Infection Control of 2019 Novel Corona Virus Disease (COVID-19) in Cancer Patients undergoing Radiotherapy in Wuhan
Xie, C.; Wang, X.; Liu, H.; Bao, Z.; Yu, J.; Zhong, Y.; Chua, M. L.
Show abstract
BackgroundA pandemic of 2019 novel corona virus disease (COVID-19), which was first reported in Wuhan city, has affected more than 100,000 patients worldwide. Patients with cancer are at a higher risk of COVID-19, but currently, there is no guidance on the management of cancer patients during this outbreak. Here, we report the infection control measures and early outcomes of patients who received radiotherapy (RT) at a tertiary cancer centre in Wuhan. MethodsWe reviewed all patients who were treated at the Zhongnan Hospital of Wuhan University (ZHWU) from Jan 20 to Mar 6, 2020. This preceded the city lock-down date of Jan 23, 2020. Infection control measures were implemented, which included a clinical pathway for managing suspect COVID-19 cases, on-site screening, modifications to the RT facility, and protection of healthcare workers. Primary end-point was infection rate among patients and healthcare staff. Diagnosis of COVID-19 was based on the 5th edition criteria. Findings209 patients completed RT during the study period. Median age was 55 y (IQR = 48-64). Thoracic, head and neck, and lower gastrointestinal and gynaecological cancer patients consisted the majority of patients. Treatment sites included thoracic (38.3%), head and neck (25.4%), and abdomen and pelvis (25.8%); 47.4%, 27.3%, and 25.4% of treatments were for adjuvant, radical, and palliative indications, respectively. 188 treatments/day were performed prior to the lock-down, in contrast to 12.4 treatments/day post-lock-down. Only one (0.48%) patient was diagnosed with COVID-19 during the study period. No healthcare worker was infected. InterpretationHerein, we show that in a susceptible population to COVID-19, strict infection control measures can curb human-to-human transmission, and ensure timely delivery of RT to cancer patients. FundingThis study was funded by Health Commission of Hubei Province Scientific Research Project, WJ2019H002, Health Commission of Hubei Province Medical Leading Talent Project. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThe 2019 novel coronavirus disease (COVID-19) is now a global pandemic. Cancer patients are at risk of COVID-19 pneumonia, and thus infection control measures are crucial to mitigate their risk of infection. We searched PubMed and Medline for articles published up to Mar 12, 2020, using the following keywords: "COVID-19", "SARS", "SARS-CoV-2", "infection control", and "cancer". No evidence exists that informs on the appropriate infection control measures for COVID-19. Added value of this studyWe report our single centre experience on the detailed infection control measures that were undertaken to minimise cross transmission between cancer patients undergoing radiotherapy, and between patients and healthcare workers. Measures entailing screening of suspect cases, re-organisation of the treatment facility, and protection of healthcare workers were described. With our infection control protocol, we recorded only one COVID-19 case among the 209 patients (0.48%) who were treated at our centre during the period of Jan 20 to Mar 6, 2020. No healthcare worker was affected. Implications of all the available evidenceThe effective infection control measures outlined in this study will help institutions worldwide affected by COVID-19 to formulate guidelines to mitigate nosocomial human-to-human transmission, especially among susceptible patients.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Surgical Resection, Radiotherapy, And Percutaneous Thermal Ablation for Treatment of Stage 1 Non-Small Cell Lung Cancer: A Systematic Review and Network Meta-Analysis 92%
- Protocol of the observational study STRATUM-OS: First step in the development and validation of the STRATUM tool based on multimodal data processing to assist surgery in patients affected by intra-axial brain tumours 90%
- Reproducibility and transparency characteristics of oncology research evidence 90%
Similar papers in this journal
- Multi-institutional Normal Tissue Complication Probability (NTCP) Prediction Model for Mandibular Osteoradionecrosis: Results from the PREDMORN Study 94%
- Normal Tissue Complication Probability (NTCP) prediction model for osteoradionecrosis of the mandible in head and neck cancer patients following radiotherapy: Large-scale observational cohort 94%
- FLASH Radiotherapy Mitigates Radiation-Induced Lymphopenia and Prevents Immunosuppression via Chk1-STAT3 Axis Modulation in a Preclinical Thoracic Irradiation Model 93%
Similar papers in this journal
- Identifying optimal combinations of symptoms to trigger diagnostic work-up of suspected COVID-19 cases in vaccine trials: analysis from a community-based, prospective, observational cohort 86%
- High-risk exposure without personal protective equipment and infection with SARS-CoV-2 in healthcare workers: results of the CoV-CONTACT prospective cohort 85%
- Prevalence and impact of SARS-CoV-2, influenza, respiratory syncytial virus (RSV) infection and respiratory illness on UK healthcare workers during winter 2023/24 (September 2023 to March 2024): SIREN cohort study 85%
Similar papers in this journal
- Dysphagia and shortness-of-breath as markers for treatment failure and survival in oropharyngeal cancer after radiation 93%
- Detailed patient-individual reporting of lymph node involvement in oropharyngeal squamous cell carcinoma with an online interface 93%
- Artificial Intelligence Uncertainty Quantification in Radiotherapy Applications - A Scoping Review 92%
Similar papers in this journal
- Intermittent radiotherapy as alternative treatment for recurrent high grade glioma: A modelling study based on longitudinal tumor measurements 91%
- Comparison of Radiomic Feature Aggregation Methods for Patients with Multiple Tumors 90%
- Pan-cancer analyses of the associations between 109 pre-existing conditions and cancer treatment patterns across 19 adult cancers 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.