ArticleOncoTargets and therapy2016
Apparent diffusion coefficient values detected by diffusion-weighted imaging in the prognosis of patients with locally advanced esophageal squamous cell carcinoma receiving chemoradiation.
Article in OncoTargets and therapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Predicting the effects of radiotherapy based on diffusion kurtosis imaging in a xenograft mouse model of esophageal carcinoma.Experimental and therapeutic medicine · 2021Article
- Clinical response assessment on DW-MRI compared with FDG-PET/CT after neoadjuvant chemoradiotherapy in patients with oesophageal cancer.European journal of nuclear medicine and molecular imaging · 2021Article
- Histogram analysis of DCE-MRI for chemoradiotherapy response evaluation in locally advanced esophageal squamous cell carcinoma.La Radiologia medica · 2020Article
- Dynamic contrast-enhanced MRI for advanced esophageal cancer response assessment after concurrent chemoradiotherapy.Diagnostic and interventional radiology (Ankara, Turkey) · 2018Article
- Tuberculosis of the parotid lymph nodes: clinical and imaging features.Infection and drug resistance · 2018Article
- On predicting clinical response to chemoradiotherapy in esophageal squamous cell carcinoma: additional evaluation by magnetic resonance imaging may help.Annals of translational medicine · 2017Article
- Oesophageal cancer staging: a minefield of measurements-author's reply.The British journal of radiology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposePrevious studies have demonstrated that apparent diffusion coefficient (ADC) values measured by magnetic resonance imaging have prognostic value in patients with esophageal squamous cell carcinoma (ESCC). However, the role of ADC needs to be validated in a cohort of Chinese ESCC patients. This study assessed the role of ADC in predicting the outcome of patients with ESCC treated only by chemoradiation in the People's Republic of China. PATIENTS AND
methodsSeventy-three patients with local advanced ESCC were retrospectively analyzed in this study; none of the patients underwent surgery before or after chemoradiation. The ADC values of the primary tumors were determined by magnetic resonance imaging. The ADC values were then correlated with clinicopathological and other radiological parameters. Survival analysis was carried out to determine if ADC had an impact on survival of these patients.
resultsThe median ADC value of the esophageal cancer tissue was 1.256*10
conclusionThe ADC value is a potent prognostic factor which can be used to predict the outcome of patients with ESCC treated only by chemoradiation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.