Thursday, June 12, 2025

MolDx Releases Two Cardiac Genetic LCDs - Final LCDs

MolDx releases two cardiac genetic LCDs, requested by Invitae in about February 2023 (about 2.5 years ago).   Both were issued as draft LCDs last year.

Note that Invitae writes it requested two genetic LCDs, one neurologic, one cardiologic, and what it has gotten, today, is two cardiologic LCDs.  The LCDs were proposed in mid-June 2025, so they appear as final about 52 weeks later.

The bottom line?

The bottom line is: The LCDs, in Medicare terminology, are close to recent professional society guidelines for cardio-genetics in adults.

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L39946

Genetic Testing for Heritable Thoracic Aortic Disease

LCD here.

Billing and Coding A59870.

Q&A A60207     Request letter here.

The LCD is 8 pages with 24 references.  See original for the full rules. 

  • The patient has aortic abnormalities and meets ONE of the following.  Before age 60; OR syndromic features (e.g. Marfan); OR Family hisotry in 1st or 2nd degree; OR unexplained sudden death in 1st or 2nd degree relative.
  • The test must have ample recommended genetic content but not "unvalidated" content.

The billing article points to 81410/81411 or 81479, plus Z code.

The Q&A discussion includes a discussion of alignment to ACC guidelines for genetic testing and features that suggest a hereditary as opposed to inborn anatomic origin.

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L39950  

Molecular Testing for Identification and Management of Hereditary Transthyretin Amyloidosis  ATTR

LCD here.  

Billing and Coding A59874.

Q&A A60202.  Request letter here.

The LCD is 9 pages and has 53 references.

In summary - see original for the full rules:

  • The patient has a clinical diagnosis of ATTR, OR, has features suggesting of ATTR cardiomyopathy AND African, OR first degree-relative, OR additional guideline suggested feature.
  • OR has progressive sensorimotor or autonomic neuropathy AND 1st degree relative with ATTR Dx OR one additional feature per guidelines.
  • The patient has had counseling and result will inform treatment decisions.  The test has minimum genetic content and does not included unvalidated genes.

The Billing Article simply says "use appropriate CPT code" (!!! thanks) and Z code.

The Q&A notes that a draft exclusion of "test that includes genetic content considered harmful" was revised to 'test does not include content that is not properly validated" etc.


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AI Corner

I asked for re-write of the coverage criteria, for clarity.  At link.

https://brucedocumentblog.blogspot.com/2025/06/moldx-cardio-genetic-lcds-june-2025.html

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AI CORNER

For your curiousity only, here are Chat GPT summarizes of the LCDs.  Do not make any decisions except by reference to the original LCD text, not this AI summary.

Here is a summary of the two complementary MolDX Local Coverage Determinations (LCDs), L39950 and L39946, both effective July 27, 2025, for Medicare beneficiaries with cardiac conditions requiring genetic testing. 

These LCDs mark a significant expansion in Medicare coverage for cardiogenetic diagnostics.


1. L39950: Molecular Testing for Hereditary Transthyretin Amyloidosis (hATTR)

LCD Title: MolDX: Molecular Testing for Identification and Management of Hereditary Transthyretin Amyloidosis
Jurisdiction: Noridian MAC J-F (13 states, incl. WA, AZ, UT)

Covered Indications

Genetic testing is covered when the patient:

  • Has a clinical diagnosis or cardiac features suggestive of ATTR-CM, and

    • Is of African ancestry, or

    • Has a first-degree relative with hATTR, or

    • Displays features consistent with expert consensus or guidelines (e.g., neuropathy, autonomic failure)

  • Has sensorimotor/autonomic neuropathy plus relevant family history or clinical indicators

  • Has been counseled on test implications

  • Will use the result to inform treatment decisions

  • Receives a test with validated genes (minimum content includes TTR and possibly others)

  • Uses a test that has passed MolDX Technical Assessment

Clinical Rationale

  • hATTR is a treatable, underdiagnosed cause of cardiomyopathy and polyneuropathy.

  • The most common U.S. pathogenic variant, TTR p.Val142Ile, is highly prevalent (~3.4%) in African ancestry populations and primarily cardiac in expression.

  • Gene sequencing improves diagnostic accuracy, especially as clinical features overlap with other conditions (e.g., diabetic neuropathy, hypertensive heart disease).

  • The test supports earlier diagnosis and therapy (e.g., tafamidis, RNAi drugs like patisiran and vutrisiran).


2. L39946: Genetic Testing for Heritable Thoracic Aortic Disease (HTAD)

LCD Title: MolDX: Genetic Testing for Heritable Thoracic Aortic Disease
Jurisdiction: Noridian MAC J-F (same 13 states)

Covered Indications

Genetic testing is covered when:

  • The patient has aortic root/ascending aorta dilation, aneurysm, or dissection, and

    • Presents before age 60, or

    • Has syndromic features (e.g., Marfan, Loeys-Dietz, vascular Ehlers-Danlos), or

    • Has a family history of thoracic aortic disease, aneurysms, or sudden death

  • Counseling is provided

  • The test:

    • Covers the minimum validated gene set, including FBN1, TGFBR1/2, SMAD3, COL3A1, ACTA2, etc.

    • Excludes non-validated or unclear variants

    • Has completed MolDX Technical Assessment

    • Does not violate repeat germline testing policies (L38353)

Clinical Rationale

  • HTAD accounts for ~20% of thoracic aortic aneurysms (TAA).

  • Guidelines from the ACC/AHA (2022) and ClinGen strongly recommend genetic evaluation for younger TAA cases or syndromic/familial presentations.

  • Identifying pathogenic variants informs timing of surgery, surveillance strategies, and cascade testing.

  • Recognized gene panels influence decisions well before aortic diameter reaches generic intervention thresholds.


Summary Implications

Together, these LCDs establish broad Medicare coverage for two distinct forms of inherited cardiovascular disease:

  • One focused on amyloidosis of cardiac and/or neurologic origin (hATTR),

  • The other on genetic aneurysmal disease of the thoracic aorta (HTAD).

Both policies:

  • Require pre-test counseling, use of validated gene panels, and MolDX TA approval

  • Emphasize early intervention and family risk stratification

  • Are anchored in strong guideline support and target diseases with overlapping but misdiagnosed phenotypes

These LCDs will likely drive:

  • Expansion of NGS panels in cardiovascular practice,

  • Increased testing in Black Medicare populations (esp. hATTR),

  • Coverage for multigene panels aligned with ACC/AHA guidelines, and

  • Pressure for national harmonization of cardiac genetics coverage.

Let me know if you'd like side-by-side tables, CPT implications, or billing summaries.

