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Medicine is a field which is based on statistical analysis of thousands of patient outcomes. This is very apparent in the field of cancer treatment.

In order to research and evaluate various cancer treatments, it's important to be able to understand some medical statistical terms. The goal of this article is to help you comprehend some of the more commonly used medical statistical terms.

The exact outcome of any particular patients is, of course, impossible to predict with any degree of certainty. The reality is that cancer mortality rates are based on the statistical analysis of a large number of patients who have had the same cancer. Remember, medical statistics are only probabilities.

Every particular type of cancer has different outcome statistics. Some cancers clearly have worse prognoses than others.

It's also important to be aware that the probability of being cured from a particular cancer depends very much on the stage of the cancer.

In all forms of cancers, the survival rates of patients with stage 1 disease exceed the survival rates of patients with stage 2 disease. Similarly, the survival rates of patients with patients with stage 2 disease exceed the survival rates of patients with stage 3 disease. Finally, the survival rates of patients with patients with stage 3 cancer exceed the survival rates of patients with stage 4 cancer.

Thus, being aware of the stage of the disease you have is critical.

Here then is a brief list of some of the more common medical statistical terms.

Five Year Survival

When doctors discuss the probability of survival, they discuss a term that's known as the 5 year survival. The 5 year survival represents the probability that someone with a particular cancer will be alive five years after diagnosis.

As an example, if the 5 year survival is 25%, this means that the odds of being alive after 5 years are 25%. To be sure that this term is being used accurately, it's necessary to look at the actual type of patients for whom the 5 year survival number is being quoted. For example, it might include all patients with a certain type of cancer or it could only involve patients with a certain stage of that cancer.

For example, 49 percent, or about half, of people diagnosed with early-stage lung cancer live for at least five years after diagnosis. So, the five year survival for patients with early-stage lung cancer is 49%. In contrast, the five year survival rate for patients diagnosed with metastatic lung cancer (lung cancer that has widely spread or metastasized to other areas of the body) is only 3 percent.

Thus, it's critical to know the survival rate for patients with the same stage of disease.

Remission

Shrinking of a cancer is referred to as remission.

There are remissions which are known as complete remissions those which are known as partial remissions. Remissions are called either complete or partial depending on whether or not any trace of cancer remains. If no evidence of cancer can be found after treatment, then the remission is considered complete.

If the cancer has decreased in size but hasn't disappeared completely, then the remission is considered to be partial.

A complete remission may represent a cure. But the possibility exists that the cancer will regrow. This depends usually to a great extent on the type of cancer as some cancers have more of a tendency to regrow than others. In people who achieve only partial remissions, the cancer nearly always regrows.

The 5 year survival rate predicts the percentage of patients that will be alive at the end of 5 years. It doesn't predict however the number of patients that will be in complete remission at the end of 5 years (in other words how many people will have survived for 5 years and have no evidence of cancer).

So here are two more specific terms:

Disease-free 5 year Survival Rate

This term refers to the percentage of patients who are not only alive after 5 years but are in complete remission.

Progression-free 5 Survival Rate

This term refers to the percentage of patients who are alive after 5 years but who still have evidence of cancer, although the cancer isn't progressing. This category includes patients who may have had some success with treatment but not enough to completely eliminate the cancer.

Two other statistical terms that are important to understand are relative risk and absolute risk:

Absolute Risk Reduction Or Benefit

This term refers to the absolute difference in results between treatments. So, for example, if treatment A increased survival by 12% and treatment B increased survival by 10% then treatment A resulted in an absolute benefit of (12%-10%) = 2%.

Relative Risk Reduction Or Benefit

This term refers to the relative difference in results between alternatives. In the example above, the relative benefit is (12%-10%)/10% = 20%. This number is calculated by taking the difference in outcome as a percentage.

Frequently, results are presented as relative risk reduction or benefit rather than absolute risk reduction or benefit because the numbers sound more impressive when presented in this fashion. For example, in the example above, a relative benefit of 20% sounds more impressive than an absolute benefit of 2%.

Hopefully, you now have a better understanding about how to interpret cancer statistics.