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A risk model for prolonged air leak after lobectomy using the National Clinical Database in Japan

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Abstract

Purpose

The objective of our study was to develop a clinical prediction model for prolonged air leak (PAL) after lobectomy for lung cancer using preoperative variables in a large patient dataset from the National Clinical Database (NCD) in Japan.

Methods

The preoperative characteristics of 57,532 and 30,967 patients who had undergone standard lobectomy for lung cancer were derived from the 2014 to 2015 and 2016 NCD datasets, respectively. PAL was defined as air leak persisting ≥ 7 days postoperatively or requiring postoperative interventional treatment, such as pleurodesis or reoperation. Risk models were developed from the 2014 to 2015 dataset and validated using the 2016 dataset. When performing model derivation, the least absolute shrinkage and selection operator (LASSO) method were applied for parameter selection.

Results

The rate of PAL was 4.5% in 2014–2015 and 5.3% in 2016. The age, sex, body mass index, comorbid interstitial pneumonia, smoking habits, forced expiratory volume in 1 s, tumor histology, multiple lung cancer, and tumor location were selected as important variables for PAL. Our risk model for predicting PAL was fair with a concordance index of 0.6895.

Conclusion

The LASSO-based risk model for PAL after lobectomy provided important preoperative variables for PAL and risk weighting for each variable.

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Abbreviations

PAL:

Prolonged air leak

NCD:

National Clinical Database

BMI:

Body mass index

FEV1:

Forced expiratory volume in 1 s

FVC:

Forced vital capacity

LASSO:

Least absolute shrinkage and selection operator

BIC:

Bayesian information criterion

VC:

Vital capacity

ROC:

Receiver-operating characteristic

AUC:

Area under the curve

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Acknowledgements

The authors wish to thank all of the data managers and contributors at the participating institutions in this NCD project.

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Authors and Affiliations

  1. Japanese Association for Chest Surgery, Kyoto, Japan

    Yasushi Shintani, Yukio Sato, Kimihiro Shimizu, Shunsuke Endo, Morihito Okada, Kenji Suzuki & Masayuki Chida

  2. Department of General Thoracic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan

    Yasushi Shintani

  3. Department of Healthcare Quality Assessment, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

    Hiroyuki Yamamoto, Eriko Fukuchi & Hiroaki Miyata

  4. Faculty of Medicine, Department of Thoracic Surgery, University of Tsukuba, Ibaraki, Japan

    Yukio Sato

  5. Division of Thoracic Surgery, Department of Surgery, Shinshu University School of Medicine, Nagano, Japan

    Kimihiro Shimizu

  6. Department of Thoracic Surgery, Jichi Medical University, Tochigi, Japan

    Shunsuke Endo

  7. Department of Surgical Oncology, Hiroshima University, Hiroshima, Japan

    Morihito Okada

  8. Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan

    Kenji Suzuki

  9. Department of General Thoracic Surgery, Dokkyo Medical University, Tochigi, Japan

    Masayuki Chida

Authors
  1. Yasushi Shintani
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  2. Hiroyuki Yamamoto
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  3. Yukio Sato
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  4. Kimihiro Shimizu
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  5. Shunsuke Endo
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  6. Morihito Okada
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  7. Kenji Suzuki
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  8. Eriko Fukuchi
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  9. Hiroaki Miyata
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  10. Masayuki Chida
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Corresponding author

Correspondence to Yasushi Shintani.

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Conflict of interest

Yamamoto H, Fukuchi E, and Miyata H are affiliated with the Department of Healthcare Quality Assessment at the University of Tokyo. The department is a social collaboration department supported by grants from NCD, Johnson & Johnson K.K., and Nipro Co.

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Shintani, Y., Yamamoto, H., Sato, Y. et al. A risk model for prolonged air leak after lobectomy using the National Clinical Database in Japan. Surg Today 52, 69–74 (2022). https://doi.org/10.1007/s00595-021-02300-x

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  • DOI: https://doi.org/10.1007/s00595-021-02300-x

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