Looking at research
This page is a brief guide to making sense of statistics in research papers. There is information about
More and more people with cancer are looking for information about treatments for themselves. Many people use the internet to try to find out about new treatments. But it is important to think about what you read. Cancer research is going on all over the world. A single research paper in isolation will not give you the whole picture about research into that particular type of cancer. It needs to be read in the context of all the other relevant research.
Each time a new treatment makes it through all the stages of research and clinical trials, it will have a large number of published research papers about it. Mostly these will have shown it to be a useful new treatment that may contribute to slowing down, or curing a cancer. But amongst those papers, there are likely to be one or two that showed that it didn't work better than the existing treatment it was compared to. These results that seem opposite to the others may have happened by chance. Or there may have been problems with the patient group that was selected. Or there may have been difficulties with giving the treatment.
What the doctors are looking for is evidence that on balance the treatment is an improvement. Sometimes statisticians gather together all the results of all the trials and do a 'meta-analysis'. This is an academic paper that compares all the results to give a broader picture.
The point that we are trying to make is that reading any one of these papers is unlikely to give you the broader picture. You probably can't rely on research results that come from just one study.
We can't give you a crash course in understanding statistical analysis here. If you read academic papers, you will be faced with the names of statistical tests and results claiming '95% confidence intervals'.
These are based on statistical tests, such as, 'T tests' and 'chi squared tests', which are ways of mathematically comparing results to see if there really is a difference between two treatments. 'Confidence intervals' are used to show the likelihood of a result happening by chance. For example, if a result is declared with 95% confidence, then it means the researchers are pretty sure that the result is OK and has not happened by chance.
If you understand statistics you may find reading the results of research helpful. If not, don't worry. Read the discussion at the end of the paper you are looking at. This part usually explains the claims in the research paper more clearly.
There are a few important points you may like to bear in mind when looking at research. Here are a few questions you might ask
- What type of cancer is being investigated? If it is not the type you have, then the treatment is unlikely to be helpful to you.
- What stage are the patients in the study? Is it a treatment for early stage or advanced cancer, or for treatment after surgery to try to stop the cancer coming back?
- How many patients were involved in the study? The bigger the numbers, the more likely the results are accurate. The fewer there are, the more likely the results happened by chance. The most accurate studies use thousands of people, often in many different countries.
- What was the aim of the trial? Phase 3 clinical trials compare a new treatment with the current standard treatment. Earlier phase trials look more at things such as what happens to the drug inside the body and what the side effects are.
- Was it a controlled trial? This means the treatment was compared with standard treatment (which might be no treatment). Patients were allocated one or other treatment at random to prevent 'bias' (for example, a treatment may seem better because the doctors used it for all the healthier patients and gave the other treatment to all the sicker patients).
- How much did the new treatment help? Sometimes a new treatment seems really promising when you read the reports. But when you look in more detail, people only lived a few weeks longer.
- Did the trial look at the patients' quality of life? For a treatment to be useful, the benefits need to outweigh any inconvenience or side effects. If the side effects are too severe, then your quality of life could be made worse than it would be without the treatment. This is especially important if the treatment is only going to slow down the cancer for a while.
It is fine to look for information about a new treatment if you know the answer to all these questions and decide it is still for you. But it is important to understand clearly what you are likely to gain.
The questions above are important when looking at 'alternative treatments' too. Many 'research studies' used to promote alternative treatments are case studies. This means they are the story of one or two patients who have been given the treatment. There is no comparison with other patients in a case study. So, in this situation we don't know whether the treatment worked or whether the patients would have stayed well anyway.
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