Tuesday, December 2, 2025

Senator Escalates Concerns about AMA "Monopoly" (Coding)

On December 2, 2026, Washington Post features a story on Sen. Cassidy's escalating tensions with AMA, regarding coding and the RVU payment system.  The Senator kicks off by asserting that AMA's response to an October 6 letter "was anything but open and transparent."

  • See our October 29 blog on this topic here.
  • See updates, December 2 at Washington Post,here.
  • See the new 5-page Senate letter to the FDA, dated December 1, here.

AMA Summit on Digital Medicine

The exchanges come as AMA is on the brink of holding a major summit meeting in Chicago, December 8, on the future of new technologies coding and reimbursement, covering digital medicine, digital pathology, and AI.   More here.

CMS Innovative Work-arounds for Digital Reimbursement

And the letters, and that AMA meeting, come just as CMS announces its CMMI "ACCESS" model, under which some new, FDA-approved software-based or software-intensive interventions like remote monitoring will be reimbursed directly by Medicare as part of its new comprehensive approaches to chronic disease management, potentially outside the usual CPT coding channels.  Entry point here.


Monday, December 1, 2025

El-Khoury & Zaatari: Pathologist, AI, and the Future. Plus lots of great citations.

I probably saw this post via someone at Linked-In, but I've mislaid how I heard about it.  

Worth reading, a new open-access paper, which projects into the future and asks if pathologists will be "partners" or "bystanders" to AI.

Find the September 2025 paper by El-Khoury and Zaatari online at Diagnostics, here:

https://www.mdpi.com/2075-4418/15/18/2308

In addition to the main story, the article offers an excellent bibliography of nearly 100 references, some of them hard to find (history of microscopes), many others up-to-date through 2025.


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Sidebar:
I asked Chat GPT to compare the history of autopilots in airlines (1940-2025) to the future of pathologists in the AI lab (2025-2050).  Here.

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AI CORNER

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El-Khoury and Zaatari provide a sweeping, historically anchored analysis of how digital pathology and AI are jointly reshaping diagnostic practice, culminating in the provocative question of whether pathologists may eventually become “bystanders” in workflows they once wholly governed. They trace the discipline’s evolution from early microscopy and microtechnique innovations to contemporary whole-slide imaging (WSI)—establishing digital pathology as the essential substrate upon which AI systems now depend. This historical framing underscores that AI represents not merely another tool but a structural inflection analogous to the rise of cellular pathology itself.

The authors categorize current AI systems into task-specific deep learning models and emerging general-purpose “foundation models”, noting that the former already deliver expert-level or superhuman performance in constrained tasks—metastasis detection, Gleason grading, MSI inference, mutation prediction, biomarker quantification—supported by regulatory milestones such as Paige Prostate Detect (FDA-cleared) and Ibex Galen Prostate (510(k)). These systems reduce interobserver variability, shorten turnaround time, and uncover otherwise-missed cancers. However, they remain narrow, brittle, and dependent on pathologist-labeled data.

Foundation models—e.g., Virchow, GigaPath, PLIP, and the multimodal copilot PathChat—reflect a deeper conceptual shift. Trained with self-supervision on diverse histologic corpora, they operate across tasks, integrate language, and can propose differentials, ancillary stains, and draft reports. Their flexibility suggests that future diagnostic pipelines may not be built around individual algorithms but around generalist, multimodal AI agents capable of interacting directly with clinicians.

A central contribution of the paper is its scenario analysis of a hypothetical pathologist-free workflow, in which AI interacts directly with the referring physician. The authors map each step—from grossing and scanning to AI-generated interpretations—arguing that this model is technologically imaginable but clinically, ethically, and legally fraught. They emphasize key obstacles: domain shift vulnerability, demographic bias, the opacity of deep networks (“black box” problem), and unresolved questions of liability when AI errors cause harm. The risk of deskilling the pathology workforce and undermining quality in rare or ambiguous cases is highlighted as a structural hazard.

Ultimately, the authors outline three trajectories: a symbiotic model (AI augments pathologists), a transformational model (pathologists become diagnostic integrators and AI supervisors), and a disruptive model (AI performs routine diagnosis autonomously). They argue that the profession’s future relevance will depend on active engagement with AI tools, evolution of training programs, and leadership in ethical and regulatory frameworks. The paper concludes that while full replacement is unlikely in the near term, long-term disruption—particularly with domain-specific AGI—cannot be dismissed.


Communications Expert Assesses Trump-Mamdani Conference, Line by Line

On YouTube, communications expert Chris Miller goes through the Trump-Mamdani Oval Office meeting and describes his view of how each politician handled framing, seizing initiative, dodging conflict, etc.

You don't have to buy into every single idea the communications expert has, to benefit from this magnifying-glass view of the dialog.    Watch it online - 15 minutes - or I've included a transcript below.

https://www.youtube.com/watch?v=Ju0URMztrzs


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Transcript from Rev.com from link.

Chris Miller:

Okay, no one would expect this, but President Trump and New York City Mayor like Mamdani just met in the Oval Office at the White House. And the presentation they just gave to the media and the question and answer portion was surprising.

 

It was a communication showdown. So in this video, we're going to break down the dynamics, the framing, the use of humor, and how what we expected was much different than what we got.

I'm going to show you a lot of different clips. I'm going to pause often, so just stick with me. Before we start, let's think about what's been going on. So the past few months, both Trump and Mamdani have been going at each other's necks. I just did a reaction video to Mamdani's victory speech, and here's some of the things you said.

