Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study
- 1 January 2021
- journal article
- research article
- Published by American Society of Clinical Oncology (ASCO) in Journal of Clinical Oncology
- Vol. 39 (1), 66-+
- https://doi.org/10.1200/JCO.20.01933
Abstract
PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks.This publication has 19 references indexed in Scilit:
- Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort studyThe Lancet Infectious Diseases, 2018
- Perioperative patient outcomes in the African Surgical Outcomes Study: a 7-day prospective observational cohort studyThe Lancet, 2018
- Postoperative Pulmonary Complications, Early Mortality, and Hospital Stay Following Noncardiothoracic SurgeryJAMA Surgery, 2017
- The Prevention of Respiratory Insufficiency after Surgical Management (PRISM) Trial. Report of the protocol for a pragmatic randomized controlled trial of CPAP to prevent respiratory complications and improve survival following major abdominal surgeryMinerva Anestesiologica, 2017
- Advanced pancreatic adenocarcinoma outcomes with transition from devolved to centralised care in a regional Cancer CentreBritish Journal of Cancer, 2017
- Global cancer surgery: delivering safe, affordable, and timely cancer surgeryThe Lancet Oncology, 2015
- Basic statistical reporting for articles published in Biomedical Journals: The “Statistical Analyses and Methods in the Published Literature” or the SAMPL GuidelinesInternational Journal of Nursing Studies, 2015
- Centralisation of services for gynaecological cancers — A Cochrane systematic reviewGynecologic Oncology, 2012
- The Split-Apply-Combine Strategy for Data AnalysisJournal of Statistical Software, 2011
- Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics supportJournal of Biomedical Informatics, 2008