Evidence map›Paper›PMID 28361059›Full record

ArticleAnnals of translational medicine2017

Michael J McKay, Jezzie Maneerat, Timothy M McKay, Jeremy N McKay, Reza Masoud-Rahbari

Abstract read
In one paragraph

Article in Annals of translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Michael J McKayDepartment of Medicine, University of Sydney, Camperdown, 2050 NSW, Australia.
Jezzie ManeeratPeter MacCallum Cancer Centre, Melbourne, VIC, Australia.
Timothy M McKayDeakin University, Burwood, 3125 VIC, Australia.
Jeremy N McKayMonash University, Clayton, 3260 VIC, Australia.
Reza Masoud-RahbariNorth Coast Cancer Institute, Lismore, 2480 NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnderstanding the basis of clinical radiosensitivity is a key goal of radiation research. In this study, we used the limiting dilution assay (LDA) to analyze

methodsLymphoblastoid cell lines (LCLs) were created from 29 cancer patients including 19 RS patients, 10 controls who had not developed severe normal tissue reactions, and 1 ataxia telangiectasia RS control cell line. The clinically RS patients had grade 3 or grade 4 reactions; one had a grade 2 reaction. All cells were exposed to graded doses of gamma-radiation

resultsOur LDA analysis yielded two notable positive results. Firstly, it could distinguish control cells from cells from pooled breast cancer cases with severe reactions of all types (acute reactors, consequential late reactors and late reactors). Secondly, two radiosensitivity outliers were detected on the fitted curves, corresponding clinically to grade 3 and 4 late radiation reactions in breast and head and neck cancer cases respectively. The assay showed considerable cell survival heterogeneity.

conclusionsThe LDA as used here may provide unique clinical utility in detecting potential RS breast cancer patients prior to radiotherapy (RT), a form of personalized medicine. The assay may be especially useful in situations where its results can be temporally available prior to therapy initiation (e.g., those patients not undergoing RT until some months after surgery, typically those having adjuvant chemotherapy prior to RT). Two LCLs from RS outliers could potentially yield insight into the cellular and/or genetic basis of radiosensitivity, for example by undertaking genomic analyses on these cell lines.

Indexed as

breastcancercell survivalclonogenic survivalIonizingradiationradiotherapy (RT)

Identifiers

PMID28361059
PMCPMC5360602

What OpenQuestion holds

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Registered trials

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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.