Evidence map›Paper›PMID 29258857›Full record

ReviewSeminars in cancer biology2018

Understanding preanalytical variables and their effects on clinical biomarkers of oncology and immunotherapy.

Lokesh Agrawal, Kelly B Engel, Sarah R Greytak, Helen M Moore

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Seminars in cancer biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 3 pooled it
–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

50 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  18. Analysis of DNA Methylation in Gliomas: Assessment of Preanalytical Variables.Laboratory investigation; a journal of technical methods and pathology · 2024
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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

4 authors.

Lokesh AgrawalBiorepositories and Biospecimen Research Branch (BBRB), Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Drive, Bethesda, Maryland, USA.
Kelly B EngelPreferred Solutions Group, Washington D.C., USA.
Sarah R GreytakKelly Government Solutions, Rockville, Maryland, USA.
Helen M MooreBiorepositories and Biospecimen Research Branch (BBRB), Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Drive, Bethesda, Maryland, USA. Electronic address: moorehe@mail.nih.gov.

Funding

Intramural NIH HHS Z99 CA999999NULL Z99 CA999999
6 · The paper itself

Abstract

Identifying a suitable course of immunotherapy treatment for a given patient as well as monitoring treatment response is heavily reliant on biomarkers detected and quantified in blood and tissue biospecimens. Suboptimal or variable biospecimen collection, processing, and storage practices have the potential to alter clinically relevant biomarkers, including those used in cancer immunotherapy. In the present review, we summarize effects reported for immunologically relevant biomarkers and highlight preanalytical factors associated with specific analytical platforms and assays used to predict and gauge immunotherapy response. Given that many of the effects introduced by preanalytical variability are gene-, transcript-, and protein-specific, biospecimen practices should be standardized and validated for each biomarker and assay to ensure accurate results and facilitate clinical implementation of newly identified immunotherapy approaches.

Indexed as

AnimalsBiomarkers, TumorHumansImmunotherapyMedical OncologyNeoplasmsBiomarkers, TumorBiomarkerBiospecimen scienceCancer immunotherapyPreanalytical variability

Identifiers

PMID29258857
PMCPMC6004232

What OpenQuestion holds

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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.