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Disclaimer.  The AI summary is for curiousity only.  I haven't proofed it against every detail of the LCDs.

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I then asked Chat GPT to provide constructive criticism for the LCD author.

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Yes — both LCDs (L39950 and L39946) are generally well-aligned with clinical guidelines and thoughtfully written, but they do suffer from some recurring issues that may hinder clarity, consistent application, and efficient use by labs, clinicians, and payers. Here's a structured critique:


⚠️ Common Issues Across Both LCDs

1. Overly Verbose and Redundant Language

Both LCDs repeat ideas in multiple places, especially in the coverage sections. For example:

  • The need for counseling, minimum gene content, and test utility appears multiple times, sometimes with slightly different phrasing.

  • They mix clinical eligibility, test design requirements, and regulatory compliance into a single list, when they could be cleanly separated.

Impact: Slows comprehension and increases the risk that clinicians or test developers misinterpret which criteria are patient-facing vs lab-facing.


2. Vague Terms Without Operational Definitions

Both LCDs use terms like:

  • "Features consistent with expert consensus"

  • "Genes with definitive or well-established evidence"

  • "Properly validated" or "unclear clinical utility"

These phrases are not anchored to a specific source, leaving ambiguity:

  • Which specific guidelines qualify as “expert consensus”? ACC/AHA? ESC?

  • Which genes are deemed valid? The LCD references ClinGen in L39946 but does not give a list.

Impact: Creates interpretive flexibility that could lead to coverage disputes or inconsistent TA approvals.


3. Lack of Clarity About Single-Gene Testing vs Panel Testing

While both LCDs permit single-variant testing when a familial mutation is known, they don’t:

  • Clarify if this applies to duo/trio testing or reflex testing.

  • Clarify if limited panels (e.g. just TTR, or just FBN1/ACTA2) are acceptable for patients without known familial variants.

Impact: Labs may be uncertain whether they can offer targeted panels unless a family mutation is already known, potentially discouraging cost-effective testing.


4. Limited Guidance on Cascade or Family Testing

Both LCDs imply support for familial risk assessment, but do not clearly state:

  • Whether testing in asymptomatic relatives is covered

  • Whether cascade testing is included when the proband is Medicare-eligible

This is particularly relevant in L39946 (HTAD), where early detection in relatives can be life-saving.

Impact: May deter cascade testing or lead to unnecessary denials.


5. Technical Assessment (TA) Language Is Ambiguous

Both LCDs require that a test:

“has successfully completed a technical assessment (TA)...”

However, they don’t:

  • Define what the TA evaluates (analytical validity, clinical validity, or both?)

  • Link to a checklist or reference document explaining TA criteria

  • Distinguish between new and grandfathered tests

Impact: Adds friction for test developers seeking coverage, particularly new market entrants.


🔍 LCD-Specific Observations

📄 L39950 (hATTR)

  • The clinical phenotypes of hATTR-CM and hATTR-PN are mixed together in one long bulleted list. It would be clearer to break them into two distinct diagnostic pathways.

  • There's an overemphasis on detailed drug mechanisms and trials (tafamidis, acoramidis, RNAi agents). This may be more appropriate in a background article, not an LCD.

📄 L39946 (HTAD)

  • The LCD refers to ACC/AHA and ClinGen guidelines, but doesn’t specify a minimum list of genes (though it hints at 11 validated genes). A table of “required core genes” would enhance usability.

  • While it’s based on high-quality data, the gene–phenotype correlations are buried in long paragraphs that make it hard to parse actionable coverage implications.


What They Do Well

  • Align with current guidelines (especially 2022 ACC/AHA for aortopathies and hATTR diagnosis).

  • Emphasize clinical utility, not just analytic validity — a good signal for payers and clinicians.

  • Include appropriate flexibility for new evidence or guideline changes.


🛠️ Suggested Fixes

  • Help the reader - Streamline coverage criteria into 3 buckets: (1) Patient eligibility, (2) Test design, (3) Compliance.

  • Provide an appendix or hyperlink to required gene lists (ClinGen, ACC/AHA)

  • Clarify whether family member testing is covered when a proband has a known mutation

  • Offer TA submission guidance in a separate MolDX companion article


Would you like a suggested redraft of the coverage criteria section using these structural improvements?

Wednesday, June 11, 2025

Joe Grogan in WSJ: Time to Pull the Plug on "CED" in NCDs

Health policy expert Joe Grogan, of USC's Schaeffer Institute, pens an Op Ed in the WSJ today, arguing that it is time to pull the plug on the arthritic and outdated "Coverage with Evidence" era at CMS.

CED was the heart of the "TCET" Transitional Coverage for Emerging Technologies" framework from the recent Biden administration.

Find Grogan's article here.   (Grogan handled health policy for the White House in 2019-2020).

https://www.wsj.com/opinion/agency-overreach-leaves-patients-untreated-4ead2d0a


Here are some opening quotations:

Medical innovations remain stuck between FDA approval and full Medicare coverage. Of 27 medical devices covered under CED since 2005, four have “graduated” to unrestricted coverage. Two product decisions were ceded to Medicare’s regional administrative contractors. The other 21 remain in limbo. Implantable cardioverter defibrillators languished under CED for 18 years. How much data does CMS need?

The program’s fatal flaw stems from confusion about agency roles. The FDA evaluates safety and efficacy. CMS’s mandate is to determine whether a product or service is reasonable and necessary to diagnose or treat an illness or injury. CED gave CMS free range to infringe on the FDA’s authority with predictable results: slowing access and blocking patients and doctors from making informed treatment decisions.

The program is also outdated. Unlike in 2005, digital health data is ubiquitous. The FDA can employ real-world evidence and artificial intelligence to analyze millions of patients’ treatments. CED’s clinical trial constructs are obsolete.

CED also restricts access by location, favoring urbanites who live near large academic medical centers over rural Americans. CMS should dramatically reform its process for making coverage decisions, with an eye toward speeding up access for patients. After decades of disappointing results, CED has earned its place in the regulatory graveyard.

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Grogan does not mention, but where data is available, the program also strongly favored White participants (e.g. Amyvid PET trials).

Also not mentioned, there were publicly issued legal arguments against the use of CED in the 2020/2021 closing months of the prior Trump administration.  

In recent comments, ACLA described the NCD change process as intolerably slow - here.

See a 2024 paper, Roadmap for Improving CED, here.

Tuesday, June 10, 2025

Caris Files for IPO at $5B: Documentation Links; Key Quotations and Metrics

Caris Life Sciences has filed for an IPO, with a planned value of $424M, at a valuation per share of $16-18.  According to one summary, this yields a market cap of $4.8-5.3B.

