Evidence map›Paper›PMID 27802182›Full record

ArticleOncotarget2017

Dynamic contrast-enhanced magnetic resonance imaging for pretreatment prediction of early chemo-radiotherapy response in larynx and hypopharynx carcinoma.

Wei Guo, Dehong Luo, Xinyi Chen, Meng Lin, Lin Li, Yanfeng Zhao, Liang Yang, Lei Hu, Xinming Zhao, Chunwu Zhou

Abstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Routine restaging after primary non-surgical treatment of laryngeal squamous cell carcinoma-a review.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2021
    Pooled it
  2. Concordance between head and neck MRI and histopathology in detecting laryngeal subsite invasion among patients with laryngeal cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023
    Article
  3. Article
  4. Article
  5. 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

10 authors.

Wei GuoDepartment of Diagnostic Radiology, Peking Union Medical College, Cancer Institute & Hospital, Chinese Academy of Medical Sciences, Beijing,China.
Dehong LuoDepartment of Diagnostic Radiology, Peking Union Medical College, Cancer Institute & Hospital, Chinese Academy of Medical Sciences, Beijing,China.
Xinyi ChenDepartment of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Meng LinDepartment of Diagnostic Radiology, Peking Union Medical College, Cancer Institute & Hospital, Chinese Academy of Medical Sciences, Beijing,China.
Lin LiDepartment of Diagnostic Radiology, Peking Union Medical College, Cancer Institute & Hospital, Chinese Academy of Medical Sciences, Beijing,China.
Yanfeng ZhaoDepartment of Diagnostic Radiology, Peking Union Medical College, Cancer Institute & Hospital, Chinese Academy of Medical Sciences, Beijing,China.
Liang YangDepartment of Diagnostic Radiology, Peking Union Medical College, Cancer Institute & Hospital, Chinese Academy of Medical Sciences, Beijing,China.
Lei HuDepartment of Diagnostic Radiology, Peking Union Medical College, Cancer Institute & Hospital, Chinese Academy of Medical Sciences, Beijing,China.
Xinming ZhaoDepartment of Diagnostic Radiology, Peking Union Medical College, Cancer Institute & Hospital, Chinese Academy of Medical Sciences, Beijing,China.
Chunwu ZhouDepartment of Diagnostic Radiology, Peking Union Medical College, Cancer Institute & Hospital, Chinese Academy of Medical Sciences, Beijing,China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study is to investigate the use of dynamic contrast-enhanced magnetic resonance imaging in predicting early response to CRT (chemo-radiotherapy) in patients with larynx and hypopharynx carcinoma from primary tumors.

methodSixty-two patients with larynx and hypopharynx carcinoma underwent two DCE-MRI studies: a baseline exam before any treatmentanda post-treatment exam 3 weeks after CRT. At the end of treatment, patients were classified as responders, or non-responders according to the Response Evaluation Criteria in Solid Tumors criteria (RECIST). The time intensity curves (TIC) were extracted and processed to obtain time to peak (TTP), maximum slope of increase (MSI), maximum slope of decrease (MSD) and positive enhancement integral (PEI), and the semi-quantitative MRI parameters were compared and analyzed between the two groups.

resultsFifty-four and 8 patients were included the responder and non-responder groups. It was observed that the MSI, MSD, and PEI were significantly lower post-treatment than pre-treatment(P < 0.05). The pretreatment MSI, MSD, and PEI parameters of responders were significantly higher than those of non-responders (P< 0.05). The post-treatment MSI, MSD, and PEI parameters of responders were significantly lower than those of non-responders (P< 0.05). Based on ROC curve analysis, at a threshold of 154.81 for pretreatment MSI, the corresponding AUC, sensitivity, and specificity were 0.882, 89.3% and 73.5%, respectively.

conclusionThe semi-quantitative DCE-MRI may aid in the prediction of early response to CRT in patients with larynx and hypopharynx carcinoma.

Indexed as

Image EnhancementMagnetic Resonance ImagingArea Under CurveChemoradiotherapyCombined Modality TherapyHumansHypopharyngeal NeoplasmsLaryngeal NeoplasmsMaleMiddle AgedPrognosisROC CurveTreatment OutcomeChemo-radiotherapyDynamic contrast-enhanced magnetic resonance imagingLarynx and hypopharynx carcinomaSemi-quantitative parameters

Identifiers

PMID27802182
PMCPMC5464915

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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.