MétaCan
Menu
Back to cohort
Record W4319296062 · doi:10.1136/bmj-2022-072133

Medial retropharyngeal nodal region sparing radiotherapy versus standard radiotherapy in patients with nasopharyngeal carcinoma: open label, non-inferiority, multicentre, randomised, phase 3 trial

2023· article· en· W4319296062 on OpenAlexaff
Yan‐Ping Mao, Shunxin Wang, Tian-Sheng Gao, Ning Zhang, Xiaoyu Liang, Fang‐Yun Xie, Yuan Zhang, Guan‐Qun Zhou, Rui Guo, Yongjie Li, Shaoqiang Liang, Li Lin, Wen‐Fei Li, Xu Liu, Cheng Xu, Yu‐Pei Chen, Jia‐Wei Lv, Lizhi Liu, Jibin Li, Ling‐Long Tang, Lei Chen, Ying Sun, Jun Ma

Bibliographic record

VenueBMJ · 2023
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersHigher Education Discipline Innovation ProjectSun Yat-sen University Cancer CenterNational Natural Science Foundation of ChinaOverseas Expertise Introduction Project for Discipline InnovationSun Yat-sen UniversityNatural Science Foundation of Guangdong Province
KeywordsNasopharyngeal carcinomaMedicineRadiation therapyOpen labelSurgeryRandomized controlled trialRadiology

Abstract

fetched live from OpenAlex

OBJECTIVES: To address whether sparing the medial retropharyngeal lymph node (MRLN) region from elective irradiation volume provides non-inferior local relapse-free survival versus standard radiotherapy in patients with nasopharyngeal carcinoma. DESIGN: Open-label, non-inferiority, multicentre, randomised, phase 3 trial. SETTING: Three Chinese hospitals between 20 November 2017 and 3 December 2018. PARTICIPANTS: Adults (18-65 years) with newly diagnosed, non-keratinising, non-distant metastatic nasopharyngeal carcinoma without MRLN involvement. INTERVENTIONS: Randomisation was done centrally by the Clinical Trials Centre at Sun Yat-sen University Cancer Center. Eligible patients were randomly assigned (1:1; block size of four) to receive MRLN sparing radiotherapy or standard radiotherapy (both medial and lateral retropharyngeal lymph node groups), and stratified by institution and treatment modality as follows: radiotherapy alone; concurrent chemoradiotherapy; induction chemotherapy plus radiotherapy or concurrent chemoradiotherapy. MAIN OUTCOME MEASURES: Non-inferiority was met if the lower limit of the one sided 97.5% confidence interval of the absolute difference in three year local relapse-free survival (MRLN sparing radiotherapy minus standard radiotherapy) was greater than -8%. RESULTS: 34.3%, P=0.008). Patient reported outcomes at three years after MRLN sparing radiotherapy were better in multiple domains after adjusting for the baseline values: global health status (mean difference -5.6 (95% confidence interval -9.1 to -2.0), P=0.002), role functioning (-5.5 (-7.4 to -3.6), P<0.001), social functioning (-6.2 (-8.9 to -3.6), P<0.001), fatigue (7.9 (4.0 to 11.8), P<0.001), and swallowing (11.0 (8.4 to 13.6), P<0.001). The difference in swallowing scores reached clinical significance (>10 points difference). CONCLUSION: Compared with standard radiotherapy, MRLN sparing radiotherapy showed non-inferiority in terms of risk of local relapse with fewer radiation related toxicity and improved patient reported outcomes in patients with non-metastatic nasopharyngeal carcinoma. TRIAL REGISTRATION: ClinicalTrials.gov NCT03346109.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.367
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations42
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBMJSame topicHead and Neck Cancer StudiesFrench-language works237,207