Small cell carcinoma as an independent prognostic factor for cervical cancer patients: a population-based analysis.

Aim: To compare cervical small cell carcinoma (SmCC) with squamous cell carcinoma (SCC) in patient characteristics and survival outcomes. Methods: Cervical SmCC and SCC patients in Surveillance, Epidemiology, and End Results database from 2004 to 2015 were enrolled. Propensity-score matching analysis (PSM) paired subjects with similar background variables. Cox regression, Kaplan-Meier and stratified analyses were conducted before and after PSM. Results: Cervical SmCC patients showed a higher rate of larger tumor size, advanced grade disease, lymph node involvement and distant metastasis (p < 0.001). Before and after PSM, SmCC histology and advanced Federation International of Gynecology and Obstetrics stages (p < 0.001) were principal prognostic factors of survival, and cervical SmCC was associated with worse survival in all stages (stage I-IV). Conclusion: SmCC was an independent poor prognostic factor in cervical cancer patients.

The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study

BackgroundRecent outbreak of a novel coronavirus disease 2019 (COVID-19) has led a rapid global spread around the world. For controlling COVID-19 outbreaks, many countries have implemented two non-pharmaceutical interventions: suppression like immediate lock-downs in cities at epicentre of outbreak; or mitigation that slows down but not stopping epidemic for reducing peak healthcare demand. Both interventions have apparent pros and cons; the effectiveness of any one intervention in isolation is limited. It is crucial but hard to know how and when to take which level of interventions tailored to the specific situation in each country. We aimed to conduct a feasibility study for robustly accessing the effect of multiple interventions to control the number and distribution of infections, growth of deaths, peaks and lengths of COVID-19 breakouts in the UK and other European countries, accounting for balance of healthcare demand. MethodsWe developed a model to attempt to infer the impact of mitigation, suppression and multiple rolling interventions for controlling COVID-19 outbreaks in the UK. Our model assumed that each intervention has equivalent effect on the reproduction number R across countries and over time; where its intensity was presented by average-number contacts with susceptible individuals as infectious individuals; early immediate intensive intervention led to increased health need and social anxiety. We considered two important features: direct link between Exposed and Recovered population, and practical healthcare demand by separation of infections into mild, moderate and critical cases. Our model was fitted and calibrated with date on cases of COVID-19 in Wuhan to estimate how suppression intervention impacted on the number and distribution of infections, growth of deaths over time during January 2020, and April 2020. We combined the calibrated model with data on the cases of COVID-19 in London and non-London regions in the UK during February 2020 and April 2020 to estimate the number and distribution of infections, growth of deaths, and healthcare demand by using multiple interventions. We applied the calibrated model to the prediction of infection and healthcare resource changes in other 6 European countries based on actual measures they have implemented during this period. FindingsWe estimated given that 1) By the date (5th March 2020) of the first report death in the UK, around 7499 people would have already been infected with the virus. After taking suppression on 23rd March, the peak of infection in the UK would have occurred between 28th March and 4th April 2020; the peak of death would have occurred between 18th April and 24th April 2020. 2) By 29th April, no significant collapse of health system in the UK have occurred, where there have been sufficient hospital beds for severe and critical cases. But in the Europe, Italy, Spain and France have experienced a 3 weeks period of shortage of hospital beds for severe and critical cases, leading to many deaths outside hospitals. 3) One optimal strategy to control COVID-19 outbreaks in the UK is to take region-level specific intervention. If taking suppression with very high intensity in London from 23rd March 2020 for 100 days, and 3 weeks rolling intervention between very high intensity and high intensity in non-London regions. The total infections and deaths in the UK were limited to 9.3 million and 143 thousand; the peak time of healthcare demand was due to the 96th day (12th May, 2020), where it needs hospital beds for 68.9 thousand severe and critical cases. 4) If taking a simultaneous 3 weeks rolling intervention between very high intensity and high intensity in all regions of the UK, the total infections and deaths increased slightly to 10 million and 154 thousand; the peak time of healthcare occurs at the 97th day (13th May, 2020), where it needs equivalent hospital beds for severe and critical cases of 73.5 thousand. 5) If too early releasing intervention intensity above moderate level and simultaneously implemented them in all regions of the UK, there would be a risk of second wave, where the total infections and deaths in the UK possibly reached to 23.4 million and 897 thousand. InterpretationConsidering social and economic costs in controlling COVID-19 outbreaks, long-term suppression is not economically viable. Our finding suggests that rolling intervention is an optimal strategy to effectively and efficiently control COVID-19 outbreaks in the UK and potential other countries for balancing healthcare demand and morality ratio. As for huge difference of population density and social distancing between different regions in the UK, it is more appropriate to implement regional level specific intervention with varied intensities and maintenance periods. We suggest an intervention strategy to the UK that take a consistent suppression in London for 100 days and 3 weeks rolling intervention in other regions. This strategy would reduce the overall infections and deaths of COVID-19 outbreaks, and balance healthcare demand in the UK.