Zohran Mamdani:

After all, if anyone can show a nation betrayed by Donald Trump, how to defeat him, it is the city that gave rise to him. And if there is any way to terrify a despot, it is by dismantling the very conditions that allowed him to accumulate power. So Donald Trump, since I know you're watching, I have four words for you. Turn the volume up.

Reporter:

Did you see his victory speech?

Donald Trump:

By the way, it's literally never worked. Yeah, I thought it was a very angry speech, certainly angry toward me, and I think he should be very nice to me. I'm the one that sort of has to approve a lot of things coming to him, so he's off to a bad start.

Reporter:

At one point he says, "Turn the volume up." How do you respond to that? Does that affect anything you're going to do?

Donald Trump:

It's a very dangerous statement for him to make.

Chris Miller:

So with what we would perceive as tensions being high, let's see how this starts. But before we do that, could you quickly like this video and subscribe to the YouTube channel? I have a new analysis every Monday and Thursday so that you can learn how to communicate in the world's biggest moments.

Donald Trump:

Well, thank you very much. We've just had a great meeting, a really good, very productive meeting. We have one thing in common. We want this city of ours that we love to do very well. And I wanted to congratulate the mayor. He really ran an incredible race against a lot of smart people, starting with the early primaries against some very tough people, very smart people. And he beat them and he beat them easily, and I congratulated him.

Chris Miller:

Trump starts us off with a status hug. A status hug is when a dominant person gives off so much more and so much praise that ultimately it gives them control. First, he introduces Mamdani as a big success and he ultimately narrates the success of his campaign. And in communication, typically, the narrator is the one who holds the power. He's the one with the pin. So with all of this praise, it seems like, oh wow, that's really nice. But in high power settings, praise is an example of positional power by saying Mamdani beat him out easily, it puts Trump as the judge. By saying, "If Mamdani does really good, then I'll be even more happy." That puts him as the evaluator. It's these little framing tactics.

Donald Trump:

But I just want to congratulate. I think you're going to have hopefully a really great mayor. The better he does, the happier I am, I will say. There's no difference in party. There's no difference in anything. And we're going to be helping him to make everybody's dream come true, having a strong and very safe New York. And congratulations, Mr. Mayor. Thank you, Mr. President.

Chris Miller:

For instance, you may have been surprised whenever Trump said there's no difference in political parties, there's no difference in anything when factually that isn't true. There is a lot of difference. But what that does is it sets the frame of this is apolitical, this is harmonious, and it removes the oxygen from this room full of reporters who are going to bring up all these attacks of like, "Didn't you just say that thing last week? Or didn't you say that thing a month ago?" And this is something expert communicators do so well. They set the frame so that if anybody goes against it, that person is going to seem combative.

Zohran Mamdani:

Thank you, Mr. President.

Donald Trump:

Thank you.

Zohran Mamdani:

I appreciate it.

Donald Trump:

Please.

Zohran Mamdani:

I appreciated the meeting with the President. And as he said, it was a productive meeting focused on a place of shared admiration and love, which is New York City and the need to deliver affordability to New Yorkers, the eight and a half million people who call our city their home, who are struggling to afford life in the most expensive city of the United States of America.

We spoke about rent, we spoke about groceries, we spoke about utilities, we spoke about the different ways in which people are being pushed out. And I appreciated the time with the President. I appreciated the conversation. I look forward to working together to deliver that affordability for New Yorkers.

Chris Miller:

Mamdani starts with a lot of strategy rather than accepting the frame that Trump has set. He accepts hospitality, but he pivots the frame. He first says, "I'm grateful. I'm glad I get to talk with the President," but he doesn't mimic the over the top praise that Trump uses because he wants to be perceived as independent from the President. He is a lower power figure in this power situation, but he doesn't want to seem like he can be co-opted by Trump. So he's going to say thank you to Trump, but he's not going to give Trump all of this praise back or he's not going to echo the praises that Trump gave him like, "Yeah, I did beat him easily. And, yeah, I am going to save New York."

And something that you see Mamdani do really well here is absorb and redirect. Immediately, he talks about affordability. So Mamdani isn't going to come into this conversation with a big personality. He's going to come into the conversation with the logic, the numbers, and the stories. He doesn't want to set the frame of, "Hey, we're best friends." And, "Hey, we're going to enjoy working together this whole time." He wants to be gracious, leader-like, reduce friction, but he doesn't want to seem as if he's tied to the hip of Trump.

Now, when question and answer starts, that's when you can really see the dynamics and all of the strategic moves that the both of them make. The reporters know that there's a lot more than they're putting on, so they begin to ask very pointed questions like this one.

Reporter:

Mr. Mamdani, it sounds like you had a productive discussion, but just days ago, you referred to President Trump as a despot who betrayed the country. He said it would be his worst nightmare and accused him of having a fascist agenda. Are you planning to retract any of these remarks in order to improve the relationship?

Chris Miller:

The reporter asks, "You referred to President Trump as a despot, accused him of a fascist agenda. Are you going to retract?" Now, this is a trap question. There's 99 ways to answer this and 98 of them are going to get you in hot water. If you retract, you look weak. If you double down, you look combative. If you evade or dodge the question, then it looks like you are avoiding something and scared to approach it, but Mamdani does something very strategic here.

