Cancer can be treated very well for many people. In fact, more people than ever before lead full lives after cancer treatment, but it is important to note that cancer that is diagnosed at an early stage, before it’s had the chance to get too big or spread is more likely to be treated successfully. If the cancer has spread, treatment becomes more difficult, and generally a person’s chances of surviving are much lower.
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.
Factors that affect Prognosis of Cancer
There are several factors that affect the prognosis of a cancer. 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:
- Type of cancer
- Subtype of cancer based on the type of cells or tissue (histology)
- 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:
- 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
Types of survival statistics
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 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 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 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 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
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 Disease-Free Survival (DFS) and Progression-Free Survival (PFS):
- Disease-Free Survival Rate. This is the number of people who have no evidence of cancer after treatment.
- Progression-Free Survival Rate. This is the number of people who have been treated for cancer and either have no signs of cancer recurrence or who have cancer that has remained stable without growing.