RESUMEN
This work presents a practical proposal for estimating health system utilization for COVID-19 cases. The novel methodology developed is based on the dynamic model known as Susceptible, Infected, Removed and Dead (SIRD). The model was modified to focus on the healthcare system dynamics, rather than modeling all cases of the disease. It was tuned using data available for each Brazilian state and updated with daily figures. A figure of merit that assesses the quality of the model fit to the data was defined and used to optimize the free parameters. The parameters of an epidemiological model for the whole of Brazil, comprising a linear combination of the models for each state, were estimated considering the data available for the 26 Brazilian states. The model was validated, and strong adherence was demonstrated in most cases.
Asunto(s)
COVID-19/epidemiología , Brasil/epidemiología , Atención a la Salud , Humanos , Aprendizaje Automático , Modelos Estadísticos , SARS-CoV-2/aislamiento & purificaciónRESUMEN
PURPOSE: Activation of proto-oncogenes and inactivation of tumour suppressor genes are the major genetic alterations involved in carcinogenesis. The increase in methylation at the promoter region of a tumour suppressor gene can lead to gene inactivation, selecting cells with proliferative advantage. Thus, promoter hypermethylation is considered a marker in a variety of malignant tumours, including oral cavity. EXPERIMENTAL DESIGN: The methylation pattern of eight genes was evaluated in 40 oral cavity squamous cell carcinomas (OSCCs) and 40 saliva samples from healthy individuals by Q-MSP. Different combinations of genes were also assessed in order to identify gene panels that could better distinguish between OSCC and saliva samples. RESULTS: CCNA1, DAPK, DCC and TIMP3 methylation were highly specific for being found in the OSCC samples. Moreover, the combination of these genes improved detection when compared with single markers, reaching values of 92.5% for sensitivity and specificity (when using the panel CCNA1, DCC, TIMP3). Moreover, DAPK, DCC and TIMP3 were hypermethylated in nearly 90% of clinically T1 and T2 cases. CONCLUSION: The pursuing of this panel of hypermethylated genes is an important tool for the detection of individuals with OSCC. Moreover, the identification of these markers in early stages of OSCC shows the feasibility of using the panel on saliva as possible biomarkers for early diagnosis. The lack of association between the methylation status of these genes and clinical characteristics shows that they are able to distinguish OSCC cases irrespective of social and clinical factors (gender, age, human papillomavirus (HPV) status, clinical stage, vascular embolisation and perineural invasion).
Asunto(s)
Biomarcadores de Tumor/genética , Carcinoma de Células Escamosas/genética , Metilación de ADN , Epigénesis Genética , Pruebas Genéticas/métodos , Neoplasias de Cabeza y Cuello/genética , Neoplasias de la Boca/genética , Adulto , Anciano , Brasil , Estudios de Casos y Controles , Ciclina A1/genética , Receptor DCC , Proteínas Quinasas Asociadas a Muerte Celular/genética , Estudios de Factibilidad , Femenino , Humanos , Masculino , Persona de Mediana Edad , Valor Predictivo de las Pruebas , Regiones Promotoras Genéticas , Receptores de Superficie Celular/genética , Reproducibilidad de los Resultados , Carcinoma de Células Escamosas de Cabeza y Cuello , Inhibidor Tisular de Metaloproteinasa-3/genética , Proteínas Supresoras de Tumor/genéticaRESUMEN
This study aims at documenting differentials in the cancer mortality profile of European countries during the recent process of intense geo-political transformations. The World Health Organization Regional Office for Europe provided information on cancer mortality and several covariates for each country. In contrast with the European Union and Nordic countries, Central and Eastern Europe presented higher current levels and increasing trend of cancer mortality. Age-standardized rates for overall cancer mortality increased at an annual average of 2.43% in Central and Eastern European countries during the period from 1980 to 2001, while the European Union, Nordic countries and Switzerland underwent an average decrease of 7.27% per year. Trends in cancer death rates were associated with indices of welfare and socio-economic status at the country level: gross national product, health expenditure, unemployment, food intake, smoking habits and air pollution. Concurrent with this observation, we registered an extended gap in standings for these figures between richer and poorer European countries. These observations suggest that part of cancer mortality in Central and Eastern Europe could be prevented with current technology and health promotion. The drop of rates in Nordic and Western European countries indicates a progress in cancer control that, regrettably, does not hold for the whole Continent.