Evidence map›Paper›PMID 38993196›Full record

ArticleAdvances in radiation oncology2024

A Visualization and Radiation Treatment Plan Quality Scoring Method for Triage in a Population-Based Context.

Alexandra O Leone, Abdallah S R Mohamed, Clifton D Fuller, Christine B Peterson, Adam S Garden, Anna Lee, Lauren L Mayo, Amy C Moreno, Jay P Reddy, Karen Hoffman and 3 more

Abstract read
In one paragraph

Article in Advances in radiation oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Alexandra O LeoneDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Abdallah S R MohamedDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Clifton D FullerDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Christine B PetersonUTHealth Houston Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Adam S GardenDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Anna LeeDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Lauren L MayoDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Amy C MorenoDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Jay P ReddyDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Karen HoffmanDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Joshua S NiedzielskiDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Laurence E CourtDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Thomas J WhitakerDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Our purpose was to develop a clinically intuitive and easily understandable scoring method using statistical metrics to visually determine the quality of a radiation treatment plan. Methods and Materials: Data from 111 patients with head and neck cancer were used to establish a percentile-based scoring system for treatment plan quality evaluation on both a plan-by-plan and objective-by-objective basis. The percentile scores for each clinical objective and the overall treatment plan score were then visualized using a daisy plot. To validate our scoring method, 6 physicians were recruited to assess 60 plans, each using a scoring table consisting of a 5-point Likert scale (with scores ≥3 considered passing). Spearman correlation analysis was conducted to assess the association between increasing treatment plan percentile rank and physician rating, with Likert scores of 1 and 2 representing clinically unacceptable plans, scores of 3 and 4 representing plans needing minor edits, and a score of 5 representing clinically acceptable plans. Receiver operating characteristic curve analysis was used to assess the scoring system's ability to quantify plan quality. Results: Of the 60 plans scored by the physicians, 8 were deemed as clinically acceptable; these plans had an 89.0th ± 14.5 percentile value using our scoring system. The plans needing minor edits or deemed unacceptable had more variation, with scores falling in the 62.6nd ± 25.1 percentile and 35.6th ± 25.7 percentile, respectively. The estimated Spearman correlation coefficient between the physician score and treatment plan percentile was 0.53 ( Conclusions: Our scoring system correlates with physician ratings while providing intuitive visual feedback for identifying good treatment plan quality, thereby indicating its utility in the quality assurance process.

Identifiers

PMID38993196
PMCPMC11233889

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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.