Background In this descriptive case series, 80 soldiers from Fort Campbell, Kentucky, with inhalational exposures during service in Iraq and Afghanistan were evaluated for dyspnea on exertion that prevented them from meeting the U.S. Army's standards for physical fitness. Methods The soldiers underwent extensive evaluation of their medical and exposure history, physical examination, pulmonary-function testing, and high-resolution computed tomography (CT). A total of 49 soldiers underwent thoracoscopic lung biopsy after noninvasive evaluation did not provide an explanation for their symptoms. Data on cardiopulmonary-exercise and pulmonary-function testing were compared with data obtained from historical military control subjects. Results Among the soldiers who were referred for evaluation, a history of inhalational exposure to a 2003 sulfur-mine fire in Iraq was common but not universal. Of the 49 soldiers who underwent lung biopsy, all biopsy samples were abnormal, with 38 soldiers having changes that were diagnostic of constrictive bronchiolitis. In the remaining 11 soldiers, diagnoses other than constrictive bronchiolitis that could explain the presenting dyspnea were established. All soldiers with constrictive bronchiolitis had normal results on chest radiography, but about one quarter were found to have mosaic air trapping or centrilobular nodules on chest CT. The results of pulmonary-function and cardiopulmonary-exercise testing were generally within normal population limits but were inferior to those of the military control subjects. Conclusions In 49 previously healthy soldiers with unexplained exertional dyspnea and diminished exercise tolerance after deployment, an analysis of biopsy samples showed diffuse constrictive bronchiolitis, which was possibly associated with inhalational exposure, in 38 soldiers.

Background 18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) is used to evaluate suspicious pulmonary lesions due to its diagnostic accuracy. The southeastern United States has a high prevalence of infectious granulomatous lung disease, and the accuracy of FDGPET may be reduced in this population. We examined the diagnostic accuracy of FDG-PET in patients with known or suspected NSCLC treated at our institution. Methods 279 patients identified through our prospective database, underwent an operation for known or suspected lung cancer. Preoperative FDG-PET in 211 eligible patients was defined by standardized uptake value, SUV > 2.5 or by description (“moderate” or “intense”) as avid. Sensitivity, specificity, positive and negative predictive values, likelihood ratios, and decision diagrams were calculated for FDG-PET in all patients and in patients with indeterminate nodules. Results In all eligible patients (n=211), sensitivity and specificity of FDG-PET were 92% and 40%. Positive and negative predictive values were 86% and 55%. Overall FDG-PET accuracy to diagnose lung cancer was 81%. Preoperative positive likelihood ratio for FDG-PET diagnosis of lung cancer in this population was 1.5 compared to previously published values of 7.1. In 113 indeterminate lesions, 65% had lung cancer and the sensitivity and specificity were 89% and 40% respectively. 24 benign nodules (60%) had false positive FDG-PET scans. 22 of 43 benign nodules (51%) were granulomas. Conclusions In a region with endemic granulomatous diseases, the specificity of FDG-PET for diagnosis of lung cancer was 40%. Clinical decisions and future clinical predictive models for lung cancer must accommodate regional variation of FDG-PET scan results.

Replication-incompetent adenoviruses (Ad) carrying the herpes simplex thymidine kinase (HSVtk) gene have been used in a number of human cancer gene therapy trials, however transduction has generally been limited to a small minority of tumor cells. To solve this problem, replication-competent adenoviral vectors carrying transgenes such as HSVtk have been developed. However, contradictory evidence exists regarding the efficacy of these new vectors. Accordingly, we constructed and tested a replication-competent E3-deleted adenoviral vector containing the HSVtk suicide gene driven by the endogenous E3 promoter (Ad.wt.tk). This virus

Background Timely care of lung cancer is presumed critical, yet clear evidence of stage progression with delays in care is lacking. We investigated the reasons for delays in treatment and the impact these delays have on tumor-stage progression. Methods We queried our retrospective database of 265 veterans who underwent cancer resection from 2005 to 2015. We extracted time intervals between nodule identification, diagnosis, and surgical resection; changes in nodule radiographic size over time; final pathologic staging; and reasons for delays in care. Pearson’s correlation and Fisher’s exact test were used to compare cancer growth and stage by time to treatment. Results Median time from referral to surgical evaluation was 11 days (interquartile range, 8 to 17). Median time from identification to therapeutic resection was 98 days (interquartile range, 66 to 139), and from diagnosis to resection, 53 days (interquartile range, 35 to 77). Sixty-eight patients (26%) were diagnosed at resection; the remainder had preoperative tissue diagnoses. No significant correlation existed between tumor growth and time between nodule identification and resection, or between tumor growth and time between diagnosis and resection. Among 197 patients with preoperative diagnoses, 42% (83) had intervals longer than 60 days between diagnosis and resection. Most common reasons for delay were cardiac clearance, staging, and smoking cessation. Larger nodules had fewer days between identification and resection (p = 0.03). Conclusions Evaluation, staging, and smoking cessation drive resection delays. The lack of association between tumor growth and time to treatment suggests other clinical or biological factors, not time alone, underlie growth risk. Until these factors are identified, delays to diagnosis and treatment should be minimized.

