Reviews of MCED come out regularly in major journals; here is the latest one. See the latest in Annals of Internal Medicine, Kahwati et al. (November issue; ahead of print 9/16/25). Sponsored by AHRQ, it comes with an op ed by Weinberg. See the May 2025 AHRQ output, by Kahwati, at 139pp - here.
I think most of us are used to seeing "MCED" - Multi-cancer early detection. These articles are headlining with MCDT - Multi-cancer detection tests.
####
I'd put those articles in context of a major new paper by a health economics team on "determining the value of genomics in healthcare." See the home page here:
https://healtheconomicsandgenomics.com/
And see Goranitis et al. in Nature Medicine, dateline November 27:
https://www.nature.com/articles/s41591-025-04061-3
Tidbit: For another view of similar material, see Buchanan, Goranitis et al, 2025, "Health economics of genomics, a growing evidence base of value.' At Applied Health Economics Policy;
https://pmc.ncbi.nlm.nih.gov/articles/PMC12053066/
Here's Chat GPT 5 on Goranitis and on Buchanan, Goranitis.
#####
AI CORNER
####
The two papers jointly depict a field moving beyond narrow cost-effectiveness analysis toward a multidimensional, system-level understanding of genomic value. The Applied Health Economics and Health Policy editorial surveys recent evidence showing that while genomic testing is often cost-effective in selected oncology and rare-disease contexts, the overall evidence base remains fragmented, dominated by QALY-focused analyses that omit major sources of value. Studies in cancer show mixed cost-effectiveness outside a few well-validated indications, whereas early genomic testing in rare disease consistently improves diagnostic yield and reduces overall cost. Preference-elicitation research demonstrates that patients and families place substantial monetary value on diagnostic certainty and non-clinical benefits, but these outcomes rarely appear in formal HTAs.
The Nature Medicine review expands the frame, arguing that genomics produces layered diagnostic, clinical, personal, familial, system-level and macroeconomic value that traditional HTA frameworks cannot capture. The authors highlight new tools such as C-GUIDE, GENE-U, PrU and the GUV scale, which quantify utility beyond health outcomes, and call for dynamic, real-world–informed “life-cycle HTA” to accommodate rapidly evolving evidence. Implementation factors—including data-infrastructure readiness, mainstreamed clinical pathways, and equity considerations—are shown to be primary determinants of real-world value. Both papers converge on the need for comprehensive, agile, and equity-aware evaluation methods to guide sustainable genomic integration into healthcare systems.
#####
#####
Below is a professional synthesis of the two uploaded articles—Buchanan, Goranitis et al., Applied Health Economics and Health Policy (2025) and Goranitis et al., Nature Medicine (2025)—written for experts in genomics, precision-medicine policy, and genomic economics.
Citations to each document use the required format.
Key Takeaways from Two Landmark Papers on the Value and Economics of Genomics
1. The Economic Evidence Base for Genomic Technologies is Expanding but Uneven
The Applied Health Economics and Health Policy editorial surveys 12 studies covering cancer, rare diseases, and preference-based valuation. It emphasizes that while sequencing costs have fallen, the economic evidence base remains highly heterogeneous, dominated by QALY-based cost-utility analyses for oncology and rare diseases, with significant gaps in non-clinical value assessment.
2025 AHEHP Buchanan Goranitis H…
Key patterns include:
-
Cost-effectiveness is strongest in breast cancer, hematologic malignancies, and advanced NSCLC, but remains weak or mixed in many other cancer types.
-
In rare disease diagnostics, early genomic testing (particularly exome first-line) repeatedly demonstrates higher diagnostic yield and lower cost than traditional pathways.
-
Preference studies show that stakeholders value genomic information far beyond clinical utility, and quantifying this is increasingly essential for health-system decision-making.
2. Traditional HTA Frameworks Cannot Capture the Multi-Dimensional Value of Genomics
The Nature Medicine review argues forcefully that genomics produces health, non-health, family, system-level, and societal value components that exceed the scope of conventional HTA tools.
2025 NAT MED Gorantitis HEOR of…
Major conceptual deficits in traditional HTA include:
-
QALYs cannot represent diagnostic certainty, psychosocial utility, spillover effects on relatives, or life-course value.
-
Genomic data are reusable, allowing reanalysis and new diagnoses over time; this generates future value that standard economic models “flatten” or ignore.
-
The real-world impact of genomics depends heavily on health-system configuration, laboratory architectures, workforce readiness, and data-infrastructure investments—almost never incorporated in traditional cost-effectiveness models.
The authors advocate for extended valuation frameworks, which incorporate:
-
Personal utility
-
Family spillover
-
Equity impacts
-
Societal value
-
Macroeconomic effects of genomic innovation ecosystems
3. Measurement Tools for Genomic Utility Are Rapidly Maturing
Validated measures such as C-GUIDE, GENE-U, PrU, and the newly developed Genomic Utility Valuation (GUV) scale provide a structured way to quantify the broader outcomes of genomic testing.
