On October 15, 2026, MolDx announced it was canceling its draft non-coverage LCD for Prelude's DCISionRT. This follows recent announcements (1) first, the draft would be delayed and (2) and second, a CAC meeting 10/13 on the topic.
See message from CEO here.
I have updated my September 21 blog to keep the storyline in one place.
https://www.discoveriesinhealthpolicy.com/2026/09/when-does-moldx-change-its-mind-prelude.html
Bioreference acquisitioni by LabCorp features some carve-outs for 4Kscore behavior. Here's how it fared in recent Medicare Part B sales and in PAMA.
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In 2025, Part B sales for 81539 were $12.6M for 16,500 units.
In 2024, Part B sales for 81339 were $11.7M for 15,300 units.
In 2023, Part B sales for 81339 were $10.4M for 13,700 units.
In current PAMA price data, 81539 has a 2026 price of $760, but its PAMA target price falls to $532, a ($228) or 30% drop.
Interestingly 11 TINS of commercial insurers reported 81539 pricing to PAMA, so I thought CMS might have also issued granular PAMA survey data, but there is none.
Wholly unrelated data, CMS payments outbound to labs, showed 4 npi geting paid by CMS, but 99% of volume in 2024 paid from CMS to Bioreference (Opko Labs).
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Below find a Chat GPT and a CLAUDE review of the Labcorp-Bioreference acqiusition.
Each had the same prompt (350-400, use internet).
This is AI writing and should not be taken as ground truth. It can be taken as an example of current AI research and writing skills.
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Chat GPT
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OPKO acquired BioReference in 2015 through a stock transaction announced at $1.47 billion, but valued at approximately $950 million at closing after OPKO’s shares declined. The strategic ambition was clear: BioReference’s national sales and laboratory infrastructure would accelerate adoption of OPKO’s 4Kscore prostate cancer test and future diagnostics.
Eleven years later, that distribution strategy is effectively being handed to Labcorp. OPKO Health, Inc. (OPK)
After a pandemic booom, the post-pandemic reversal was severe. In third-quarter 2022, BioReference’s COVID PCR volume fell to approximately 200,000 tests from 2.2 million a year earlier.
OPKO’s diagnostics segment swung from $19.7 million in operating income to a $49.5 million loss. Management cut staffing and digital-health investment, revealing how difficult it was to resize the business after emergency testing demand evaporated. OPKO Health, Inc. (OPK)
Retrenchment became a sequence of sales. Labcorp bought clinical and women’s-health assets outside New York and New Jersey for $237.5 million in 2024. In 2025, Labcorp acquired oncology and related testing assets for $192.5 million upfront, with contingent consideration. OPKO presented the remaining regional laboratory -- and 4Kscore franchise -- as a more focused route to "sustainable profitability." OPKO Health, Inc. (OPK)
Recent investor disclosures show why that destination remained elusive. Diagnostics lost $18.3 million in fourth-quarter 2025 and $13 million in first-quarter 2026. Second-quarter 2026’s reported $4.8 million operating profit included an $18.1 million earnout benefit from the previous Labcorp sale. Subtracting that benefit leaves approximately $13.3 million of operating loss. Shrinking the footprint had reduced losses without establishing durable profitability. opko.com
Yet October’s proposed transaction carries substantial value: $722 million, plus up to $150 million contingent on 4Kscore revenue. The upfront price equals approximately 2.9 times Labcorp’s projected $250 million first-year revenue from the acquired business. That suggests Labcorp sees considerable value in the customer relationships, specialty testing and opportunities within its larger network. Closing remains subject to approvals. opko.com
The parallel with Labcorp’s $239 million acquisition of Invitae assets through bankruptcy in 2024 is instructive, although BioReference’s transaction today is a negotiated divestiture. My reading is that both illustrate the value of combining distinctive diagnostics with national operating scale. OPKO gains capital and a sharper biopharmaceutical focus; Labcorp gains assets it believes can perform better within its infrastructure. The original promise of broader access for 4Kscore survives—but with a different owner delivering it. Labcorp
CMS has released a final regulation on (mostly PRICE) transparency in coverage. See Fed Reg, see Press Release, Fact Sheet. Here, in this blog, see an AI summary.
Meanwhile, the House has posted HR 9393, a bill called Lower Costs, More Transparency Act.
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AI discusses.
