Prognosis and survival
Many people want to know their chance of surviving after a diagnosis of cancer. Your doctor is the best person to ask. A prognosis is your doctor’s best estimate of how cancer will affect you and how it will respond to treatment.
Prognostic and predictive factors are used to help develop a treatment plan and predict the outcome.
- A prognostic factor is a feature of the cancer (like the size of the tumour) or a characteristic of the person (like their age) that may affect the outcome.
- A predictive factor can help predict if a cancer will respond to a certain treatment. Some drugs only work if molecules (such as proteins) are on cancer cells or inside them.
Your doctor will also consider survival statistics for your type of cancer. Only a doctor familiar with all of these factors can put the information together to arrive at a prognosis. Ask your doctor about the factors that affect your prognosis and what they mean for you. Also, remember that a prognosis can change over time because cancer does not always do what it is expected to do.
Generally, the earlier cancer is found and treated, the better the outcome.
Prognostic factors @(Model.HeadingTag)>
Favourable prognostic factors can have a positive effect on the outcome. Unfavourable prognostic factors can have a negative effect on the outcome.
These are some important prognostic factors related to the cancer:
- the type of cancer
- the subtype of cancer based on the type of cells or tissue (histology)
- the size of the tumour
- how far and where the cancer has spread (stage)
- how fast the cancer cells are growing (grade)
These are important prognostic factors related to the person diagnosed with cancer:
- their age and sex
- any health problems and their overall health
- the ability to do everyday tasks like taking care of physical needs (performance status)
- any weight loss, and how weight has been lost
- how well they can cope with treatment side effects
- response to treatment
Predictive factors @(Model.HeadingTag)>
Important predictive factors include some types of
Some treatments are only effective if you have a specific marker or genetic mutation. This can help your doctor plan which treatment is best for you.
Types of survival statistics @(Model.HeadingTag)>
Doctors often look at studies that measure survival for a particular type of cancer, stage or risk group.
Keep in mind that cancer survival statistics are only very general estimates based on large numbers of people with cancer. Survival will be very different depending on the type and stage of the cancer. Also, statistics are based on numbers from several years ago and may not show the impact of recent advances in treating a certain cancer. They also may not account for different responses to treatment, other illnesses or dying from causes other than cancer.
So while cancer statistics can give you a general idea, they can’t predict exactly what will happen to you. Ask which type of survival rate your doctor is using and how it applies to you.
There are many different ways to measure and report cancer survival statistics. Most statistics are reported for a specific time period, usually for 5 years, but it may also be for 1, 3 or 10 years.
Net survival @(Model.HeadingTag)>
Net survival represents how likely it is to survive 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. Net survival tracks survival over time and compares survival between populations.
For example, a 5-year net survival of 50% means that, on average, about 50% of people will survive their cancer for at least 5 years.
Observed survival @(Model.HeadingTag)>
Observed survival is the percentage of people with a particular cancer who are alive at a certain point in time after their diagnosis. Observed survival does not consider the cause of death, so the people who are not alive 5 years after their diagnosis could have died from cancer or from another cause.
For example, a 5-year observed survival of 70% means that, on average, people have a 7 out of 10 chance of being alive 5 years after their diagnosis.
Relative survival @(Model.HeadingTag)>
Relative survival compares the survival for a group of people with cancer to the survival expected for a group of people in the general population who share the same characteristics as the people with cancer (such as age, sex or where they live). Ideally, the group of people used in the general population would not include people with cancer, but this estimate can be difficult to obtain. So relative survival can sometimes be overestimated.
Unlike observed survival, which considers all causes of death, relative survival measures survival from cancer only.
For example, a 5-year relative survival of 63% means that, on average, people diagnosed with cancer are 63% as likely to live for at least 5 years after their diagnosis compared to people in the general population. Estimates of relative survival can be greater than 100%. This means that the observed survival of the people with cancer is better than the expected survival from the general population.
Median survival @(Model.HeadingTag)>
Median means the middle value, or midpoint. Median survival is the length of time after diagnosis or the start of treatment at which half of the people with cancer are still alive. In other words, half of the people are expected to live at or beyond the median survival and the other half are not.
For example, if 50% of people with a cancer are still alive 12 months after their diagnosis, then the median survival is 12 months.
Other types of survival statistics @(Model.HeadingTag)>
There are other types of survival statistics that are used more often by researchers who are reporting results of clinical trials looking at new treatments for cancer. Examples of these include
American Society of Clinical Oncology. Understanding statistics used to guide prognosis and evaluate treatment. 2016: http://www.cancer.net/navigating-cancer-care/cancer-basics/understanding-statistics-used-guide-prognosis-and-evaluate-treatment.
Bauer A. Talking with your doctor about prognosis. 2016: http://www.cancer.net/blog/2014-08/talking-your-doctor-about-prognosis.
Mayo Clinic . Cancer survival rate: a tool to understand your prognosis . 2014 : https://www.mayoclinic.org/.
Nalejska E, Maczynska E, Lewandowska MA . Prognostic and predictive biomarkers: tools in personalized oncology. Molecular Diagnostics and Therapy. 2014: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4031398/.
National Cancer Institute. Understanding cancer prognosis. 2014: https://www.cancer.gov/about-cancer/diagnosis-staging/prognosis.
Simms L, Barraclough H, Govindan R . Biostatistics primer: what a clinician ought to know--prognostic and predictive factors . Journal of Thoracic Oncology . 2013 .