See coverage at MedTechDive here:

https://www.medtechdive.com/news/Caris-Life-Sciences-files-424M-IPO/750341/

See also Axios here and Reuters here.

See the June 9 press release here:

https://www.carislifesciences.com/about/news-and-media/caris-life-sciences-announces-launch-of-initial-public-offering/

See the SEC Preliminary Prospectus (dated June 9) here:

https://www.sec.gov/Archives/edgar/data/2019410/000110465925057593/tm2415719-16_s1a.htm

For me the PDF of the web document tallies 364 pages.

Recall that Caris won FDA approval for its paraffin comprehensive genomic profiling test in November 2024; the assay includes a full transcriptome and whole exome sequencing.  Here.  See the extensive FDA documentation for the test (P240010) here.

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Caris states it has:

  • Profiled 849,000 cases
  • Measured 38 billion biomarkers
  • Built 51 petabytes of genomic data
  • Utilized 220 AI tools
  • Digitized 4.4M slides
  • Now assesses 23,000 genes per order (RNA, WES)
  • 5,500 regularly ordering oncologists (> 4/yr)
  • 270 commercial sales force
  • 96 members of the Caris Precision Oncology Alliance
  • 200+  patents
  • 1700+ employees
  • 31% CAGR (case volume) 2019-2024.. Revenue CAGR 28%.


Caris opens its summary by stating:

  • We are a leading, patient-centric, next-generation AI TechBio company and precision medicinepioneer. We develop and commercialize innovative solutions to transform healthcare through the use of comprehensive molecular information and artificial intelligence/machine learning algorithms at scale. 
  • Our entire portfolio of precision medicine solutions is designed to benefit patients, with an initial focus on oncology, and serves the clinical, academic, and biopharma markets.

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Caris states that its current MolDx pricing for LBx therapy selection (Caris Assure) is $3649.   By my tally, the word "MOLDX" occurs 37 times in the prospectus.

Topics like LCDs, NCDs (p. 40), crosswalk/gapfill, and PLA coding are discussed.  They note (page 217) that AMA issued a PLA code for MI Cancer Seek of 0211U which is priced by CMS at $8455.  

They add, "We have obtained Medicare coverage for MI Cancer Seek for CPT code 0211 under the NGS NCD" and that "we began to market MI Cancer Seek in the first quarter as the WES WTS NGS component of MI Profile."  

MI Profile

See the web page hereMI Profile is the full package and includes DNA, RNA, proteins (IHC).  When ordering MI Profile, Caris will perform MI Cancer Seek CDx.  But, if the sample does not qualify for the FDA CDx test, then they will run the comparable LDT, MI Tumor Seek Hybrid.

MI Profile will also run IHC on 25+ markers, CISH, pyrosequencing for MGMT methylation (for glioma), and AI signatures, which include Caris GPSai for CUP (cancer of unknown type) and Caris FOLFIRSTai for CRC cases.

Gapfill

Separately, they describe that AMA issued PLA code 0485U for liquid biopsy Caris Assure for therapy selection, which is being priced by "the gapfill method."  As released in April for public comment, the proposed national gapfill price is $3649 for 0485U.  See my April 2025 article on the gapfill process here.

Risks

As to risks, among other statements Caris remarks,
  • Third-party payers are increasingly attempting to contain healthcare costs by limiting both coverage of certain diagnostic tests and the amounts that they will pay for such tests. Payers may also create conditions for coverage or may contract with third-party vendors to manage laboratory benefits, in both cases creating administrative hurdles for ordering physicians and patients that may make our services more difficult to sell.....
  • Obtaining approvals from third-party payers to cover our existing and new solutions and establishing adequate coding recognition and reimbursement levels is an unpredictable, challenging, time-consuming, and costly process, and we may not always be successful. 
AI Corner (Not Guaranteed)

I gave Chat GPT the 364-page prospectus and asked the AI to read and summary Caris' AI strategy.  

I have not read the full prospectus, so I can't vouch for the summary, and I copy it below "as is" and "if of interest" only.

Based on the S-1 filing, Caris Life Sciences' AI strategy is a core pillar of its business model, deeply integrated into its clinical services, research tools, and pharmaceutical partnerships. Their approach can be described as a data-driven precision oncology platform, where AI and machine learning (ML) are used to unlock insights from complex multi-omic and clinical datasets at scale.


1. AI Strategy Overview

Caris has created a vertically integrated platform that generates, aggregates, and analyzes whole exome sequencing (WES), whole transcriptome sequencing (WTS), and matched clinical data. Their AI strategy focuses on:

  • Automating the interpretation of molecular profiles

  • Predicting therapeutic response

  • Identifying novel biomarkers

  • Supporting clinical decision-making and trial enrollment


2. Key AI Products

Caris offers several AI-driven tools that exemplify their strategic priorities:

  • DETECT: A proprietary dataset of over 1.6 million molecular profiles linked with detailed clinical outcomes. This forms the training and validation foundation for their AI models.

  • CODEai: A cloud-based analytics engine that allows pharma partners to explore the DETECT dataset using natural language processing and AI. It supports hypothesis generation, biomarker validation, and trial site selection.

  • Caris Molecular Artificial Intelligence (MAI™): A suite of AI-based predictive algorithms trained on WES/WTS and outcomes data. These models aim to:

    • Predict patient benefit from specific therapies (e.g., checkpoint inhibitors, EGFR inhibitors)

    • Classify cancer subtypes based on transcriptomic signatures

    • Forecast prognosis and therapy resistance

  • Biosimilarity AI Models: These include models that predict which therapy classes (not just individual drugs) a tumor is most similar to in terms of molecular response, which is useful when direct evidence is limited.


3. AI Infrastructure

Caris has made significant investments in AI infrastructure, including:

  • A dedicated bioinformatics and AI team of ~140 employees

  • A cloud-native architecture optimized for high-throughput computation

  • Integration of deep learning and natural language processing (NLP) models for data extraction, annotation, and hypothesis testing


4. Strategic Use Cases

Caris deploys its AI for both clinical and biopharma-facing applications:

  • In the clinic, MAI algorithms provide oncologists with therapy prediction scores and help interpret complex molecular data.

  • In biopharma, AI is used for:

    • Patient stratification and trial matching

    • Novel target identification

    • Biomarker-driven drug development support

They highlight AI as a tool to reduce time and cost in drug development and increase R&D efficiency for their pharma clients.


5. Differentiation

Unlike some peers that rely primarily on static gene panels, Caris emphasizes multi-omic breadth (DNA, RNA, protein) and AI-enhanced interpretation. This gives them a competitive edge in producing actionable insights from complex biology.


