Multilevel Body Composition Analysis on Chest Computed Tomography Predicts Hospital Length of Stay and Complications after Lobectomy for Lung Cancer: A Multicenter Study

Till D. Best; Sarah F. Mercaldo; Darren S. Bryan; Jan Peter Marquardt; Maria M. Wrobel; Christopher P. Bridge; Fabian M. Troschel; Cylen Javidan; Jonathan H. Chung; Ashok Muniappan; Sanjeev Bhalla; Bryan F. Meyers; Mark K. Ferguson; Henning A. Gaissert; Florian J. Fintelmann

doi:10.1097/SLA.0000000000004040

Multilevel Body Composition Analysis on Chest Computed Tomography Predicts Hospital Length of Stay and Complications after Lobectomy for Lung Cancer: A Multicenter Study

Till D. Best, Sarah F. Mercaldo, Darren S. Bryan, Jan Peter Marquardt, Maria M. Wrobel, Christopher P. Bridge, Fabian M. Troschel, Cylen Javidan, Jonathan H. Chung, Ashok Muniappan, Sanjeev Bhalla, Bryan F. Meyers, Mark K. Ferguson, Henning A. Gaissert, Florian J. Fintelmann

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21 Scopus citations

Abstract

Objective:To investigate the impact of thoracic body composition on outcomes after lobectomy for lung cancerSummary and Background Data:Preoperative identification of patients at risk for adverse outcomes permits treatment modification. The impact of body composition on lung resection outcomes has not been investigated in a multicenter setting.Methods:A total of 958 consecutive patients undergoing lobectomy for lung cancer at 3 centers from 2014 to 2017 were retrospectively analyzed. Muscle and adipose tissue cross-sectional area at the fifth, eighth, and tenth thoracic vertebral body was quantified. Prospectively collected outcomes from a national database were abstracted to characterize the association between sums of muscle and adipose tissue and hospital length of stay (LOS), number of any postoperative complications, and number of respiratory postoperative complications using multivariate regression. A priori determined covariates were forced expiratory volume in 1 second and diffusion capacity of the lungs for carbon monoxide predicted, age, sex, body mass index, race, surgical approach, smoking status, Zubrod and American Society of Anesthesiologists scores.Results:Mean patient age was 67 years, body mass index 27.4 kg/m²and 65% had stage i disease. Sixty-three percent underwent minimally invasive lobectomy. Median LOS was 4 days and 34% of patients experienced complications. Muscle (using 30 cm²increments) was an independent predictor of LOS (adjusted coefficient 0.972; P = 0.002), any postoperative complications (odds ratio 0.897; P = 0.007) and postoperative respiratory complications (odds ratio 0.860; P = 0.010). Sarcopenic obesity was also associated with LOS and adverse outcomes.Conclusions:Body composition on preoperative chest computed tomography is an independent predictor of LOS and postoperative complications after lobectomy for lung cancer.

Original language	English
Pages (from-to)	E708-E715
Journal	Annals of surgery
Volume	275
Issue number	5
DOIs	https://doi.org/10.1097/SLA.0000000000004040
State	Published - May 1 2022

Keywords

BMI
LOS
adipose tissue
adverse events
body composition
body composition analysis
body mass index
complications
length of stay
lobectomy
lung cancer
lung resection
morphometric analysis
morphometrics
multilevel
multilevel body composition
muscle
postoperative events
sarcopenia
sarcopenic obesity
skeletal muscle
surgery

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10.1097/SLA.0000000000004040

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Best, T. D., Mercaldo, S. F., Bryan, D. S., Marquardt, J. P., Wrobel, M. M., Bridge, C. P., Troschel, F. M., Javidan, C., Chung, J. H., Muniappan, A., Bhalla, S., Meyers, B. F., Ferguson, M. K., Gaissert, H. A., & Fintelmann, F. J. (2022). Multilevel Body Composition Analysis on Chest Computed Tomography Predicts Hospital Length of Stay and Complications after Lobectomy for Lung Cancer: A Multicenter Study. Annals of surgery, 275(5), E708-E715. https://doi.org/10.1097/SLA.0000000000004040