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The new Transparency in Coverage final rule, announced October 5 and published October 6, improves the usability of health insurers’ price disclosures. CMS’s press release promises clearer information about both what insurance covers and what patients will pay. The operational changes, however, primarily concern price transparency.
The rule updates the 2020 framework for non-grandfathered group and individual health coverage. Insurers must produce smaller, more meaningful machine-readable files: consolidate in-network rates by provider network, remove implausible provider-service combinations, identify networks and insurance products more clearly, and expand available out-of-network payment data. New attestations strengthen accountability for accuracy. In-network and out-of-network files move from monthly to quarterly updates. Personalized cost-sharing information must also be available by telephone. Implementation is phased through 2027.
The business logic is straightforward: enormous, confusing files technically disclose prices without necessarily enabling useful comparisons. (That might be the goal of some stakeholders - block discovery.)
Better data should help employers negotiate, researchers analyze markets, and software developers build shopping tools. Whether patients actually switch providers—and whether prices fall—remains a separate question.
What about coverage transparency? The existing consumer-tool rules already require personalized deductible and cost-sharing information and notification of prerequisites such as prior authorization or step therapy. But they also expressly require a warning that a cost estimate does not guarantee benefits. The new telephone requirement expands access to this information; it does not turn an estimate into a binding coverage determination.
There is also a narrower, genuinely new disclosure: “taxonomy” files expose provider-specialty mappings used to exclude implausible rates, while utilization files identify actual reimbursed provider-service combinations. These illuminate aspects of payment operations, but do not establish a comprehensive public repository of medical-necessity criteria, investigational exclusions, or patient-specific coverage decisions.
Medicare's exclusion authorities - kicking you out of the program for 10 or 20 years - was previously handle by the legal eagles in the OIG.
With a quick announcement in the Federal Register, that exclusion can now also be handled by CMS staff, in the name of the Administrator (RFK/HHS).
Find more news here:
MEDPAC has a dozen short articles, usually two-pagers, on the different payment systems (one of which is Clin Lab Fee Schedule.)
It's says they're updated for 2026; I suppose most had little change from the last version.
Find them here:
https://www.medpac.gov/document-type/payment-basic/
We saw this LCD topic as Final in February from CGS* and in Draft from Wellpoint Federal, here it comes from Palmetto GBA in draft in October..
On October 1, Palmetto released for comment LCD DL40464, "Automated Detection and Quantification of Brain MRIs." The take-home lesson is simple:
Examples include ARIA detection and quantification (vascular and tissue abnormatlies in dementia therapy. Petrella 2026).
Obviously, the same principle could be applied to detection and quantification of features and properties of glass slides intead of MRI images.
Could AI-drafted pathology reports become something physicians actively want to use—as some surgeons came to love da Vinci robotics?
This white paper explores that possibility through surgeons’ experiences describing their enjoyment of robotic surgery.
Roche acquires Path AI, Agilent acquires Proscia. Tempus acquires PAIGE. In a carefully guided Chat GPT 6 essay, we try to figure out what it means and where we're going.
This is an AI generated report. It should not be taken as ground truth ,but as an example of currrent AI abilities to grasp, plan, and write multi-part essays.
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Access this white paper as a 15-page PDF here.
Two Presentations, Two Acquisitions, and the Future of Clinical Digital Pathology
Dr. Maria Wilson and the meetings described below are fictional. The demonstrations are a teaching device, not accounts of actual vendor presentations or comparative product testing. Company and product descriptions draw on the public sources linked throughout.
At 1:45 p.m., Dr. Maria Wilson, chair of a large academic pathology department, looks over her afternoon schedule.
The department is preparing to go digital. Scanners have been selected. Storage and networking are being arranged. But the software decision remains unsettled: what will the pathologists actually use, and how will it change their clinical work?
Representatives from PathAI and Proscia will each have thirty minutes. At five, Maria will discuss the proposals with five departmental leaders and two representatives of the Dean’s office.
She sends both vendors the same instruction:
“Please walk us through a prostate biopsy, a breast biopsy with immunostains, and a colon resection with multiple blocks and lymph nodes. Begin when the scanned slides become available. Finish when the pathologist signs the report.”
She adds one more request:
“Show us an ordinary working day, including the things that go wrong.”
We're in the run-up to Visions 2026, the annual digital pathology conference in San Diego this weekend. Find it here.
DPA has released 3 policy documents on AI and software-intensive reimbursement.