Zohran Mamdani:

I think both President Trump and I, we are very clear about our positions and our views. And what I really appreciate about the President is the meeting that we had focused not on places of disagreement, which there are many, and also focused on the shared purpose that we have in serving New Yorkers. And frankly, that is something that could transform the lives of the eight and a half million people who are currently struggling under a cost of living crisis with one in four living in poverty. And the meeting came back again and again to what it could look like to lift those New Yorkers out of struggle and start to deliver them a city that they could do more than just struggle to afford it, but actually start to live in it.

Chris Miller:

Mamdani says in response, "We are very clear about our positions and our views, the meeting focused on our shared purpose, lifting 8.5 million New Yorkers out of struggle." So this is very strategic by him. He doesn't repeat the charged word fascist. He doesn't retract what he says. Rather, he instantly pivots back to this focus of affordability and he reframes it. So in doing this, he lowers the temperature in the room. Now, what we'll see later on, they're not going to let that go, but in the moment, it was a really good opportunity to reframe and that's what he did.

Reporter:

I want to clarify your answer to Steven Nelson. He asked about your comment calling the president a fascist and your answer was, "Both President Trump and I have been clear about our positions and our views." Are you affirming that you think President Trump is a fascist?

Zohran Mamdani:

I've spoken about the-

Donald Trump:

That's okay. You can just say yes.

Zohran Mamdani:

Okay. All right.

Donald Trump:

It's easier. It's easier than explaining it. I don't mind.

Chris Miller:

And this is one of the best things that Trump does in the meeting, because he immediately collapses the tension with humor. He also signals emotional superiority of like, "Hey, I've been called much worse things. Honestly, that doesn't even bug me at all." Unbothered. He does something very important here and that's protecting Mamdani from having to answer directly.

Mamdani would have redirected back to affordability somehow, but he says, "Hey, don't worry about it." And it signals confidence and it again gives him this chance to reframe through levity. He establishes dominance. So a great example how two different tools, both Mamdani and Trump are doing two different strategies to bring the energy down and make this seem like a much more harmonious event and a win for the both of them. Another really big way that the reporters try to trip both of them up is comments about ICE.

Reporter:

Mr. President. You threatened to send federal troops to New York City. You both have differences when it comes to ICE agents of New York City. Mr. Mamdani, you've called ICE a rogue government entity. I wonder how you'd reconcile your differences on both of those issues.

Donald Trump:

Well, I think we're going to work them out. And I think that if we have known murderers and known drug dealers and some very bad people, we want to get them out. And the Mayor wants to have peace. We discussed this at great length actually, maybe more than anything else. He wants to have a safe New York. Ultimately, a safe New York is going to be a great New York.

If it's not safe, no matter how well we do with pricing and with anything else, we can talk about anything you want. If you don't have safe streets, it's not going to be a success. So we're going to work together. We're going to make sure that if there are horrible people there, we want to get them out. I think he wants to get them out maybe more than I do, so we'll work together. We discussed it at great length.

Chris Miller:

This is classic Trump framing, because he's shifting the topic from ICE into crime. Talking about ICE in this moment may be controversial, but talking about eliminating crime is not controversial. It's something everybody wants. So he reduces the tension again, again, again. "Hey, this doesn't need to be a conflict. We're on the same page here. We both want to reduce crime." And as you notice, he says we, and he speaks from Mamdani. He wants it even more than I do maybe.

Zohran Mamdani:

We discussed ICE and New York City and I spoke about how the laws that we have in New York City allow for New York City government to speak to the federal administration for about 170 serious crimes. The concerns that many New Yorkers have are around the enforcement of immigration laws on New Yorkers across the five boroughs. And most recently, we're talking about a mother and her two children, how this has very little to do with what that is.

Chris Miller:

And when Mamdani speaks about this, he speaks with a lot of precision, but he also reframes this. He says, "New York City can coordinate with federal agencies for 170 serious crimes," so he's co-opting that crime frame. But he's also saying the concern is around enforcement on New Yorkers, and he gives example of a mother and her two children facing immigration enforcement. So what he's doing here by sharing that story is he's changing the frame away from crime and towards families.

Trump frames ICE as removing murderers, while Mamdani frames ICE as traumatizing citizens and their families. So he avoids debating Trump directly because that would take a hit on his persona in this moment. He doesn't say you're wrong or I'm actually right here, but he does change the lens, which is strategic. And then you see Trump double down again talking about ICE, he says ...

Donald Trump:

What we did is we discussed crime more than ICE per se. We discussed crime and he doesn't want to see crime and I don't want to see crime. And I have very little doubt that we're not going to get along on that issue.

Chris Miller:

Well, we discussed more than ICE was crime. He doesn't want to see crime and I don't want to see crime. We discussed this at great length. So he's changing it again. He's reasserting this frame of crime equals ICE or ICE equals crime. And you don't want crime, you actually want safety, so we need to take action and make decisions on this. So neither Mamdani or Trump are accepting one another's frame, but they're not openly disagreeing, which is good for the both of them. So they're tactically talking while tactically not talking.

Zohran Mamdani:

... the time with the President. I appreciated the conversation. I look forward to working together to deliver that affordability for New Yorkers. That came back to the same issue, cost of living, cost of living, cost of living. We heard them speak about cost of living. We focused on that same cost of living, and that's where I am really looking forward to delivering for New Yorkers in partnership with the President on the affordability agenda. And I know there might be differences about ideology, but the place of agreement is the work that needs to be done to make New York City affordable. That's what I look forward to. We focused on affordability. We focused on the cost of living crisis. What I will say is that I am very much interested in property tax reform.