Summary

Caris’s AI strategy is tightly woven into its clinical, research, and business operations. By linking comprehensive WES/WTS data with real-world clinical outcomes—and applying robust AI/ML analytics—Caris positions itself not only as a test provider but as a molecular intelligence company that bridges diagnostics, therapeutics, and data science. This strategy underpins their goal of becoming a market leader in precision oncology and biomarker-driven drug development.

Reminder: AI summary offered "as is" and "for interest only."


New June 10: Makary and Prasad on "Priorities for a New FDA"

 A few days ago I highlighted a new paper by Vinay Prasad on "surrogate endpoints" - here.

Today, June 10, Markary and Prasad publish a new paper, in JAMA, called, "PRIORITIES FOR A NEW FDA."

Find it at JAMA here, open access:

https://jamanetwork.com/journals/jama/fullarticle/2835314

The use of AI in FDA reviews was rapidly picked up by NYT:

https://www.nytimes.com/2025/06/10/health/fda-drug-approvals-artificial-intelligence.html

At Genomeweb, Turna Ray discusses whether the FDA priorities leave space for precision medicine:

https://www.precisionmedicineonline.com/precision-oncology/new-fda-priorities-there-room-precision-medicines


###     OPENING OF FDA ESSAY

Why does it take more than 10 years for a new drug to come to market? Why are childhood chronic diseases so prevalent? And how can regulators adapt to meet the challenges facing clinicians today? These questions are at the forefront for the US Food and Drug Administration (FDA).

The US leads the world in sophisticated cell and gene therapies and other innovative treatments, but in terms of the health of the population, our medical system has been a 50-year failure....Obesity, diabetes, colon cancer, depression, and autoimmune diseases have increased in young people, and early-onset Alzheimer disease has increased by at least 300%. ...At the FDA, we will examine the role of ultraprocessed foods, food additives, and environmental toxins, the introduction of which has paralleled the epidemic of chronic diseases.

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Here's a Chat GPT summary -

For Health Policy Experts — Summary of FDA Vision (Makary, JAMA, June 2025)

The FDA under Martin Makary presents a reformist vision aimed at addressing systemic failures in U.S. population health despite biomedical innovation. The strategy prioritizes faster therapeutic access, root-cause prevention, and regulatory modernization, emphasizing science-based pragmatism.


1. U.S. Health Outcomes: Innovation–Prevention Gap

  • U.S. leads in cell/gene therapies but lags in public health: 40% of children have chronic illness, 1 in 6 neurodevelopmental disorder, life expectancy plateaued or falling.

  • Rise in obesity, autoimmune diseases, early-onset Alzheimer’s not explained by genetics—points to environmental and dietary causes.


2. FDA Priorities: A Reoriented Mission

A. Accelerating Cures

  • COVID showed fast-track reviews are possible; pilot pathways will aim for weeks, not years.

  • Pre-submission paperwork review to reduce post-trial approval lag.

  • Target: Reduce delays in areas like infant formula innovation, outdated monographs, and redundant animal testing.

B. Regulatory Culture Shift

  • FDA will partner with industry for efficiency—especially for small firms—while avoiding regulatory capture.

  • Recent moves: Removed industry members from non-statutory advisory committees; ended COI waivers in VRBPAC.


3. AI Integration

  • Launched first generative AI pilot in May 2025 to support pre-review of massive application documents (>500,000 pages).

  • AI to modernize device/software reviews, especially in dynamic AI/ML domains.

  • Computational modeling (e.g., organs-on-chip) will aid in toxicity prediction and reduce animal testing.


4. Food as a Public Health Priority

  • FDA will now emphasize the “F”: food regulation.

  • Actions already underway:

    • Removal of 9 petroleum-based dyes.

    • Inventory of ingredients banned abroad but common in U.S. (e.g., talc in meds and candy).

    • Early definition and labeling standards for ultraprocessed foods.


5. Big Data as Regulatory Infrastructure

  • Shift from sole reliance on RCTs to causal inference from real-world data (e.g., target trials).

  • Use of postmarket surveillance to assess safety and real-world effectiveness, especially in rare diseases.

  • Potential to move from “2 pivotal trials” standard to 1 trial + real-world data.


6. Financial Toxicity

  • U.S. drug pricing is a global outlier. Though FDA cannot regulate price, it will:

    • Expedite generics and biosimilars.

    • Support most-favored-nation pricing.

    • Highlight excessive marketing vs. R&D spend in pharma.


Bottom Line:
The FDA plans to rebalance from reactive drug policing toward proactive health stewardship, including regulatory agility, food safety, and equitable access. A hybrid model of fast-tracked innovation, real-world validation, and conflict-free science is at the core of Makary’s FDA transformation.


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Here's what Chat GPT makes of the NYT article:

The New York Times presents the FDA’s proposal to expand AI use—especially to speed drug and device approvals—as a bold but controversial initiative.

While Commissioner Dr. Marty Makary claims AI will “radically increase efficiency,” the article underscores widespread skepticism. Experts caution that current AI tools like the FDA’s new model “Elsa” still hallucinate, save little time, and must be checked closely. Critics also raise concerns that the AI push, combined with staff cuts and cozy industry ties, reflects Trump-era deregulatory ambitions more than true innovation. Overall, the Times casts the plan as aspirational but unproven, and potentially vulnerable to political and scientific backlash.

Novitas MAC Updates LCD for "Gender/Sex"

The Novitas MAC has updated its oncology LCD to account for administration requirements regarding use of gender and sex.

Here's the April 24 "R2" version:

https://www.cms.gov/medicare-coverage-database/view/lcd.aspx?lcdid=39365&ver=149&stateRegion=all&contractorNumber=all&proposedStatus=F&sortBy=noticeStart&bc=11

  • LCD revised and published on 05/01/2025 in response to Executive Order 14168, DEFENDING WOMEN FROM GENDER IDEOLOGY EXTREMISM AND RESTORING BIOLOGICAL TRUTH TO THE FEDERAL GOVERNMENT, the term "gender" has been replaced with the term "sex" throughout the LCD. 
  • Please note, there is no change in the effective date of service.
  • Due to the 60-day delay for the effective date, this is to clarify that this LCD posted for notice on 01/09/2025 and became effective 04/24/2025.

RATIONALE

Other (In response to Executive Order 14168)

https://www.federalregister.gov/documents/2025/01/30/2025-02090/defending-women-from-gender-ideology-extremism-and-restoring-biological-truth-to-the-federal

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Monday, June 9, 2025

Some New Papers: Fojo, Bates on Interpreting Clinical Trials. FDA's Prasad on Surrogate Endpoints.

 A flurry of interesting articles in the last few days.