@article{577db7d144c5477f99948ca423523f33,

title = "Multilevel Body Composition Analysis on Chest Computed Tomography Predicts Hospital Length of Stay and Complications after Lobectomy for Lung Cancer: A Multicenter Study",

abstract = "Objective:To investigate the impact of thoracic body composition on outcomes after lobectomy for lung cancerSummary and Background Data:Preoperative identification of patients at risk for adverse outcomes permits treatment modification. The impact of body composition on lung resection outcomes has not been investigated in a multicenter setting.Methods:A total of 958 consecutive patients undergoing lobectomy for lung cancer at 3 centers from 2014 to 2017 were retrospectively analyzed. Muscle and adipose tissue cross-sectional area at the fifth, eighth, and tenth thoracic vertebral body was quantified. Prospectively collected outcomes from a national database were abstracted to characterize the association between sums of muscle and adipose tissue and hospital length of stay (LOS), number of any postoperative complications, and number of respiratory postoperative complications using multivariate regression. A priori determined covariates were forced expiratory volume in 1 second and diffusion capacity of the lungs for carbon monoxide predicted, age, sex, body mass index, race, surgical approach, smoking status, Zubrod and American Society of Anesthesiologists scores.Results:Mean patient age was 67 years, body mass index 27.4 kg/m2and 65% had stage i disease. Sixty-three percent underwent minimally invasive lobectomy. Median LOS was 4 days and 34% of patients experienced complications. Muscle (using 30 cm2increments) was an independent predictor of LOS (adjusted coefficient 0.972; P = 0.002), any postoperative complications (odds ratio 0.897; P = 0.007) and postoperative respiratory complications (odds ratio 0.860; P = 0.010). Sarcopenic obesity was also associated with LOS and adverse outcomes.Conclusions:Body composition on preoperative chest computed tomography is an independent predictor of LOS and postoperative complications after lobectomy for lung cancer.",

keywords = "BMI, LOS, adipose tissue, adverse events, body composition, body composition analysis, body mass index, complications, length of stay, lobectomy, lung cancer, lung resection, morphometric analysis, morphometrics, multilevel, multilevel body composition, muscle, postoperative events, sarcopenia, sarcopenic obesity, skeletal muscle, surgery",

author = "Best, {Till D.} and Mercaldo, {Sarah F.} and Bryan, {Darren S.} and Marquardt, {Jan Peter} and Wrobel, {Maria M.} and Bridge, {Christopher P.} and Troschel, {Fabian M.} and Cylen Javidan and Chung, {Jonathan H.} and Ashok Muniappan and Sanjeev Bhalla and Meyers, {Bryan F.} and Ferguson, {Mark K.} and Gaissert, {Henning A.} and Fintelmann, {Florian J.}",

year = "2022",

month = may,

day = "1",

doi = "10.1097/SLA.0000000000004040",

language = "English",

volume = "275",

pages = "E708--E715",

journal = "Annals of surgery",

issn = "0003-4932",

number = "5",

}

Best, TD, Mercaldo, SF, Bryan, DS, Marquardt, JP, Wrobel, MM, Bridge, CP, Troschel, FM, Javidan, C, Chung, JH, Muniappan, A, Bhalla, S , Meyers, BF, Ferguson, MK, Gaissert, HA & Fintelmann, FJ 2022, 'Multilevel Body Composition Analysis on Chest Computed Tomography Predicts Hospital Length of Stay and Complications after Lobectomy for Lung Cancer: A Multicenter Study', Annals of surgery, vol. 275, no. 5, pp. E708-E715. https://doi.org/10.1097/SLA.0000000000004040

TY - JOUR

T1 - Multilevel Body Composition Analysis on Chest Computed Tomography Predicts Hospital Length of Stay and Complications after Lobectomy for Lung Cancer

T2 - A Multicenter Study

AU - Best, Till D.

AU - Mercaldo, Sarah F.

AU - Bryan, Darren S.

AU - Marquardt, Jan Peter

AU - Wrobel, Maria M.

AU - Bridge, Christopher P.

AU - Troschel, Fabian M.

AU - Javidan, Cylen

AU - Chung, Jonathan H.

AU - Muniappan, Ashok

AU - Bhalla, Sanjeev

AU - Meyers, Bryan F.

AU - Ferguson, Mark K.

AU - Gaissert, Henning A.

AU - Fintelmann, Florian J.

