https://www.dmepdac.com/palmetto/jjb.nsf/DID/KVLUXG5RYU
Based on the preamble and the 17 questions from the MolDX CAC meeting document, here’s how the tone and framing read:
1. Evidence-Seeking vs. Evidence-Challenging
The questions are structured in a balanced way. They ask both about shortcomings of current EGD surveillance (Q1–4) and about how non-invasive tests might add value (Q5–8). They also probe whether existing molecular tests demonstrate utility beyond current surveillance (Q10–11) and how real-world evidence compares to trials like BEST1–3 (Q15).
That balance suggests the MACs are genuinely canvassing for arguments both for and against current non-coverage.
2. Signs of Skepticism
Several questions highlight limitations and risks:
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Concerns about false positives/false negatives (Q6, Q8).
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Concerns about operator error and variable failure rates (Q16).
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Questions about whether biomarkers are merely correlative vs. causative (Q13).
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Questions about applicability of UK trial data to the U.S. (Q15).
These lean toward reinforcing a cautious stance.
3. Signs of Openness
Other questions explicitly invite experts to articulate positive use cases:
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Q5 and Q7 ask how management would change if rule-in or rule-out tests were reliable.
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Q10 asks what evidence is the “most compelling case” to support their use.
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Q11 probes whether such tests identify more patients than traditional surveillance.
These provide open doors for panelists to argue for clinical utility.
4. Strategic Reading
Given MolDX’s history, the default position is skepticism (hence the existing non-coverage LCD). However, the framing is not one-sided—questions are written so that if panelists bring strong arguments and data, MACs can justify a shift.
The fact that they are holding a multi-jurisdictional CAC meeting (rather than simply re-affirming non-coverage internally) suggests they are at least willing to re-examine the evidence landscape.
Bottom Line
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It is not a one-directional “shore up the no” exercise—too many questions invite positive evidence.
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At the same time, the skeptical undertone (trial generalizability, operator error, biomarker causality) shows they are wary of over-promising.
👉 I would call it too close to call—but leaning toward B (openness to conversion) if stakeholders present convincing data, because otherwise they could have let the negative LCD stand without convening a CAC.
Would you like me to draft a matrix of the 17 questions categorized as “pro-coverage opportunities” vs. “anti-coverage concerns”? That might make it clearer which way the balance tips.
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