Modeling the COVID Pandemic: Do Delays in Surgery Justify Using Stereotactic Radiation to Treat Low-Risk Early Stage Non-Small Cell Lung Cancer?

INTRODUCTION: It was suggested that stereotactic radiation (SBRT) is an "alternative if no surgical capacity is available" for non-small cell lung cancer (NSCLC) care during the COVID-19 pandemic. The purpose of this study was to compare the oncologic outcomes of delayed surgical resection and early SBRT among operable patients with early stage lung cancer. METHODS: The National Cancer Database was queried for patients with cT1aN0M0 NSCLC who underwent surgery or SBRT (2010-2016) with no comorbidity. Patients with any comorbidities or age >80 were excluded. The outcome of interest was overall survival. Delays in surgical care were modeled using different times from diagnosis to surgery. A 1:1 propensity match was performed and survival was analyzed using multivariable Cox regression. RESULTS: Of 6720 healthy cT1aN0M0 NSCLC patients, 6008 (89.4%) received surgery and 712 (10.6%) received SBRT. Among surgery patients, time to surgery >30 d was associated with inferior survival (HR > 1.4, P ≤ 0.013) compared with patients receiving surgery ≤14 d. Relative to SBRT, surgery demonstrated superior survival at all time points evaluated: 0-30 d, 31-60 d, 61-90 d, and >90 d (all P < 0.001). Among a propensity-matched cohort of 256 pairs of patients, delayed surgery (>90 d) remained association with better overall survival relative to early SBRT (5-year survival 76.9% versus 32.3%, HR = 0.266, P < 0.001). CONCLUSIONS: Although longer time to surgery is associated with inferior survival among surgery patients, delayed surgery is superior to early SBRT. Surgical resection should remain the standard of care to treat operable early stage lung cancer despite delays imposed by the COVID-19 pandemic.

Repair, Reconstruct, or Divert: Fate of the Perforated Esophagus.

OBJECTIVES: The aim of this study was to determine differences in esophageal perforation populations undergoing different advanced interventions for perforated esophagus and identify predictors of treatment outcomes. SUMMARY BACKGROUND DATA: Contained esophageal perforation can often be managed expectantly, but uncontained perforation is uniformly fatal without invasive intervention. Treatment options for the latter range from simple endoscopic control through advanced intervention. Clinical presentation varies greatly and directs which intervention is most appropriate. METHODS: From 1996 to 2017, 335 patients were treated for esophageal perforation, and 166 for advanced interventions: 74 primary repair with tissue flap (repair), 26 esophagectomy and gastric pull-up (resection), and 66 esophagectomy and immediate diversion with planned delayed reconstruction (resection-diversion). Patient characteristics, clinical presentation, operative outcomes, and survival were abstracted. Pittsburgh Severity Scores (PSS) were retrospectively calculated. Random survival forest analysis was performed for 90-day mortality and competing risks for reconstruction after resection-diversion. RESULTS: Repair and resection patients had lower PSS than resection-diversion patients (3 vs 3 vs 6, respectively). Ninety-day mortality for repair, resection, and resection-diversion was 11% vs 7.7% vs 23%, and 5-year survival was 71% vs 63% vs 47%. Risk of death after resection-diversion was highest within 1 year, but 52% of patients had reconstruction of the upper alimentary tract within 2 years. CONCLUSIONS: Several advanced interventions exist for critically ill patients with uncontained esophageal perforation. Repair and organ preservation are always preferred; however, patients at extremes of illness might best be treated with resection-diversion, with the understanding that the competing risk of death may preclude eventual reconstruction.

Computational risk model for predicting 2-year malignancy of pulmonary nodules using demographic and radiographic characteristics.

OBJECTIVES: To determine whether discriminatory performance of a computational risk model in classifying pulmonary lesion malignancy using demographic, radiographic, and clinical characteristics is superior to the opinion of experienced providers. We hypothesized that computational risk models would outperform providers. METHODS: Outcome of malignancy was obtained from selected patients enrolled in the NAVIGATE trial (NCT02410837). Five predictive risk models were developed using an 80:20 train-test split: univariable logistic regression model based solely on provider opinion, multivariable logistic regression model, random forest classifier, extreme gradient boosting model, and artificial neural network. Area under the receiver operating characteristic curve achieved during testing of the predictive models was compared to that of prebiopsy provider opinion baseline using the DeLong test with 10,000 bootstrapped iterations. RESULTS: The cohort included 984 patients, 735 (74.7%) of which were diagnosed with malignancy. Factors associated with malignancy from multivariable logistic regression included age, history of cancer, largest lesion size, lung zone, and positron-emission tomography positivity. Testing area under the receiver operating characteristic curve were 0.830 for provider opinion baseline, 0.770 for provider opinion univariable logistic regression, 0.659 for multivariable logistic regression model, 0.743 for random forest classifier, 0.740 for extreme gradient boosting, and 0.679 for artificial neural network. Provider opinion baseline was determined to be the best predictive classification system. CONCLUSIONS: Computational models predicting malignancy of pulmonary lesions using clinical, demographic, and radiographic characteristics are inferior to provider opinion. This study questions the ability of these models to provide additional insight into patient care. Expert clinician evaluation of pulmonary lesion malignancy is paramount.