Evidence map›Paper›PMID 26760958›Full record

ArticleOmics : a journal of integrative biology2016

Early Stage Health Technology Assessment for Precision Biomarkers in Oral Health and Systems Medicine.

Lotte M G Steuten

Abstract read
In one paragraph

Article in Omics : a journal of integrative biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

1 author.

Lotte M G Steuten1 Fred Hutchinson Cancer Research Center, Hutchinson Institute for Cancer Outcomes Research , Seattle, Washington, United States .

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health technology assessment (HTA) is a crucial science that influences the responsible and evidence-based transition of new discoveries from laboratory to applications in the clinic and society. HTA has recently moved "upstream" so as to assess technologies from their onset at their discovery, design, or planning phase. Biomarker research is relatively recent in oral health, but growing rapidly with investments made to advance dentistry and oral health and importantly, to build effective bridges between oral health and systems medicine since what happens in oral health affects systems pathophysiology, and vice versa. This article offers a synthesis of the latest trends and approaches in early phase HTA, with a view to near future applications in oral health, systems medicine, and biomarker-guided precision medicine. In brief, this review underscores that demonstrating health outcomes of biomarkers and next-generation diagnostics is particularly challenging because they do not always influence long-term outcomes directly, but rather impact subsequent care processes. Biomarker testing costs are typically less of a barrier to uptake in practice than the biomarker's impact on longer term health outcomes. As a single biomarker or next-generation diagnostic in oral health can inform decisions about numerous downstream diagnosis-treatment combinations, early stage "upstream" HTA is crucial in prioritizing the most valuable diagnostic applications to pursue first. For the vast array of oral health biomarkers currently developed, early HTA is necessary to timely and iteratively assess their comparative effectiveness and anticipate the inevitable questions about value for money from regulators and payers.

Indexed as

AnimalsBiomarkersHumansPrecision MedicineSystems AnalysisBiomarkers

Identifiers

PMID26760958
PMCPMC4739424

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.