Gene-expression testing provides better estimates of cancer aggressiveness and assist in treatment decision making for men with prostate cancer. In a new study by Yale Cancer Center, researchers found substantial regional variation in use of genomic testing for prostate cancer, raising questions about access and other factors that might promote rapid adoption of new cancer technologies. The study is published online today in the journal JAMA Oncology.
Little was known about how genomic testing was used in routine clinical care. We aimed to understand national patterns of uptake within regions in the United States. One of the interesting findings we uncovered was the extent of regional variation in the use of genomic testing."
Michael Leapman, MD, Assistant Professor of Urology, Clinical Program Leader of the Prostate and Urologic Cancers Program at Smilow Cancer Hospital and Yale Cancer Center and lead author of the study
The study examined data from 92,418 patients aged 40 to 89 diagnosed with prostate cancer between 2012 and 2018 using insurance claims from Blue Cross Blue Shield Axis®, the largest resource for healthcare claims, provider and cost data. The researchers looked to identify trends in the use of testing and employed a form of statistical modeling to uncover groups of regions that shared similar patterns of uptake. Findings showed the adoption of commercial tissue-based genomic testing for prostate cancer was highly variable at the regional level in the U.S. and may be associated with contextual measures related to socioeconomic status and patterns of prostate cancer care.
"Some regions had minimal or no use of genomic testing, while others had high levels of use, implying that decisions to test are highly discretionary," said Leapman. "In addition, there were groups of geographically unrelated regions that shared a similar pace of growth over time. These findings raise questions about shared factors that might promote rapid uptake of new cancer technologies."
Study scientists added further research is needed to clarify the contribution of patient level factors to testing, as well as the effectiveness of these tests in improving clinical decision-making.