Reporter:

Mr. President, you say you love New York City. Mr. Mamdani, does New York City love President Trump?

Donald Trump:

New York City loves a future that is affordable.

Chris Miller:

And ending with one of the most impressive things, and that's Mamdani's affordability message and his discipline to the message. He keeps going back to it over and over again. He says, 8.5 million New Yorkers, he drops stats. He talks about cost of living. He talks about rent, groceries, utilities. He talks about how all of these people are struggling to afford life in the most expensive city.

So to him, he knows that affordability is the safe zone. If he can go throughout this whole entire conversation and make affordability as the thing that he's remembered for, then it's a victory. Trump talks about his victories and talks about the things he's done and how he's done really well and how the last president's not done as well. And Trump talks about how Mamdani's done really well and how Mamdani's going to make New York City great.

Mamdani doesn't do any of that. He talks about affordability. He talks about his values. A very intentional decision, because ultimately, he doesn't want to get in the hot water, but he also doesn't want to be perceived as someone who folded under pressure and who changed. So it's really impressive the discipline of the message. Repetition, repetition, repetition. The more you repeat something, the more likely you're going to be remembered by that, and it's really good for you to be remembered by your core message.

So despite all of the questions coming in, if you can pivot, if you can absorb and if you can reframe back to your core message, that's a plus. Overall, I think this was a great conversation and I think it was a great instance of seeing how people reframe in high power situations and how they're incredibly attentive to detail to make sure they're not doubling down on something they don't want to be associated with while also changing the direction and going back to their core message and their core strategy.

I did an analysis over Tucker Carlson and Putin. You can watch that video next. And be sure to subscribe to the channel if you like moments like this and you like analysis and you want to learn how people communicate in the biggest moments in the world. As always, I'll see you next time.

 


LegislationWatch: Proposed: Bill for Alzheimer Blood Testing in Medicare, H.R. 6130

Legislation watch:  A bill is introduced which would cover preventive screening with blood tests for Alzheimer's disease.   

The full legislative text isn't posted yet, but if it resembles recent bills for MCED at Medicare, it would give CMS authority to create NCDs in this area without waiting for an endorsement from USPTF. (Prior HR 2407, now HR 842).

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See also this week:

JAMA Meta-Analysis of Tau217 plasma diagnostics, Malek-Ahmadi et al.  

JAMA Op-Ed, 'Bood Tests for Alzheimer Disease - What to Do with the Holy Grail' by Grill.

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Repr. Buchanan (R-FL) had early publicity November 7 at AXIOS - here.

See the November 19 press release about the bill - here.

Read the bill, when it is posted at Congress.gov as HR 6130 - here.



Humor: When Medicare Pays for a Covid Test / Nursing Home

From time to time I have work related to Medicare's 14-day-rule, which is difficult to explain even with graphics and charts.

This looks like comparable complexity: When does Medicare pay for a nursing home Covid test?   Sit down and take your hat off, this will be a while.


See link for several pages of additional explanation.
https://www.cms.gov/files/document/covid-medicare-payment-covid-19-viral-testing-flow-chart.pdf

Saturday, November 29, 2025

Noted: Luis Cano's Essay on "Invisible War in Digital Pathology"

 Luis Cano MD PhD is a Paris-based expert on digital pathology.  Find his Linked in here.  His article feed here.   His Substack articles, "Beyond the Slide," here.

His new 5000-word mega-essay about digital pathology system dynamics:

https://beyondtheslide.substack.com/p/the-invisible-war-in-digital-pathology

By the way, the bibliography of his new article is quite impressive too.

Enjoy the original essay but here's a 300 word summary (AI):

Digital pathology, Cano argues, is less a neat “digital upgrade” and more an invisible war: a messy, protracted collision between technology that already works and systems that are nowhere near ready to absorb it. The microscope era was stable, tactile, and culturally entrenched; digital workflows turn glass into data, demanding scanners, clouds, networks, standards, and cybersecurity. 

COVID accelerated adoption by necessity, proving feasibility but also exposing fragile infrastructure and improvisational workflows, especially in low-resource settings where digital tools could help most but basic prerequisites—power, bandwidth, capital—are lacking. The result is a tug-of-war between an analog world that won’t die and a digital one not yet fully born.

The conflict is driven less by algorithms than by misaligned incentives and timelines. Startups sprint on 18-month venture clocks; hospitals move on 5–10-year cycles; pathologists, as final signatories, face an identity and liability crisis. 

Economics form a central minefield: capital costs are huge, ROI is mostly indirect efficiency, and reimbursement for digitization or AI is nascent and fragmented. Technologically, proprietary formats, weak interoperability, domain shift, and brittle real-world performance keep AI stuck in “demo mode.” Regulatory fog deepens the tension: the FDA’s PCCP and the EU AI Act try to tame evolving, data-hungry models with frameworks built for static devices, while liability for AI-driven errors remains unclear.

Cano’s core thesis is that progress hinges on alignment, not more clever models. He points to federated and swarm learning, shared infrastructures like BigPicture, and human-centered design as early blueprints for cooperation. The future pathologist becomes an integrator of multi-modal information, not a human scanner; AI should amplify rather than replace. The “war” ends, he suggests, when stakeholders stop behaving like rival armies and start acting as architects—building standards, economic models, regulations, and lab designs that are interoperable, explainable, and explicitly human-centered.

