Survival statistics for non–small cell lung cancer
Survival statistics for non–small cell lung cancer (NSCLC) are very general estimates and must be interpreted very carefully. Because these statistics are based on the experience of groups of people, they cannot be used to predict a particular person’s chances of survival.
There are many different ways to measure and report cancer survival statistics. Your doctor can explain the statistics for NSCLC and what they mean to you.
Net survival represents the probability of surviving cancer in the absence of other causes of death. It is used to give an estimate of the percentage of people who will survive their cancer.
In Canada, the 5-year net survival for non–small cell lung cancer is 17%. This means that, on average, about 17% of people diagnosed with non–small cell lung cancer will survive for at least 5 years.
Relative survival looks at how likely people with cancer are to survive after their diagnosis compared to people in the general population who do not have cancer, but who share similar characteristics (such as age and sex).
Survival by stage
Survival varies with each stage of non–small cell lung cancer. The following factors can also affect survival for non–small cell lung cancer.
- Generally, the earlier NSCLC is diagnosed and treated, the better the outcome.
- However, NSCLC is often not found until it is at an advanced stage, which can make it somewhat more difficult to treat.
There are no specific Canadian statistics available for the different stages of non–small cell lung cancer. The following information comes from a variety of sources and may include statistics from other countries.
|Stage||5-year relative survival|
Questions about survival
Talk to your doctor about your prognosis. A prognosis depends on many factors, including:
- your health history
- the type of cancer
- the stage
- certain characteristics of the cancer
- the treatments chosen
- how the cancer responds to treatment
Only a doctor familiar with these factors can put all of this information together with survival statistics to arrive at a prognosis.
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