This article being about cancer and the class being statistics reminded me of my cancer biostatistics course from last semester. We read about the Deception at Duke regarding Dr. Anil Potti, a physician and cancer researcher from Duke University that manipulated his data to prove he had made a groundbreaking discovery. His falsification was discovered by statisticians Drs. Coombes and Baggerly, but it took an embarrassingly long time before anyone paid heed to the allegations. It led to clinical trials of patients getting a treatment that wasn't accurately matched for their tumor type and some died because of it. The lesson my professor was trying to teach us was two-fold: the importance lies in properly interpreting the data and it must be reproducible. I think the bigger the impact of the research, the more it should be vetted prior to reaching the media. Especially in the case of cancer patients, they’re a unique patient population in sheer numbers and the mortality rates make us as researchers really want to cure cancer and save lives. But that gets lost in the hype, which we need to do a much better job at containing and adequately vetting it before speaking these words out loud.
Monday, January 22, 2018
Cancer Drugs: Ain't My Type of Hype
Cancer is the second-leading cause of death in the United States so it’s one that many people, including myself, have experienced or are currently experiencing one way or another. It’s not surprising the attraction and hype surrounding cancer research, primarily drugs. As noted by Belluz, these drugs are marketed as being miracles, groundbreaking, and potential cures. I’m not at all shocked by the lack of oversight when claiming the ‘next big thing,’ however I was appalled that 14% of the articles lacked human data. As a translational scientist, I care immensely about going from bench side to bedside and any scientist knows the difficulty in that. It’s this desire of power and money and recognition that has even doctors making unjustified claims. There's also the issue of money being a driving factor whether it's on behalf of a university or pharmaceutical company. The intentions lack purity and as rigorous as the clinical trial process is, people still find reasons to cheat the system.
This article being about cancer and the class being statistics reminded me of my cancer biostatistics course from last semester. We read about the Deception at Duke regarding Dr. Anil Potti, a physician and cancer researcher from Duke University that manipulated his data to prove he had made a groundbreaking discovery. His falsification was discovered by statisticians Drs. Coombes and Baggerly, but it took an embarrassingly long time before anyone paid heed to the allegations. It led to clinical trials of patients getting a treatment that wasn't accurately matched for their tumor type and some died because of it. The lesson my professor was trying to teach us was two-fold: the importance lies in properly interpreting the data and it must be reproducible. I think the bigger the impact of the research, the more it should be vetted prior to reaching the media. Especially in the case of cancer patients, they’re a unique patient population in sheer numbers and the mortality rates make us as researchers really want to cure cancer and save lives. But that gets lost in the hype, which we need to do a much better job at containing and adequately vetting it before speaking these words out loud.
This article being about cancer and the class being statistics reminded me of my cancer biostatistics course from last semester. We read about the Deception at Duke regarding Dr. Anil Potti, a physician and cancer researcher from Duke University that manipulated his data to prove he had made a groundbreaking discovery. His falsification was discovered by statisticians Drs. Coombes and Baggerly, but it took an embarrassingly long time before anyone paid heed to the allegations. It led to clinical trials of patients getting a treatment that wasn't accurately matched for their tumor type and some died because of it. The lesson my professor was trying to teach us was two-fold: the importance lies in properly interpreting the data and it must be reproducible. I think the bigger the impact of the research, the more it should be vetted prior to reaching the media. Especially in the case of cancer patients, they’re a unique patient population in sheer numbers and the mortality rates make us as researchers really want to cure cancer and save lives. But that gets lost in the hype, which we need to do a much better job at containing and adequately vetting it before speaking these words out loud.
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