Background atients undergoing resections for suspicious pulmonary lesions have a 9-55% benign rate. Validated prediction models exist to estimate the probability of malignancy in a general population and current practice guidelines recommend their use. We evaluated these models in a surgical population to determine the accuracy of existing models to predict benign or malignant disease. Methods We conducted a retrospective review of our thoracic surgery quality improvement database (2005-2008) to identify patients who underwent resection of a pulmonary lesion. Patients were stratified into subgroups based on age, smoking status and fluorodeoxyglucose positron emission tomography (PET) results. The probability of malignancy was calculated for each patient using the Mayo and SPN prediction models. Receiver operating characteristic (ROC) and calibration curves were used to measure model performance. Results 89 patients met selection criteria; 73% were malignant. Patients with preoperative PET scans were divided into 4 subgroups based on age, smoking history and nodule PET avidity. Older smokers with PET-avid lesions had a 90% malignancy rate. Patients with PET- non-avid lesions, or PET-avid lesions with age<50 years or never smokers of any age had a 62% malignancy rate. The area under the ROC curve for the Mayo and SPN models was 0.79 and 0.80, respectively; however, the models were poorly calibrated (p<0.001). Conclusions Despite improvements in diagnostic and imaging techniques, current general population models do not accurately predict lung cancer among patients ref erred for surgical evaluation. Prediction models with greater accuracy are needed to identify patients with benign disease to reduce non-therapeutic resections.

Background Existing predictive models for lung cancer focus on improving screening or referral for biopsy in general medical populations. A predictive model calibrated for use during preoperative evaluation of suspicious lung lesions is needed to reduce unnecessary operations for benign disease. A clinical prediction model (TREAT) is proposed for this purpose. Methods We developed and internally validated a clinical prediction model for lung cancer in a prospective cohort evaluated at our institution. Best statistical practices were used to construct, evaluate and validate the logistic regression model in the presence of missing covariate data using bootstrap and optimism corrected techniques. The TREAT model was externally validated in a retrospectively collected Veteran Affairs population. The discrimination and calibration of the model was estimated and compared to the Mayo Clinic model in both populations. Results The TREAT model was developed in 492 patients from Vanderbilt whose lung cancer prevalence was 72% and validated among 226 Veteran Affairs patients with a lung cancer prevalence of 93%. In the development cohort the area under the receiver operating curve (AUC) and Brier score were 0.87 (95%CI: 0.83–0.92) and 0.12 respectively compared to the AUC 0.89 (95%CI: 0.79–0.98) and Brier score 0.13 in the validation dataset. The TREAT model had significantly higher accuracy (p<0.001) and better calibration than the Mayo Clinic model (AUC=0.80, 95%CI: 75–85; Brier score=0.17). Conclusion The validated TREAT model had better diagnostic accuracy than the Mayo Clinic model in preoperative assessment of suspicious lung lesions in a population being evaluated for lung resection.

Background: Clusterin is a glycoprotein that has been implicated in many processes, including apoptosis, cell cycle regulation, and DNA repair. Previous studies have examined the prognostic value of clusterin expression in various malignancies. In the present study, we examined clusterin staining in tumors resected from patients with non -small cell lung cancer (NSCLC). Materials and Methods: Tumor specimens were obtained for 113 patients with completely resected NSCLC from paraffin-embedded tissue microarrays and stained with an antibody specific for clusterin. Staining patterns were observed and graded based on intensity and then correlated with clinical data. Results: Positive cytoplasmic clusterin staining was observed in 44 patients, and weak/negative staining was observed in 62 patients. Patients who had

Dedicated instruction of fourth-year medical students with deliberate and distributed practice of microvascular techniques using a porcine end-to-side coronary artery anastomosis simulation model results in performance comparable to that of senior general surgery residents. These results suggest that focused tissue simulator training can compress the learning curve to acquire technical proficiency in comparison with real-time training.