Find the new October Fask Force blog here.
Find the DPA CMS PFS comment letter here.
Find the DPA CMS OPPS comment letter here.
They're summarized individually then holistically below. (Chat GPT 6). For "Holistic," I stir into the mix their April 2026 blog about new initiatives, plans, and zeal re: reimbursement policy. DPA April.
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1. October blog — DPA Reimbursement Task Force
30-word summary
The DPA warns that Medicare’s proposed reclassification of diagnostic algorithms threatens payment predictability and laboratory billing, with implications for investment, commercialization, and access extending well beyond the nominal reimbursement rate.
The 14-day rule or Date of Service rule is generally unpopular with oncologists and cancer patients and societies. Here are some recent (2024) positions from ASCO, AMA, CAP.
The topic is found on page 22 of a 40 page summary document from AMA.
The topic is also found on pages 136-137 of the longer meeting handbook.
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2024 AMA Governing Council Report (40pp)
https://www.ama-assn.org/system/files/i24-omss-report-a.pdf
See page 22 of 40 (aka Item 18).
RESOLVED, that our American Medical Association actively lobby the federal government to readdress and change laboratory date of service rules under Medicare, e.g. the Medicare 14-Day Laboratory Date of Service Rule (Medicare 14-Day Rule), such that complex laboratory services performed on pathologic specimens collected from an inpatient hospital procedure be paid separately from inpatient bundled payments, consistent with Outpatient rules. (Directive to Take Action).
In headline news today, Agilent (market cap $50B) will acquire Proscia in a deal for $240M in cash. See news below.
I've had a number of blogs recently on strategies in digital pathology. Here's a lookback to a white paper I wrote in May 2026 comparing the digital pathology business strategies of Philips and Roche. It comprises two deep-dive reports by AI, one by Claude and one by Chat GPT. Find it here:
https://www.discoveriesinhealthpolicy.com/2026/05/can-ai-write-deep-strategic-business.html
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Guest Author: Chat GPT looks into the deal for us.
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Agilent’s planned acquisition of Proscia illustrates a broader contest in cancer diagnostics: who will supply the software connecting laboratory instruments, tissue images, and artificial intelligence? On October 13, 2026, Agilent announced an agreement to buy the digital pathology company for $240 million in cash, plus up to $30 million in performance milestones. Closing is expected early in Agilent’s fiscal 2027. Announcement here.
Agilent is a global supplier of laboratory instruments, reagents, software, and services, with fiscal 2025 revenue of $6.95 billion. Its pathology business includes Dako, the cancer diagnostics company acquired in 2012, and Biocare Medical, whose acquisition closed in June 2026. These businesses supply staining instruments and reagents that help laboratories identify biological markers in tissue. Proscia would extend that presence further into the digital work performed after slides are prepared. Agilent has already had a cooperative alliance with Proscia.
Philadelphia-based Proscia develops and supplies "Concentriq," a software platform for managing, viewing, and analyzing digitized pathology images. Scanners create the images; Concentriq connects them with laboratory systems, pathologists, and AI applications. According to Agilent, by means of Concentriq software, Proscia serves more than 4,000 laboratories, hospitals, and clinics, plus 16 of the 20 largest pharmaceutical companies. Its trailing annual revenue exceeded $18 million. The companies have already worked together under a distribution agreement dating to 2022. That distribution channel is now tightened into an acquisition.
The strategic logic is straightforward. Owning software used throughout a laboratory’s daily work could deepen Agilent’s customer relationships, generate recurring revenue, and create additional opportunities in pharmaceutical research and companion diagnostics. A platform connecting tissue preparation with image interpretation could also make it easier to develop and deploy quantitative biomarker tests. These are business opportunities, however, rather than demonstrated financial benefits of the acquisition.
The price reflects substantial expectations. Using $18 million as a reference, the upfront payment represents approximately 13.3 times annual sales; the actual multiple is lower because reported revenue exceeds that figure. Agilent describes Proscia as a growing, high-margin software business but provides no numerical growth, margin, or earnings targets in the announcement. Buyers are therefore being asked to assess the strategic potential with limited financial detail.
For Leica Biosystems, part of Danaher, the implications include both competition and cooperation. Proscia’s August 2026 FDA clearance included compatibility with Leica’s Aperio GT 450 DX scanner. Agilent could consequently gain software revenue from laboratories using Leica hardware. That makes preserving interoperability commercially important: supporting competing instruments can expand the software’s market. Roche likewise supports third-party algorithms through its Digital Pathology Open Environment, demonstrating that these competitive boundaries already overlap.
