Evidence map›Paper›PMID 29051037›Full record

ArticleInternational journal of radiation oncology, biology, physics2018

Serum MicroRNA Signature Predicts Response to High-Dose Radiation Therapy in Locally Advanced Non-Small Cell Lung Cancer.

Yilun Sun, Peter G Hawkins, Nan Bi, Robert T Dess, Muneesh Tewari, Jason W D Hearn, James A Hayman, Gregory P Kalemkerian, Theodore S Lawrence, Randall K Ten Haken and 4 more

Open access · greenAbstract read
In one paragraph

Article in International journal of radiation oncology, biology, physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
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

25 citing papers in PubMed, 38 citations in OpenAlex.

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  13. MicroRNAs as Biomarkers for Ionizing Radiation Injury.Frontiers in cell and developmental biology · 2022
    Review
  14. MicroRNAs Responding to Space Radiation.International journal of molecular sciences · 2020
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 4 institutions in 2 countries.

Yilun SunDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan.
Peter G HawkinsDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Nan BiDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Radiation Oncology, Cancer Hospital and Institute, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking, People's Republic of China.
Robert T DessDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Muneesh TewariDivision of Hematology/Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan; Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan; Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan; Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan.
Jason W D HearnDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
James A HaymanDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Gregory P KalemkerianDivision of Hematology/Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan.
Theodore S LawrenceDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Randall K Ten HakenDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Martha M MatuszakDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Feng-Ming KongDepartment of Radiation Oncology, Indiana University, Indianapolis, Indiana.
Shruti JollyDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan. Electronic address: shrutij@med.umich.edu.
Matthew J SchipperDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan; Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
University of Michigan–Ann Arbor · USBioSurfaces (United States) · USChinese Academy of Medical Sciences & Peking Union Medical College · CNIndiana University – Purdue University Indianapolis · US

Funding

TREATMENT VERIFICATION AND TREATMENT PLAN REFINEMENTP01CA059827 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KESSLER, MARC LEWIS, LAWRENCE, THEODORE S · 1993 to 2018
$37.9M
FUNCTIONAL IMAGE AND MOLECULAR MARKER TO INDIVIDUALIZE ADAPTIVE RADIATION DOSE ESR01CA142840 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KONG, FENG-MING P. · 2010 to 2015
$2.0M
NCI NIH HHS P01 CA059827NCI NIH HHS R01 CA142840
6 · The paper itself

Abstract

purposeTo assess the utility of circulating serum microRNAs (c-miRNAs) to predict response to high-dose radiation therapy for locally advanced non-small cell lung cancer (NSCLC). METHODS AND MATERIALS: Data from 80 patients treated from 2004 to 2013 with definitive standard- or high-dose radiation therapy for stages II-III NSCLC as part of 4 prospective institutional clinical trials were evaluated. Pretreatment serum levels of 62 miRNAs were measured by quantitative reverse transcription-polymerase chain reaction array. We combined miRNA data and clinical factors to generate a dose-response score (DRS) for predicting overall survival (OS) after high-dose versus standard-dose radiation therapy. Elastic net Cox regression was used for variable selection and parameter estimation. Model assessment and tuning parameter selection were performed through full cross-validation. The DRS was also correlated with local progression, distant metastasis, and grade 3 or higher cardiac toxicity using Cox regression, and grade 2 or higher esophageal and pulmonary toxicity using logistic regression.

resultsEleven predictive miRNAs were combined with clinical factors to generate a DRS for each patient. In patients with low DRS, high-dose radiation therapy was associated with significantly improved OS compared to treatment with standard-dose radiation therapy (hazard ratio 0.22). In these patients, high-dose radiation also conferred lower risk of distant metastasis and local progression, although the latter association was not statistically significant. Patients with high DRS exhibited similar rates of OS regardless of dose (hazard ratio 0.78). The DRS did not correlate with treatment-related toxicity.

conclusionsUsing c-miRNA signature and clinical factors, we developed a DRS that identified a subset of patients with locally advanced NSCLC who derive an OS benefit from high-dose radiation therapy. This DRS may guide dose escalation in a patient-specific manner.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorCarcinoma, Non-Small-Cell LungClinical Trials as TopicDisease ProgressionDose-Response Relationship, RadiationFemaleHumansKaplan-Meier EstimateLung NeoplasmsMaleMicroRNAsMiddle AgedRadiotherapy DosageBiomarkers, TumorMicroRNAs

Identifiers

PMID29051037
PMCPMC5736451
OpenAlexW2753136088

What OpenQuestion holds

Textmetadata
LicenceTDM
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.