Author Interviews, Opiods, Pain Research / 06.05.2019
Few Valid Tools to Identify Pain Patients Who Can Be Safely Prescribed Opioids
MedicalResearch.com Interview with:
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Dr. Klimas[/caption]
Jan Klimas, PhD, MSc
Senior Postdoctoral Fellow
BC Centre on Substance Use (BCCSU)
Vancouver, BC
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Some individuals prescribed opioid analgesic medications for pain develop opioid use disorder. So, much research has been conducted to develop strategies to identify patients who can be safely prescribed opioid analgesics. However, this research has not been critically reviewed through rigorous quality assessment.
This study therefore sought to identify signs, symptoms & screening tools to identify patients with pain who can be safely prescribed opioids
Dr. Klimas[/caption]
Jan Klimas, PhD, MSc
Senior Postdoctoral Fellow
BC Centre on Substance Use (BCCSU)
Vancouver, BC
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Some individuals prescribed opioid analgesic medications for pain develop opioid use disorder. So, much research has been conducted to develop strategies to identify patients who can be safely prescribed opioid analgesics. However, this research has not been critically reviewed through rigorous quality assessment.
This study therefore sought to identify signs, symptoms & screening tools to identify patients with pain who can be safely prescribed opioids


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.

Dr. Schwartz[/caption]
Dr. Joseph A Schwartz PhD
Public Affairs and
Community Service, Criminology and Criminal Justice
University of Nebraska Omaha, Omaha, NE
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: My larger research agenda is focused on identifying the ways in which environmental and biological influences work collectively to shape behavioral patterns across major stages of the life course. I am particularly interested in identifying environmental influences that can change biological functioning or activity to result in behavioral change.
Brain injury was a natural progression of these interests since brain injury is expected to result in changes in the structure and functioning of the brain, which has been linked to meaningful changes in behavior. There have also been a sizable number of studies that indicate that justice involved populations experience brain injury at a rate that is between five and eight times what is observed in the general population. I was fascinated by this finding and thought that brain injury may be a good candidate influence to investigate further.