Tempus offers another comparison. The precision-medicine and AI company acquired Paige in August 2025, emphasizing its pathology images, technical expertise, and AI capabilities. Strategically, Tempus approached pathology from data and computational medicine; Agilent approaches it from laboratory infrastructure and diagnostics. Both transactions suggest that pathology software is becoming an important component of larger healthcare businesses.
For independent AI developers, larger platforms could offer broader distribution while gaining greater influence over commercial terms and customer access. (Compare: Cerner/Epic in EHRs).
For laboratories, the practical questions remain concrete: Will integration become easier? Will pathologists save time? Will new capabilities justify their cost? Agilent’s investment strengthens its ability to compete for that business; execution will determine the return.
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What's Interesting or Surprising about Agilent-Proscia?
Agilent is paying for a strategic position well ahead of current revenue. Proscia generates just over $18 million annually; the $240 million upfront price implies roughly 13 times sales, using $18 million as the reference. That revenue is only about 0.3% of Agilent’s annual revenue. The investment’s importance lies in what Proscia could enable across Agilent’s business. www.agilent.com
The central asset is the software pathologists work in—not simply an AI algorithm. Concentriq connects images, laboratory systems, people, and analytical applications. Strategically, owning that daily workspace could give Agilent influence over how numerous AI products reach customers. Its distribution relationship with Proscia since 2022 also means this follows several years of commercial experience together. www.agilent.com
Agilent could benefit when a laboratory buys a competitor’s scanner. Proscia’s FDA-cleared platform supports Leica’s Aperio GT 450 DX. That creates an unusual competitive relationship: Leica supplies the scanning hardware, while Agilent could supply the software used with its images. Preserving compatibility with rival equipment therefore has direct commercial value. www.globenewswire.com
The pharmaceutical footprint is striking for such a small company. Proscia serves 16 of the top 20 pharmaceutical companies, according to the announcement. That gives Agilent an established software presence in drug-development organizations—potentially valuable for biomarker research and companion diagnostics. However, customer reach alone does not reveal contract size or depth of adoption. www.agilent.com
The deal follows a much larger move by Roche into the same territory. Roche announced its PathAI acquisition in May for $750 million upfront, potentially $1.05 billion. Alongside Tempus–Paige, these transactions suggest a shift toward pathology software being owned by larger diagnostics and data businesses. An important strategic question is how those platforms will balance their parent companies’ priorities with the openness customers and independent AI developers value. www.roche.com
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Review of Deals
The Broader Picture: Eight Major Deals and Financings in Digital Pathology
Agilent’s purchase of Proscia joins a substantial wave of acquisitions, investment, and consolidation. Eight notable transactions from 2025–2026 illustrate how laboratory manufacturers, software companies, and investors are positioning themselves:
Agilent–Proscia: $240 million, plus up to $30 million in milestones. Announced October 13, 2026. Agilent agreed to acquire Proscia, the company that makes Concentriq, adding digital pathology software to its tissue-diagnostics portfolio. Announcement.
Roche–PathAI: $750 million upfront, potentially $1.05 billion. Announced May 7, 2026. Roche agreed to acquire PathAI, including its AISight image-management software, AI capabilities, and pharmaceutical research services. This would deepen Roche’s presence across laboratory workflow and computational diagnostics. Announcement.
Agilent–Biocare Medical: $950 million. Announced March 2026 and completed in June. This is an adjacent tissue-pathology acquisition: Biocare supplies staining instruments, antibodies, and reagents. Together, Biocare and Proscia would expand Agilent’s presence from slide preparation through digital review. Announcement; completion.
Grundium–Visiopharm: price undisclosed. Announced May 21, 2026. Finnish scanner manufacturer Grundium acquired Danish pathology AI and image-analysis company Visiopharm, combining slide digitization with quantitative tissue analysis and biomarker applications. Announcement.
Tempus–Paige: $81.25 million, predominantly in stock, plus assumed cloud commitments. Announced August 22, 2025. Tempus acquired Paige’s pathology AI technology and expertise, alongside a dataset of nearly seven million digitized slides with associated information. Announcement.