Not Bad for a Machine: Chat GPT Offers to Review CMS & AI for Me

For almost three years, I've had a $20 a month subscription to Chat GPT.  Like other AI's, the home page me offers me topics for the AI to discuss (as if I could think of none, myself?)

This morning the home page of Chat GPT offered me:

  • What are the latest CMS policy updates on AI reimbursement and digital health? Any new regulations or pilot programs worth noting?

I thought, OK, it's a holiday, I'll bite.   

Here's what I got.  

NOTE: I would not necessarily make the same recommendations or emphasize the same things as Chat GPT.  What follows is offered only as an example of automated internet research and automated conclusions and summaries.

I asked it about turnkey venders for remote monitoring; in that section, I've stripped the websites it found but left the AI text.

Remarkable Series of Articles on Digital Medicine from Flavio Angei (Linked In)

I've started noticing the rapid flow of articles highlighted every week by Flavio Angei at Linked-In.

Find his home page here:

https://www.linkedin.com/in/flavio-angei-b5476841/


This should take you to his Linked-In postings:

https://www.linkedin.com/in/flavio-angei-b5476841/recent-activity/all/

He highlights top papers in digital medicine from a wide range of journals.

  • Evolving health technologies: Aligning with and enhancing the NIH Care Excellence Standards Framework.
  • Success factors for sclaing patient-facing digital health technologies: Leaders' insights
  • Navigating regulatory challenges across the life cycle of SaMD
  • LSE: Evaluation framework for health professionals' digital health and AI technologies.
  • Rethinking clinical trials for emdical AI with dynamic deployments of adaptive systems.
  • AI policy in healthcare; A checklist-based methodology for structured implementation.
  • Artificial intelligence in key pricing, reimbursement, market access processes.  Faster better cheaper - Can you really pick two?
  • Systematic review of cost effectiveness and budget impact of AI in healthcare.
  • Commercialization of medical AI technologies: Challenges and Opportunities

Etc etc etc....


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Goranatis et al. Weigh In on "Value & Valuation" of Genomics

  • First, updating some links on new reviews of MCED.  
  • Then, we look at a new paper by Goriatis, Buchanan, et al in Nature Medicine on valuation of genomics in healthcare.

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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.

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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

Below, find Chat GPT 5 on Goranitis and on Buchanan, Goranitis.

Tuesday, November 25, 2025

CMS Issues "Request for Information" - Strategic Directions for Medicare Advantage

 CMS has issued its CY2027 proposed rule for Medicare Advantage.  It includes a "request for information" about future strategic directions for the program.

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CMS issues four major Medicare rules each year.  In the spring, we have the Inpatient Rule, which finalizes in August, ahead of the October fiscal year.  In the summer, we have the Physician and the Hospital Outpatient rules, which publish November 1, ahead of the new calendar year.

And around November, we get the Medicare Advantage proposals, which finalize in the spring, and of the next MA contract year.

Find the MA press release here:
https://www.cms.gov/newsroom/press-releases/cms-proposes-new-policies-strengthen-quality-access-competition-medicare-advantage-part-d

Find the fact sheet here:
https://www.cms.gov/newsroom/fact-sheets/contract-year-2027-medicare-advantage-part-d-proposed-rule

Find the actual proposed rule here (paginated publication on 11/28):
https://www.federalregister.gov/public-inspection/2025-21456/medicare-program-contract-year-2027-policy-and-technical-changes-to-the-medicare-advantage-program

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The word "coverage" occurs 726 times, but I don't see the words LCD or NCD this year. Prior Authorization 17 times, denial 3 times.  Artificial intelligence, twice.

The request for information on "Future Directions in Medicare Advantage" starts on inspection copy page 6-11.  

Comment to January 26, 2026.

Big News: FDA to Down-Classify Many Companion Diagnostics as Class II (510k)

Last year, when FDA was sparring with stakeholders and courts over its LDT regulations, FDA promised to downclassify many types of diagnostics from Class III to Class II.   They went radio-silent from April to November, but now, the regulation is in print.

This is big news because it changes the landscape of how hard it is to get an FDA label as a companion diagnostic.  It also means that new ranges of tests will qualify for Medicare benefits.  NCD 90.2, for NGS testing in cancer, automatically covers NGS tests that are "cleared or approved" as CDx.   And sole-source tests (run from one lab) are eligible for ADLT pricing rules if they are "cleared or approved."   Now the range of "cleared" tests will be larger.

See an early essay at Linked In by Karin Hughes PhD here.  By Lawrence Worden here.  At Genomeweb here.  Kahles et al. review EU and US IVD regulations - prior to this FDA change - here.

See the Fed Reg regulation proposal here.  Comment in 60 days until January 26, 2026.

The rule runs 14 pages and covers many considerations and details.  The regulation for 510K aka Class II CDx will be at 21 CFR 866.6075, as “Nucleic Acid-Based Test Systems for Use with a Corresponding Approved Oncology Therapeutic Product.”  Within the 14-page publication, the actual regulation at 21 CFR will be about 680 words long (two full columns of the Federal Register).


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AI CORNER

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FDA Down-Classifies 
Key Oncology Companion Diagnostics:
A Policy-Level Summary

In a significant regulatory shift, FDA has proposed reclassifying a cluster of oncology companion diagnostics (CDx) and CDx-adjacent molecular tests—from Class III (PMA) to Class II with special controls. The 14-page notice marks FDA’s first broad structural change to CDx oversight in more than a decade and reflects the agency’s conclusion that these technologies are now mature, well-characterized, and manageable within the 510(k) framework.

