Personalized Chemotherapy: Understanding Clinical Trials - the Kaplan Meier Graph
In this video of Personalized Cancer Chemotherapy, Dr. Larry M. Weisenthal explains the Kaplan-Meier graph. The graph is often used in clinical trials to compare survival times among patients with the same type of cancer who received different chemotherapy treatments. Understanding the graph is easy and also very useful as it will enable you to cut through the clutter in published clinical trial manuscripts and see at glance if any chemotherapy regimen provided a superior survival benefit.
http://www.youtube.com/watch?v=1Fz6kBXmAt0
Big Data Meets Cancer: Neil Hunt at TEDxBeaconStreet
https://www.youtube.com/watch?v=IWu6XWzbPBs
The consistent and specific cure or control of cancer will require multiple drugs administered in combination targeted to abnormal patterns of normal cellular machinery that effect or reflect malignant behavior, according to Dr. Arnold Glazier, former Oncology Fellow at Johns Hopkins. It is finding the patterns of malignant cells and developing a set of 5 to 10 drugs in order to cure or control cancer that classical clinical trials are not going to solve.
In clinical research, studies are deemed reportable when they achieve statistical significance. The so-called power analysis is the purview of the biostatistician who examines the desired outcome and explores the number of patients (subjects) required to achieve significance. The term “N” is this number. The most famous clinical trials are those large, cooperative group studies that, when successful, are considered practice-changing. That is, a new paradigm for a disease is described. To achieve this level of significance it is generally necessary to accrue hundreds, even thousands of patients. This is the “N” that satisfies the power analysis and fulfills the investigators expectations.
So what about Trials of N=1? This disrupts every tenet of cancer research, upends every power analysis and completely rewrites the book of developmental therapeutics, according to Laboratory Oncologist Dr. Robert A. Nagourney. Every patient is his or her own control. Their good outcome reflects the success or failure of "the trial." There is no power analysis. It is an "N" of 1.
This “breakthrough” concept however, has been the underpinning of the work of investigators like Drs. Larry Weisenthal, Andrew Bosanquet, Ian Cree, Robert Nagourney and all the other dedicated researchers who pioneered the concept of advancing cancer outcomes one patient at a time. These intrepid scientists described the use of each patient’s tissue to guide therapy selection.
They wrote papers, conducted trials and reported their successful results in the peer-reviewed literature. These results have provided statistically significant improvements in clinical responses, times to progression, even survival. By incorporating the contribution of the cellular milieu into clinical response prediction, these functional platforms have consistently outperformed their genomic counterparts in therapy selection.
With Cancer, Don’t Ask the Experts
http://robertanagourney.wordpress.co...k-the-experts/