2025 NAT MED Gorantitis HEOR of…
These tools allow:
-
Clinician-reported utility
-
Patient and family-reported utility
-
Preference-weighted scoring across diagnostic, clinical, familial, economic, and societal indicators
-
Conversion of utility into monetary terms using discrete choice experiments (DCE) and contingent valuation
Collectively, they represent a major methodological advance over the last 5–7 years, enabling new forms of economic evaluation beyond standard QALYs.
4. Real-World Evidence (RWE) and Life-Cycle HTA are Becoming Central
Both articles emphasize that static, one-time HTA processes are poorly suited to genomics, because:
-
Evidence evolves rapidly
-
Variant interpretation changes over time
-
Diagnostic and therapeutic paradigms shift as new gene–disease associations are discovered
The Nature Medicine article argues for life-cycle HTA, which continually updates economic and clinical assessments using RWE from learning healthcare systems.
2025 NAT MED Gorantitis HEOR of…
Examples include:
-
National genomic test directories updated annually (e.g., NHS England)
-
Models where data reuse yields additional diagnoses and economic value
-
Dynamic re-pricing and re-evaluation mechanisms (e.g., Australia’s MSAC use of rebates at partial cost coverage)
This shift represents a paradigm change in genomics governance.
5. Cancer and Rare Disease Economics Show Contrasting Patterns
Cancer Genomics (per AHEHP editorial)
-
Genomic testing for targeted therapies in advanced cancers can be high-value but often remains not cost-effective when test prices are high or when downstream therapies are expensive.
-
Sequential testing strategies may improve survival but fall outside acceptable willingness-to-pay thresholds in middle-income settings.
-
Panel testing for myeloid malignancy demonstrated limited QALY gain at high incremental cost.
2025 AHEHP Buchanan Goranitis H…
Rare Disease Genomics
-
Early exome/genome sequencing is consistently cost-saving, with higher diagnostic yield and shorter diagnostic odysseys.
-
Families show substantial willingness to pay for sequencing, with strong variation depending on whether a diagnosis is achieved.
-
Gene therapies (e.g., hemophilia B gene therapy) can be dominant—producing both QALY improvements and massive lifetime cost savings.
2025 AHEHP Buchanan Goranitis H…
These disparities highlight how clinical context profoundly shapes economic value.
6. Health-System Infrastructure is a Determinant of Real-World Value
The Nature Medicine authors emphasize that genomic value is co-produced by the technology and the system in which it is embedded.
2025 NAT MED Gorantitis HEOR of…
Determinants of realized value include:
-
Workforce training and mainstreaming (non-geneticists ordering tests)
-
National genomic laboratory networks (e.g., England’s Genomic Laboratory Hubs)
-
Data management and variant-interpretation pipelines
-
Policies for reanalysis, data reuse, and feedback loops
-
Equity-focused implementation strategies
Without system-level integration, genomic technologies risk producing low uptake, poor turnaround times, inequitable access, and limited clinical utility.
7. Macroeconomic Value: An Emerging but Underdeveloped Dimension
The Nature Medicine review points to evidence that national investment in genomics can produce large macroeconomic multipliers (e.g., 4.75:1 return in the US). Yet this is poorly represented in HTA frameworks and rarely included in policy analysis.
2025 NAT MED Gorantitis HEOR of…
Future research needs to quantify:
-
Job creation
-
Innovation spillovers
-
Technology export potential
-
Long-run cost offsets from genomic-enabled preventative care
8. Strategic Challenges Identified Across Both Papers
Evidence Gaps
-
Lack of standardized outcome measures
-
Few long-term clinical follow-up studies
-
Limited data on equity impacts of genomics
-
Substantial variation in cost estimation for sequencing
Process Limitations
-
Reimbursement pathways are often misaligned with genomic testing’s evolving value
-
Fragmented payer systems (e.g., US) struggle to incorporate broader genomic utility
-
HTA bodies remain cautious about non-clinical outcomes and RWE
Implementation Risks
-
Adoption outpaces workforce training
-
Lack of cross-institutional data infrastructure can undermine clinical value
-
Multi-year lags between technology emergence and reimbursement decisions
Together, these challenges illustrate why many health systems struggle to achieve the promise of genomics despite strong technological advances.
Synthesis: What These Two Papers Signal About the Next Phase of Genomic Economics
-
The field is transitioning from cost-effectiveness of specific tests to system-level evaluation of genomic ecosystems.
-
Non-clinical value (personal utility, family impact, psychosocial outcomes) is no longer peripheral—it is central to valuation.
-
Standard HTA methods are insufficient; extended frameworks and dynamic evaluation models are becoming the norm.
-
Data infrastructure and learning-health-system models will increasingly determine the real-world ROI of genomics.
-
Equity, access, and implementation science must be integrated into economic models—not treated as externalities.
-
Macroeconomic consequences of national genomics programs represent a new frontier in valuation.
Together, these papers reflect a methodological and conceptual maturation of genomic economics—from early emphasis on diagnostic yield and QALYs toward comprehensive valuation across clinical, personal, familial, societal, and macroeconomic domains.
