Risk factors for postoperative pulmonary infection in patients with non-small cell lung cancer: analysis based on regression models and construction of a nomogram prediction model.
This study was designed to analyze risk factors for postoperative pulmonary infection (PPI) in patients with non-small cell lung cancer (NSCLC) based on regression models and to construct a corresponding nomogram prediction model.
A total of 244 patients with NSCLC who received surgical treatment from June 2015 to January 2017 were retrospectively analyzed. According to the PPI, they were assigned to a pulmonary infection group (n=27) or non-pulmonary infection group (n=217). The independent risk factors for PPI in NSCLC patients were screened through least absolute shrinkage and selection operator (LASSO) and logistic regression analysis, and a corresponding nomogram prediction model was constructed.
A total of 244 NSCLC patients were included, including 27 with PPI (11.06%). According to LASSO regression-based screening, age, diabetes mellitus (DM), tumor node metastasis (TNM) staging, chemotherapy regimen, chemotherapy cycle, post-chemotherapy albumin (g/L), pre-chemotherapy KPS and operation time were all significant and found to be the influencing factors for PPI. The risk model constructed based on LASSO was 0.0035770333 + (0.0020227686* age) + (0.057554487* DM) + (0.016365428* TNM staging) + (0.048514458* chemotherapy regimen) + (0.00871801* chemotherapy cycle) + (-0.002096683* post-chemotherapy albumin (g/L) + (-0.00090206* pre-chemotherapy Karnofsky performance score (KPS)) + (0.000296876* operation time). The pulmonary infection group got significantly higher risk scores than the non-pulmonary infection group (P<0.0001). According to receiver operating characteristic (ROC) curve-based analysis, the area under the curve (AUC) of risk score in predicting pulmonary infection was 0.894. Based on 4 independent predictors, a risk-prediction nomogram model was constructed to predict pulmonary infection in NSCLC patients after surgery. The internal verification C-index was 0.900 (95% CI: 0.839-0.961), and the calibration curves were well fitted with the ideal ones.
The prediction model based on a regression model for PPI in NSCLC patients demonstrates good prediction efficiency, which is conducive to early screening of high-risk patients and further improvement of treatment regimen.
Ding Z
，Wang X
，Jiang S
，Liu J
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GLIM diagnosed malnutrition predicts clinical outcomes and quality of life in patients with non-small cell lung cancer.
The high prevalence of malnutrition in non-small cell lung cancer (NSCLC) patients has numerous negative consequences on patients' outcome when undergoing anti-neoplastic treatment. The Global Leadership Initiative on Malnutrition (GLIM) criteria for diagnosis of malnutrition are currently being verified; however, studies validating GLIM criteria in NSCLC patients are lacking. This study aimed to evaluate clinical outcomes and Quality of Life (QoL) in malnourished compared to well-nourished NSCLC patients to determine the predictive validity of GLIM criteria.
We collected data on adverse events, survival, and QoL from NSCLC patients undergoing first line anti-neoplastic treatment collected from two prospective trials. Patients were categorized by GLIM criteria as malnourished or well-nourished, based on non-volitional weight loss, low Body Mass Index, reduced muscle mass (Computed Tomography-scans), reduced food intake (24-h recall), and inflammatory condition (modified Glasgow Prognostic Score). Differences in descriptive data, adverse events, survival, and QoL between the malnourished and well-nourished patients were analyzed.
Overall, 120 patients were included in the study. Malnourished patients compared to well-nourished patients had significantly worse outcome in terms of treatment cessation (n = 21 vs 13, p = 0.049), disease progression (n = 20 vs 12, p = 0.034) and shorter overall survival (HR 2.0, 95% CI: 1.2, 3.4, p = 0.009). Stratifying by severity, moderately malnourished patients had a shorter overall survival compared to well-nourished patients (HR 2.1, 95% CI: 1.2, 3.6, p = 0.007). Malnutrition at baseline was associated with poor QoL by lower physical (p < 0.001) and role functioning (p = 0.011), more symptoms of fatigue (p = 0.001), nausea and vomiting (p = 0.009), pain (p < 0.001), dyspnea (p = 0.032), appetite loss (p < 0.001), and constipation (p = 0.029). No significant differences were found in hospitalization, dose reductions, or treatment postponement.
Malnutrition defined by GLIM criteria in NSCLC patients was associated with more frequent early cessation of anti-neoplastic treatment, shorter overall survival, and poorer QoL compared to well-nourished patients.
Landgrebe M
，Tobberup R
，Carus A
，Rasmussen HH
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ResearchGate
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