AMA Genomic Workgroups Continue (A: Dec 6, Jan 8; B: Dec 18, Jan 23)

The AMA is in its third year of running publicly available workgroups that plan consensus code revisions for genomic tests, such as hereditary disease panels.   The AMA workgroups hold meetings and discussions, and periodically, these are open to the public to listen in, and then join a Q&A session.

See an AMA webpage which is updated on a rolling basis:

 https://www.ama-assn.org/about/cpt-editorial-panel/cpt-workgroups

Currently, Workgroup A is looking at recessive hereditary disease testing (both core panels, like CFTR and SMN, and large panels).  Workgroup B is looking at cancer hereditary panels, mostly dominant genes (both limited Lynch panels, like 81435, and large multi-cancer panels).

I've clipped the current registration opportunities below.

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Upcoming calls (all times are Central)

Subgroup A

Dec. 6, 2023: 6-7:30 p.m.

• Register now

Jan. 8, 2024: 5-6:30 p.m.

• Register now

Subgroup B

Dec. 18, 2023: 6:30-8 p.m.

• Register now

Jan. 23, 2024: 6:30-8 p.m.

• Register now

ACLA Comment to FDA Features...MolDx!

ACLA announced that it has submitted a detailed, 107-page comment letter to the FDA, in response to the FDA's proposal to regulate lab developed tests. Here.

At several points the comment extensively discusses and highlights MolDx.  Here they are: 

IN THE BODY OF THE LETTER

The clinical validity of tests is also closely scrutinized by both public and private payers.  For  example,  the  Molecular  Diagnostic  Program  (MolDX)  provides  Medicare  coverage  for  molecular  diagnostic tests, including LDTs, only once those tests have demonstrated analytical validity, clinical  validity and clinical utility.  To obtain coverage, laboratories must submit dossiers with scientific  information  to  demonstrate  these  standards  and  the  requirements  of  the  specific  coverage  determination are met, and those dossiers are reviewed by unbiased subject matter experts.  The  MolDX  program  has  been  adopted  in  28  states  and  additional  US  territories,  and  according  to  MolDX, most molecular labs in the United States operate within its jurisdiction. MolDX reviews over  1,500 tests per year, and it has reviewed approximately 20,000 tests, a vast majority of which are  LDTs, to date since the program was established in 2011....   

Accordingly, it is simply false to refer to LDTs as unregulated, inadequately regulated, or  unscrutinized.  High-complexity laboratories are subject to multi-layered regulation, and individual  LDTs are scrutinized by federal regulatory regimes (CLIA), state regulatory regimes (state clinical  laboratory laws), accrediting organizations (e.g., CAP), proficiency testing entities, federal coverage  programs, private payers, and individual clinicians in search of the best care for their patients.   

IN THE "ALTERNATE IDEAS" SECTION

FDA  could  recognize  approvals  by  New  York  State  and  coverage  decisions  by  MolDX  as  clearances and approvals of LDTs for purposes of device regulation to reduce, but not eliminate, the  net harm of the rule.  

As detailed above, both of these programs review LDTs for their analytical and  clinical validity based on detailed technical submissions.  Accordingly, FDA could reduce, but not  eliminate, net harm from the rule by recognizing their decisions as satisfying the FDA requirement  for clearance or approval by exercising enforcement discretion for tests that have gone through such  programs, or, at minimum, structure an expedited approval/clearance pathway that would alleviate  the burden of FDA re-review of such tests.  Likewise, with respect to LDT clinical trial assays that  New  York  State  permits  to  be  used  for  clinical  management  without  prior  approval,  FDA  could  reduce the net harm of the rule by continuing enforcement discretion with respect to such clinical  trial assays.  

  

MolDx Covers Head and Neck MRD Test - Based on Circulating HPV DNA

MolDx has granted coverage under its "Minimal Residual Disease" LCD, for monitoring head and neck cancer.

There's a twist.  Most MRD tests are based on the return of, or disappearance of, circulating tumor DNA.   The NAVDX test from NAVERIS is based instead on detection of tumor-modified HPV DNA in the circulation.

See press release at Biospace:

https://www.biospace.com/article/releases/naveris-receives-medicare-coverage-for-navdx-test/

There's more detail in a subscription article at Genomeweb/Precision Medicine Online:

https://www.precisionmedicineonline.com/precision-oncology/naveris-optimistic-about-hpv-liquid-biopsy-test-uptake-after-medicare-coverage

I confirmed that NAVDX is listed as "covered" on the DEX registry run by Palmetto (app.dexzcodes.com). No price is listed, but the company has a not-yet-nationally-priced PLA code.  Here's the DEX description. Note, it's based on droplet digital PCR.  

