Evidence map›Paper›PMID 38831192›Full record

ArticleClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2024

Clinical effects of re-evaluating a lung SBRT failure mode and effects analysis in a radiotherapy department.

Sergi Benavente, Alexandra Giraldo, Alejandro Seoane, Mónica Ramos, Ramona Vergés

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Article in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  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

5 authors.

Sergi BenaventeDepartment of Radiation Oncology, Vall d'Hebron University Hospital Campus, Barcelona, Spain. sergi.benavente@vallhebron.cat.ORCID http://orcid.org/0000-0002-2700-3522
Alexandra GiraldoDepartment of Radiation Oncology, Vall d'Hebron University Hospital Campus, Barcelona, Spain.
Alejandro SeoaneDepartment of Medical Physics and Radiation Protection, Vall d'Hebron University Hospital Campus, Barcelona, Spain.
Mónica RamosDepartment of Radiation Oncology, Vall d'Hebron University Hospital Campus, Barcelona, Spain.
Ramona VergésDepartment of Radiation Oncology, Vall d'Hebron University Hospital Campus, Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe increasing complexity of radiation treatments can hinder its clinical success. This study aimed to better understand evolving risks by re-evaluating a Failure Mode and Effects Analysis (FMEA) in lung SBRT.

methodsAn experienced multidisciplinary team conducted an FMEA and made a reassessment 3 years later. A process map was developed with potential failure modes (FMs) identified. High-risk FMs and their possible causes and corrective actions were determined. The initial FMEA analysis was compared to gain a deeper perspective.

resultsWe identified 232 FMs. The high-risk processes were plan approval, target contouring, and patient evaluation. The corrective measures were based on stricter standardization of plan approval, pre-planning peer review, and a supporting pretreatment checklist, which substantially reduced the risk priority number in the revised FMEA. In the FMEA reassessment, we observed that the increased complexity and number of patients receiving lung SBRT conditioned a more substantial presence of human factors and communication errors as causal conditions and a potential wrong dose as a final effect.

conclusionsConducting a lung SBRT FMEA analysis has identified high-risk conditions that have been effectively mitigated in an FMEA reanalysis. Plan approval has shown to be a weak link in the process. The increasing complexity of treatments and patient numbers have shifted causal factors toward human failure and communication errors. The potential of a wrong dose as a final effect augments in this scenario. We propose that digital and artificial intelligence options are needed to mitigate potential errors in high-complexity and high-risk RT scenarios.

Indexed as

Healthcare Failure Mode and Effect AnalysisLung NeoplasmsRadiosurgeryHumansRadiotherapy Planning, Computer-AssistedRadiotherapyRisk analysisSafetySBRT

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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.