Evidence map›Paper›PMID 42569846›Full record

ArticleJournal of managed care & specialty pharmacy2026

Key considerations when assessing clinical utility for biomarker testing: A checklist.

Tianyi Wang, Kimberly Tsai, Steven S Kheloussi, Dana McCormick, Pamala A Pawloski

Abstract read
In one paragraph

Article in Journal of managed care & specialty pharmacy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Tianyi WangOmnicom Health Market Access, New York, NY.
Kimberly TsaiOmnicom Health Market Access, Millington, NJ.
Steven S KheloussiKheloussi Consulting, LLC, Wilkes-Barre, PA.
Dana McCormickAMCP, Grapevine, TX.
Pamala A PawloskiAMCP Research Institute, Alexandria, VA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Establishing the clinical utility of biomarker tests is a critical component of benefit design. However, payers and laboratory benefit manager organizations may differ in how they evaluate clinical utility for a given test, including how they determine whether evaluated outcomes are clinically meaningful. These differences can create challenges for providers and manufacturers when navigating coverage policies across organizations. Based on expert insights from a partnership forum hosted by AMCP on June 24-25, 2025, in Alexandria, VA, on the topic of precision medicine in oncology, we developed a checklist of considerations to align payers and laboratory benefit managers around a shared, actionable approach to evaluating the clinical utility of biomarker tests and the types of evidence used to demonstrate it. The checklist begins with confirmation that analytical and clinical validity have been established before assessing clinical utility. Tests should then be categorized based on their intended use and whether they provide actionable information that informs clinical decision-making and improves patient health outcomes. Assessment of clinical utility includes consideration of the relevance, strength, and consistency of the supporting evidence base. After clinical utility is established, economic and operational considerations may also be evaluated. This checklist is intended to support a more transparent and structured approach to evaluating clinical utility in coverage decision-making.

Indexed as

BiomarkersChecklistPrecision MedicineClinical Decision-MakingClinical RelevanceHumansBiomarkers

Identifiers

PMID42569846
PMCPMC13452049

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.