Normalized Pulmonary Artery Diameter Predicts Occurrence of Postpneumonectomy Respiratory Failure, ARDS, and Mortality

Risk Factor Analysis Including Inflammatory Markers for ICU Admission and Survival After Pneumonectomy

Background and Objectives: To assess the impact of preoperative inflammatory parameters on the necessity for intensive care unit (ICU) admission and survival after pneumonectomy. Materials and Methods: We enrolled 207 adult patients who underwent pneumonectomy between December 2016 and January 2022. We collected data from patients' electronic medical records. Results: The preoperative albumin level was statistically lower, need for blood transfusion was higher, and length of hospital stay was longer in ICU-admitted patients (p = 0.017, p = 0.020, and p = 0.026, respectively). In multivariate analysis, intra-pericardial pneumonectomy and postoperative complications were predictive factors for ICU admission (OR = 3.46; 95%CI: 1.45-8.23; p = 0.005 and OR = 5.10; 95%CI: 2.21-11.79; p < 0.001, respectively). Sleeve or pericardial pneumonectomy (p = 0.010), intraoperative vascular injury (p = 0.003), the need for mechanical ventilation (p < 0.001), acute renal failure (p = 0.018), sepsis (p = 0.008), respiratory failure (p < 0.001), pneumonia (p = 0.025), the need for blood transfusion (p = 0.047), elevated blood urea nitrogen (BUN) (p = 0.046), and elevated creatinine levels (p = 0.004) were more common in patients who died within 28 days. Patients who died within 90 days exhibited higher preoperative neutrophil-to-lymphocyte ratio (NLR) values (p = 0.019) and serum creatinine levels (p = 0.008), had a greater prevalence of sleeve or intra-pericardial pneumonectomy (p = 0.002), the need for mechanical ventilation (p < 0.001), intraoperative vascular injury (p = 0.049), sepsis (p < 0.001), respiratory failure (p = 0.019), and contralateral pneumonia (p = 0.008) than those who did not. Conclusions: Intra-pericardial pneumonectomy and postoperative complications are independent predictors of ICU admission after pneumonectomy. Tracheal sleeve and intra-pericardial procedures, intraoperative and postoperative complications, the need for blood transfusion, preoperative NLR ratio, BUN and creatinine levels may also be potential risk factors for mortality.

Predicting complication risks after sleeve lobectomy for non-small cell lung cancer

Background

Sleeve lobectomy is a challenging procedure with a high risk of postoperative complications. To facilitate surgical decision-making and optimize perioperative treatment, we developed risk stratification models to quantify the probability of postoperative complications after sleeve lobectomy.

Methods

We retrospectively analyzed the clinical features of 691 non-small cell lung cancer (NSCLC) patients who underwent sleeve lobectomy between July 2016 and December 2019. Logistic regression models were trained and validated in the cohort to predict overall complications, major complications, and specific minor complications. The impact of specific complications in prognostic stratification was explored via the Kaplan-Meier method.

Results

Of 691 included patients, 232 (33.5%) developed complications, including 35 (5.1%) and 197 (28.5%) patients with major and minor complications, respectively. The models showed robust discrimination, yielding an area under the receiver operating characteristic (ROC) curve (AUC) of 0.853 [95% confidence interval (CI): 0.705-0.885] for predicting overall postoperative complication risk and 0.751 (95% CI: 0.727-0.762) specifically for major complication risks. Models predicting minor complications also achieved good performance, with AUCs ranging from 0.78 to 0.89. Survival analyses revealed a significant association between postoperative complications and poor prognosis.

Conclusions

Risk stratification models could accurately predict the probability and severity of complications in NSCLC patients following sleeve lobectomy, which may inform clinical decision-making for future patients.

Targeting Cell Signaling Pathways in Lung Cancer by Bioactive Phytocompounds

Lung cancer is a heterogeneous group of malignancies with high incidence worldwide. It is the most frequently occurring cancer in men and the second most common in women. Due to its frequent diagnosis and variable response to treatment, lung cancer was reported as the top cause of cancer-related deaths worldwide in 2020. Many aberrant signaling cascades are implicated in the pathogenesis of lung cancer, including those involved in apoptosis (B cell lymphoma protein, Bcl-2-associated X protein, first apoptosis signal ligand), growth inhibition (tumor suppressor protein or gene and serine/threonine kinase 11), and growth promotion (epidermal growth factor receptor/proto-oncogenes/phosphatidylinositol-3 kinase). Accordingly, these pathways and their signaling molecules have become promising targets for chemopreventive and chemotherapeutic agents. Recent research provides compelling evidence for the use of plant-based compounds, known collectively as phytochemicals, as anticancer agents. This review discusses major contributing signaling pathways involved in the pathophysiology of lung cancer, as well as currently available treatments and prospective drug candidates. The anticancer potential of naturally occurring bioactive compounds in the context of lung cancer is also discussed, with critical analysis of their mechanistic actions presented by preclinical and clinical studies.