Fojo and Bates on Interpretation

At JAMA Oncology, Fojo and Bates write a 3-page short article on problems and biases when interpreting Kaplan-Meier curves for conclusions like median survival. 

While this may seem like one of the simplest measures, they point out that when curves grow relatively flat, a small difference in survival of a few patients can pull the "median" of the two populations far apart.   That is, a small difference in the vertical data makes a big difference in the left to right data.

They raise some other topics as well, like contrasting problems with hazard ratios under some circumstances.   See an AI summary of Fojo & Bates at the bottom of this blog.

Find Fojo and Bates 2025 here:

https://jamanetwork.com/journals/jamaoncology/fullarticle/2834385

Bonus - See an article by Fojo in JAMA in 2023, "Journeys to failure that litter the path to developing new cancer therapeutics," here.  


Vinay Prasad on Surrogate Endpoints

On March 25, Vinay Prasad (now a senior leader at FDA) published an article in Nature Reviews Clinical Oncology, refreshing us on his thoughts on suggogate endpoints. Find it here:

https://www.nature.com/articles/s41571-025-01007-z

Note that a comment letter has appeared by Vogel et al., and a reply from Prasad (both 6 June).

https://www.nature.com/articles/s41571-025-01031-z

https://www.nature.com/articles/s41571-025-01032-y

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See David Gorski's take on FDA current thinking at Science Based Medicine blog here.

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See a new JAMA article on standardized reporting of surrogate endpoints (as in CONSORT 2025 criteria):

https://jamanetwork.com/journals/jama/fullarticle/2822038


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See also: articles by McCabe and by Dominitz et al. on the rising diversity of cancer screening methods:

McCabe et al, NRCO

https://www.nature.com/articles/s41571-025-01037-7

Dominitz et al., JAMA

https://pubmed.ncbi.nlm.nih.gov/40455619/

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AI Summary of Fojo and Bates (Chat GPT)

Here's a summary of the JAMA Oncology Viewpoint by Fojo and Bates (May 2025), titled “Skimming the Median and the Problem of Exaggerated Survival Gains”:


Main Argument:
Fojo and Bates challenge the reliability of median overall survival (OS) as a headline statistic in oncology trials, warning that “skimming the median” can exaggerate treatment benefit. When Kaplan-Meier survival curves linger just above or below the 50% survival threshold, small differences in curve shape or timing can create the illusion of large OS gains—even when hazard ratios (HRs) suggest otherwise.


Key Examples Highlighted:

  1. CheckMate067 (Melanoma):

    • Median OS: 72.1 mo (nivo+ipi) vs. 36.9 mo (nivo alone)

    • HR: 0.84 (not significant)

    • Interpretation: A dramatic doubling of median OS was overstated due to slow tail decline of the experimental arm just above 50%.

  2. ADRIATIC Trial (Limited-stage SCLC):

    • Median OS: 55.9 mo (durvalumab) vs. 33.4 mo (placebo)

    • HR: 0.73

    • Reality: Kaplan-Meier curves diverged by only ~11 months at 60% survival—not 22 months as suggested by medians.

  3. ESOPEC Trial (Esophageal Adenocarcinoma):

    • Median OS: 66 mo (FLOT) vs. 37 mo (CROSS)

    • HR: 0.70

    • Observation: A 29-month median OS difference overstated real benefit, which was closer to 7.5 months at 60% survival.


Broader Takeaways:

  • HRs vs. Median OS: Neither metric alone suffices. HRs can obscure absolute benefit; medians can be gamed by curve shape.

  • KM Curves Matter: Visual inspection of entire Kaplan-Meier curves is crucial to avoid misinterpretation.

  • Effect Size Contextualized: An HR of ~0.73 yields vastly different absolute OS gains depending on baseline OS—~3.5 months in extensive-stage SCLC vs. ~11.5 months in limited-stage SCLC.


Implication for Practice:

Cancer clinicians and trialists should resist oversimplified metrics. Instead of relying on median OS or HRs alone, a more nuanced interpretation of survival curves is essential—particularly when shaping patient expectations or influencing regulatory/payer decisions.


This article adds an important cautionary note to how we interpret high-impact trial results—especially in the current era of immune checkpoint inhibitors and cancer immunotherapy.

###

###

###

Here's an AI summary of Prasad 2025 on Surrogates, 
and the Vogel letter in response.

###

Here's a concise, expert-level summary of the three-part exchange in Nature Reviews Clinical Oncology involving Vinay Prasad and Sebastian Vogel:


1. Prasad’s Original Article (NRCO, 2025)

Title: “A measured approach to surrogate end points in cancer screening and early detection”

Summary:
Prasad critiques the growing enthusiasm for early detection tools (e.g., liquid biopsies) based solely on surrogate endpoints—like stage shift or earlier diagnosis—without evidence of reduced cancer-specific or all-cause mortality. He argues:

  • Surrogates are unreliable: Earlier stage at diagnosis doesn’t necessarily reduce death if the treatment is ineffective or if lead-time and overdiagnosis biases exist.

  • Empirical validation needed: Historical examples (e.g., ovarian cancer screening, PSA) show that mortality benefit must be demonstrated in randomized trials before endorsing new screening tools.

  • Call for caution: Without solid mortality data, adoption of early detection tools risks overdiagnosis, overtreatment, and wasted resources.


2. Vogel’s Letter to the Editor

Tone: Critical but constructive.

Main Points:

  • Vogel defends early detection and stage shift as promising and biologically plausible surrogates, especially for cancers with poor late-stage prognosis (e.g., pancreatic cancer).

  • He notes that randomized mortality trials take years, and delaying implementation may hinder progress and innovation.

  • Vogel suggests that perfect shouldn’t be the enemy of good, advocating for a pragmatic, risk-adapted approach that balances early use of promising tests with real-world evidence generation.


3. Prasad’s Reply to Vogel

Tone: Firm, skeptical of compromise.

Main Arguments:

  • Prasad reiterates that plausibility is not proof: many biologically sound interventions have failed to improve survival or even caused harm when tested rigorously.

  • He warns against the “leap of faith” model of approving screening tools without RCT-level evidence, arguing this leads to medical reversals.

  • Prasad acknowledges the urgency but insists that clinical benefit must be shown, not assumed, especially in screening where harm from overdiagnosis can be substantial.


Bottom Line for Experts:

This exchange crystallizes the core debate in cancer screening: Should promising early detection tools be adopted based on surrogate endpoints like stage shift, or should the field adhere strictly to proven mortality benefit? Prasad urges scientific discipline and caution, while Vogel advocates for timely pragmatism in advancing potentially lifesaving tools.

