Impact of COVID-19 pandemic on oncology clinical trial design, data collection and analysis.

BACKGROUND: To identify and assess via simulation the impact of COVID-19 pandemic on oncology trials and discuss potential mitigation strategies for study design, data collection, endpoints and analyses. METHODS: We simulated clinical trials to evaluate the COVID-19 impact on overall survival and progression-free survival. We evaluated survival in single-region trials with different proportions of impacted patients across treatment arms, and in multi-region randomized trials with different proportions of impacted patients across regions. We also assessed the impact on PFS when the missingness of disease assessment and censoring rules vary. Impact on the trial success and robustness of statistical inference was summarized. RESULTS: Without regional impact, the impact on OS analysis is minimal if proportions of impacted patients are similar across arms, however, if a larger proportion of treatment arm patients are impacted, trials may suffer substantial power loss and underestimate treatment effect size. For multi-region trials, if more treatment arm patients are enrolled from more severely impacted regions, trials also have poorer performance. For PFS analysis, the intent-to-treat rule performs well even when the treatment arm patients are more likely to miss disease assessments, while the consecutive-missing censoring rule may lead to poorer performance. CONCLUSION: COVID-19 affects oncology trials. Simulations would be highly informative to Data Monitoring Committee in understanding the impact and making appropriate recommendations, upon which the sponsor could start planning potential remedies. We also recommend a decision tree for choosing the appropriate methods for PFS evaluation in the presence of missing disease assessments due to COVID-19.

Health-Related Quality of Life and Influencing Factors of Pediatric Medical Staff During the COVID-19 Outbreak.

Objective: To evaluate the health-related quality of life (HRQoL) status and explore its associated factors in pediatric medical staff during the COVID-19 epidemic so as to provide fundamental evidence for clinicians and administrators to formulate targeted intervention measures to improve the HRQoL and mental health status in pediatric medical staff during this, and future pandemics. Methods: A cross-sectional study was conducted to investigate the HRQoL of pediatric medical staff. Univariable and multivariable logistic regression were used to analyze the associated factors. Results: A total of 2,997 participants were recruited. Females scored worse than males in terms of emotional functioning (OR = 1.6, 95% CI: 1.2-2.1) and cognitive functioning (OR = 1.4, 95% CI: 1.1-1.8). The respondents aged 30-39 and 40-49 years scored worse in nearly all domains of HRQoL compared health care professionals under 30 years old. Respondents with high education had lower scores in physical functioning (OR = 1.3, 95% CI: 1.0-1.7) and emotional functioning (OR = 1.5, 95% CI: 1.2-1.9). Compared with doctors, nurses had higher scores in all domains except for summary score and worry. The respondents whose working places had not set up pediatric fever clinics and isolated observation areas independently had lower scores in all domains except for worry. The respondents who had ever treated patients with COVID-19 had lower scores in all domains. Conclusion: During the COVID-19 outbreak, the HRQoL of pediatric medical staff decreased. The factors associated with HRQoL can be used to develop intervention to improve HRQoL in pediatric medical staff.

Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control.

In a large-scale epidemic, such as the novel coronavirus pneumonia (COVID-19), there is huge demand for a variety of medical supplies, such as medical masks, ventilators, and sickbeds. Resources from civilian medical services are often not sufficient for fully satisfying all of these demands. Resources from military medical services, which are normally reserved for military use, can be an effective supplement to these demands. In this paper, we formulate a problem of integrated civilian-military scheduling of medical supplies for epidemic prevention and control, the aim of which is to simultaneously maximize the overall satisfaction rate of the medical supplies and minimize the total scheduling cost, while keeping a minimum ratio of medical supplies reservation for military use. We propose a multi-objective water wave optimization (WWO) algorithm in order to efficiently solve this problem. Computational results on a set of problem instances constructed based on real COVID-19 data demonstrate the effectiveness of the proposed method.