DEX 

Oncology (oropharyngeal), cell-free DNA, droplet digital PCR to profile the fragmentation pattern of tumor tissue modified viral (TTMV) HPV DNA using 17 DNA biomarkers, weighted fragment size distribution algorithmic analysis, whole blood, algorithm reported as a prognostic TTMV risk score for cancer recurrence. (NavDx(r), Naveris Inc.) The intended use of the test is for monitoring patients with previously diagnosed HPV-driven head and neck cancers for recurrent and or residual HPV-driven oropharyngeal cancer.

Pricing Nerd Note

Code 0356U was just finalized as a 2024 gapfill code by CMS.  (Here) . The AMA PLA code text is, Oncology (oropharyngeal), evaluation of 17 DNA biomarkers using droplet digital PCR (ddPCR), cell-free DNA, algorithm reported as a prognostic risk score for cancer recurrence.

Since the code 0356U is "NOT" yet price on a national fee schedule, it must have a locally set price (until 1/1/2025) as a covered test.  So I'm surprised its price isn't on the DEX database page, which normally does list the price for all covered tests which are not paid on a fee schedule.

According to my notes from the summer lab pricing meetings at CMS, there was no presentation on 0356U in June at the public meeting, and the expert panel in July briefly noted the code and quickly recommended "gapfill."  

Geography

According to its press release, Naveris is based in Massachusetts and North Carolina.  The North Carolina entity may be, to take advantage of the MolDx system, and the press release specifies it got MOLDX coverage (North Carolina) not NGS MAC coverage (Mass.)  Data for 2022 shows that NGS MAC rarely pays for genomic tests unless they are FDA-approved tests covered by an NCD (here).

Funding

Naveris raised $51M in 2022, here.

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ddPCR - Other

Another commercial digital PCR test is Oncocyte's liquid biopsy kidney transplant test, here.

Head and Neck- Other
0356U (plasma, HPV, head and neck cancer recurrence) is not to be confused with 0296U, Viome, saliva, HPV, mRNA, also for head and neck cancer detection, $1755.  

ACLA Issues 107-Page Comment Against FDA Regulation of LDTs

The ACLA issued a 107-page comment letter that urges the FDA to drop its present proposal to rapidly regulate lab developed tests usings its 1976 medical device regulation.

See the press release here:

https://www.acla.com/fda-proposed-rule-to-regulate-ldts-as-medical-devices-would-slow-development-of-critical-lab-tests-and-should-be-withdrawn-acla-urges/

See the comment letter here:

https://www.acla.com/aclas-comments-on-fdas-proposed-regulation-of-laboratory-developed-tests-as-medical-devices/

The document kicks off with a four-page, 2500 word executive summary.  The rule should be withdrawn for multiple policy and legal reasons.  First, it would be significantly worse for patients.  Second, the proposal profoundly misunderstands or mischaracterizes the lab industry ("based on flimsy and inaccurate data.") Third, the balance of costs and benefits is badly flawed.  Fourth, the proposal is not legal; lab services are not "devices."  While these seem enough to sink the rule, ACLA closes with some input on alternatives.

The report  concludes with a 26-page analysis of the flawed cost-benefit analysis by an economist. See an AI summary of those 26 pages, here.

The report mentions both NY State and MOLDX as efficient review processes, unrelated to the strangeness of 1976 device law, that validate the accuracy of LDT tests.  ACLA notes that MolDx has validated some 20,000 tests.  See MolDx paragraphs extracted here.

AI Corner

I provide Chat GPT-4 and Claude.AI summaries of the 107 page document in a side bar, here:

https://brucedocumentblog.blogspot.com/2023/12/ai-corner-acla-fda-ldt-comment.html

Chat GPT-4 also provided a video script version:

https://brucedocumentblog.blogspot.com/2023/12/extra-ai-corner-video-script-about.html

FDA, Multi-Cancer Screening, and Mortality? Consider Three Additional Points

 As we move towards an era of blood-based multi-cancer screening, there have been arguments that adoption must follow overall mortality benefits used as an endpoint.   This arose in the FDA's advisory panel on the topic November 29.   For that, see the FDA's meeting web page here, and see a pre-meeting essay by Mullen & Gibbs here.   

