Comparing trials like Sequoia (zanubrutinib) and Amplify (acalabrutinib-venetoclax) is invalid without adjusting for baseline population differences. Amplify's inclusion of an FCR chemo-arm meant its patients were inherently more fit, necessitating statistical matching for a fair comparison.

The SAVANNAH study showed that targeting MET amplification after TKI failure is only effective with stringent diagnostic criteria (e.g., IHC 3+ in >90% of cells). Lower cutoffs lead to poor outcomes, highlighting the need for precise biomarker testing to select patients for this therapy.

While the need for prospective trials dominates the ctDNA discussion, a more fundamental obstacle is the lack of standardization between assay types (e.g., tumor-informed vs. agnostic). Without a common measurement approach, data from disparate trials cannot be pooled to create a universally accepted surrogate endpoint for regulatory approval.

Despite newer MET TKIs like capmatinib and tipotinib being available, the older drug crizotinib remains a valuable option for NSCLC patients with MET alterations. It is often better tolerated, making it a practical choice for patients who cannot handle the side effects of newer agents.

Standard Next-Generation Sequencing (NGS) reports often just state "MET amplification" without a specific copy number. To make informed treatment decisions with MET inhibitors, clinicians must proactively contact the testing company's molecular pathology department to obtain this crucial, unlisted data point.

In the Luminosity study of Taliso-V for MET-overexpressed NSCLC, patients with high C-MET expression had better response rates than those with intermediate expression. However, this did not translate into a significant improvement in median Progression-Free Survival (PFS) or Overall Survival (OS).

Inconsistent methods for assessing biomarkers like PD-L1 (CPS vs. TAP scoring), p53 (IHC vs. sequencing), and HRR (different panels) across major clinical trials make it difficult to compare results and identify a reliable predictive marker for endometrial cancer.

Even when trials like LITESPARK 022 and Keynote 564 use identical eligibility criteria, outdated staging systems result in patient populations with different underlying risks. This makes direct comparison of outcomes between trials, even for the same drug, an unfair and statistically flawed analysis that ignores the function of a control arm.

Despite meeting its primary endpoint, the PROTEUS trial provides no validated biomarkers to identify which patients actually benefit from the intensified therapy. This lack of a predictive signature means applying the results in the clinic amounts to uniform escalation, likely overtreating many patients for an uncertain benefit, making it difficult to implement.