Conventional Cancer Statistics

When it comes to conventional cancer treatment, another key point to consider is the way its statistics are packaged. In her well-researched and well-written book “Outsmart Your Cancer”, Tanya Harter Pierce outlines 6 main ways in which cancer statistics are manipulated to make them look better than they are – she had obtained these findings mainly from the excellent work of Lorraine Day, MD, and Ralph W Moss, PhD.

* “Cure” is defined as being alive 5 years after diagnosis. This means that a person could be very sick with cancer for 5 years and 1 day, after which he or she dies, and still be declared as “cured” by chemotherapy. Isn’t this simply playing with words?

* Certain types of cancer and certain groups of people which exhibit poor recovery rates are simply excluded from overall statistics. This artificially raises the average “cure” rate.

* Easily curable cancerous and even pre-cancerous conditions are included in overall statistics. An example for the latter is ductal carcinoma in situ (DCIS), which was included in and now accounts for a significant portion of breast cancer statistics. This move artificially increases the overall recovery rate.

* Earlier detection is taken to mean longer survival time. This means that a person may die at the exact same point of cancer development as another person, but the former is taken to have lived longer simply by virtue of the fact that his tumor was discovered earlier. In other words, different start points are used. Isn’t this merely delusional?

* Patients who fail to “complete” conventional treatment protocols are excluded from overall statistics. This means that if a patient prescribed a 10-course chemotherapy protocol dies after 9 sessions, he is not included as a “failure” case. Control groups, however, play by different rules. This, again, artificially raises cure rates for conventional protocols. Isn’t this totally unscientific?

* Adjusting for “Relative Survival Rate”. This is perhaps best explained by Dr Moss: “Relative survival rates take into account the ‘expected mortality figures’. Put simply, this means that if a person hadn’t died of cancer he might have been run over by a truck, and that must be factored into the equation.” Once again, this artificially raises the success rates of conventional treatment.