ARDS after Pneumonectomy: How to Prevent It? Development of a Nomogram to Predict the Risk of ARDS after Pneumonectomy for Lung Cancer

(1) Background: The cause of ARDS after pneumonectomy is still unclear, and the study of risk factors is a subject of debate. (2) Methods: We reviewed a large panel of pre-, peri- and postoperative data of 211 patients who underwent pneumonectomy during the period 2014−2021. Univariable and multivariable logistic regression was used to quantify the association between preoperative parameters and the risk of developing ARDS, in addition to odds ratios and their respective 95% confidence intervals. A backward stepwise selection approach was used to limit the number of variables in the final multivariable model to significant independent predictors of ARDS. A nomogram was constructed based on the results of the final multivariable model, making it possible to estimate the probability of developing ARDS. Statistical significance was defined by a two-tailed p-value < 0.05. (3) Results: Out of 211 patients (13.3%), 28 developed ARDS. In the univariate analysis, increasing age, Charlson Comorbidity Index and ASA scores, DLCO < 75% predicted, preoperative C-reactive protein (CRP), lung perfusion and duration of surgery were associated with ARDS; a significant increase in ARDS was also observed with decreasing VO2max level. Multivariable analysis confirmed the role of ASA score, DLCO < 75% predicted, preoperative C-reactive protein and lung perfusion. Using the nomogram, we classified patients into four classes with rates of ARDS ranking from 2.0% to 34.0%. (4) Conclusions: Classification in four classes of growing risk allows a correct preoperative stratification of these patients in order to quantify the postoperative risk of ARDS and facilitate their global management.

A Multiple-Center Nomogram to Predict Pneumonectomy Complication Risk for Non-Small Cell Lung Cancer Patients

OBJECTIVE

This study aimed to construct a nomogram to quantitatively predict pneumonectomy complication risks for non-small cell lung cancer (NSCLC) patients.

METHODS

Data from 1052 NSCLC patients who underwent pneumonectomy were retrospectively retrieved from the databases of three thoracic centers. Multivariable logistic regression was used to investigate postoperative morbidity predictors. Clinical parameters and operative features were analyzed using univariable and multivariable logistic regression analyses, and a nomogram to predict the risk of postoperative complications was constructed using bootstrap resampling. A receiver operating characteristic (ROC) curve was used to estimate the discrimination power for the nomogram.

RESULTS

A total of 212 patients (20.2%) had major complications. After regression analysis, forced expiratory volume in 1 s, Charlson Comorbidity Index score, male sex, and right-sided pneumonectomy were identified and entered into the nomogram. The nomogram showed a robust discrimination, with an area under the ROC curve of 0.753 (95% confidence interval 0.604-0.818). The calibration curves for the probability of postoperative complications showed optimal agreement between the nomogram and the actual probability.

CONCLUSIONS

Based on preoperative data, we developed a nomogram for predicting complication risks after pneumonectomy. This model may be helpful for thoracic surgeons in selecting appropriate patients for adopting prophylactic measures after surgery.

New Therapeutic Strategies for Lung Cancer

Non-small cell lung cancer (NSCLC) accounts for approximately 27% of all cancer-related deaths worldwide, thus representing a major health problem [...].

Total Psoas Area and Total Muscular Parietal Area Affect Long-Term Survival of Patients Undergoing Pneumonectomy for Non-Small Cell Lung Cancer

There is no standardization in methods to assess sarcopenia; in particular the prognostic significance of muscular fatty infiltration in lung cancer patients undergoing surgery has not been evaluated so far. We thus performed several computed tomography (CT)-based morphometric measurements of sarcopenia in 238 consecutive non-small cell lung-cancer patients undergoing pneumonectomy from 1 January 2007 to 31 December 2015. Sarcopenia was assessed by the following CT-based parameters: cross-sectional total psoas area (TPA), cross-sectional total muscle area (TMA), and total parietal muscle area (TPMA), defined as TMA without TPA. Measures were performed at the level of the third lumbar vertebra and were obtained for the entire muscle surface, as well as by excluding fatty infiltration based on CT attenuation. Findings were stratified for gender, and a threshold of the 33rd percentile was set to define sarcopenia. Furthermore, we assessed the possibility of being sarcopenic at both the TPA and TPMA level, or not, by taking into account of not fatty infiltration. Five-year survival was 39.1% for the whole population. Lower TPA, TMA, and TPA were associated with lower survival at univariate analysis; taking into account muscular fatty infiltration did not result in more powerful discrimination. Being sarcopenic at both psoas and parietal muscle level had the optimum discriminating power. At the multivariable analysis, being sarcopenic at both psoas and parietal muscles (considering the whole muscle areas, including muscular fat), male sex, increasing age, and tumor stage, as well as Charlson Comorbidity Index (CCI), were independently associated with worse long-term outcomes. We conclude that sarcopenia is a powerful negative prognostic factor in patients with lung cancer treated by pneumonectomy.