Evidence map›Paper›PMID 36578278›Full record

ArticleAdvances in radiation oncology

Development and Clinical Implementation of an Automated Virtual Integrative Planner for Radiation Therapy of Head and Neck Cancer.

Elizabeth M Jaworski, Michelle L Mierzwa, Karen A Vineberg, John Yao, Jennifer L Shah, Caitlin A Schonewolf, Dale Litzenberg, Laila A Gharzai, Martha M Matuszak, Kelly C Paradis and 8 more

Open access · goldAbstract read
In one paragraph

Article in Advances in radiation oncology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Survey in radiation oncology departments in Germany, Austria, and Switzerland: state of digitalization by 2023.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2024
    Article
  4. Article
  5. 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

18 authors at 1 institution in 1 country.

Elizabeth M JaworskiDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Michelle L MierzwaDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Karen A VinebergDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
John YaoDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Jennifer L ShahDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Caitlin A SchonewolfDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Dale LitzenbergDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Laila A GharzaiDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Martha M MatuszakDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Kelly C ParadisDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Ashley DoughertyDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Pamela BurgerDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Daniel TatroDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
George Spencer ArnouldDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Jean M MoranDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Choonik LeeDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Avraham EisbruchDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Charles S MayoDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
University of Michigan · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Head and neck (HN) radiation (RT) treatment planning is complex and resource intensive. Deviations and inconsistent plan quality significantly affect clinical outcomes. We sought to develop a novel automated virtual integrative (AVI) knowledge-based planning application to reduce planning time, increase consistency, and improve baseline quality. Methods and Materials: An in-house write-enabled script was developed from a library of 668 previously treated HN RT plans. Prospective hazard analysis was performed, and mitigation strategies were implemented before clinical release. The AVI-planner software was retrospectively validated in a cohort of 52 recent HN cases. A physician panel evaluated planning limitations during initial deployment, and feedback was enacted via software refinements. A final second set of plans was generated and evaluated. Kolmogorov-Smirnov test in addition to generalized evaluation metric and weighted experience score were used to compare normal tissue sparing between final AVI planner versus respective clinically treated and historically accepted plans. A Results: Initially, 86% of plans were acceptable to treat, with 10% minor and 4% major revisions or rejection recommended. Variability was noted in plan quality among HN subsites, with high initial quality for oropharynx and oral cavity plans. Plans needing revisions were comprised of sinonasal, nasopharynx, P-16 negative squamous cell carcinoma unknown primary, or cutaneous primary sites. Normal tissue sparing varied within subsites, but AVI planner significantly lowered mean larynx dose (median, 18.5 vs 19.7 Gy; Conclusions: AVI planner reliably generated clinically acceptable RT plans for oral cavity, salivary, oropharynx, larynx, and hypopharynx cancers. Physician-driven iterative learning processes resulted in favorable evolution in HN RT plan quality with significant time savings and improved consistency using AVI planner.

Identifiers

PMID36578278
PMCPMC9791598
OpenAlexW4285680250

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.