The Burden of Cancer

A paradigm shift has occurred in oncology toward precision oncology, in which the molecular profile of the tumor is guiding decision-making for cancer therapies.  Indeed, perhaps one day (and soon) we may talk more about cancer treatment in the context of gene aberrations and less about the body site where the cancer presents (take, for example, the recommended treatment for NTRK fusion-positive cancers).  The last few years we have seen an unprecedented increase in the number of approved novel immunotherapy and targeted therapy agents across different indications.  Coupled with this paradigm shift has been the increase in the incidence and prevalence of patients, the significant financial costs of these new therapeutics, and the fact that oncologists are retiring at a rate greater than the number of new entrants into the field.  Questions arise: How do we equip community oncologists and what other models of care delivery do we need to manage this cancer crisis?  What is thevalue of precision medicine and how do we deliver this value to providers and patients, so all that are eligible benefit?

Our Study:

Costs & Benefits of Precision Medicine

We designed a study to compare the costs and benefits of precision medicine to standard of care in oncology. The study included 75 advanced cancer patients (45 breast cancer and 30 ovarian cancer patients, stages III/IV) in a community oncology practice setting.  Of the 45 breast cancer patients, 27 received precision medicine (PM) therapies guided by genomic sequencing in addition to standard of care (SOC) and 18 received only SOC. Half of the breast patients received two or more lines of SOC treatment. Ten of the ovarian cancer patients received PM with SOC and 20 received SOC only. The majority of ovarian cancer patients (83%) had two or more lines

of SOC treatment.

What did we learn?

Precision medicine was more effective.

Precision Medicine patients were more likely to be alive at the time our study concluded compared to those who received standard therapy.  Overall, PM was more effective:breast patients were 1.7x more likely to be alive compared to SOC breast patients. PM ovarian patients were 1.4x more likely to be alive compared to
SOC ovarian patients. 

This diagram shows the precision medicine patients in the study and their  status, based on which line of therapy precision medicine was first added to SOC. None of the breast cancer patients who received 4 lines of SOC when we concluded the study were alive.  In contrast, over half (55%) of breast patients who received 3 lines of SOC plus 1 line of PM were alive. Ovarian patients treated with 3 lines of SOC followed by PM were 1.6x more likely to be alive.

Comparing to the widely referenced DeVita statistics, where probability of response success across all types and stages of cancer is 60% for one line of therapy, 30% for two lines, 15% for 3 lines and 7.5% after 4 lines, yields an even more interesting result.  This graph includes all precision medicine patients.  


Our breast PM patients had success rates of 78% when precision medicine was added as the second line of treatment, 57% when PM was third line, 100% for patients who received PM as the fourth line, 50% for PM as line 5 and when PM was the 6th line of therapy 50% of patients were successful. The graph to the left shows the relative improvement of adding precision medicine to standard of care contrasted to DeVita success probabilities, respectively, acknowledging these are not

yet 5-year numbers. 

Our ovarian PM patients also compared favorably, with success rates of 100% for 3 lines of therapy, when PM was added as the third line, 33% when PM was given as fourth line treatment, 100% for PM as the fifth line and 67% for patients receiving PM as line 6.  The graph below shows the relative improvement of adding precision medicine to standard of care contrasted to DeVita success probabilities, respectively.   (No ovarian patients had only 2 lines of therapy). 

Our data showed that PM offers breast cancer patients an average of an additional 26 months of life (and counting) from the time PM treatment was added to standard of care. Our ovarian patient data showed an average of

27 additional months and counting.

Precision Medicine:

Accelerating Cancer's Demise

August 31, 2020

Devan Birch, BA, Gerry Hogue, Nancy Hogue, CPA,
Frederick Ashbury, PhD

ORION by VieCure

Volume 1, Issue 4





Key Messages:

Randomized trials are expensive and require a long time to get results.  Collection of real-world data (RWD), however, can accelerate applications to the Food & Drug Administration (FDA) for approval of drugs for new indications or novel agents by accruing sufficient numbers of patients more rapidly and using analytics to determine patterns.  In order to do this in a cost-effective manner, computerized tools that systematically collect RWD are necessary.

Our data, while admittedly involves a small number of patients, supports using NGS testing and adoption of genomic-guided therapies earlier in the process (i.e. moving the use of these technologies to an earlier point in the process to improve outcomes and eliminate waste inherent with failed lines of standard of care therapies.

Overall, further investigation using RWD such as those underlying our study, is necessary. In a subsequent  issue, we will describe the financial impacts of precision medicine based on our study.


  “DeVita, Hellman, and Rosenberg's Cancer: Principles & Practice   of Oncology (Cancer Principles and Practice of Oncology)”

4949 South Syracuse Street, Suite 450, Denver, CO 80237

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