Monday, June 2, 2025

Hogan Lovells Posts Summary: AI and Reimbursement Today and Tomorrow

 Recently, Hogan Lovells held a workshop on cutting edge issues in reimbursement, including AI.   Luckily, they've posted a detailed summary for those who couldn't attend.  Find it here:

https://www.hoganlovells.com/en/publications/ai-summit-panelists-offer-tips-for-obtaining-reimbursement-for-innovative-health-care-technology


It's part of their fourth annual AI Health Law & Policy summit.

Speakers included:

  • Victoria Wallace, Partner
  • Anitra Graves, CMS / FCSO
  • Richard Frank MD, in his role as AMA CPT digital medicine co-chair
  • David Reich MD, Mt Sinai Health System
  • Clark Daniel, Heartflow Govt Relations
Read Hogan Lovell's full summary at the link above.

On the topic of AI and reimbursement, that's one of 5 points raised by Jonathan Blum in a new essay about modernizing CMS.

###
AI CORNER
A mini-summary by AI (Chat GPT)

As AI-enabled medical technologies surge forward, the reimbursement landscape is struggling to keep pace. At a recent summit, Hogan Lovells' Victoria Wallace laid out the challenge: Medicare reimbursement is governed by decades-old legislation that never envisioned artificial intelligence. CMS lacks a defined benefit category for AI, and sponsors must wedge cutting-edge tools into outdated regulatory frameworks.

Dr. Anitra Graves, a key Medicare contractor medical director, described efforts to build a CMS taxonomy for autonomous technologies—essential groundwork for future pricing and coverage. But many questions remain, including how to value the complexity of algorithms versus the data they analyze.

Heartflow’s Clark Daniel and Mount Sinai’s Dr. David Reich added real-world insight: from the battles to secure appropriate coding and payer acceptance, to the necessity of embedding AI into clinical workflows. Reich emphasized that AI won’t replace physicians, but those who adopt it will outpace those who don’t.

Representing an AMA committee, Dr. Richard Frank highlighted how CPT coding and regulatory validation must align. A major update to CPT guidance is underway, aiming to define algorithm-specific codes. For now, the message is clear: reimbursement for AI is still a moving target—and stakeholder input is critical.

Sunday, June 1, 2025

ACLA POSTS: LDT RULE is DEAD

 According to ACLA, the HHS has let pass its 60-day deadline to lodge notice-of-appeal regarding the FDA LDT Rule.  The Notice of Appeal would have kept alive the case which otherwise terminated with the Texas judge's ruling 60 days ago.  O quote the ACLA below; see the original link for ongoing community commentary.

https://www.linkedin.com/feed/update/urn:li:activity:7334443741191057408/

See similarly a blog at FDA LAW BLOG:

https://www.thefdalawblog.com/2025/06/fda-abandons-its-defense-of-the-ldt-rule-but-is-it-signaling-an-increase-in-ruo-scrutiny/

See Bruce Carlson's blog on implications for IVD Mfgr here.

 

The ACLA writes,

The U.S. Department of Health and Human Services (HHS) declined to appeal the landmark ruling issued on March 31, 2025 by the U.S. District Court for the Eastern District of Texas that vacated the final rule seeking to regulate laboratory developed tests (LDTs) issued by the FDA, confirming that laboratory developed testing services are not “medical devices” subject to FDA’s regulatory oversight. The FDA had until May 30 to file its appeal.


The Court held that the FDA lacks authority to regulate LDTs. These testing services are not mass-produced devices introduced into interstate commerce, but rather diagnostic services developed and performed by laboratory professionals. Congress has never granted the FDA jurisdiction over such services, which are regulated under the Clinical Laboratory Improvement Act (CLIA) by the Centers for Medicare & Medicaid Services (CMS).

This ruling affirms what ACLA has long maintained: the FDA may not regulate laboratory developed testing services as medical devices. FDA’s rule would have resulted in reduced patient access to innovative tests that improve and save lives. Laboratory testing services provide patients and physicians with vital diagnostic information to inform clinical care, advance precision medicine, contribute to the discovery of novel therapeutics, identify rare diseases, and lead the fight against emerging pathogens.

ACLA members remain committed to the highest standards of quality and to ensuring patients benefit from timely, accurate, and accessible testing. ACLA represents the nation’s leading clinical laboratories, and all ACLA member clinical laboratories are fully accredited by the College of American Pathologists (CAP). We look forward to continued collaboration with policymakers to support patients, innovation, and America’s clinical laboratories.


Saturday, May 31, 2025

The MAHA Report --> AI Used Dumbly

By now, you've probably heard that the May 22 version of the Make America Healthy Again report had many errors due to AI-created false citations.   

This blog points out that problem was COMPLETELY unnecessary and could have been avoided with easily available better choices.

##

  • See May 22 article at NYT here.  See 68-page version archived at NYT here.
  • Original article at "NOTUS" exploring errors - May 29 here.
  • Washington Post updates on errors; May 30 here.   New errors, here.
  • I post a comparision of Mayy and May 31 versions in the cloud.
    • I used Draftable.com online to compare the 68-page May 22 version (NYT) and the current May 31 73-page version at Whitehouse.   
    • You have to click on little red triangles to see changes.  At the google cloud pdf upload by me, here.
Rather than belabor problems in the original manuscript, I'd make the point, it didn't have to be that way.  

#1
For example, even in Chat GPT, you have an option to send it to the internet for sources which it will retain as links; this at least eliminates the risk of non-existent sources.

#2
Another method - and I'm sure there are others - is to use the science research tool Scite.ai.  I don't use Scite often, but I've had a subscription for a year or two.  

For me, it has two main modes.  One does elaborate research on index publications - find out what papers cite the publication, and, see a clip of the sentences that make the citation.  For example, Lubarski 2008 cites 76 papers, and see what sentence in Lubarski cites which paper in the bibliography.  Since 2008, 60 newer papers have cited Lubarski, and you instantly see the sentence or two that each newer paper used to make the citations to Lubarski.

The second SCITE mode is a writing mode, where you offer a question (a prompt) and it responds in a couple minutes with an assay based on PubMed citations.  This would have helped MAHA. 

Now, OK, it may not have the best citations, or cite every article exactly correctly.   However, you WILL avoid the MAHA problem of literally fictitious citations and global humiliation.   And Scite's about $20 a month.

##

I give an extremely simplistic example below.   It took me five or ten seconds to ask for and a minute in creation by Scite.  That is, this is a "no effort" example.

  • Cite recent sources in the last 3 years that document an increase in chronic disease in children such as asthma, autism, autoimmune diseases, obesity, etc.

