Author Interviews, Cancer Research, Cost of Health Care, JAMA / 19.05.2019
Cancer Survivors: Insurance Patterns Before and After Affordable Care Act
MedicalResearch.com Interview with:
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Dr. Sanford[/caption]
Nina Niu Sanford, M.D.
Assistant Professor
UT Southwestern Department of Radiation Oncology
Dallas TX 75390
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: The background for this study is that we know cancer survivors are at risk for uninsurance or underinsurance and the most commonly cited reason for this is cost of insurance. However, there have been no prior studies assessing from the patient perspective the reasons for not having insurance.
In addition, there has been further recent controversy over the Affordable Care Act, including threats from the current administration to dismantle it. Thus assessing the impact of the ACA among at risk populations including cancer survivors is timely.
Dr. Sanford[/caption]
Nina Niu Sanford, M.D.
Assistant Professor
UT Southwestern Department of Radiation Oncology
Dallas TX 75390
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: The background for this study is that we know cancer survivors are at risk for uninsurance or underinsurance and the most commonly cited reason for this is cost of insurance. However, there have been no prior studies assessing from the patient perspective the reasons for not having insurance.
In addition, there has been further recent controversy over the Affordable Care Act, including threats from the current administration to dismantle it. Thus assessing the impact of the ACA among at risk populations including cancer survivors is timely.





Dr. Shaker[/caption]
Marcus S. Shaker, MD
Associate Professor of Pediatrics
Associate Professor of Community and Family Medicine
Dartmouth-Hitchcock Medical Center
MedicalResearch.com: What is the background for this study?
Response: There are two peanut allergy treatments that are being evaluated for potential FDA approval—an orally administered treatment and an epicutaneous (skin based) treatment. Both have tremendous potential benefit. The focus of our study was to explore the range of health and economic benefits in terms of establishing pathways for how each therapy could be cost effective.
We want to be clear that our purpose was not to suggest one therapy is or is not cost effective at present. That would be a ridiculous statement to make regarding two treatments that not only lack FDA approval, but do not have established pricing. Rather, we used preliminary inputs that are presently available to create as robust a model as we could to better determine the individual paths that would make them more or less cost-effective.


Jasleen Grewal, BSc.
Genome Sciences Centre
British Columbia Cancer Research Centre
Vancouver, British Columbia, Canada
MedicalResearch.com: What is the background for this study?
Response: Cancer diagnosis requires manual analysis of tissue appearance, histology, and protein expression. However, there are certain types of cancers, known as cancers of unknown primary, that are difficult to diagnose based purely on their appearance and a small set of proteins. In our precision medicine oncogenomics program, we needed an accurate approach to confirm diagnosis of biopsied samples and determine candidate tumour types for where the primary site of the cancer was uncertain. We developed a machine learning approach, trained on the gene expression data of over 10,688 individual tumours and healthy tissues, that has been able to achieve this task with high accuracy.
Genome sequencing offers a high-resolution view of the biological landscape of cancers. RNA-Seq in particular quantifies how much each gene is expressed in a given sample. In this study, we used the entire transcriptome, spanning 17,688 genes in the human genome, to train a machine learning method for cancer diagnosis. The resultant method, SCOPE, takes in the entire transcriptome and outputs an interpretable confidence score from across a set of 40 different cancer types and 26 healthy tissues.