Evidence map›Paper›PMID 29423223›Full record

ArticleMolecular and clinical oncology2018

Meta-analysis of diffusion-weighted imaging for predicting locoregional failure of chemoradiotherapy in patients with head and neck squamous cell carcinoma.

Qiming Zhou, Fangfang Zeng, Yao Ding, Clifton D Fuller, Jihong Wang

Abstract read
In one paragraph

Article in Molecular and clinical oncology, 2018. 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. Review
  2. Article
  3. Impact of a dedicated radiologist as a member of the head and neck tumour board: a single-institution experience.Acta otorhinolaryngologica Italica : organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale · 2020
    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

5 authors.

Qiming ZhouDepartment of Oncology, The Sixth People's Hospital, Shenzhen, Guangdong 518052, P.R. China.
Fangfang ZengGuangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, P.R. China.
Yao DingDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Clifton D FullerDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Jihong WangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to evaluate the accuracy of diffusion-weighted imaging (DWI) for predicting locoregional failure of chemoradiotherapy in patients with head and neck squamous cell carcinoma (HNSCC). A comprehensive search was conducted through the EMBASE, PubMed and Cochrane Library databases for relevant publications. Stata software was used to calculate the pooled sensitivity, specificity, likelihood ratios and diagnostic odds ratios, and to construct a summary receiver operating characteristics (sROC) curve for DWI. A total of 9 studies comprising 421 patients were included. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio were 0.82 [95% confidence interval (CI): 0.72-0.88], 0.70 (95% CI: 0.62-0.77), 2.7 (95% CI: 2.1-3.6), 0.26 (95% CI: 0.17-0.41), and 10.48 (95% CI: 5.35-20.53), respectively. The area under the sROC curve was 0.84 (95% CI: 0.81-0.87). Therefore, DWI appears to be a promising imaging modality for predicting local failure of chemoradiotherapy in patients with HNSCC.

Indexed as

chemoradiotherapydiffusion-weighted imaginghead and neck squamous cell carcinomalocoregional failure

Identifiers

PMID29423223
PMCPMC5772961

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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.