Feasibility of Controlling COVID-19 Outbreaks in the UK by Rolling Interventions

BackgroundRecent outbreak of a novel coronavirus disease 2019 (COVID-19) has led a rapid global spread around the world. For controlling COVID-19 outbreaks, many countries have implemented two non-pharmaceutical interventions: suppression like immediate lock-downs in cities at epicentre of outbreak; or mitigation that slows down but not stopping epidemic for reducing peak healthcare demand. Both interventions have apparent pros and cons; the effectiveness of any one intervention in isolation is limited. We aimed to conduct a feasibility study for robustly estimating the number and distribution of infections, growth of deaths, peaks and lengths of COVID-19 breakouts by taking multiple interventions in London and the UK, accounting for reduction of healthcare demand. MethodsWe developed a model to attempt to infer the impact of mitigation, suppression and multiple rolling interventions for controlling COVID-19 outbreaks in London and the UK. Our model assumed that each intervention has equivalent effect on the reproduction number R across countries and over time; where its intensity was presented by average-number contacts with susceptible individuals as infectious individuals; early immediate intensive intervention led to increased health need and social anxiety. We considered two important features: direct link between Exposed and Recovered population, and practical healthcare demand by separation of infections into mild and critical cases. Our model was fitted and calibrated with data on cases of COVID-19 in Wuhan to estimate how suppression intervention impacted on the number and distribution of infections, growth of deaths over time during January 2020, and April 2020. We combined the calibrated model with data on the cases of COVID-19 in London and non-London regions in the UK during February 2020 and March 2020 to estimate the number and distribution of infections, growth of deaths, and healthcare demand by using multiple interventions. FindingsWe estimated given that multiple interventions with an intensity range from 3 to 15, one optimal strategy was to take suppression with intensity 3 in London from 23rd March for 100 days, and 3 weeks rolling intervention with intensity between 3 and 5 in non-London regions. In this scenario, the total infections and deaths in the UK were limited to 2.43 million and 33.8 thousand; the peak time of healthcare demand was due to the 65th day (April 11th), where it needs hospital beds for 25.3 thousand severe and critical cases. If we took a simultaneous 3 weeks rolling intervention with intensity between 3 and 5 in all regions of the UK, the total infections and deaths increased slightly to 2.69 million and 37 thousand; the peak time of healthcare kept the same at the 65th day, where it needs equivalent hospital beds for severe and critical cases of 25.3 thousand. But if we released high band of rolling intervention intensity to 6 or 8 and simultaneously implemented them in all regions of the UK, the COVID-19 outbreak would not end in 1 year and distribute a multi-modal mode, where the total infections and deaths in the UK possibly reached to 16.2 million and 257 thousand. InterpretationOur results show that taking rolling intervention is probably an optimal strategy to effectively and efficiently control COVID-19 outbreaks in the UK. As large difference of population density and social distancing between London and non-London regions in the UK, it is more appropriate to implement consistent suppression in London for 100 days and rolling intervention in other regions. This strategy would potentially reduce the overall infections and deaths, and delay and reduce peak healthcare demand. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSuppression and mitigation are two common interventions for controlling infectious disease outbreaks. Previous works show rapid suppression is able to immediately reduce infections to low levels by eliminating human-to-human transmission, but needs consistent maintenance; mitigation does not interrupt transmission completely and tolerates some increase of infections, but minimises health and economic impacts of viral spread.3 While current planning in many countries is focused on implementing either suppression or mitigation, it is not clear how and when to take which level of interventions for control COVID-19 breakouts to certain country in light of balancing its healthcare demands and economic impacts. Added value of this studyWe used a mathematical model to access the feasibility of multiple intervention to control COVID-19 outbreaks in the UK. Our model distinguished self-recovered populations, infection with mild and critical cases for estimating healthcare demand. It combined available evidence from available data source in Wuhan. We estimated how suppression, mitigation and multiple rolling interventions impact on controlling outbreaks in London and non-London regions of the UK. We provided an evidence verification point that implementing suppression in London and rolling intervention with high intensity in non-London regions is probably an optimal strategy to control COVID-19 breakouts in the UK with minimised deaths and economic impacts. Implications of all the available evidenceThe effectiveness and impact of suppression and mitigation to control outbreaks of COVID-19 depends on intervention intensity and duration, which remain unclear at the present time. Using the current best understanding of this model, implementing consistent suppression in London for 100 days and 3 weeks rolling intervention with intensity between 3 and 5 in other regions potentially limit the total deaths in the UK to 33.8 thousand. Future research on how to quantify and measure intervention activities could improve precision on control estimates.

