Patient-Reported Outcome-Based Symptom Management Versus Usual Care After Lung Cancer Surgery: A Multicenter Randomized Controlled Trial

PURPOSE We aimed to evaluate the efficacy and feasibility of patient-reported outcome (PRO)-based symptom management in the early period after lung cancer surgery. METHODS Before surgery, patients with clinically diagnosed lung cancer were randomly assigned 1:1 to receive postoperative PRO-based symptom management or usual care. All patients reported symptoms on MD Anderson Symptom Inventory-Lung Cancer presurgery, daily postsurgery, and twice a week after discharge for up to 4 weeks via an electronic PRO system. In the intervention group, treating surgeons responded to overthreshold electronic alerts driven by any of the five target symptom scores (score ≥ 4 on a 0-10 scale for pain, fatigue, disturbed sleep, shortness of breath, and coughing). The control group patients received usual care and no alerts were generated. The primary outcome was the number of symptom threshold events (any target symptom with a score of ≥ 4) at discharge. Per-protocol analyses were conducted. RESULTS Of the 166 participants, 83 were randomly allocated to each group. At discharge, the intervention group reported fewer symptom threshold events than the control group (median [interquartile range], 0 [0-2] v 2 [0-3]; P = .007). At 4 weeks postdischarge, this difference was maintained between the intervention and control groups (median [interquartile range], 0 [0-0] v 0 [0-1]; P = .018). The intervention group had a lower complication rate than the control group (21.5% v 40.6%; P = .019). Surgeons spent a median of 3 minutes managing an alert. CONCLUSION PRO-based symptom management after lung cancer surgery showed lower symptom burden and fewer complications than usual care for up to 4 weeks postdischarge.

Impact of the SARS-CoV-2 Epidemic on Lung Cancer Surgery in France: A Nationwide Study

Few studies have investigated the link between SARS-CoV-2 and health restrictions and its effects on the health of lung cancer (LC) patients. The aim of this study was to assess the impact of the SARS-CoV-2 epidemic on surgical activity volume, postoperative complications and in-hospital mortality (IHM) for LC resections in France. All data for adult patients who underwent pulmonary resection for LC in France in 2020, collected from the national administrative database, were compared to 2018–2019. The effect of SARS-CoV-2 on the risk of IHM and severe complications within 30 days among LC surgery patients was examined using a logistic regression analysis adjusted for age, sex, comorbidities and type of resection. There was a slight decrease in the volume of LC resections in 2020 (n = 11,634), as compared to 2018 (n = 12,153) and 2019 (n = 12,227), with a noticeable decrease in April 2020 (the peak of the first wave of epidemic in France). We found that SARS-CoV-2 (0.43% of 2020 resections) was associated with IHM and severe complications, with, respectively, a sevenfold (aOR = 7.17 (3.30–15.55)) and almost a fivefold (aOR = 4.76 (2.31–9.80)) increase in risk. Our study suggests that LC surgery is feasible even during a pandemic, provided that general guidance protocols edited by the surgical societies are respected.

Magnetic Resonance Imaging Segmentation on the Basis of Boundary Tracking Algorithm in Lung Cancer Surgery

This work was to study the guiding value of magnetic resonance imaging (MRI) based on the target region boundary tracking algorithm in lung cancer surgery. In this study, the traditional boundary tracking algorithm was optimized, and the target neighborhood point boundary tracking method was proposed. The iterative method was used to binarize the lung MRI image, which was applied to the MRI images of 50 lung cancer patients in hospital. The patients were divided into two groups as the progression-free survival (PFS) and overall survival (OS) of surgical treatment group (experimental group, n = 25) and nonsurgical treatment group (control group, n = 25). The experimental group received surgical resection, while the control group received systemic chemotherapy. The results showed that the traditional boundary tracking algorithm needed to manually rejudge whether the concave and convex parts of the image were missing. The target boundary tracking algorithm can effectively avoid the leakage of concave and convex parts and accurately locate the target image contour, fast operation, without manual intervention. The PFS time of the experimental group (325 days) was significantly higher than that of the control group (186 days) P < 0.05 . The OS time of the experimental group (697 days) was significantly higher than that of the control group (428 days) P < 0.05 . Fisher exact probability method was used to test the total survival time of patients in the two groups, and the tumor classification and treatment group had significant influence on the OS time P < 0.05 . The target boundary tracking algorithm in this study can effectively locate the contour of the target image, and the operation speed was fast. Surgical resection of lung cancer can improve the PFS and OS of patients.