One of the more interesting websites that has some interesting tools for making cancer-related predictions is nomograms.org, part of the website for Memorial Sloan Kettering Cancer Center. A nomogram is similar to the venerable slide rule, the old calculating device, but the important thing to know is that it allows for people to either use a pencil and paper to assign points for each of various risk factors that can be added together in a weighted way to produce a master “predicted risk” for a problem. Folks at Memorial Sloan Kettering and other centers have produced some very helpful tools, particularly in other cancer settings. Their predictive calculators for risks in prostate cancer can be very helpful in predicting outcomes after various treatments for prostate cancer based on multiple very relevant clinical variables.
There is only a single nomogram relevant to the field of lung cancer, and it relates not to treatment outcomes but to risk among current or former smokers of developing lung cancer in the next 10 years. This could be very helpful in determining who has a risk high enough to warrant screening CT scans, for instance (it can also demonstrate the difference in risk by quitting smoking vs. not). This tool is based on some very complex computerized modeling work done on a collection of more than 18,000 people enrolled on a trial of lung cancer prevention (looking at beta carotene and a form of vitamin A, and it didn’t work). From this modeling, a tool was developed that can predict risk in a limited group of people who were represented by the data on the trial (full article on the development of this tool here): it can only provide predictions for current or former smokers who quit within the last 20 years, smoked between 10 and 60 cigarettes per day for between 25 and 55 years, and are currently between the ages of 55 and 75. These are the situations for which the large trial data were available, so the calculation only applies for this population. The tool looks like this:
(Click to enlarge)
and the website where it’s available is here.
It would be great if we had more tools like this, based on large databases of cases with multiple variables and outcomes data. In a way, work I’ve described on serum proteins predicting survival on EGFR inhibitors (prior post here) and tumor gene signatures (prior post here) have a similar strategy, just looking at molecular instead of clinical variables. I hope we see a lot more of these, calculating based on molecular or clinical variables or both, in the next few years to help us refine our assessments of risk vs. benefit and make better predictions of what treatments will be most helpful.
posted by Dr. West @ 11:14 pm link to this post
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October 12th, 2007 at 11:03 am
Dr. West:
It seems to me that as a first step to get sophisticated algorithms to give more precise prognosis predictions one need to have large database available for NSCLC patients.
A natural way of achieving that is to ask for every statistical study done in NSCLC (either clinical or for risk assessment) to follow the same format and to be deposited in a fixed archival place that has free access.
In this way, statisticians, doctors, computer scientists and actually anyone who comes up with a nice prognostic hypothesis may go to the archival site and run multivariate analysis on the data . Furthermore, prognostic algorithms may be tested and refined using the database.
Nowadays the tools to run these statistical analysis as well as the ones needed to develop and calibrate algorithms are within the technological reach of almost anybody. The bottleneck is in the access to the data (and the more the better).
The natural organization that should be collecting all of the data and archiving it for everybody’s use is the International Association for the Study of Lung Cancer (IASLC). However I checked their web site and could not find any info on databases.
Do you know of any such effort to collect, format and archive results of clinical studies in lung cancer? I believe open access to this data can only benefits patients and doctors. I also know that other disciplines had done similar things (the Human Genome project for example) and it seems to me that it is a very economical way of putting all of these gigabytes of data that are lying dormant in different parts of the world to good use.
Carlos
October 13th, 2007 at 5:19 am
I agree with Carlos. I have also been somewhat taken aback by the way that clinical studies often report bivariate (they usually refer to them as “univariate”) results first, and only seem to report multivariate analysis as an afterthought. I think that is part of the reason for some of the misinformation out there (some of the Tarceva legends, for example).
I’d been thinking in terms of a depository, too, but the other item I’d put on the agenda is more pooled analysis and meta-analysis.
Anyway, I’m sure, Dr. West, that you can get this done in your “spare” time.–Neil
October 13th, 2007 at 1:38 pm
Carlos and Neil,
Several institutions have their own tumor registry, in which they are archiving pieces of tissue from tumors along with clinical information in a database, but there are several daunting issues. The first, as is often the case, is money. It takes significant time and effort for the data to be entered, as well as to store tissue for future use (you didn’t specifically mention this, but we’d really love to be able to correlate molecular markers with clinical outcomes of patients in a huge data set). Money and labor issues are probably the top 5 problems, but beyond that there is also concern by Institutional Review Boards (IRBs) about keeping records and tissue of people when it likely won’t be directly in their benefit. Confidentiality issues are real, and IRBs are especially sensitive to keeping patient DNA archived, just stockpiled because “we might need this some day”. And then there’s barriers like getting these major and somewhat competing institutions to collaborate when they might be inclined to squabble for 5 years over who leads the project, and the sheer scope of managing a national or international database that could include tens or hundreds of thousands of cases. The International Association for the Study of Lung Cancer would likely be thrilled to manage a registry like that, but until Bill Gates takes a major interest, I think it’s something to dream about in an ideal world.
Sorry to be a wet blanket here. Great idea, but very hard to execute.
-Dr. West