Rationale for Reclassification

FDA’s justification rests on two main pillars:

1. A Large, Stable PMA Evidence Base

FDA points to 17 prior PMA approvals and a panel-track supplement covering tests such as NGS panels, PCR hotspot assays, MSI/LOH signatures, and gene-specific mutation assays. Across these submissions, the agency notes:

  • Highly consistent technology (PCR and NGS platforms with known performance boundaries).

  • Longstanding and predictable risk modes.

  • No unique or recurring post-market safety events.

  • Extensive analytic validation data accumulated over more than a decade.

In effect, FDA signals that this body of PMA experience now functions as the predicate scientific foundation for safe 510(k) benchmarking.

2. Technological Maturity and Standardized Methods

The agency emphasizes that these oncology molecular devices no longer present the novelty or uncertainty that once justified PMA status. Their design, specimen types, analytic characteristics, and error profiles are sufficiently well understood that FDA can now define the controls needed to mitigate risks without PMA-level scrutiny.

The agency also implicitly acknowledges that analytic performance expectations for CDx have converged across platforms, making differentiated regulatory treatment (PMA vs. 510(k)) less scientifically justified than it once appeared.

Special Controls Framework

FDA proposes a structured set of special controls that anchor the new Class II classification. These include:

  • Analytic validity requirements: Defined performance characteristics for accuracy, precision, LoD, reportable range, reference materials, and quality system parameters.

  • Clinical validity expectations: A requirement that sponsors demonstrate the test’s ability to identify the biomarker for which the associated therapeutic product is indicated.

  • Design and labeling requirements: Clear statements on intended use, limitations, specimen types, cutoff justification, and the relationship between biomarker detection and associated therapies.

  • Quality system-oriented controls: Ensuring calibration, reagent stability, and software verification meet standards previously demonstrated in PMAs.

  • Post-market controls where appropriate, although FDA explicitly states that historical PMA experience shows minimal adverse trends.

Importantly, these special controls are structured such that substantial equivalence to a well-characterized archetype is possible, eliminating the need for clinical trials for each new test if analytic comparability is demonstrated.

FDA’s Regulatory Method: A Retrospective Meta-Analysis of PMAs

The agency’s method is unusually transparent: it explicitly “looks back” across the entire set of oncology CDx PMAs, extracts shared risk profiles, and evaluates the sufficiency of accumulated scientific knowledge. This retrospective analysis provides the risk-benefit justification required under the statute’s reclassification provisions (including the six-year rule for PMA vintage).

In short, FDA is codifying what many regulators have long concluded informally—that these tests behave like a well-bounded technological family, and that PMA is no longer proportionate to risk.

Summary of the Actual Regulatory Text (Final Pages)

In the final codified section, FDA formally:

  1. Amends the classification regulations to place these oncology CDx molecular assays into Class II.

  2. Defines the device type as tests intended to detect specified genetic alterations for the purpose of selecting patients for targeted therapies.

  3. Lists the special controls, which function as binding performance, design, labeling, and verification requirements necessary for reasonable assurance of safety and effectiveness.

  4. Establishes that future devices in this category will follow the 510(k) pathway, provided they meet the special controls and demonstrate substantial equivalence.

This codified amendment is concise—essentially a legal wrapper around the analytic and risk-based reasoning laid out in the earlier narrative. But its practical impact is substantial: it opens a 510(k) pathway for a major class of oncology molecular diagnostics that, until now, were locked into PMA.

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With this change, how does this future FDA rule and method for CDx compare to the current recently revised European union rule and method for CDx? Would you say this change brings the two regimes into closer alignment, or would you say the alignment WAS close, and now the FDA is pulling away? Asking because of the harmonization thing.

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Here is a more concise, paragraph-style summary that preserves the key policy and practical points.


Concise Practical Comparison: FDA’s New CDx Pathway vs. IVDR

Under the EU IVDR, all companion diagnostics are locked into Class C, requiring a full technical file, Notified Body review, and a mandatory EMA (or national authority) consultation on the drug–test linkage. In practice, this produces long, multi-step reviews often running 12–24 months, driven partly by Notified Body capacity constraints. Costs are substantial: NB technical-file reviews, EMA consultation fees, and heavy internal preparation. Change control also remains strict; many modifications trigger new formal reviews. IVDR has therefore become a high-friction, high-burden system for CDx, even when the underlying assay technology is mature.

Historically, the FDA PMA pathway for oncology CDx was similarly burdensome: sponsors routinely submitted massive analytic and clinical datasets, endured multi-year PMA cycles, and managed ongoing PMA supplement obligations. The process could be exacting and expensive, with user fees in the hundreds of thousands of dollars and multi-year internal program costs.

The new FDA proposal fundamentally changes this equation for nucleic-acid based oncology CDx. After reviewing 17 PMAs and a decade of experience, FDA concludes that these technologies are now well understood, with risks fully characterizable through special controls. As a result, these CDx will move from Class III (PMA) to Class II (510(k)). The required evidence—robust analytical validation and a clear demonstration of clinical relevance—remains rigorous, but the submission is now structured against a defined regulatory template with narrower debates than PMA. User fees fall dramatically, and review timelines align with the 90-day 510(k) process, even if oncology CDx will receive close scrutiny.