Feasibility Study of Mitigation and Suppression Intervention Strategies for Controlling COVID-19 Outbreaks in London and Wuhan

Recent outbreaks of coronavirus disease 2019 (COVID-19) has led a global pandemic cross the world. Most countries took two main interventions: suppression like immediate lockdown cities at epicentre or mitigation that slows down but not stopping epidemic for reducing peak healthcare demand. Both strategies have their apparent merits and limitations; it becomes extremely hard to conduct one intervention as the most feasible way to all countries. Targeting at this problem, this paper conducted a feasibility study by defining a mathematical model named SEMCR that can access effectiveness of mitigation, suppression and hybrid interventions for controlling COVID-19 outbreaks in London and Wuhan. It extended traditional SEIR (Susceptible-Exposed-Infectious-Recovered) model by adding two key features: a direct connection between Exposed and Recovered populations, and separating infections into mild and critical cases. It defined parameters to classify two stages of COVID-19 control: active contain by isolation of cases and contacts, passive contain by suppression or mitigation. The model was fitted and evaluated with public dataset containing daily number of confirmed active cases including Wuhan and London during January, 2020 and March 2020. The simulated results showed that 1) Immediate suppression taken in Wuhan significantly reduced the total exposed and infectious populations to 119610, but it has to be consistently maintained at least 90 days (by the middle of April 2020). Its success heavily relied on sufficiently external support from other places of China. This mode were not suitable to other countries that have no sufficient health resources. 2) In London, it is possible to take a hybrid intervention of suppression and mitigation for every 2 or 3 weeks over a longer period to balance the total infections and economic loss. While the total infectious populations in this scenario would be possibly 2 times than the one taking suppression, economic loss and recovery of London would be less affected. 3) Both in Wuhan and London cases, one important issue of fitting practical data was that there were a large portion (probably 62.9% in Wuhan) of self-recovered populations that were asymptomatic or mild symptomatic. These people might think they have been healthy at home and did not go to hospital for COVID-19 tests. Early release of intervention intensity potentially increased a risk of the second outbreak. One limitation of our model was that our prediction of infections and deaths depended on a parameter estimation of intervention intensity that presented by average-number contacts with susceptible individuals as infectious individuals in a certain region. It assumed that each intervention had equivalent effects on the reproduction number R in different regions over time. Practical effectiveness of implementing intervention intensity might be varied with respect to cultures or other issues of certain county.