The FDA panel was  big deal in the MCED industry, but didn't get much other press.  I added some materials like an auto-transcript and auto-summary to my blog about the meeting (here, look for keyword, Update November 30).

With regard to the FDA advisory board, much discussion of the role of mortality or overall survival as an outcome variable.   To my mind, a lot of the discussion was confused, perhaps caused by the FDA's scanty briefing materials (noted by Mullen, link above).

I think there are three critical ways of thinking about overall survival.

First, overall survival is extremely difficult to show.  People are being screened, they have no symptoms, and their overall survival  is many decades!  And any one, or even several, causes of death by cancer is a tiny widget of all  causes of death, and, for any cancer, at best, MCED will only prevent some of the deaths (like any cancer screening method).  The US has about 3.5M deaths per year.  Of those, deaths from pancreatic cancer are about 50,000, deaths from ovarian cancer, 13,000.  So even if you (incredibly) halved the death rate from pancreatic cancer and from ovarian cancer, it would be a truly minute  percentage of all deaths. 

Added to that, there is no perfect 50,000 patient, 10 year trial.  Such trials have high dropout and lost-to-follow-up rates, and numerous puzzling subgroup differences will accrue.   Let alone the fact, that 12 or 15 years from now, any particular medical technology will be several generations advanced from that used 15 years ago when the trial commenced.  In the real world, that definitive 50,000 patient 10 year trial is forever a mirage on the horizon.

So while you can, and would, show that you prevented 5000 ovarian cancer deaths, showing that you changed the mortality of millions of people is practically nearly impossible.

Second, would MCED just provide a stage-shift, picking up patients earlier without much impact on morbidity or survival?   Under this concern, a cancer with a five-year survival is picked up (per patient) two years earlier, and the result is merely seven-year survival from the same cancer.   This is a worthwhile topic of study, and people are well aware of that, but it is different from overall survival.  

Third, what about the risk the MCED causes increased mortality?  To me, this seems like a fairly distant hypothetical, but on principal, discussing it, or assuring that this does not occur, is logical.

In short, questions of overall survival and mortality can be important, but shouldn't be lumped into one bucket.  Each of the three scenarios listed above has its special ins-and-outs.  When the topic of overall survival is launched into the air, it's rare to see these components laid out concurrently.

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On the topic of RCT trial designs and how they calibrate unexpected harms, see a new review article Junqueira et al., 2023, J Clin Epidem, here.

Five Interesting Law Firm Essays about FDA LDT Proposals

In the last couple weeks, I ran across a number of interesting articles from law firms about the FDA proposal to regulate lab developed tests  - LDTs.

ESSAY #1

FDA LDT & LAW [Amin/Morrison & Foerster]

See also my blog November 10.  This is an essay by Stacy Amin, a former FDA attorney, now at Morrison & Foerster.  Amin's essay focuses on potential legal weaknesses of the FDA's proposal to regulate LDTs, and how the FDA has tried hard to preempt them rebuttals or justifications.

https://assets.contentstack.io/v3/assets/blt5775cc69c999c255/bltff2f4e0cf88d3aac/654d7a74b4ccc3040a594e45/231108-fda-lab-developed-test-rule.pdf

ESSAY #2

FDA SWOOPS INTO MCED [Mullen, Gibbs/Hyman Phelps Mcnamara]

This fits the "FDA LDT" topic because Mullen and Gibbs see the surprisingly sudden appearance of an FDA workshop on MCED, as tied to the FDA LDT rule. They note several oddities about the workshop.  Good essay. "FDA Stealthily Convenes Multi-Cancer Testing Panel Meeting."

• Here.

ESSAYS #3,4,5

The Mullen/MCED essay includes three track-backs to prior essays about the LDT rule.  

• The first simply introduces the FDA's land grab, by Cato, Mullen, Javitt on September 29.  
• Here.
• The second is a livelier style and opens with the headline, "Raises Many Questions, Provides Few Answers."  By Mullen, Javitt, Won, on October 6.
• Here.
• The third essay has the same topic as Stacy Amin's essay, the legal weaknesses of the FDA's position.  "Would a Final Rule Withstand Judicial Scrutiny?"  By Mullen, Javitt, et al, on November 2.
• Here.
• Comparing Amin's essay and Mullen's may be of interest to legal eagles.  See "AI Corner" on the comparison. 
• You can find the home page for HPM's law blog here.

