Background There are no large reported series determining the Covid-19 cancer patient's characteristics. We determine whether differences exist in cumulative incidence and mortality of Covid-19 infection between cancer patients and general population in Madrid. Material and methods We reviewed 1069 medical records of all cancer patients admitted at Oncology department between Feb 1 and April 7, 2020. We described Covid-19 cumulative incidence, treatment outcome, mortality, and associated risk factors. Results We detected 45/1069 Covid-19 diagnoses in cancer patients vs 42,450/6,662,000 in total population (p < 0.00001). Mortality rate: 19/45 cancer patients vs 5586/42,450 (p = 0.0001). Mortality was associated with older median age, adjusted by staging and histology (74 vs 63.5 years old, OR 1.06, p = 0.03). Patients who combined hydroxychloroquine and azithromycin presented 3/18 deaths, regardless of age, staging, histology, cancer treatment and comorbidities (OR 0.02, p = 0.03). Conclusion Cancer patients are vulnerable to Covid-19 with an increase in complications. Combined hydroxychloroquine and azithromycin is presented as a good treatment option.

Background: Currently there are no reported series determining the Covid-19 infected lung cancer patient´s characteristics and outcome that allow us to clarify strategies to protect our patients. In our study we determine whether exists differences in cumulative incidence and severity of Covid-19 infection between lung cancer patients visiting our Medical Oncology department and the reference population of our center (320,000 people), in the current epicenter of the pandemic in Europe (Madrid, Spain). We also describe clinical and demographic factors associated with poor prognosis and Covid-19 treatment outcomes. Patients and methods: We retrospectively reviewed 1878 medical records of all Covid-19 patients who were admitted at Hospital Universitario Infanta Leonor of Madrid between March 5, 2020 and April 7, 2020, in order to detect cumulative incidence of Covid-19 in lung cancer patients. We also described Covid-19 treatment outcome, mortality and associated risk factors using univariate and multivariate logistic regression analysis. Results: 17/1878 total diagnosis in our center had lung cancer (0.9 %) versus 1878/320,000 of the total reference population (p = 0.09). 9/17 lung cancer patients with Covid-19 diagnosis died (52.3 %) versus 192/ 1878 Covid-19 patients in our center (p < 0.0001). Dead lung cancer patients were elderly compared to survivors: 72 versus 64.5 years old (p = 0.12). Combined treatment with hydroxychloroquine and azithromycin improves the outcome of Covid-19 in lung cancer patients, detecting only 1/6 deaths between patients under this treatment versus others treatment, with statistical significance in the univariate and multivariate logistic regression (OR 0.04, p = 0.018). Conclusions: Lung cancer patients have a higher mortality rate than general population. Combined hydroxychloroquine and azithromycin treatment seems like a good treatment option. It is important to try to minimize visits to hospitals (without removing their active treatments) in order to decrease nosocomial transmission.

Background Patients with thoracic malignancies are at increased risk for mortality from Coronavirus disease 2019 (COVID-19) and large number of intertwined prognostic variables have been identified so far. Methods Capitalizing data from the TERAVOLT registry, a global study created with the aim of describing the impact of COVID-19 in patients with thoracic malignancies, we used a clustering approach, a fast-backward step-down selection procedure and a tree-based model to screen and optimize a broad panel of demographics, clinical COVID-19 and cancer characteristics. Results As of April 15, 2021, 1491 consecutive evaluable patients from 18 countries were included in the analysis. With a mean observation period of 42 days, 361 events were reported with an all-cause case fatality rate of 24.2%. The clustering procedure screened approximately 73 covariates in 13 clusters. A further multivariable logistic regression for the association between clusters and death was performed, resulting in five clusters significantly associated with the outcome. The fast-backward step-down selection then identified seven major determinants of death ECOG-PS (OR 2.47 1.87-3.26), neutrophil count (OR 2.46 1.76-3.44), serum procalcitonin (OR 2.37 1.64-3.43), development of pneumonia (OR 1.95 1.48-2.58), c-reactive protein (CRP) (OR 1.90 1.43-2.51), tumor stage at COVID-19 diagnosis (OR 1.97 1.46-2.66) and age (OR 1.71 1.29-2.26). The ROC analysis for death of the selected model confirmed its diagnostic ability (AUC 0.78; 95%CI: 0.75 – 0.81). The nomogram was able to classify the COVID-19 mortality in an interval ranging from 8% to 90% and the tree-based model recognized ECOG-PS, neutrophil count and CRP as the major determinants of prognosis. Conclusion From 73 variables analyzed, seven major determinants of death have been identified. Poor ECOG-PS demonstrated the strongest association with poor outcome from COVID-19. With our analysis we provide clinicians with a definitive prognostication system to help determine the risk of mortality for patients with thoracic malignancies and COVID-19.

The treatment of small cell lung cancer (SCLC) is a challenge for all specialists involved. New treatments have been added to the therapeutic armamentarium in recent months, but efforts must continue to improve both survival and quality of life. Advances in surgery and radiotherapy have resulted in prolonged survival times and fewer complications, while more careful patient selection has led to increased staging accuracy. Developments in the field of systemic therapy have resulted in changes to clinical guidelines and the management of patients with advanced disease, mainly with the introduction of immunotherapy. In this article, we describe recent improvements in the management of patients with SCLC, review current treatments, and discuss future lines of research.

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