Hi

I hope someone here may be able to point me in the right direction.

I am an undergraduate medical student doing a project which aims to look at
whether information obtained in the diagnosis of certain forms of cancer can
predict the presence of lymph node metastasis.

A "core biopsy" of tissue is removed from the cancer lump either using
imaging techniques or palpation to ensure that the needle passes through the
tumour. These pieces of tissue are examined by a pathologist who determines
whether cancer is present and grades it accordingly. I would like to ask the
following question with the information obtained: Is there any information
in the core which can either predict the presence of disease positive lymph
nodes or the absence? Lymph node disease is detected at subsequent surgery.
I also hope to combine this with measurement of tumour size by clinical or
radiological techniques.
Therefore the fields I am using from my data set are:

Positive Lymph Nodes (yes/no or 1/0); grading criteria A (a numerical scale
1-3), B (1-3), C (1-3) and tumour size (diameter in mm).

I have been advised to use binary logistical regression and have been
looking at Minitab, but have not really got that far despite reading every
text book I can find with a chapter on this. I am beginning to think that
the key problem is that each variable is not binary, they all have 3 values
and the size can be a wide range, however, I can categorise this.

Basically I want to identify if any of the criteria alone or preferably in
combination can predict lymph node disease. How do I interpret the results
from Minitab. Is it possible to convert the results to % so for example I
could say A1 B<2 C1 and tumour size less than 5mm means you are 5% likely to
have mets.

Is there anyone who is able to help me out, it shouldn't take more than a
couple of emails.

Thanks in advance

Ronan

P.S. Help on the best way to assemble the data and run the dialogues in
Minitab would also be a great help.


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