Prognosis and survival for prostate cancer
If you have prostate cancer, you may have questions about your prognosis. A prognosis is the doctor's best estimate of how cancer will affect someone and how it will respond to treatment. Prognosis and survival depend on many factors. Only a doctor familiar with your medical history, the type and stage and other features of the cancer, the treatments chosen and the response to treatment can put all of this information together with survival statistics to arrive at a prognosis.
A prognostic factor is an aspect of the cancer or a characteristic of the person that the doctor will consider when making a prognosis. A predictive factor influences how a cancer will respond to a certain treatment. Prognostic and predictive factors are often discussed together. They both play a part in deciding on a treatment plan and a prognosis.
The following are prognostic and predictive factors for prostate cancer.
Prostate cancer with a lower stage at diagnosis has a more favourable prognosis. Cancer that hasn't spread outside of the prostate at the time of diagnosis has a better prognosis than cancer that has spread outside of the prostate.
The lower the Gleason score the better the prognosis. Prostate cancer with a Gleason score lower than 7 has a more favourable prognosis than prostate cancer with a score of 7 or higher.
Prostate-specific antigen (PSA) level @(Model.HeadingTag)>
Some research shows that a higher than normal
PSA doubling time @(Model.HeadingTag)>
PSA doubling time measures the time it takes the PSA level to double. For example, a PSA doubling time of 3 years means that, on average, the PSA level doubles every 3 years. PSA doubling time can help doctors find out if a prostate cancer is aggressive, which means it is more likely to grow quickly and spread. Shorter doubling times are linked to a worse prognosis.
Risk groups @(Model.HeadingTag)>
Doctors may classify prostate cancer into groups based on the risk of the cancer coming back (recurring) after treatment. These risk groups are based on the tumour (T), Gleason score and PSA level. The lower the risk group, the lower the risk of prostate cancer recurring after a radical prostatectomy.
Learn more about risk groups for prostate cancer.
Nomograms are statistical models that predict a probable outcome. They take into account the stage, Gleason score, PSA level, pathology reports based on biopsy samples, use of hormone therapy, radiation dose and other specific information about you, such as your age or treatments you have already received.
The nomograms used to predict a prognosis for prostate cancer include:
Cancer of the prostate risk assessment (CAPRA) nomogram @(Model.HeadingTag)>
Doctors use the cancer of the prostate risk assessment (CAPRA) nomogram to help them predict the risk that prostate cancer will spread, predict the risk of dying from prostate cancer and make treatment decisions. This nomogram is based on:
- the PSA level
- the Gleason score
- the percentage of biopsy samples that have cancer
- the stage
- your age when you are diagnosed
Partin tables @(Model.HeadingTag)>
Partin tables are a nomogram that helps doctors predict the chance that cancer will spread before surgery to remove the prostate. This helps them make treatment decisions. Partin tables are based on the:
- Gleason score
- PSA level
There is some evidence that those who smoke at the time of diagnosis are more likely to have a biochemical recurrence (also called a biochemical failure) and die from prostate cancer than those who don't smoke. A biochemical recurrence means that the PSA level starts to rise after treatment but there are no other signs of cancer.
Levels of certain chemicals in the blood @(Model.HeadingTag)>
The levels of certain chemicals in the blood can predict a worse prognosis in men with metastatic castrate-resistant prostate cancer. They include:
- high alkaline phosphatase
- low hemoglobin
- low albumin
- high lactate dehydrogenase
Learn more about chemicals measured in the blood.
Genetic signatures @(Model.HeadingTag)>
Gene expression profiling is a way to analyze many
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