My Two Cents

I liked Mullen's tie-in of the rushed MCED workshop with the FDA LDT proposal.  

In the same spirit, I'd add, the LDT proposal in September also has precedents in the FDA's June proposal to provide guidelines under which LDT cancer biomarkers could be considered equivalent to biomarkers used in clinical trials for a cancer drug.  I think is because FDA knew it planned to declare LDT's illegal, yet the FDA also knew, that sometimes drugs are approved prior to their companion diagnostic  That gap has hitherto been peacefully bridged by LDTs for the biomarker. 

I think the FDA LDT proposal also ties to FDA's flip-floppy and messy actions over the legality of PGx software recently (see Genomeweb here.)  FDA's new LDT proposal has no space for an FDA approved lab test coming from multiple locations (chemistry here, software there) as exists under some current CAP-CLIA models.

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AI Corner.

Chat GPT 4 provides us with its comparison of the Amin and the Mullen legal authority articles.  GPT4 finds the Amin essay is more even-handed towards the FDA, the Mullen essay more skeptical.  I read the Amin essay as also skeptical, but on review, I can see GPT-4's viewpoint that Amin carefully shows the FDA's rebuttals of each of its potential weaknesses.   (On first reading, I probably judged those rebuttals as scanty, amd thus I judged the listing of weaknesses as the main point.  In fact, as GPT-4 noted, the Amin essay is pretty  balanced, more than I  perceived at first reading).

Chat GPT 4:

The articles by Amin and Mullen offer differing perspectives on the FDA's proposed rule to regulate Laboratory Developed Tests (LDTs). Here is a comparison and contrast of their key points:

Similarities

Background of FDA’s Claim to Regulate LDTs: Both Amin and Mullen acknowledge the FDA’s historical claim that it has the legal authority to regulate LDTs as medical devices under the Federal Food Drug and Cosmetic Act (FD&C Act)​​​​.

Proposed Rule Details: Each article outlines the FDA's proposed rule that aims to regulate LDTs like other medical devices, noting the shift from the agency's historical enforcement discretion policy​​.

Differences

Legal Basis and Challenges:

Mullen: Mullen focuses on the questionable legal basis for the FDA’s authority to regulate LDTs, highlighting the challenges and counterarguments against the FDA’s jurisdiction. This includes the historical failure of FDA-supported legislative efforts to amend the FD&C Act and the potential major questions doctrine challenge​​.

Amin: Amin emphasizes the FDA's effort to establish its jurisdiction over LDTs through historical evidence, suggesting that the agency has always asserted its authority in this area. Amin also discusses the potential major questions doctrine but in the context of supporting the FDA's position​​.

Scope and Impact of FDA Regulation:

Mullen: Highlights the economic and political significance of the proposed rule, hinting at potential overreach by the FDA and the major costs involved, as well as the possibility of broad legal challenges​​.

Amin: Discusses the evolving nature of LDTs and the FDA's justification for the rule based on public health concerns, including issues with false positives/negatives and inadequate validation studies​​.

Administrative and Legal Precedents:

Mullen: Raises concerns about the FDA’s potential overestimation of its authority and underestimation of challenges, referencing specific legal cases and doctrines that might be used to challenge the rule​​.

Amin: Focuses on the legal and administrative procedures the FDA has undertaken to strengthen its rulemaking, discussing the role of the major-questions doctrine and the agency's attempt to preempt arguments against its authority​​.

Public and Industry Reaction:

Mullen: Suggests a likely strong reaction from stakeholders against the FDA’s rule, including potential lawsuits and challenges based on the rule's economic impact and legal basis​​.

Amin: Notes the historical resistance to FDA regulation of LDTs and the intricate efforts the FDA has made to counter these arguments, acknowledging the potential for significant legal battles but focusing more on the FDA's preparedness and justification for the rule​​.

Implications and Predictions:

Mullen: Predicts that the proposed rule will lead to significant legal battles and scrutinizes the FDA’s legal standing and the potential impact of recent Supreme Court decisions on the agency's regulatory authority​​.

Amin: Also anticipates significant litigation but frames it in the context of a historic moment for the FDA, underscoring the importance of the rulemaking and the potential for precedent-setting outcomes​​.

Conclusion

While both articles recognize the significance of the FDA's proposed rule on LDTs and its potential to invoke major legal challenges, Mullen's article is more critical of the FDA’s legal standing and potential overreach, whereas Amin's article places greater emphasis on the FDA's historical assertions of authority and the public health implications of the rule.