##  Scite writes, and cites:

The prevalence of chronic diseases among children, including obesity, asthma, autism, and autoimmune diseases, has shown a marked increase in recent years, as evidenced by numerous studies conducted globally.

Obesity rates in children have been documented to rise sharply. A systematic review highlighted that the prevalence of childhood obesity in Spain has escalated substantially over the past decade, necessitating urgent policy measures to address this growing epidemic (Bravo-Saquicela et al., 2022). Furthermore, a nationwide observational study in Japan revealed similar trends, indicating that childhood obesity has increased consistently from 2012 to 2021 (Fujiwara et al., 2023). This escalation in obesity prevalence is further illustrated by various studies indicating a rise in overweight and obesity rates among children in different regions, including Geneva Narvaez et al. (2024) and Brazil, where obesity prevalence displayed wide regional variations, underscoring the urgency for preventive strategies (Santos et al., 2023).

The association of childhood obesity with other chronic conditions, particularly the link between obesity and autoimmune diseases, has become a focal point in recent research. For instance, a study examining antibody-mediated autoimmune diseases in children found a gradual rise in incidence, suggesting a concerning pattern that may be correlated with the increased rate of obesity (Kang et al., 2023). Additionally, chronic conditions such as atopic dermatitis have also seen a rise, and while it is suggested that genetic and environmental influences play a role, the classification of these diseases as autoimmune is still debated (Floca et al., 2022).

Asthma prevalence has not remained static either. Research has indicated that chronic childhood asthma symptoms fluctuate with environmental changes, and there is ongoing concern that the prevalence of asthma among children has been exacerbated by factors such as exposure to passive smoking during childhood (Jaakkola et al., 2021). This suggests a complex interplay between environmental conditions and the manifestation of chronic respiratory conditions in children.

Moreover, the COVID-19 pandemic has adversely affected the prevalence of childhood obesity. Studies indicate that a deterioration in behavioral and environmental factors during the pandemic has led to an increase in obesity rates among children (Emiroğlu et al., 2024). Particularly, the socioeconomic status of families has been shown to correlate strongly with higher rates of childhood obesity and associated health problems, which may exacerbate overall health disparities within populations (Batioja et al., 2024; ,Sritart et al., 2022).

The multifactorial nature of these chronic diseases amongst children encompasses not only environmental and genetic components but also socio-economic elements that can influence health outcomes. As research continues to reveal interconnections between various chronic conditions and emerging trends in obesity, these findings highlight the need for comprehensive public health strategies that address the multifaceted factors contributing to chronic diseases in children today.

[End scite auto generated text]

References:

Batioja, K., Elenwo, C., Hendrix‐Dicken, A., Ali, L., Wetherill, M., & Hartwell, M. (2024). Associations of social determinants of health and childhood obesity: a cross-sectional analysis of the 2021 national survey of children’s health. Journal of Osteopathic Medicine, 124(5), 231-239. https://doi.org/10.1515/jom-2023-0239
Bravo-Saquicela, D., Sabag, A., Rezende, L., & Rey-López, J. (2022). Has the prevalence of childhood obesity in spain plateaued? a systematic review and meta-analysis. International Journal of Environmental Research and Public Health, 19(9), 5240. https://doi.org/10.3390/ijerph19095240
Emiroğlu, P., Taneri, P., & Güner, A. (2024). Impact of the covid-19 pandemic on childhood obesity prevalence. Bagcilar Medical Bulletin. https://doi.org/10.4274/bmb.galenos.2024.2024-02-0183
Floca, E., Gaga, R., Sur, G., Lupan, I., Armat, I., Samaşcă, G., … & Sur, L. (2022). A new autoimmune disease: atopic dermatitis in children. Allergologia Et Immunopathologia, 50(6), 17-21. https://doi.org/10.15586/aei.v50i6.655
Fujiwara, S., Harada, K., Hagiya, H., Koyama, T., Hasegawa, K., Tsukahara, H., … & Otsuka, F. (2023). Trends in childhood obesity in japan: a nationwide observational study from 2012 to 2021. Clinical Obesity, 14(2). https://doi.org/10.1111/cob.12636
Jaakkola, J., Rovio, S., Pahkala, K., Viikari, J., Rönnemaa, T., Jula, A., … & Raitakari, O. (2021). Childhood exposure to parental smoking and life-course overweight and central obesity. Annals of Medicine, 53(1), 208-216. https://doi.org/10.1080/07853890.2020.1853215
Kang, Q., Liao, H., Yang, L., Fang, H., Ning, Z., Liao, C., … & Wu, L. (2023). Clinical analysis of 173 pediatric patients with antibody-mediated autoimmune diseases of the central nervous system: a single-center cohort study. Frontiers in Immunology, 14. https://doi.org/10.3389/fimmu.2023.1140872
Narvaez, L., Mahler, P., Baratti-Mayer, D., & Jeannot, É. (2024). Changes in body weight and risk factors for overweight and obesity in 5–6-year-old children attending school in geneva. Children, 11(5), 529. https://doi.org/10.3390/children11050529
Santos, F., Silva, E., Baêta, C., Campos, F., & Campos, H. (2023). Prevalence of childhood obesity in brazil: a systematic review. Journal of Tropical Pediatrics, 69(2). https://doi.org/10.1093/tropej/fmad017
Sritart, H., Taertulakarn, S., & Miyazaki, H. (2022). Disparities in childhood obesity prevalence and spatial clustering related to socioeconomic factors in isaan, thailand. International Journal of Environmental Research and Public Health, 20(1), 626. https://doi.org/10.3390/ijerph20010626

Friday, May 30, 2025

CMS Publishes Updated Code List for Summer Lab Pricing Meetings

For the summer Annual Lab Meeting, CMS has published an expanded code list, with 91 action items.   

Go to this site and scroll down for Meeting Notice - Agenda, and find "Code List v.2 5 28 2025."

In the expanded list (released May 28) CMS adds codes confirmed by AMA in early May 2025.

##

For full background on this public meeting (June 27) and the Expert Panel Meeting (July 23-24), see my original blog:  


(From Endpoints): Illumina's Diaspora, Customers and Competitors

The interesting news site Endpoints News has an article on Illumina and the sequencing ecosystem, by editor Jared Whitlock.   Find it here:

https://endpts.com/how-illuminas-ex-employees-became-its-customers-and-competitors/


Endpoints is switching to a new "dot-news" website June 1:

https://endpoints.news/


Chat GPT summarizes,

  • In a sweeping feature for Endpoints News, Jared Whitlock explores how Illumina — the DNA sequencing giant that helped democratize genomics — has paradoxically seeded a wave of competition from within. Over 70 companies have been founded by former Illumina employees, forming a "diaspora" that’s both reliant on and rival to their former employer. While some of these spinouts, like Element Biosciences, have become fierce competitors, many still use Illumina sequencers or complement its tech. 
  • The article details how Illumina, grappling with the results of its Grail acquisition, is now expanding beyond DNA into multiomics — often into the same markets its alumni now occupy. 
  • For readers tracking the genomics industry's evolution, this piece is a fascinating look at innovation, spinout culture, and corporate strategy in real time.


