Development and validation of a predictive model for postoperative pulmonary
complications after colorectal cancer surgery: a retrospective study
#MMPMID41121106
Huang Y
; Zhong Y
; Wei W
; Zheng N
; Lin N
World J Surg Oncol
2025[Oct]; 23
(1
): 391
PMID41121106
show ga
BACKGROUND: Postoperative pulmonary complications (PPCs) significantly impact
patient outcomes after colorectal cancer (CRC) surgery. Studies on PPCs
associated with CRC remain limited. This study was designed to create and verify
a risk prediction model through the identification of factors associated with a
higher risk of PPCs after CRC surgery. METHODS: Patients who underwent CRC
surgery at Fujian Medical University Union Hospital from September 2019 through
September 2021 were included in this study. They were divided into training and
validation groups and categorized into the PPC group and non-PPC group. We used
multivariable logistic regression analysis to determine independent predictors of
PPCs. A nomogram was constructed using the identified risk factors and later
validated via receiver operating characteristic (ROC) curves, calibration curves,
and decision curve analysis to assess its predictive performance. RESULTS: A
total of 1861 patients were enrolled and allocated to training and testing sets
at an 80:20 ratio. The analyzed results revealed that surgical site, surgical
approach, duration of surgery, age, perioperative blood transfusion, asthma, and
fasting plasma glucose were risk factors for PPCs in patients with CRC. The
receiver operating characteristic curve areas under the curve (AUCs) for the
training and validation sets were 0.734 and 0.732, respectively. We found that
the model calibration curve showed favorable consistency, whereas decision curve
analysis (DCA) revealed a substantial expected net benefit. CONCLUSIONS: The
model demonstrates high predictive accuracy and efficiency for PPCs in patients
undergoing CRC surgery. TRIAL REGISTRATION: This study was registered at the
Chinese Clinical Trials Registry ( http://www.chictr.org.cn ) on November 28,
2024, with registration number ChiCTR2400093107.
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