NEJM Op Ed Tackles CMS Efforts to Modernize Coverage Policy

 

A policy opinion piece in the November 30, 2023 NEJM, by Kadakia et al., provides a fairly detailed overview of coverage problems at CMS, and the historically unsuccessful attempts to navigate them with either Parallel Review or with CED (Coverage with Evidence Development).  

The authors describe the Trump administration MCIT proposal, its collision (and sinking) with Biden policymakers, and the still-in-progress CMS proposal to create "TCET," temporary coverage for emerging technologies.  A table compares MCIT and TCET. (Below, click to enlarge).  

click to enlarge

While having a somewhat guarded view of TCET - it relies on CED and strongly mirrors the Parallel Review flop in terms of the proposed process - the authors seem to conclude that at least CMS is moving forward with something (TCET).   

While the citation list in their short paper is brief, I'd add they might have cited the Dartmouth/Zeitler paper last year on CED (here).

NEJM includes a 9 minute podcast interview with coauthor Robert Yeh.  Yeh is director of the Center for Outcomes at Beth Israel.

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AI Corner

See AI summary of Kadakia, here.

New Alzheimer Codes Dominate Lab Agenda for AMA CPT Feb 2024

Registration is open for the February 1-3, 2024, AMA CPT Editorial Meeting in San Diego.  Registration may be both in person or virtual.  Here.

Lab codes were posted in mid-November for an early comment cycle (request Nov 20[*], comment Dec 4).  All other codes will be posted for comment December 1.

Here's the lab agenda link:

https://www.ama-assn.org/system/files/feb-2024-path-lab-mo-path-agenda.pdf

There's a bonanza of codes for Alzheimer's disease.  Note that the codes have "placeholder" codes at this time, which I'm also using here.

• Amyloid Protein in plasma or CSF (82XX0, 82XX1)
• 40 and 42
• Possibly, one code for plasma and one for CSF
• Usually measured as a pair for calculating the ratio, not the absolute amount
• Neurofilament light chain, blood (83XX0)
• Immunoassay Alzheimer Pathology (835XX)
• This is puzzling, possibly tau isoforms??
• Tau protein, Total (8X3XX)
• Tau protein, Phosphorylated (8X3X0)

Some of these tests are represented by PLA codes; the 80,000 series  codes will apply to any user.  The 80,000 series codes do not differentiated FDA and LDT versions.  Different brands or different isoforms may have different clinical accuracy.

There are several other lab codes: 815XX, brain tumor methylation; 8156X, kidney transplant gene expression; 81XX0, fetal recessive conditions (mentions XX28U, a PLA code).

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[*] As the agenda PDF indicates, someone wanting to review and comment on the code packetts for lab tests is directed to an AMA software portal [select the tab for Interested Party, not the tab for Applicant].  However, AMA locks out requests after 11/20/23, the lab request deadline.  This early request deadline ensures that any lab comments are available to internal subcommittees like MPAG and PCC.  

FDA Posts Agenda and Questions for MCED Panel November 29, 2023

On November 29, 2023, FDA is holding   ^held  an all-day panel on how the FDA should plan for trials and evaluations of MCED, multi cancer early detection.   

See original blog about the FDA workshop, by me, here.

• Update November 30 - I've put several different AI summaries of the 6-hour meeting in a Google doc, here.  
• This includes a 10-page bullet point summary by Otter.AI, my transcription program.
• Also short summaries by Claude.AI and Chat GPT4.  (And then, having got the 2 summaries, I asked them to compare the two summaries, too.) 
• See an excellent pre meeting article by Hyman Phelps here.

# # #

FDA has posted the agenda 9-5, the key questions, and an executive summary of 10 pages.

Find them all at the FDA, here, as "Event Materials," as well as the FDA's link to the streaming video for November 29.

AI CORNER

I've posted a Claude.ai summary of the ten-page executive summary written by FDA.

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The FDA is convening an advisory panel to get input on regulatory considerations for multi-cancer early detection (MCED) tests. These blood-based tests aim to screen for multiple cancers simultaneously in asymptomatic individuals. Currently no MCED tests have FDA authorization.

The panel will provide recommendations on study design to demonstrate clinical validity of MCED tests. This includes determining appropriate methods to confirm cancer status, diagnostic workup following positive results, and follow-up for negatives. The panel will also discuss use of tissue-of-origin assays to help localize tumors after initial MCED positive, as well as benefit-risk considerations.

