions). PAL, prolonged air leak
Fig. 5
Fig. 5
Decision curve analysis for the PAL nomogram in the training and validation cohorts. The y-axis measures the net benefit, the black line represents the assumption of PAL-none-patients, the gray line represents the assumption of PAL-all-patients, the red line represents the training cohort, and the blue line represents the validation cohort. PAL, prolonged air leak
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Oudkerk M, Liu S, Heuvelmans MA, Walter JE, Field JK. Lung cancer LDCT screening and mortality reduction - evidence, pitfalls and future perspectives. Nat Rev Clin Oncol. 2021;18(3):135–151. doi: 10.1038/s41571-020-00432-6. - DOI - PubMed
    1. Demmy TL, Yendamuri S, D'Amico TA, Burfeind WR. Oncologic equivalence of minimally invasive lobectomy: the scientific and practical arguments. Ann Thorac Surg. 2018;106(2):609–617. doi: 10.1016/j.athoracsur.2018.02.089. - DOI - PubMed
    1. Shen H, Wang X, Nie Y, Zhang K, Wei Z, Yang F, et al. Minimally invasive surgery versus thoracotomy for resectable stage II and III non-small-cell lung cancers: a systematic review and meta-analysis. Eur J Cardio-Thor Surg. 2021;59(5):940–950. doi: 10.1093/ejcts/ezaa437. - DOI - PubMed
    1. Bronstein ME, Koo DC, Weigel TL. Management of air leaks post-surgical lung resection. Ann Transl Med. 2019;7(15):361. doi: 10.21037/atm.2019.04.30. - DOI - PMC - PubMed
    1. Hoeijmakers F, Hartemink KJ, Verhagen AF, Steup WH, Marra E, Roell WFB, et al. Variation in incidence, prevention and treatment of persistent air leak after lung cancer surgery. Eur J Cardio-Thor Surg. 2021;61(1):110–117. doi: 10.1093/ejcts/ezab376. - DOI - PMC - PubMed

Publication types

LinkOut - more resources