Back in May 2024, I wrote a blog about a remarkable new article from MolDx discussing, "When Pathologists Can Order Molecular Tests." Find it here:
https://www.discoveriesinhealthpolicy.com/2024/05/moldx-publishes-major-guidance-document.html
Here's a major new article on the same topic, which is being called "Pathologist Directed Workflow" (let's say PDWF).
Find the new publication by Dowdell et al. here:
https://ascopubs.org/doi/pdf/10.1200/OP.24.00226
There is also a summary at Genomeweb, I believe open-access:
See the press release from Illumina here. See coverage at ASCO NEWS here. See a 9/2024 paper from the group, Meng et al. here, which looked at the lung cancer subset. See an AI comparison of Meng and Dowdell here.
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Comment
Pathologist-directed test ordering has many advantages, but raises a few collateral questions. What if Dr. A wants the Foundation Medicine test and Dr. B the Caris test? Here, all patients got the same Provdience LDT (based on an Illumina platform). Who handles prior authorization? In this study, at Providence health system, all patients got a 523-gene test, and tests were ordered in the absence of any insurance coverage decision. (Writing, "We developed a novel programmatic approach where testing was initiated at the time of diagnosis and performed at no cost to patients.") In the real-world, someone would have to invest time into problems like prior authorization paperwork.
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Here is a diagram of the shorter, faster pathway with PDWF:
Here is the abstract of Dowdell et al:
Purpose
Precision therapies and immunotherapies have revolutionized cancer care, with novel genomic biomarker-associated therapies being introduced into clinical practice rapidly, resulting in notable gains in patient survival. Despite this, there is significant variability in the utilization of tumor molecular profiling that spans the timing of test ordering, comprehensiveness of gene panels, and clinical decision support through therapy and trial recommendations.
Methods
To standardize testing, we designed a pathologist-directed test ordering system at the time of diagnosis using a 523-gene DNA/RNA hybrid comprehensive genomic profiling (CGP) panel and extensive clinical decision support tools. To comprehensively characterize the clinical impact of this protocol, we developed a novel natural language processing (NLP)–based approach to extract clinical features from physician chart notes. We assessed test actionability rates, therapy choice, and outcomes across a set of 3,216 patients with advanced cancer.
Results
We observed 49% of patients had at least one actionable genomic biomarker-driven–approved and/or guideline-recommended targeted or immunotherapy (IO) and 53% of patients would have been eligible for a precision therapy clinical trial from three large basket trials. When assessing CGP versus an in silico 50-gene panel, 67% of tumors compared with 33% harbored actionable alterations including clinical trials. Among patients with 6 months or more of follow-up, over 52% received a targeted therapy (TT) or IO, versus 32% who received conventional chemotherapy alone. Furthermore, patients receiving TT had significantly improved overall survival compared with patients receiving chemotherapy alone (P < .001).
Conclusion
Overall, these data represent a major shift in standard clinical practice toward molecularly guided treatments (targeted and immunotherapies) over conventional systemic chemotherapy. As guidelines continue to evolve and more precision therapeutics gain approval, we expect this gap to continue to widen.
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Bonus. See an article on Clinical Lab 2.0 and Project Santa Fe re: Lab-initiated care model and liver disease here.