Key questions for the panel include [for original FDA text see FDA link above]:

• Should MCED tests be evaluated by cancer type or in aggregate? What minimum sensitivity per cancer?
• How to evaluate MCED versus existing single cancer screening tests? Risk of patients foregoing current methods?
• Definition of "early detection"? Supportive data needed?
• Acceptable false positive rates? Should specificity be fixed to support low false positives?
• Harms of false negatives/positives? Diagnostic odyssey? Overdiagnosis/overtreatment?
• Use of stage shift as surrogate endpoint to show benefit?
• Role of real-world evidence for expanding cancer claims, validating rare cancers, demonstrating stage shift?

The panel's discussion and recommendations will inform the FDA's thinking on evaluation of safety and effectiveness for future MCED test marketing submissions.

NEJM AI: With Complex Cases, GPT-4 Usually Beats Humans (Eriksen et al.)

Last April, NEJM announced it would launch ai.NEJM, a new AI-focused journal (see coverage at MedPageToday).  At the time, it publishes Lee et al., a Microsoft-based article on "benefits, limits, risks of GPT-4" in medicine (here).

In today's news, NEJM publishes Erikesen et al, on the success rate of GPT-4 to "diagnose complex clinical cases."  Based on online data, the authors found GPT-4 (which was right 57% of the time) outperformed 99% of human readers.

See the article here:

https://onepub-media.nejmgroup-production.org/ai/media/000de933-9406-4f17-87b5-8e28c5cf5da7.pdf?

See open-access coverage at MobiHealthNews by Jessica Hagen here:

https://www.mobihealthnews.com/news/gpt-4-outperformed-9998-simulated-human-readers-diagnosing-complex-clinical-cases

Glitch: The article refers to supplemental information, including methods, but at least on the day of release, I couldn't find any at NEJM/

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Here's a summary from Claude.ai:

Eriksen et al. Use of GPT-4 to Diagnose Complex Clinical Cases. AI.NEJM.ORG.

In this perspective article published on ai.nejm.org, Eriksen and colleagues assessed the performance of the AI system GPT-4 in diagnosing complex real-world medical cases. They compared GPT-4's diagnostic accuracy to that of medical journal readers answering the same questions online.

The authors utilized 38 open-access clinical case challenges with comprehensive patient information and a multiple choice question on the diagnosis. They provided the cases to GPT-4 along with instructions to solve the case and select the most likely diagnosis. They ran GPT-4 on the cases multiple times to assess reproducibility.

GPT-4 correctly diagnosed 21.8 out of the 38 cases on average (57%), with very high reproducibility across runs. In comparison, simulated medical journal readers answering the same cases [based on 248,000 online answers) only diagnosed 13.7 cases correctly on average (36%). 

Based on distributions of reader answers, GPT-4 performed better than 99.98% of a simulated population of readers.

The authors conclude that GPT-4 performed surprisingly well on these complex real-world cases, even outperforming most medical journal readers. However, GPT-4 still missed almost half of diagnoses. More research is needed before considering clinical implementation of such AI systems. Specialized medical AI models, additional data sources beyond text, transparency of commercial models like GPT-4, and further evaluation of safety and validity are still required first. But these early findings indicate AI could become a powerful supportive tool for clinical diagnosis in the future.

MolDxOlogy - Payments for 2022 Category 1 Genomic Codes, by MAC

Header:  Of Category I genomic CPT codes, about 65% MolDx payments, 20% NGS MAC, 15% Novitas.  But, most NGS MAC payments represented Cologuard, an NCD-driven code.  Otherwise, NGS MAC had 4% of payments.

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In October, I posted some data on national CY2022 spending by CPT code (here).  

This week, in prior blogs, I broke out spending by MAC, first by 81479 miscellaneous code (here) and then by PLA code (here).

In this third and final blog for today, I show Category I CPT code spending by MAC (or MolDx).  I pulled cloud data for all 2022 payments on codes starting with (811, 812, 813, 814, 815).  

I then used an Excel pivot table to sum spending by "carrier" (usually "state") and rolled the results up by MAC and MAC system. The MAC policy systems are MolDx, Novitas/FCSO, and NGS MAC.

Results

Of $1.5B in genomic spending in this code set, 63% was via MolDx, 22% via NGS MAC, and 15% from Novitas/FCSO MACs.

