Evidence map›Paper›PMID 37810970›Full record

ArticleFrontiers in oncology2023

Response assessment of post-treatment head and neck cancers to determine further management using NI-RADS (Neck Imaging Reporting and Data System): a subgroup analysis of a randomized controlled trial.

Abhishek Mahajan, Himangi Unde, Nilesh P Sable, Shreya Shukla, Richa Vaish, Vijay Patil, Ujjwal Agarwal, Archi Agrawal, Vanita Noronha, Amit Joshi and 11 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.4field-weighted citation impact, top 11% 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.

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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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

21 authors at 3 institutions in 2 countries.

Abhishek MahajanDepartment of Radiodiagnosis, The Clatterbridge Cancer Centre, University of Liverpool, Liverpool, United Kingdom.
Himangi UndeDepartment of Radiodiagnosis and Imaging, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Nilesh P SableDepartment of Radiodiagnosis and Imaging, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Shreya ShuklaDepartment of Radiodiagnosis and Imaging, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Richa VaishDepartment of Head and Neck Surgery, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Vijay PatilDepartment of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Ujjwal AgarwalDepartment of Radiodiagnosis and Imaging, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Archi AgrawalDepartment of Nuclear Medicine, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Vanita NoronhaDepartment of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Amit JoshiDepartment of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Akhil KapoorDepartment of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Nandini MenonDepartment of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Jai Prakash AgarwalDepartment of Radiation Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Sarbani Ghosh LaskarDepartment of Radiation Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Anil Keith DcruzDepartment of Head and Neck Surgery, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Pankaj ChaturvediDepartment of Head and Neck Surgery, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Prathamesh PaiDepartment of Head and Neck Surgery, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Swapnil Ulhas RaneDepartment of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Munita BalDepartment of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Asawari PatilDepartment of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Kumar PrabhashDepartment of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India.
Tata Memorial Hospital · INHomi Bhabha National Institute · INClatterbridge Cancer Centre NHS Foundation Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Interpreting complex post-treatment changes in head and neck cancer (HNC) is challenging with further added perplexity due to variable interobserver interpretation and hence evolved the NI-RADS lexicon. We evaluated the accuracy of NI-RADS in predicting disease status on 1st post-treatment follow-up CECT in a homogenous cohort of those who received only chemoradiation. Methods: Retrospective analysis of imaging was done for LASHNC patients who received radical chemoradiation in an open-label, investigator-initiated, phase 3 randomized trial (2012-2018) randomly assigned to either radical radiotherapy with concurrent weekly cisplatin (CRT) or CRT with the same schedule plus weekly nimotuzumab (NCRT). 536 patients were accrued, and 74 patients who did not undergo PET/CECT after 8 weeks post-CRT were excluded. After assessing 462 patients for eligibility to allocate NI-RADS at primary and node sites, 435 cases fell in the Primary disease cohort and 412 cases in the Node disease cohort. We evaluated sensitivity, disease prevalence, the positive and negative predictive value of the NI-RADS lexicon, and accuracy, which were expressed as percentages. We also prepared flow charts to determine concordance with allocated NI-RADS category and established accuracy with which it can identify disease status. Results: Out of 435 primary disease cohort, 92%, 55%, 48%,70% were concordant and had 100%, 72%, 70%, 82% accuracy in NI-RADS1 (n=12), NI-RADS2 (n=261), NIRADS3 (n=105), and NI-RADS 4 (n=60) respectively. Out of 412 nodes disease cohort, 95%, 90%, 48%, 70%were concordant and had 92%, 97%, 90%, 67% accuracy in NI-RADS1 (n=57), NI-RADS2 (n=255), NI-RADS3 (n=105) and NI-RADS4 (n=60) respectively. % concordance of PET/CT and CECT across all primary and node disease cohorts revealed that PET/CT was 91% concordant in primary NI-RADS2 as compared to 55% concordance of CECT whereas concordance of CECT was better with 57% in primary NI-RADS3 cohort as compared to PET/CT concordance of 41%. Conclusion: The accuracy with which the NI-RADS lexicon performed in our study at node sites was better than that at the primary site. There is a great scope of research to understand if CECT performs better over clinical disease status in NI-RADS 3 and 4 categories. Further research should be carried out to understand if PET/CECT can be used for close interval follow-up in stage III/IV NI-RADS 2 cases.

Indexed as

computed tomographyhead neck cancer follow-uphead neck cancer imagingMRINIRADSPETpost treatment responsesurveillance

Identifiers

PMID37810970
PMCPMC10552531
OpenAlexW4386916051

What OpenQuestion holds

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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.