Análise de sobrevivência de mulheres com câncer de mama: modelos de riscos competitivos

Abstract

This study aimed to estimate the effects of prognostic factors on breast cancer survival, such as age, staging, and extension of the tumor, using proportional hazards and competing risks models proposed by Cox and Fine-Gray, respectively. This is a retrospective cohort study, based on a population of 524 women, who were diagnosed with breast cancer in the period from 1993 to 1995 and monitored until 2011, residents in the city of Campinas, São Paulo, Brazil. The cutoff points for the variable of age were defined with Cox simple models. In the settings of simple and multiple Fine-Gray models, age was not significant to the presence of competing risks, neither it was in Cox models. For both models, death by breast cancer was the event of interest. The survival functions, estimated by Kaplan-Meier, showed significant differences for deaths by breast cancer and by competing risks. Survival functions by breast cancer did not show significant differences when comparing the age groups, according to log-rank test. Cox and Fine-Gray models identified the same prognostic factors that influenced in breast cancer survival.

Prostate Cancer Survival and Mortality according to a 13-year retrospective cohort study in Brazil: Competing-Risk Analysis

“…These datasets allow to identify many patients across a broad spectrum of comorbidities, providing information regarding disparities in care and outcomes, such as mortality and survival, at local, state, and national levels in the countries 20,21 . Cancer survival analysis based on big data supports the public health system for preventing new cases, extending survival after cancer diagnosis, and reducing inequalities in access to cancer treatment [17][18][19][20][21] .…”

“…By interpreting the results of survival studies, in which death is the event of interest, competitive risks are an important issue to be assessed. Therefore, methods specifically designed for such analyses should be employed, such as Fine and Gray's method for competitive risks [13][14][15][16][17] , whereas many studies use traditional methods such as the Kaplan-Meier estimator and Cox's proportional hazards model 18,19 . RESUMO: Objetivo: Analisar a mortalidade câncer-específica (MCE) e a mortalidade por outras causas (MOC) em pacientes diagnosticados com câncer da próstata que iniciaram tratamento no Sistema Único de Saúde (SUS) entre 2002 e 2010, no Brasil.…”

Disparidade racial na sobrevivência em 10 anos para o câncer de mama: uma análise de mediação usando abordagem de respostas potenciais

“…Gráfico com as curvas de sobrevivência específica em 10 anos por câncer de mama estratificada por raça/cor, estimadas pelo método de Kaplan-Meier. cidade de Campinas, São Paulo, estimou uma sobrevivência específica de 68,9% em 10 anos 25 . Os outros três estudos foram feitos com coortes hospitalares: em Joinville, Santa Catarina, com mulheres diagnosticadas em 2008, a sobrevivência específica foi de 83,1% 8 ; em Juiz de Fora, Minas Gerais, com mulheres diagnosticadas em 2000 e 2001, a sobrevivência global foi de 56,3% 6 ; em Santa Maria, Rio Grande do Sul, com mulheres diagnosticadas entre 1980 e 2000, a sobrevivência global foi de 78,7% 26 .…”

Transition to exclusive palliative care for women with breast cancer

“…In North America, Sweden, and Japan, for example, the breast cancer survival rate varies around 80%, while in middle-income countries this variation is around 60%. The situation is even worse in low-income countries, with a survival rate of approximately 40%, the main reason being the delay in diagnosis and the consequent more advanced stage of the disease (1,4) .…”