However, I would rush to point out, nearly all the NGS MAC spending in this code set was driven by a single national decision (not local MAC LCDs).  It's the NCD for Exact Sciences Cologuard (state Wisconsin, payments $268M under NCD, code 81528).  Minus that, NGS MAC in all other states and codes altogether paid $64M for Category I codes (811xx etc) in 2022, or 4% of payments of $1.5B.

Click to enlarge.

Summary of 3 Posts

For the following data, I simplified each data set (e.g. dropping lines <$100K), so the numbers vary a tiny bit from exact nationwide numbers.

For Category I codes (811nn-815nn), payments were $1.4B, of which 63% MolDx, 22% NGS MAC, 15% Novitas MAC.   Excluding the NCD for Cologuard, which is close to $300M, NGS MAC payments fell to 4%.

For PLA codes, payments were about $330M of which 81% MolDx, and about 10% each to Novitas/FCSO and NGS MACs.  However, most of the 10% to NGS MACs can be accounted for by FMI payments driven by NCD 90.2 for FDA PMA NGS tests.

For 81479 miscellanous codes, payments were about $470M, of which 98% was paid by MolDx MACs.  90% of that, was via Noridian MAC.  81479 was the national highest-paid genomic CPT code.

Bonus

This fall, I used the Medicare coverage database to tally MAC Articles about genomic codes (811nn to 815nn).   There were 82 MolDx articles, 8 Novitas articles, and 4 NGS MAC articles.

 

MolDxOlogy - Payments for 2022 PLA Codes, by MAC

Header: 80% of PLA codes were paid via MolDx.  About 10% each for Novitas and NGS MAC, but the NGS MAC PLA payments were mostly NCD-driven payments for Foundation Medicine.

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In the previous blog, I looked at payments for Genomic Miscellaneous Code, 81479, by MAC - here.  I used the CMS cloud data archive for 2022 Part B payments - here.

In this blog, I pulled the CPT codes ending in "U" - the PLA codes - and sorted them in Excel for "Carrier" (usually a state), and sorted those into  the three  MACs for policies - the MolDx MACs, the NGS MACs, and the Novitas/FCSO MACs.

To save manual work, I deleted rows less than $100,000, leaving $330M of PLA payments (97% of the total).   Of this $330M, about $18M were paid out to diverse MACs (such as for a Cepheid IVD, 0241U), which I didn't try to parse by MAC.  

Of the $312M paid to specific MACs for PLA codes, I tallied $252M or 81% to MolDx MACs, and roughly $30M each to Novitas MACs and NGS MACs (about 9-10% each.)

Note, however, that much of the NGS MAC payments come from  PLA codes 0037U and 0239U, Foundation Medicine FDA CDx codes (FFPE and LBX, respectively) - these are controlled by an NCD, NCD 90.2, and are not discretionary payments under the judgment of the NGS MAC.   If you tallied NGS MAC payments NOT controlled by NCD 90.2, it would be very low.

Click to enlarge.

click to enlarge

I previously posted, in October, that national payments for PLA codes were highly concentrated, with the highest-paid codes mostly being FDA approved.  Just 3 of 500 PLA codes, had half the PLA payments.

MolDxOlogy: In 2022, MolDx Captured 98% of 81479 Payments

Header.  Genomic test spending under miscellaneous code 81479 was a third of 2022 Part B spending for Tier 1 lab codes at $470M.   98% was via MOLDX MACs.

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Back in October 2023, CMS released data for CY2022 Part B payments by CPT code.   (Payments by doctor or lab will be released in summer 2024).  See October blog here.  Molecular spending was about $1.5B for Tier 1 codes, another $340M for PLA codes.   In either code set, the top few codes garnered most of the spending.

I noted that about a third of Category I spending was Unlisted Code 81479.  For a client project, I've gone back to that data and analyzed 81479 spending in CY2022 by MAC.

I analyzed all the states with 81479 over $100K (I had 99.96% of 81479 payments.)  98.3% was in MolDx states, or about $462M of $470M.  More was spent on 81479 than all PLA codes together.  

Also for 81479, $7.5M was in Novitas (PA), and just $500K in NGS MAC states (specifically, Illinois).

70% of 81479 spending was in California (61% northern, 9% southern) and 13% was in Arizona.  

About 90% of 81479 spending was via the Noridian MAC.  

The table below can be clicked to view.

click to view

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81479 spending at MOLDX was paired with "Z codes," allowing granularity in claims processing. 

