Dr. Lagunes on the Importance of Developing More Personalized Treatments in NETs

Diane Reidy Lagunes, MD
Published: Thursday, Feb 15, 2018



Diane Reidy Lagunes, MD, medical oncologist, Memorial Sloan Kettering Cancer Center, discusses the necessity of tailored approaches in the treatment of patients with neuroendocrine tumors (NETs).

The disease itself is extremely heterogeneous, and physicians are trying to define a more personalized approach for each patient. Currently, physicians don’t have the data to sequence treatments to know which should go first, second, third, or fourth.

However, physicians are hoping to use new technology for genetic sequencing, biomarkers, and other important correlatives. If physicians are able to define patients genetically, they can better understand each patient’s disease and prognosis and ultimately tailor therapies for each patient.

One such example would be defining which patients would do better with peptide receptor radionuclide therapy earlier versus later. Although there are indications that patients with smaller burden of disease would do better, there is a lot of selection bias in that, Reidy Lagunes says.
 
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Diane Reidy Lagunes, MD, medical oncologist, Memorial Sloan Kettering Cancer Center, discusses the necessity of tailored approaches in the treatment of patients with neuroendocrine tumors (NETs).

The disease itself is extremely heterogeneous, and physicians are trying to define a more personalized approach for each patient. Currently, physicians don’t have the data to sequence treatments to know which should go first, second, third, or fourth.

However, physicians are hoping to use new technology for genetic sequencing, biomarkers, and other important correlatives. If physicians are able to define patients genetically, they can better understand each patient’s disease and prognosis and ultimately tailor therapies for each patient.

One such example would be defining which patients would do better with peptide receptor radionuclide therapy earlier versus later. Although there are indications that patients with smaller burden of disease would do better, there is a lot of selection bias in that, Reidy Lagunes says.
 



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