Thursday, July 17, 2008

Neoplasms: 10

This is the tenth blog in a series of blogs on neoplasia.

In the past few blogs, I've been trying to explain the disconnect between cancer survival data and cancer death rate data. The cancer survival data seems to indicate that we're making enormous improvements in cancer treatment. The cancer death rate indicates that Americans are dying from cancer at about the same rate as they had been a half-century ago.

Several days ago, I listed over a dozen biases in cancer survival data that contribute to an overly optimistic sense of medical progress.

In this and the next few blogs, I thought I'd review some of these biases. The purpose of this exercise is to explain that the interpretation of survival data is enormously complex and that survival data is probably not the best way to gauge progress in the field of cancer research.

Today, let's look at Marketing and Money Bias.

Bevacizumab (developed and sold by Genentech as Avastin) is one of the most popular cancer drugs in the world and has been heralded as a wonder drug. It can easily cost $50,000 to $100,000 per year of use. One of the most exciting features of Avastin is that it can potentially treat any kind of cancer. Avastin is an antibody that works by attaching to VEGF (Vascular Endothelial Growth Factor), thus reducing the ability of tumors to vascularize and grow. In responsive cancers, studies indicate that it extends life by up to four months [1].

You may not be impressed by a drug that seems to extend life by up to four months in some responsive cancer. To the best of my knowledge, nobody has claimed that Avastin will cure advanced cancers. Why is Avastin popular? A well-marketed drug that promises hope for cancer patients can have enormous appeal to desperate patients, and their oncologists.

Are the results of clinical studies skewed in favor of the corporate sponsors of the trials? In a fascinating meta-analysis, Yank and coworkers wanted to know whether the results of clinical trials conducted with financial ties to a drug company, were biased towards favorable results [2]. They reviewed the literature on clinical trials for anti-hypertensive agents, and found that ties to a drug company did not bias the results. However, the found that financial ties to a drug company are associated with favorable conclusions. This suggests that regardless of the results of a trial, the conclusions published by the investigators were more likely to be favorable, if the trial were financed by a drug company. This should not be surprising. Two scientists can look at the same results and draw entirely different conclusions. It happens every day. How could an investigators, financed by a drug company, not be influenced by their benefactors when they interpret their results?

1. [Kolata G. Pollack A. Costly cancer drug offers hope, but also a dilemma. The New York Times, July 6, 2008.]

2. [Yank V, Rennie D, Bero LA. Financial ties and concordance between results and conclusions in meta-analyses: retrospective cohort study. BMJ 335:1202-1205, 2007.]

-Copyright (C) 2008 Jules J. Berman

key words: cancer, tumor, tumour, carcinogen, neoplasia, neoplastic development, classification, biomedical informatics, tumor development, precancer, benign tumor, ontology, classification, developmental lineage classification and taxonomy of neoplasms

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