Practically, this means that for follow-on EGFR, BRAF, MSI, LOH, or similar oncology NAAT/NGS CDx, the U.S. will become materially faster, cheaper, and more predictable than Europe. The scientific expectations of FDA and IVDR remain broadly aligned—both still require strong analytical and clinical performance, drug-test linkage, and clear labeling—but the operational burden diverges sharply. IVDR continues to function as a high-cost, multi-agency process; FDA is reclassifying mature CDx technology into a streamlined, mid-tier regulatory track.

The net effect is that scientific harmonization persists, but regulatory workload is no longer harmonized. FDA’s move aligns the evidence standards but pulls away from Europe in efficiency, creating a lighter U.S. pathway for many oncology CDx than the IVDR can presently offer.

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Sections (iii) and (iv) at the end of the rule seem to require any CLAIMS FOR THE DIAGNOSTIC LABEL to match to SIMILAR CLAIMS ON THE DRUG LABEL.   Let's say I investigate GENE A, which the biopharma sponsor declined to study.  I find 20% of patients have GENE A and they have 0% chance of drug response.  I go to FDA with my data, my claim, and my check for 510K review.  But FDA won't pass my test unless the FDA drug label also discusses GENE A and its link to drug failure.  The Biopharma is disinterested in this labeling update, as it says that it sees some problem with the data

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Here is a clear, expert-level explanation of the regulatory tension you’ve identified, and why it is not just theoretical—it is built into the structure of the new rule. This can go directly on your blog.


FDA’s New Rule Creates a Required Link Between Test Claims and Drug Labeling — and That Creates a Real-World Stalemate Scenario

The FDA special controls for the new Class II oncology test category (sections (iii) and (iv)) impose a strict alignment requirement:

  • Any clinical claim made by the test about predicted drug benefit, lack of benefit, or risk must map directly to language already present in the FDA-approved drug label.

  • The test manufacturer may not imply new drug-response information that is not already articulated in the drug labeling.

  • The test’s labeling cannot exceed, reinterpret, or contradict the drug’s own efficacy or risk information.

This means, functionally:

The test’s claims about drug response must “foot to” the drug’s label; the drug’s label becomes the limiting reagent for the test’s claims.

This is exactly the issue you are raising in the hypothetical scenario.


The Hypothetical You Gave: Why It Raises a Regulatory Collision

Scenario

You develop a test for GENE A.
You have strong evidence:

  • GENE A → 0% response to Drug ABC

  • Non-GENE A → 50% response

You apply for 510(k) clearance for your GENE A test as a drug-benefit predictor (not essential, but providing clinically meaningful information about drug benefit).

Problem

The Drug ABC label does not discuss GENE A at all.
Drug ABC’s sponsor (Big Pharma) has no interest in introducing such a biomarker, because it narrows the eligible market.
The label is silent.

Under the new FDA rule

Your test claims cannot exceed the information in the drug label.
Since the drug label does not mention GENE A, FDA will not allow you to make any drug-benefit claims—or even cautious “strongly associated” language—about Drug ABC in your test labeling.

In other words:

You cannot get labeling-level recognition of your GENE A → no benefit finding unless the drug manufacturer cooperates.

And the drug manufacturer has no incentive.


Will this create face-offs or stalemates?

In practical terms: yes, and in some cases it will block clearance.

This is the same structural bottleneck that has existed for true companion diagnostics for 15 years, but now it is extended to the newly created “non-essential but drug-informative” tests.

Why it’s a stalemate:

  1. The test manufacturer needs the drug label to say something—anything—about the biomarker.
    Without that, FDA cannot allow drug-response language in the test’s labeling.

  2. The drug manufacturer may strongly prefer silence.
    Adding biomarker-negative non-responders to the drug label shrinks the indicated population, invites payer restrictions, and may trigger postmarket regulatory requirements (analytic validity, postmarketing studies, REMS-like scrutiny).

  3. FDA cannot compel the drug sponsor to update labeling based on an IVD sponsor’s evidence—unless FDA reopens the drug application, which drug sponsors fiercely resist.

  4. Therefore, the IVD sponsor is stuck:
    The test is scientifically actionable but regulatorily ineligible to make the clinically useful claim.

This has happened before under PMA, and now becomes relevant for Class II / 510(k) tests as well.


The deeper regulatory logic: FDA is avoiding the “shadow CDx” problem

FDA’s concern is that a test could effectively redefine a drug’s benefit–risk profile without the drug sponsor ever submitting supportive data.
Hence the rule:

If the test says something about drug benefit or risk,
the drug label must already say it.

This is meant to:

  • Prevent IVDs from implicitly narrowing drug indications

  • Prevent “off-label drug labeling by proxy”

  • Keep drug–IVD biological claims inside the drug’s regulatory authorization

  • Avoid contradictory or clinically destabilizing claims

But it creates the regulatory stalemate you described.


So what will happen in real life?

1. Some scientifically valid tests will be blocked from meaningful labeling.

Tests could still be cleared as purely analytical devices,
but without any mention of drug response.
This neuters commercial utility.

2. Some test sponsors will need to negotiate with pharma.

This becomes a business-development negotiation, not a scientific one.
Pharma may demand:

  • Co-development agreements

  • Exclusivity

  • Shared IP

  • Favorable economics

  • Or simply refuse

3. FDA may see industry pressure to define a path for evidence-based third-party biomarker claims

—but historically FDA has been extremely reluctant to create such a pathway.

