Disparities in breast cancer mortality among Latin American women: trends and predictions for 2030.

BACKGROUND: Breast cancer is among the leading cause of cancer-related mortality among Latin American and Caribbean (LAC) women, but a comprehensive and updated analysis of mortality trends is lacking. The objective of this study was to determine the breast cancer mortality rates between 1997 and 2017 for LAC countries and predict mortality until 2030. METHODS: We retrieved breast cancer deaths across 17 LAC countries from the World Health Organization mortality database. Age-standardized mortality rates per 100,000 women-years were estimated. Mortality trends were evaluated with Joinpoint regression analyses by country and age group (all ages, < 50 years, and ≥ 50 years). By 2030, we predict number of deaths, mortality rates, changes in population structure and size, and the risk of death from breast cancer. RESULTS: Argentina, Uruguay, and Venezuela reported the highest mortality rates throughout the study period. Guatemala, El Salvador, and Nicaragua reported the largest increases (from 2.4 to 2.8% annually), whereas Argentina, Chile, and Uruguay reported downward trends (from - 1.0 to - 1.6% annually). In women < 50y, six countries presented downward trends and five countries showed increasing trends. In women ≥ 50y, three countries had decreased trends and ten showed increased trends. In 2030, increases in mortality are expected in the LAC region, mainly in Guatemala (+ 63.0%), Nicaragua (+ 47.3), El Salvador (+ 46.2%), Ecuador (+ 38.5%) and Venezuela (+ 29.9%). CONCLUSION: Our findings suggest considerable differences in breast cancer mortality across LAC countries by age group. To achieve the 2030 sustainable developmental goals, LAC countries should implement public health strategies to reduce mortality by breast cancer.

ASCO-Sponsored Oncology Student Interest Groups in the World.

PURPOSE: In 2015, ASCO established a program designed to support medical interest in cancer-related careers: Oncology Student Interest Groups (OSIGs). The purpose of this study was to describe the characteristics of current student leaders of ASCO-sponsored OSIGs and their perceptions of cancer-related careers. METHODS: We reviewed the list of all ASCO-sponsored OSIGs between 2015 and 2021. For this study, we focused on OSIGs that were sponsored during the 2019-2020 academic year. All student leaders of the 89 OSIGs active in that academic year were invited to participate. RESULTS: The number of groups has more than tripled in the 6 years since the program's inception. The number of international groups has increased to become almost one fifth of all OSIGs; however, the range of countries represented remains limited. The majority of OSIG leaders were female. Eighty two percent of OSIGs were returning members, with most of their leaders being registered ASCO student members. Almost all participants reported an interest in pursuing a cancer-related specialty. Only a minority (14.8%) reported having a family member working in a cancer-related career. However, 85% reported having experience with a cancer diagnosis in their family. The majority of the respondents had a favorable perception of medical oncology as a specialty. Participants reported the highest levels of interest in medical oncology and pediatric oncology. CONCLUSION: The number of ASCO-sponsored OSIGs has steadily increased since the creation of the program. Most participants reported an interest in pursuing a cancer-related career. To our knowledge, this study is the first to provide insights into the makeup of this program around the world. Additional efforts are needed to increase the global reach of the program, particularly in low-income countries.

Effects and safety of SGLT2 inhibitors compared to placebo in patients with heart failure: A systematic review and meta-analysis.

BACKGROUND: Heart failure (HF) prognosis without therapy is poor, however introduction of a range of drugs has improved it. We aimed to perform a systematic review on the effects and safety of sodium-glucose transporter 2 inhibitors (SGLT2i) in HF patients. METHODS: We carried out a systematic review of randomized controlled trials (RCTs) on SGLT2i compared to placebo for HF patients. We searched in PubMed, Scopus, Web of Science and EMBASE, with no language restriction, from inception to 31 August 2020. We included nine RCTs comprising three arms (empagliflozin, dapagliflozin and placebo). Effects sizes for continuous variables were expressed as mean differences (MDs) and 95% confidence intervals (CIs). Effects sizes for dichotomous variables were expresses as risk ratio (RR) and 95% CIs. We used random-effect models with the inverse variance method. We performed subgroup meta-analyses by intervention drug and follow-up period. RESULTS: SGLT2i significantly reduced all-cause mortality (RR: 0.88, 95%CI 0.79-0.98, I2 = 0%), cardiovascular mortality (RR: 0.87, 95%CI 0.77-0.99, I2 = 0%), HF hospitalization (RR: 0.73, 95%CI 0.66-0.81, I2 = 0%) and emergency room visits due to HF (RR: 0.40, 95%CI 0.21-0.76, I2 = 0%), as well as composite outcomes including the previous ones. Besides, it significantly improved the score of the Kansas City Cardiomyopathy Questionnaire (KCCQ, MD: 1.70, 95%CI 1.67-1.73, I2 = 54%). SGLT2i reduced any serious adverse events, blood pressure and weight. However, it increased hematocrit and creatinine. The meta-analysis of RCTs of > 12 weeks of follow-up showed that SGTL2i significantly reduced NT-proBNP. CONCLUSIONS: SGLT2i showed to improve critical outcomes in HF patients, and it is apparently safe.

Metodologías Cuantitativas 2: Sesgo de confusión y cómo controlar un confusor / Quantitative Methodologies 2: Confusion bias and how to control a confounding factor

Identificar el sesgo de confusión y cómo controlarlo es uno de los desafíos metodológicos más importantes en el diseño de estudios que buscan identificar la causalidad. Este sesgo está presente en cualquier análisis de la asociación entre una exposición y un resultado de interés, una asociación que puede estar sesgada o no por una tercera variable llamada confusor. Podemos diagnosticar un confusor en todos los casos en los que este crea una asociación espuria entre una variable de exposición o variable independiente y la variable de resultado o variable dependiente. Para controlar el sesgo de confusión, podemos usar diferentes métodos. Estos incluyen aquellas técnicas aplicadas en el diseño del estudio, tales como restricción, aleatorización y coincidencia, y aquellas técnicas empleadas en el análisis de datos, como la estratificación, el análisis multivariado, la estandarización, los puntajes de propensión, el análisis de sensibilidad y el inverso ponderación de probabilidad. En esta revisión, analizamos cómo identificar una variable de confusión y las principales técnicas para controlar el sesgo de confusión.

Addressing confounding bias is one of the challenges when conducting causality studies. This occurs when we report a causal association between an exposure and an outcome, when in fact it could be result of the effect of a third factor called confounding variable. That is, when a confounder variable creates a spurious relationship between the exposure or independent variable and the outcome of interest or dependent variable. By knowing the confounding variables and their association with the exposure of interest, the confounding bias could be controlled. To control for confounding bias, we can use different methods. These include techniques applied in study design, such as restriction, randomization, and coincidence, and techniques used in data analysis, such as stratification, multivariate analysis, standardization, propensity scores, analysis sensitivity and the inverse probability weighting. In this review, we discuss how to identify a confounding variable and the main techniques for controlling for confounding bias.