The five-year survival rate is the percentage of people in a study group who survive five years after their diagnosis and treatment. This number may include recurrent disease. However, it may not include all the people with the disease. There are some ways to determine survival status in a cancer study. Here are some tips to help you understand your current survival status. The percentage varies based on the age and comorbidity of your disease.
Age
This study found that age and survival status influenced the symptoms of cancer. The severity of symptoms varied according to the survival status, but the effects of age on patient variables were not significant. Older patients were less likely to require assistance, and those younger than 65 were more likely to need care from caregivers. These findings suggest that the age of survivors may influence the severity of symptoms and other outcomes. Furthermore, aging may affect the quality of life of the patient and his family.
Comorbidity
Findings from a recent study show that comorbidity levels and insurance status have a significant impact on survival. Patients without private insurance and those with more comorbid conditions had a 40% to 90% higher risk of dying within a year. This effect may be due to differences in treatment and health insurance coverage. In the present study, the findings suggest that patients with multiple comorbidities are more likely to die than those without a comorbidity.
Stage
In 1985, Dr. Mullan published an essay on the stage of survival after cancer. The essay pointed out that patients in the advanced stages of the disease face an especially challenging transition. Since they are no longer receiving treatment, they may not be feeling active and may see cancer as a chronic condition. This is because long-term survivors tend to be more emotionally and physically inactive than those in the earlier stages of the disease. In order to cope with this, survivors should be aware of the stages of cancer and how to identify each one.
Grade
The grade of survival status is a significant predictor of mortality for breast cancer. In fact, the three variables are so powerful that combined effects result in a 20 to 40-fold increase in breast cancer mortality. Breast cancer is more fatal if it is high grade (T1N0) or large. Intermediate/high grade tumours also have high mortality rates, similar to triple negative breast cancer. The most effective strategies for early detection of breast cancer depend on the subtype of the cancer.
Alcohol consumption
There are a number of factors associated with alcohol consumption and survival, which may help us better understand the role of alcohol in cardiovascular disease. Moderate alcohol consumption may improve cardiovascular health by raising HDL levels, which are associated with greater protection from heart disease. It may also increase insulin sensitivity, improve blood clotting factors, and reduce the risk of small blood clots that can block arteries in the heart, neck, and brain.
Race
The survival status of different races in the United States varies greatly. For example, the survival rate of women who have breast cancer is about half that of women who have the same disease but are black. This discrepancy in survival rates is not entirely due to race, but rather to socioeconomic factors. In a recent study, researchers from the National Cancer Institute (NCI) analyzed data from the SEER program, which included all cases diagnosed between 1973 and 1979 and followed until 1981. The data included eight racial/ethnic groups, making it representative of 10% of U.S. population. Residents of cities such as San Francisco, Detroit, and Seattle were included in the study.
Socioeconomic status
This study found that socioeconomic differences are associated with lower cancer survival for patients from lower socioeconomic groups. The researchers conducted a systematic review and meta-analysis to determine the associations between socioeconomic status and survival of patients with lung cancer. The results showed that socioeconomic status was a reliable predictor of survival. But it was not a perfect predictor. Some of the results were based on small sample sizes. However, the findings suggest that social networks may influence survival.