4. In oncology, where independent prognostic markers are common, this could chill innovation

unless the test-maker positions the assay as, say:

  • a prognostic test,

  • a stratification biomarker,

  • a therapy-agnostic classifier,
    but not as a drug-benefit predictor, even if scientifically true.

This undermines clinical reality but aligns with FDA’s legal constraints.


Bottom-line sentence for your blog

The new Class II/CDx-adjacent category still hardwires the rule that test claims about drug benefit or risk must map exactly to the drug’s FDA labeling. As a result, test makers can discover real drug-response markers—but unless the drug sponsor cooperates and updates its own label, FDA will not allow the test to make those claims. This creates a structural stalemate in cases where pharma has no incentive to acknowledge biomarker-negative non-responders.


If you want, I can extend this into a short sidebar on historical precedents (KRAS, UGT1A1, CYP2D6, PD-L1) where FDA faced exactly this cross-pressure.

Sidebar: Historical Precedents for the “Labeling Stalemate” Problem

FDA has run into this drug–test alignment conflict before. A few examples illustrate the pattern:

KRAS and anti-EGFR therapy (circa 2008–2012)

Independent academic groups showed that KRAS-mutant colorectal cancer patients had essentially 0% response to cetuximab or panitumumab.
For years, FDA could not allow IVD manufacturers to make this claim because the drug labels had not yet been updated.
Only after strong clinical consensus—and eventually cooperation from drug sponsors—did FDA revise the labels and allow KRAS testing to be formally recognized.

UGT1A1 & irinotecan toxicity

Robust data linked UGT1A1*28 genotype to heightened neutropenia risk.
Many labs developed tests, but IVDs could not claim drug-related risk until the irinotecan label incorporated genotype-specific dosing language.
Some assay submissions were effectively stalled until the drug label caught up.

CYP2D6 & tamoxifen metabolism

By 2009, dozens of studies linked CYP2D6 variants to altered tamoxifen activation.
But FDA never incorporated CYP2D6 into the tamoxifen label, citing inconsistent data, so no IVD could claim predictive information for tamoxifen efficacy even though many clinicians used the information informally.
This remains a canonical example of a real biomarker that FDA kept out of test labeling because it was absent from drug labeling.

PD-L1 assays

PD-L1 is the opposite scenario: the drug sponsors wanted the biomarker in the label.
Because pharma cooperated, multiple PD-L1 assays moved smoothly through PMA with explicit drug-linked claims.
This underscores that drug-sponsor alignment, not analytical science, often determines whether a biomarker becomes “real” in FDA’s regulatory universe.

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KRAS and anti-EGFR therapy (what actually happened)

The KRAS non-responder finding did not originate from diagnostic companies. It emerged when investigators performed retrospective analyses of banked samples from large cetuximab/panitumumab trials. These academic groups—working outside the IVD industry—showed that KRAS-mutant metastatic colorectal cancer patients had virtually zero likelihood of benefit.

For several years, however, the drug labels did not yet include KRAS, even though the science was increasingly definitive. During that interval, no diagnostic manufacturer could obtain FDA-recognized drug-response labeling, even if their KRAS assay was analytically excellent.

Once EMA and oncology societies (ASCO/ESMO) endorsed KRAS as a true “negative predictor” and the drug sponsors cooperated in revising labeling, FDA updated the cetuximab/panitumumab labels—and only then could IVDs claim KRAS as an anti-EGFR non-responder marker.

KRAS is the archetype of a biomarker discovered academically that remained “invisible” in FDA IVD labeling until the corresponding drug label was amended.


If you’d like, I can similarly refine UGT1A1 and CYP2D6 to emphasize where the science came from (usually academia and cooperative groups, not diagnostics firms) to make the sidebar fully precise.

You said:
The academics would have even less time and money to get a generic KRAS test approved, or pursue the multiple device-drug regulatory changes with small armies of regulatory experts and lawayers.
ChatGPT said:

Exactly — and that point deserves to be made explicitly, because it exposes the structural asymmetry baked into FDA’s “test labeling must match drug labeling” rule.

Here is a clean, polished paragraph you can drop directly into your blog to make this clear:


Why academics cannot fix this problem

In cases like KRAS, UGT1A1, or similar biomarkers discovered through retrospective analyses of banked biospecimens, the scientists who discover the predictive effect have no realistic path to turning that discovery into FDA-recognized test claims. Academic groups lack the multi-million-dollar budgets, regulatory lawyers, full-time submissions teams, and multi-year program management needed to pursue:

  • a stand-alone IVD submission (even now a 510(k) with substantial special-controls burden),

  • a labeling change to a drug they do not own, and

  • simultaneous coordination across CDRH and the drug review center.

Since FDA will not allow a test to make drug-response claims unless the drug’s own labeling speaks to the biomarker, academics are structurally excluded. They cannot initiate drug-label revisions; they cannot file supplements for a biologic they do not sponsor; and they cannot force a pharmaceutical company to acknowledge a biomarker that shrinks its indicated population.

Thus, the very parties who might generate the strongest biomarker evidence (academic cooperative groups) are the least able to convert that evidence into regulated drug-linked test claims.
The system functionally depends on the drug sponsor’s willingness to take on the regulatory burden — and when that willingness is absent, the evidence cannot migrate into FDA-recognized IVD labeling.


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See a deep-dive sidebar about EU vs FDA

https://brucedocumentblog.blogspot.com/2025/11/cdx-usa-vs-eu-and-changes.html