Pneumonectomy for Primary Lung Tumors and Pulmonary Metastases: A Comprehensive Study of Postoperative Morbidity, Early Mortality, and Preoperative Clinical Prognostic Factors

Background: Pneumonectomy is a major surgical resection that still remains a high-risk operation. The current study aims to investigate perioperative risk factors for postoperative morbidity and early mortality after pneumonectomy for thoracic malignancies. Methods: We retrospectively analyzed all patients who underwent pneumonectomy for thoracic malignancies at our institution between 2014 and 2022. Complications were assessed up to 30 days after the operation. Mortality for any reason was recorded after 30 days and 90 days. Results: A total of 145 out of 169 patients undergoing pneumonectomy were included in this study. The postoperative 30-day complication rate was 41.4%. The 30-day-mortality was 8.3%, and 90-day-mortality 17.2%. The presence of cardiovascular comorbidities was a risk factor for major cardiopulmonary complications (54.2% vs. 13.2%, p p = 0.029) and American Society of Anesthesiologists (ASA) score 4 (OR: 3.023, 95% CI: 1.028–8.892, p = 0.044) were independent factors for early mortality. Conclusion: Pneumonectomy for thoracic malignancies remains a high-risk major lung resection with significant postoperative morbidity and mortality. Attention should be paid to the preoperative selection of patients

LIONS PREY: A New Logistic Scoring System for the Prediction of Malignant Pulmonary Nodules

Objectives: Classifying radiologic pulmonary lesions as malignant is challenging. Scoring systems like the Mayo model lack precision in predicting the probability of malignancy. We developed the logistic scoring system ‘LIONS PREY’ (Lung lesION Score PREdicts malignancY), which is superior to existing models in its precision in determining the likelihood of malignancy. Methods: We evaluated all patients that were presented to our multidisciplinary team between January 2013 and December 2020. Availability of pathological results after resection or CT-/EBUS-guided sampling was mandatory for study inclusion. Two groups were formed: Group A (malignant nodule; n = 238) and Group B (benign nodule; n = 148). Initially, 22 potential score parameters were derived from the patients’ medical histories. Results: After uni- and multivariate analysis, we identified the following eight parameters that were integrated into a scoring system: (1) age (Group A: 64.5 ± 10.2 years vs. Group B: 61.6 ± 13.8 years; multivariate p-value: 0.054); (2) nodule size (21.8 ± 7.5 mm vs. 18.3 ± 7.9 mm; p = 0.051); (3) spiculation (73.1% vs. 41.9%; p = 0.024); (4) solidity (84.9% vs. 62.8%; p = 0.004); (5) size dynamics (6.4 ± 7.7 mm/3 months vs. 0.2 ± 0.9 mm/3 months; p p p = 0.079); and (8) cancer history (34.9% vs. 24.3%; p = 0.052). Our model demonstrated superior precision to that of the Mayo score (p = 0.013) with an overall correct classification of 96.0%, a calibration (observed/expected-ratio) of 1.1, and a discrimination (ROC analysis) of AUC (95% CI) 0.94 (0.92–0.97). Conclusions: Focusing on essential parameters, LIONS PREY can be easily and reproducibly applied based on computed tomography (CT) scans. Multidisciplinary team members could use it to facilitate decision making. Patients may find it easier to consent to surgery knowing the likelihood of pulmonary malignancy. The LIONS PREY app is available for free on Android and iOS devices