Evidence map›Paper›PMID 28738294›Full record

ArticleTranslational oncology2017

Oral Mucosa Dose Parameters Predicting Grade ≥3 Acute Toxicity in Locally Advanced Nasopharyngeal Carcinoma Patients Treated With Concurrent Intensity-Modulated Radiation Therapy and Chemotherapy: An Independent Validation Study Comparing Oral Cavity versus Mucosal Surface Contouring Techniques.

Kaixin Li, Ling Yang, Qiang-Ying Hu, Xiao-Zhong Chen, Ming Chen, Yuanyuan Chen

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Translational oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06032767 (Prospective Observational Study to Predict Severe Oral Mucositis Associated With Chemoradiotherapy in Nasopharyngeal Carcinoma Based on Deep Learning), which is not on this map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 15% 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.

NCT06032767 unknown statusnot on this mapstarted 2023, after this paper: background citation

Prospective Observational Study to Predict Severe Oral Mucositis Associated With Chemoradiotherapy in Nasopharyngeal Carcinoma Based on Deep Learning

TypeobservationalSponsorSun Yat-sen UniversityRan2023 to 2024Enrolled480ConditionsNasopharyngeal Carcinoma, Oral MucositisArmsobservational group
3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Do grape and black mulberry molasses have an effect on oral mucositis and quality of life in patients with head and neck cancer?Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022
    Article
  17. Article
  18. Article
  19. Article
  20. 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

6 authors at 3 institutions in 1 country.

Kaixin LiDepartment of Radiation Oncology, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, China.
Ling YangDepartment of Oncology, Xinyu People's Hospital, Xinyu, China.
Qiang-Ying HuDepartment of Radiotherapy, Zhejiang cancer Hospital, Hangzhou, China.
Xiao-Zhong ChenDepartment of Radiotherapy, Zhejiang cancer Hospital, Hangzhou, China.
Ming ChenDepartment of Radiotherapy, Zhejiang cancer Hospital, Hangzhou, China. Electronic address: chenming@zjcc.org.cn.
Yuanyuan ChenDepartment of Radiotherapy, Zhejiang cancer Hospital, Hangzhou, China. Electronic address: chenyy@zjcc.org.cn.
Zhejiang Cancer Hospital · CNFujian Medical University · CNXinyu University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo determine whether volumes based on the contours of the mucosal surface instead of the oral cavity can be used to predict grade ≥3 acute oral mucosa toxicity in patients with locally advanced nasopharyngeal carcinoma (LANPC) treated with concurrent intensity-modulated radiation therapy (IMRT) and chemotherapy. METHODS AND MATERIALS: A standardized method for the oral cavity (oral cavity contours, OCC) and a novel method for the mucosal surface (mucosal surface contours, MSC) were developed for the oral mucosa and prospectively applied to the radiation treatment plans of 92 patients treated with concurrent IMRT and chemotherapy for LANPC. Dose-volume histogram (DVH) data were extracted and then toxicity was analyzed. Receiver operating characteristic analysis and logistic regression were carried out for both contouring methods.

resultsGrade ≥3 acute oral mucosa toxicity occurred to 20.7% (19/92) of patients in the study. A highly significant dose-volume relationship between oral mucosa irradiation and acute oral mucosa toxicity was supported by using both oral cavity and mucosal surface contouring techniques. In logistic regression, body weight loss was an independent factor related to grade ≥3 acute toxicity for OCC and MSC (P=.017 and 0.005, respectively), and the independent factor of dosimetric parameters for OCC and MSC were V30Gy (P=.003) and V50Gy (P=.003) respectively. In the receiver operating characteristics curve, the areas under V30Gy of the OCC curves was 0.753 (P=.001), while the areas under V50Gy of MSC curves was 0.714 (P=.004); the cut-off value was 73.155% (sensitivity, 0.842; specificity, 0.671) and 14.32% (sensitivity, 0.842; specificity, 0.575), respectively.

conclusionDVH analysis of mucosal surface volumes accurately predicts grade ≥3 acute oral mucosa toxicity in patients with LANPC receiving concurrent IMRT and chemotherapy, but in clinical practice the MSC method appears no better than the OCC one.

Identifiers

PMID28738294
PMCPMC5524298
OpenAlexW2737976744

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.