However, large amounts of molecular spending fall outside of PAMA and fall outside of public code data that can be used for academic and public health purposes.   For example, one cannot tally up how many Medicare patients had BRCA testing in 2022, if it is recoded as "81479."  (In contrast, you CAN tally up how many FFS patients had prostatectomies, colonoscopies, and so on).  

AMP Hosts FDA LDT Webinar: Monday November 27

 On Monday, November 27, 2 pm ET  11am PT, AMP will host a webinar on FDA LDT, the goal being "to stop this overreaching rule."  Hosts will be Dr Eric Konnick, chair of AMP professional relations, and Annie Scrimenti, Assoc. Director of Public Policy & Advocacy at AMP.

Here's AMP's 6 page PDF briefing on the rule:

https://amp.org/AMP/assets/File/advocacy/Summary%20FDA%20Proposed%20Rule.pdf?pass=75

Here's November 27 ZOOM registration:

https://us06web.zoom.us/webinar/register/WN_P-QgnfjISauUajGoGXP6Bg#/registration

AMP adds,

You can stop this overreaching rule from being finalized by submitting comments on how the proposed rulemaking will affect your ability to practice laboratory medicine and provide critical lifesaving tests to patients. Unique, individual and institutional comments telling the FDA why this rule is bad for patients, bad for medicine, and bad for innovation are critical.

AI Corner: Trying Out Anthropic "CLAUDE"

Since February, I've been a subscription user of Chat GPT.  With their recent management turmoil, I tried a similar competitor service, ANTHROPIC CLAUDE, in its free version.[*]   

I found CLAUDE did a good job of summarizing my recent detailed white paper on FDA proposal for LDTs (October white paper here.)  

In both ChatGPT and CLAUDE, you can now just click a "paperclip" button and upload a PDF.

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Here's the CLAUDE link (once you're registered): https://claude.ai/chats

Here's home for Anthropic, where I email-registered for CLAUDE: https://www.anthropic.com/product

Free Claude gives you 5-10 questions per 8 hours, I think.  $20/mo Claude gives you much higher bandwidth.

Here's the test:

 Please summarize in detail this complicated white paper about a new policy proposed by FDA for regulating laboratory tests [upload it]. I am the author of the white paper, and I would like to see how you summarize it. I expect a detailed summary to be in the area of 500 words long. Thank you.

ANTHROPIC CLAUDE:

Here is a 475-word detailed summary of the white paper about the FDA's proposed policy for regulating laboratory tests:

The white paper analyzes a new proposal released on September 29th, 2023 by the FDA to regulate laboratory-developed tests (LDTs). The proposal would phase out the FDA's enforcement discretion and subject LDTs, including those solely used within a single lab, to FDA oversight as medical devices. This would require LDTs to comply with requirements like registration, quality systems, premarket review pathways, and labeling rules.

The proposal lays out a 5-year timeline for phasing in compliance. However, the white paper author, Dr. Bruce Quinn, argues that the dramatic costs of compliance, estimated by FDA to be around $50 billion over the first 5 years, make the timeline wholly unrealistic and the proposal “simply impossible to execute.” The FDA also projects over $300 billion in benefits over 20 years, but the white paper contends these are based on speculative assumptions about LDT accuracy improvements.

The paper critiques how the high costs were obscured in the publicly released documents and summary. It analyzes the underlying FDA assumptions and calculations, including estimating over 200,000 regulatory expert-years and thousands of FDA reviewers would be needed in Years 3 and 4 alone to handle the influx of LDT applications. It compares this to the total yearly profits of less than $4 billion for LabCorp and Quest combined.

The white paper further examines the FDA's claimed legal authority to regulate LDTs as devices, noting this remains a disputed view. It contrasts the FDA arguments with analyses suggesting labs conducting testing may fall outside device definitions and commerce clause restrictions on federal power over intrastate activities.

In conclusion, the paper argues the proposed rule is essentially unworkable as written. It expects court challenges if finalized unchanged, as well as continued debate over the appropriateness and legality of FDA reaching into lab operations. But it suggests there may be alternative approaches, short of the complex VALID Act legislation, that could address FDA’s concerns on LDT claims and LDT accuracy without imposing such dramatic bureaucratic and financial burdens.

[*] Both ChatGPT and Anthropic Claude have good free versions, while a $20 subscription to either one gets you more bandwidth and priority when servers are overworked.