Evidence map›Paper›PMID 34917780›Full record

ArticlePhysics and imaging in radiation oncology2021

Combining inter-observer variability, range and setup uncertainty in a variance-based sensitivity analysis for proton therapy.

Jan Hofmaier, Franziska Walter, Indrawati Hadi, Maya Rottler, Rieke von Bestenbostel, George Dedes, Katia Parodi, Maximilian Niyazi, Claus Belka, Florian Kamp

Open access · goldAbstract read
In one paragraph

Article in Physics and imaging in radiation oncology, 2021. 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
1.0field-weighted citation impact, top 21% 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, 8 citations in OpenAlex.

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  5. Five years, 20 volumes and 300 publications ofPhysics and imaging in radiation oncology · 2022
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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

10 authors at 3 institutions in 1 country.

Jan HofmaierDepartment of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.
Franziska WalterDepartment of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.
Indrawati HadiDepartment of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.
Maya RottlerDepartment of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.
Rieke von BestenbostelDepartment of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.
George DedesDepartment of Medical Physics, Faculty of Physics, LMU Munich, Munich, Germany.
Katia ParodiDepartment of Medical Physics, Faculty of Physics, LMU Munich, Munich, Germany.
Maximilian NiyaziDepartment of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.
Claus BelkaDepartment of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.
Florian KampDepartment of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.
LMU Klinikum · DELudwig-Maximilians-Universität München · DEUniversity Hospital Cologne · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Margin concepts in proton therapy aim to ensure full dose coverage of the clinical target volume (CTV) in presence of setup and range uncertainty. Due to inter-observer variability (IOV), the CTV itself is uncertain. We present a framework to evaluate the combined impact of IOV, setup and range uncertainty in a variance-based sensitivity analysis (SA). For ten patients with skull base meningioma, the mean calculation time to perform the SA including 1.6 × 10

Indexed as

Inter-observer variabilityProton therapyRange uncertaintySensitivity analysisSetup uncertainty

Identifiers

PMID34917780
PMCPMC8645917
OpenAlexW4200481236

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.