Evidence map›Paper›PMID 36158240›Full record

ArticlePhysics and imaging in radiation oncology2022

Independent validation of a dysphagia dose response model for the selection of head and neck cancer patients to proton therapy.

Petros Kalendralis, Matthijs Sloep, Nibin Moni George, Jasper Snel, Joeri Veugen, Frank Hoebers, Frederik Wesseling, Mirko Unipan, Martijn Veening, Johannes A Langendijk and 3 more

Open access · goldAbstract read
In one paragraph

Article in Physics and imaging in radiation oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
1.8field-weighted citation impact, top 14% 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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 5 institutions in 1 country.

Petros KalendralisDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Matthijs SloepDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Nibin Moni GeorgeDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Jasper SnelDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Joeri VeugenDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Frank HoebersDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Frederik WesselingDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Mirko UnipanDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Martijn VeeningDepartment of Radiation Oncology, University of Groningen, University Medical Centre Groningen. Groningen. the Netherlands.
Johannes A LangendijkDepartment of Radiation Oncology, University of Groningen, University Medical Centre Groningen. Groningen. the Netherlands.
Andre DekkerDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Johan van SoestBrightlands Institute for Smart Digital Society (BISS), Faculty of Science and Engineering, Maastricht University, Heerlen, the Netherlands.
Rianne FijtenDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Maastro Clinic · NLMaastricht University Medical Centre · NLMaastricht University · NLUniversity Medical Center Groningen · NLUniversity of Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: The model based approach involves the use of normal tissue complication models for selection of head and neck cancer patients to proton therapy. Our goal was to validate the clinical utility of the related dysphagia model using an independent patient cohort. Materials and Methods: A dataset of 277 head and neck cancer (pharynx and larynx) patients treated with (chemo)radiotherapy between 2019 and 2021 was acquired. For the evaluation of the model discrimination we used statistical metrics such as the sensitivity, specificity and the area under the receiver operating characteristic curve. After the validation we evaluated if the dysphagia model can be improved using the closed testing procedure, the Brier and the Hosmer-Lemeshow score. Results: The performance of the original normal tissue complication probability model for dysphagia grade II-IV at 6 months was good (AUC = 0.80). According to the graphical calibration assessment, the original model showed underestimated dysphagia risk predictions. The closed testing procedure indicated that the model had to be updated and selected a revised model with new predictor coefficients as an optimal model. The revised model had also satisfactory discrimination (AUC = 0.83) with improved calibration. Conclusion: The validation of the normal tissue complication probability model for grade II-IV dysphagia was successful in our independent validation cohort. However, the closed testing procedure indicated that the model should be updated with new coefficients.

Identifiers

PMID36158240
PMCPMC9493379
OpenAlexW4296311929

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.