Different types of cancers vary in response to treatment. Consequently, not all patients will benefit from the same treatment. In older therapy approaches, using standard chemotherapy, treatment plans were attempted without customization and were tried in sequence until the patient responded. One or several therapies may have been attempted with this approach before the best treatment was identified. Not only would these repeated rounds of treatment expose the patient to ineffective treatment and severe side effects, but the cost often became very burdensome for both the patient and the healthcare system.
With the predictive biomarkers that are available today, it is possible to make a much more specific selection of therapy with the highest likelihood of effectively treating each individual patient. This directed approach eliminates much of the "trial and error" with its associated and unnecessary side effects and costs.
But how truly predictive are these diagnostic results? Research has shown that patients with breast cancers containing as few as 1-10% ER-positive staining cells will show improvement with estrogen-directed hormone therapy, eg, tamoxifen. Thus, it is very important that predictive testing be extremely accurate in identifying those patients who will most benefit from these specific treatments.