Evidence map›Paper›PMID 33326695›Full record

ArticleJournal of applied clinical medical physics2021

Formulation of objective indices to quantify machine failure risk analysis for interruptions in radiotherapy.

Daisuke Kawahara, Hisashi Nakano, Akito Saito, Yusuke Ochi, Yasushi Nagata

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

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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

5 authors.

Daisuke KawaharaDepartment of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University, Hiroshima, Japan.
Hisashi NakanoDepartment of Radiation Oncology, Niigata University Medical and Dental Hospital, Niigata, Japan.
Akito SaitoDepartment of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University, Hiroshima, Japan.
Yusuke OchiRadiation Therapy Section, Department of Clinical Support, Hiroshima University Hospital, Hiroshima, Japan.
Yasushi NagataDepartment of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University, Hiroshima, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo evaluate the effect of interruption in radiotherapy due to machine failure in patients and medical institutions using machine failure risk analysis (MFRA). MATERIAL AND

methodsThe risk of machine failure during treatment is assigned to three scores (biological effect, B; occurrence, O; and cost of labor and repair parts, C) for each type of machine failure. The biological patient risk (BPR) and the economic institution risk (EIR) are calculated as the product of

resultThe multileaf collimator (MLC) fault has the highest BPR and second highest EIR. In particular, TrueBeam has a higher BPR and EIR for MLC failures. The total EIR in TrueBeam was significantly higher than that in Clinac iX. The minor interlock had the second highest BPR, whereas a smaller EIR. Meanwhile, the EIR for the LaserGuard fault was the highest, and that for the monitor chamber fault was the second highest. These machine failures occurred in TrueBeam. The BPR and EIR should be evaluated for each linac. Further, the sensitivity of the BPR, it decreased with higher

conclusionThe risk faced by patients and institutions in machine failure may be reduced using MFRA. ADVANCES IN KNOWLEDGE: For clinical radiotherapy, interruption can occur from unscheduled downtime with machine failures. Interruption causes sublethal damage repair. The current study evaluated the effect of interruption in radiotherapy owing to machine failure on patients and medical institutions using a new method, that is, machine failure risk analysis.

Indexed as

Particle AcceleratorsRadiotherapy, Intensity-ModulatedHumansRadiotherapy DosageRadiotherapy Planning, Computer-AssistedRisk Assessmentbiological dose calculationdowntimemachine failure

Identifiers

PMID33326695
PMCPMC7856522

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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.