Evident–Pramana: price undisclosed. Completed August 27, 2025. Evident, the former Olympus microscopy business, acquired Pramana’s autonomous slide-scanning technology, strengthening its capabilities in automated image acquisition and quality control. Announcement.
Waiv, formerly Owkin Dx: $35 million Series A. Final closing announced April 24, 2026. Investors backed development and commercialization of AI-based oncology tests, including applications extracting biomarker and prognostic information from pathology images. Announcement.
Aiforia: €20 million venture-debt agreement. Announced July 31, 2026. European Investment Bank financing supports the Finnish pathology AI company’s product development and commercial expansion. Funding is available in tranches subject to milestones. Announcement.
The Latest Paige Development: Channel through Leica Aperio
On September 24, 2026, Leica Biosystems announced the addition of Tempus’s Paige PanCancer Detect and Paige Prostate products to its Aperio AI Store. PanCancer Detect identifies suspicious areas across more than 40 cancer types; the prostate suite supports detection, grading, quantification, and assessment of perineural invasion. The applications operate within Leica’s Aperio HALO AP software workflow, developed with Indica Labs. Leica announcement.
This is a useful example of cooperation across corporate boundaries: Tempus owns Paige, while Leica provides another distribution channel. But the announcement explicitly labels these offerings research use only, not for diagnostic or clinical use. It therefore illustrates both progress toward integrated pathology AI and the remaining distance to broadly deployable, FDA-authorized diagnostic and report-drafting systems.
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Review of Funding Events
These two funding deals bring the previous list to ten, and both fall within the past 12 months:
Waiv, formerly Owkin Dx — April 24, 2026: $35 million Series A financing. Initial investors OTB Ventures and Alpha Intelligence Capital were joined by CRB Health Tech and others. Waiv develops AI tests that extract biomarker and prognostic information from pathology images, including breast cancer risk assessment and colorectal cancer MSI screening. Funding supports development and commercial expansion. The $35 million is the completed round’s total, including its extension. Company announcement. waiv.com
Aiforia — July 31, 2026: €20 million venture-debt financing agreement with the European Investment Bank. The Finnish pathology AI company secured financing for image-analysis product development and international commercial expansion. This is debt financing, available in three tranches subject to revenue and other milestones, rather than a conventional VC equity round. EIB announcement. eib.org
My bias is that FDA-authorized systems that analyze slides and prepare draft reports before the pathologist opens the case will blow the roof off digital pathology’s growth—and that this opportunity remains underappreciated. The compelling product is a substantially completed first pass: findings, measurements, supporting images, and a report ready for physician review. Agilent’s acquisition of Proscia deserves attention through that lens.
Radiology offers an early indication of the potential. DeepHealth’s FDA-cleared breast ultrasound application analyzes images and generates reports for physician review. The company reports a 37% reduction in interpretation time in its FDA-submitted reader study—close to 40%. That is a result for a defined examination and study setting, rather than a reduction in the radiologist’s entire workday, but its commercial significance is considerable. DeepHealth announcement.
FDA is also investing in the methods needed to evaluate these products. A $1.29 million research contract awarded to Cognita Imaging will test approaches to evaluating AI-generated radiology reports across approximately one million examinations, with radiologists reviewing important discrepancies. This is regulatory-science research, not authorization of a product, but it addresses an essential bottleneck: how to assess the quality of an entire generated report at scale. Contract announcement.
Where does Agilent fit? Its proposed $240 million purchase of Proscia, plus potential milestones, combines a large diagnostics manufacturer with software positioned inside the pathologist’s workflow. Agilent brings laboratory relationships, tissue-diagnostics products, and experience commercializing regulated tests. Proscia brings the infrastructure connecting slides, case information, analytical applications, and the physician’s workstation. The strategic inference is that this combination could support development and distribution of a report-drafting product. Acquisition announcement.
Proscia’s recent product descriptions make that possibility concrete. Its fifth-generation Concentriq architecture connects images with clinical context, runs relevant analyses automatically, and prepares work for the expert. Its launch announcement describes assembling reportable findings for pathologist confirmation. Those capabilities are relevant building blocks for a case that arrives already analyzed and partially documented. Proscia’s architecture explanation.
The regulatory gap is equally revealing. Proscia explicitly distinguishes these research-use-only capabilities from Concentriq AP-Dx, its separate FDA-cleared product for primary diagnosis. Clearance of the viewer does not authorize every AI application operating within it. The public materials reviewed do not establish an FDA-authorized comprehensive draft-report system, and Agilent’s announcement makes no specific commitment to deliver one. Product-status disclosures.
