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OBJECTIVE: To identify the difference in breast cancer mortality rates among young women according to countries' economic classification. METHODS: A systematic literature review included retrospective studies on breast cancer mortality rates in women aged 20 to 49 years. Databases used were PubMed, Web of Science, Scopus, and Virtual Health Library, with articles selected in English, Portuguese, and Spanish. The study selection and analysis were conducted by two pairs of researchers. Data from 54 countries were extracted, including 39 high-income, 12 upper-middle-income, and 3 lower-middle-income countries. A meta-analysis was performed with the quantitative data from two studies. RESULTS: Six articles met the inclusion criteria. Four were analyzed descriptively due to data diversity, and two were included in the meta-analysis. The pooled mortality rate for high-income countries was 10.2 per 100,000 women (95% CI: 9.8-10.6), while for upper-middle-income countries, it was 15.5 per 100,000 women (95% CI: 14.9-16.1). Lower-middle-income countries had a pooled mortality rate of 20.3 per 100,000 women (95% CI: 19.5-21.1). The decrease in mortality rates in high-income countries was statistically significant (p<0.05). CONCLUSION: Mortality rates for breast cancer among young women have decreased significantly in high-income countries but have increased in lower-income countries. This disparity underscores the impact of insufficient investment in preventive measures, health promotion, early diagnosis, and treatment on young women's mortality in lower-income countries.
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Neoplasias de la Mama , Países Desarrollados , Países en Desarrollo , Humanos , Femenino , Neoplasias de la Mama/mortalidad , Neoplasias de la Mama/patología , Pronóstico , Adulto Joven , Adulto , Tasa de Supervivencia , Renta , Persona de Mediana Edad , Factores SocioeconómicosRESUMEN
Background: Patients in serious condition due to COVID-19 often require special care in intensive care units (ICUs). This disease has affected over 758 million people and resulted in 6.8 million deaths worldwide. Additionally, the progression of the disease may vary from individual to individual, that is, it is essential to identify the clinical parameters that indicate a good prognosis for the patient. Machine learning (ML) algorithms have been used for analyzing complex medical data and identifying prognostic indicators. However, there is still an urgent need for a model to elucidate the predictors related to patient outcomes. Therefore, this research aimed to verify, through ML, the variables involved in the discharge of patients admitted to the ICU due to COVID-19. Methods: In this study, 126 variables were collected with information on demography, hospital length stay and outcome, chronic diseases and tumors, comorbidities and risk factors, complications and adverse events, health care, and vital indicators of patients admitted to an ICU in southern Brazil. These variables were filtered and then selected by a ML algorithm known as decision trees to identify the optimal set of variables for predicting patient discharge using logistic regression. Finally, a confusion matrix was performed to evaluate the model's performance for the selected variables. Results: Of the 532 patients evaluated, 180 were discharged: female (16.92%), with a central venous catheter (23.68%), with a bladder catheter (26.13%), and with an average of 8.46- and 23.65-days using bladder catheter and submitted to mechanical ventilation, respectively. In addition, the chances of discharge increase by 14% for each additional day in the hospital, by 136% for female patients, 716% when there is no bladder catheter, and 737% when no central venous catheter is used. However, the chances of discharge decrease by 3% for each additional year of age and by 9% for each other day of mechanical ventilation. The performance of the training data presented a balanced accuracy of 0.81, sensitivity of 0.74, specificity of 0.88, and the kappa value was 0.64. The test performance had a balanced accuracy of 0.85, sensitivity 0.75, specificity 0.95, and kappa value of 0.73. The McNemar test found that there were no significant differences in the error rates in the training and test data, suggesting good classification. This work showed that female, the absence of a central venous catheter and bladder catheter, shorter mechanical ventilation, and bladder catheter duration were associated with a greater chance of hospital discharge. These results may help develop measures that lead to a good prognosis for the patient.
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COVID-19 , Unidades de Cuidados Intensivos , Aprendizaje Automático , SARS-CoV-2 , Humanos , COVID-19/mortalidad , Femenino , Masculino , Estudios Retrospectivos , Persona de Mediana Edad , Brasil/epidemiología , Anciano , Factores Protectores , Adulto , Factores de Riesgo , Pronóstico , Alta del Paciente/estadística & datos numéricos , Tiempo de Internación/estadística & datos numéricosRESUMEN
BACKGROUND: Lung cancer (LC) is one of the main causes of mortality in Brazil; geographic, cultural, socioeconomic and health access factors can affect the development of the disease. We explored the geospatial distribution of LC mortality, and associated factors, between 2015 and 2019, in Parana state, Brazil. METHODS AND FINDINGS: We obtained mortality (from the Brazilian Health Informatics Department) and population rates (from the Brazilian Institute of Geography and Statistics [IBGE]) in people over 40 years old, accessibility of oncology centers by municipality, disease diagnosis rate (from Brazilian Ministry of Health), the tobacco production rate (IBGE) and Parana Municipal Performance Index (IPDM) (from Parana Institute for Economic and Social Development). Global Moran's Index and Local Indicators of Spatial Association were performed to evaluate the spatial distribution of LC mortality in Parana state. Ordinary Least Squares Regression and Geographically Weighted Regression were used to verify spatial association between LC mortality and socioeconomic indicators and health service coverage. A strong spatial autocorrelation of LC mortality was observed, with the detection of a large cluster of high LC mortality in the South of Parana state. Spatial regression analysis showed that all independent variables analyzed were directly related to LC mortality by municipality in Paraná. CONCLUSIONS: There is a disparity in the LC mortality in Parana state, and inequality of socioeconomic and accessibility to health care services could be associated with it. Our findings may help health managers to intensify actions in regions with vulnerability in the detection and treatment of LC.
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Neoplasias Pulmonares , Humanos , Adulto , Brasil/epidemiología , Estudios Transversales , Factores Socioeconómicos , Ciudades , Neoplasias Pulmonares/epidemiologíaRESUMEN
Objective: Compare the breast cancer mortality rate and the rate of mammograms with socioeconomic factors, in Brazilian´s Federative Units, during the period of 2015 to 2021. Methods: This is an ecological study, of a descriptive nature, which covers the 27 Brazilian federative units, using secondary data extracted from the DATASUS System. The information analyzed was mammography data, breast cancer mortality, demographic and economic data of the resident population and women over 20 years of age. Results: There is a direct relationship between mortality rate and mammograms rates in the Federative Units. The data obtained for Brazil presents a total of 133,048 deaths from breast cancer and 17,324,526 mammography exams in the period from 2015 to 2021. In other words, Brazil presents a standardized mortality rate value, 19.25 deaths per 100,000 women. Regarding the mammography rate, the value of the exam-specific mammography rate was 2,506.55 per 100,000 women. In relation to socioeconomic data by mortality rate group, higher mortality rates from breast cancer present higher rates in the variables: income rate by State (2,594.86), people with income (63.5), average percentage of women with more over 50 years old (29.5%), women with average years of education (6.64), white population (55.1%) and mammography exam rate (2873.20). When analysing the highest rates of mammography exam rates, higher rates are observed income rate by State (2,161.47), people with income (62.5%), average percentage of women over 50 years old (28.6%), women with an average number of years of education (5.8). Conclusion: Brazil has a high mortality rate due to breast cancer, when compared to other countries. The reasons are diverse, such as the modern, industrialized and populous lifestyle. The Federative Units with the highest mortality rate also have high rates of mammograms, that is, in the Federative Units with "better" sociodemographic conditions, the South and Southeast.