Thursday, May 29, 2025

AdvaMed Says: CMS, FDA Leadership Care About Breakthrough Device Coverage

AdvaMed has a new posting on Linked In, highlighting a recent panel in which HHS leadership voiced a commitment to Breakthrough Device coverage.

Find the posting here, including a video clip:

https://www.linkedin.com/posts/advamed_medtech-breakthroughdevices-activity-7333871545150320640-aeui/

Here's part of what AdvaMed writes:

  • When the FDA deems breakthrough medtech safe and effective, there shouldn’t be duplicative, years-long reviews that delay patient access to lifesaving innovations. 
  • In a recent FOX interview, Dr. Makary shared that [FDA] and Dr. Mehmet Oz are working on “a way Medicare can pay for something the second the FDA approves a breakthrough device, so they don’t have to go through their own repeat, duplicative approval process for a year.” 
  • This effort aligns with the recent introduction of bipartisan legislation by U.S. Senators Todd Young (R-Ind.) and Alex Padilla (D-Calif.) aimed at improving this process and expediting coverage for FDA-designated breakthrough medical technologies. House legislation is expected soon. If enacted, this reform will accelerate patient access, improve efficiency, and ensure smarter use of taxpayer dollars.

I've pointed out as far back as March that AdvaMed has strongly supported HHS appointments like Dr. Oz:

...Whereas AMA, JAMA, NEJM, etc, have been consistently highly negative about the administration.  NEJM, etc, have gotten "vaguely threatening prosecutor's letters."  AMA got a pay cut for physicians.  This week's news is that RFK Jr would like to block NIH from publishing in journals like JAMA and NEJM.    

NEJM Covers the FDA LDT Legal Decision

It's about 60 days since a Texas federal court tossed out the FDA LDT regulation.   Recall the government had 60 days to file an appeal.   If it doesn't, FDA might issue some other kind of information, like an administrator's blog or a press release on the topic.

Along the way, New England Journal has published a 3-page article on the FDA decision.   (Spoiler alert - the authors wish the FDA would have won).    Find Sachs, Sharfstein & Zettler online here:

https://www.nejm.org/doi/full/10.1056/NEJMp2504926


One lingering question for me, as a non-attorney.  The decision clearly means that FDA can't mandate lab-developed procedures to undergo FDA review as devices.    But does this also mean the FDA is barred from review of LDTs that labs bring to the FDA voluntarily?   A lab might want its LDT to be FDA-approved in order to get some other benefit, like CMS coverage under an NCD or special CMS pricing as an ADLT (advanced diagnostic laboratory test).   But could FDA review it, voluntarily, if the FDA is generally precluded from reviewing lab procedures because they are not "devices" and not within FDA scope?   

Tuesday, May 27, 2025

CMS 2023 Lab Data Part B - HIghest Dollar Volume Codes

 In a previous blog, I noted that CMS had released CY2023 Part B claims (by doctor or by lab) for CY2023.   I showed the top ten billing labs for 81479, molecular unlisted code, for which the total dollar volume was nearly half a billion dollars ($488M) in 2023.

Here, I went back to the cloud database and extracted all the molecular codes (811 series to 815 series), plus PLA codes ending in U, plus microbiology molecular codes (87468-87999).    

The database has 130,000 lines, and weighs about 30 MB after I had done some different sorting options.

Total molecular dollar volume in 2023 was $3.4B, of which 14% or $488M went to 81479.   

After that, $300M or 9% went to 81528 (Cologuard / Exact Sciences) and $288M or 8% to 87798 (other infectious agent probe).   The next two positions were 3% for $118M for 81455 (any lab, heme CGP) and 3% $104M to 0242U Guardant FDA LBx CGP test.

The top 15 codes had 57% of all dollar volume. Click to enlarge.


Breaking out 81479, "Code #1," these were top-paid labs:



PLA CODES

CMS logged sales for 82 of the approximately 400 PLA codes at the time.   Total sales for PLA codes were $519M.   The top 10 PLA codes got 80% of the PLA code dollar volume (of all 400 PLA codes).  The top 4 PLA codes (or 400 PLA codes) had half the dollar volume.  Click to enlarge.


About half the PLA codes, that logged any Part B sales, logged less than $100,000.  About a quarter of the PLA codes, that logged any Part B sales, logged less than $10,000.  About 3/4 of the 400 PLA codes for 2023 logged 0 sales at CMS.

See It Yourself

I posted the 30 mb Excel file as a Cloud resource in Google Drive.  It's open access but you may need a google account to see and download it.

https://docs.google.com/spreadsheets/d/1a1cQNKUdB5pmcOnJDqZF8EgtPD6EYiRH/edit?usp=sharing&ouid=110053226805181888143&rtpof=true&sd=true


Some More Examples from the Data:

87798

87798 was a very widely used code in 2019-2020-2021, including in MolDx states.  Then MolDx brought out an LCD, or revised one, that made it very hard to use 87798 (other molecular probe, pathogen).   The top 20 labs biling 87798 by 2023 were almost all in non-MolDx states.  


MolDx vs Other MACs on 81455 (81456)

MolDx rarely allows labs to use the code for 50+ tumor genes (81455, about $2850).  Instead, MolDx asks labs to code 81479 instead of 81455 (see e.g. Caris billing pattern, 84% 81479).   In Illinois, conventional codes are accepted by the NGS MAC, such as from Tempus.  (81455 for DNA or for DNA and RNA analysis; 81456 for RNA analysis).  Click to enlarge:


Note that Tempus was paid for for 81455 (50+ tumor genes, DNA, RNA if performed) and 81456 (50+tumor genes, RNA).   There is a correct coding edit which would discourage co-billing these two codes on the same day.

This suggests Tempus bills them "not on the same day."  Under the outpatient genomic test biopsy rule and the 14-day inpatient rule, a genomic test can be ordered such that the date of service is not the date of biopsy, but, the date the test is performed.  This suggests that Tempus bills 81455 for DNA and 81456 for RNA on different dates-of-record for the date of test performance.  Tempus notes on its investor calls (e.g. May 2025) that the DNA and RNA tests are separately run tests, so more likely than not they would finish their procedures on different dates of performance.  The NCCI edits above are only for same date of service.