This is where pathology’s dependence on RUO-based, locally assembled and validated solutions can impose a crippling scaling penalty on itself. Dependence on RUO: it's not for nothing that we read of 1400 FDA radiology apps and 5 pathology ones (all else RUO.)
The decisive commercial test would be net physician time saved while maintaining diagnostic quality, including time spent checking and correcting drafts. A convincing result could make digital adoption easier to justify from operating economics, even before considering separate AI reimbursement.
Agilent has acquired an opportunity to pursue that result. The milestone worth watching is a product label, clinical study, and everyday workflow demonstrating that a pathologist can open a prepared case and finish it substantially faster.
Header. For 24 neuro codes, most were PLA codes with no PAMA data. For codes with PAMA data (e.g. 5,000 payments for generic ABeta 1-40 at various prices), median prices rose significantly (from $118 to $175). Interestingly, raw PAMA data shows that dozens of labs often got over $200, even over $300, for these codes despite later CLFS prices of $118.
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SEE ALSO An essay stimulated by this early data of mine - go here. It's quite long and detailed: I look forward to digesting it!
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I asked Chat GPT to look at CMS's current clinical lab fee schedule and pull out full text codes for dementia-related codes (A-Beta, Tau 217, etc.) It found 24 rows of data.
I then asked Chat GPT to search the CMS PAMA Preliminary Median file and wherever it found a median (some are blank), to insert that in the table. I then had it make ratios of "PAMA Median over Current CLFS" and plot the ratios (where possible) on a vetical bar chart. Note the bar chart has bins 1 to 24, and the table in Excel also has ordinal rows 1 to 24 (right column G).
Find the Excel data in Google Sheets here. Note there are several tabs.
This shows the full table but won't be legible (see Google Sheets) "Down" price in pink box; "up" prices in green box. Again, quite a few are PLA codes with no PAMA data so those rows are ineligible for an up/down color.
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| not legible, see google sheets |
Six of the codes rose between 1.2X and 1.8X, including 0443U, 82233, 82234, 83884, 84393, 84394. Most of these rising prices were generic CPT codes like Beta amyloid 1-40 and Beta amyloid 1-42. These were reported by dozens of TINS (101 TINS in the case of 84393 Tau phospho eg 217.
Often, PLA codes had no reported PAMA data (blanks in the bar chart).
I pulled Radiology Business's own listing of 24 recent AI articles - what does it amount to? Which way and why, are we running?
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Yes. Your document contains 24 articles: 20 from Radiology Business and four from Cardiovascular Business. I accessed the full text of 23. The BCRF venture-fund article repeatedly returned an access error, so I supplemented its available excerpts with BCRF’s original announcement.
Together, these September–October 2026 articles offer a useful picture of an industry entering commercial maturity. This is a qualitative industry synthesis, rather than a statistical meta-analysis: the collection mixes research reports, company announcements, executive interviews, and policy commentary.
My central interpretation is that radiology AI is becoming a competition over who can turn information into a reliable, economically sustainable clinical service. Algorithm performance remains necessary, but distribution, workflow, evidence, payment, and responsibility for follow-up increasingly determine commercial success.
From Nature Med, Nat Rev Clin Oncol, and NEJM.
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These papers support a substantial opportunity for digital pathology manufacturers—but the opportunity is to predict benefit from a particular ADC in a particular clinical setting, not simply to measure its target more precisely. TROP2 computational pathology is an especially important example because subcellular localization may contain information that conventional expression scoring misses. However, the papers also explain why many successful ADCs will not require a target-expression companion diagnostic.
For a manufacturer anticipating FDA CDx approvals, the strongest strategy is to establish a reliable platform for drug-specific diagnostic claims, while developing the ability to incorporate spatial biology, payload sensitivity, and treatment history. The likely future is a portfolio of validated applications sharing infrastructure, rather than one universal “ADC response score.”
The three articles are reviews or perspectives, so the appropriate synthesis is a critical narrative review rather than a pooled statistical meta-analysis. The assessment below separates established clinical uses, investigational biomarkers, and commercial forecasts.
The three papers address complementary questions.
Hurvitz explains the clinical demand: an expanding treatment menu is making selection and sequencing harder.