PY - 2022/5/1

Y1 - 2022/5/1

N2 - Objective:To investigate the impact of thoracic body composition on outcomes after lobectomy for lung cancerSummary and Background Data:Preoperative identification of patients at risk for adverse outcomes permits treatment modification. The impact of body composition on lung resection outcomes has not been investigated in a multicenter setting.Methods:A total of 958 consecutive patients undergoing lobectomy for lung cancer at 3 centers from 2014 to 2017 were retrospectively analyzed. Muscle and adipose tissue cross-sectional area at the fifth, eighth, and tenth thoracic vertebral body was quantified. Prospectively collected outcomes from a national database were abstracted to characterize the association between sums of muscle and adipose tissue and hospital length of stay (LOS), number of any postoperative complications, and number of respiratory postoperative complications using multivariate regression. A priori determined covariates were forced expiratory volume in 1 second and diffusion capacity of the lungs for carbon monoxide predicted, age, sex, body mass index, race, surgical approach, smoking status, Zubrod and American Society of Anesthesiologists scores.Results:Mean patient age was 67 years, body mass index 27.4 kg/m2and 65% had stage i disease. Sixty-three percent underwent minimally invasive lobectomy. Median LOS was 4 days and 34% of patients experienced complications. Muscle (using 30 cm2increments) was an independent predictor of LOS (adjusted coefficient 0.972; P = 0.002), any postoperative complications (odds ratio 0.897; P = 0.007) and postoperative respiratory complications (odds ratio 0.860; P = 0.010). Sarcopenic obesity was also associated with LOS and adverse outcomes.Conclusions:Body composition on preoperative chest computed tomography is an independent predictor of LOS and postoperative complications after lobectomy for lung cancer.

AB - Objective:To investigate the impact of thoracic body composition on outcomes after lobectomy for lung cancerSummary and Background Data:Preoperative identification of patients at risk for adverse outcomes permits treatment modification. The impact of body composition on lung resection outcomes has not been investigated in a multicenter setting.Methods:A total of 958 consecutive patients undergoing lobectomy for lung cancer at 3 centers from 2014 to 2017 were retrospectively analyzed. Muscle and adipose tissue cross-sectional area at the fifth, eighth, and tenth thoracic vertebral body was quantified. Prospectively collected outcomes from a national database were abstracted to characterize the association between sums of muscle and adipose tissue and hospital length of stay (LOS), number of any postoperative complications, and number of respiratory postoperative complications using multivariate regression. A priori determined covariates were forced expiratory volume in 1 second and diffusion capacity of the lungs for carbon monoxide predicted, age, sex, body mass index, race, surgical approach, smoking status, Zubrod and American Society of Anesthesiologists scores.Results:Mean patient age was 67 years, body mass index 27.4 kg/m2and 65% had stage i disease. Sixty-three percent underwent minimally invasive lobectomy. Median LOS was 4 days and 34% of patients experienced complications. Muscle (using 30 cm2increments) was an independent predictor of LOS (adjusted coefficient 0.972; P = 0.002), any postoperative complications (odds ratio 0.897; P = 0.007) and postoperative respiratory complications (odds ratio 0.860; P = 0.010). Sarcopenic obesity was also associated with LOS and adverse outcomes.Conclusions:Body composition on preoperative chest computed tomography is an independent predictor of LOS and postoperative complications after lobectomy for lung cancer.

KW - BMI

KW - LOS

KW - adipose tissue

KW - adverse events

KW - body composition

KW - body composition analysis

KW - body mass index

KW - complications

KW - length of stay

KW - lobectomy

KW - lung cancer

KW - lung resection

KW - morphometric analysis

KW - morphometrics

KW - multilevel

KW - multilevel body composition

KW - muscle

KW - postoperative events

KW - sarcopenia

KW - sarcopenic obesity

KW - skeletal muscle

KW - surgery

UR - http://www.scopus.com/inward/record.url?scp=85130004357&partnerID=8YFLogxK

U2 - 10.1097/SLA.0000000000004040

DO - 10.1097/SLA.0000000000004040

M3 - Article

C2 - 32773626

AN - SCOPUS:85130004357

SN - 0003-4932

VL - 275

SP - E708-E715

JO - Annals of surgery

JF - Annals of surgery

IS - 5

ER -

Multilevel Body Composition Analysis on Chest Computed Tomography Predicts Hospital Length of Stay and Complications after Lobectomy for Lung Cancer: A Multicenter Study

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Keywords

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