The Multidimensional Assessment for Pediatric Patients in Radiotherapy (M.A.P.-RT) Tool for Customized Treatment Preparation: RADAR Project
Open accessAbstract
Aims: Pediatric patients may experience considerable distress during radiotherapy. Combining psychological interventions with standard therapies can reduce the need for sedation. The RADAR Project aims to use a systematic method of recording data that can reveal patients' difficulties and fragility during treatment. In this context, the aim of our study was to investigate the ability of a multidimensional assessment tool (M.A.P.-RT schedule) to predict the need for sedation during radiotherapy. The schedule, which is administered during the first evaluation, was created to collect information on patients and their families in a standardized way. Materials and Methods: The study enrolled pediatric patients (aged 0–18 years or 18–21 with cognitive impairment). Data were collected by means of the M.A.P.-RT module; this explores various thematic areas, and is completed by the radiation oncologist, psychologist and nurse during their first evaluation. Features were selected by means of the Boruta method (random forest classifier), and the totals of the significant partial scores on each subsection of the module were inserted into a logistic model in order to test for their correlation with the use of anesthesia and with the frequency of psychological support. The results of logistic regression (LR) were used to identify the best predictors. The AUC was used to identify the best threshold for the scores in the evaluation. Results: A total of 99 patients were considered for this analysis. The feature that best predicted both the need for anesthesia and the frequency of psychological support was the total score (TS), the AUC of the ROC being 0.9875 for anesthesia and 0.8866 for psychological support. Conclusion: During the first evaluation, the M.A.P.-RT form can predict the need for anesthesia in pediatric patients, and is a potential tool for personalizing therapeutic and management procedures.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In studies where nurses did not lead, nurses were actively involved by identifying eligible cancer patients, undertaking clinical assessments or interviews, or analysing oncological patient data to identify clinical issues to compare to the outputs of a predictive model.
“In these studies, nurses were actively involved by identifying eligible cancer patients for a study, undertaking clinical assessments or interviews as part of the data collection process, or analysing oncological patient data to identify clinical issues to compare to the outputs of a predictive model (Olling et al., 2018;Chiesa et al., 2021;Günther et al., 2022).”
From The application and use of artificial intelligence in cancer nursing: A systematic review (2024) · cites this paper as Chiesa et al., 2021
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 30 · Cited by 13
- Authors
- Chiesa, S., Marconi, E., Dinapoli, N., Sanfilippo, M. Z., Ruggiero, A., Mastronuzzi, A., Panza, G., Serra, A., Massaccesi, M., Cacchione, A., Beghella Bartoli, F., Chieffo, D. P. R., Gambacorta, M. A., Valentini, V., & Balducci, M.
- Affiliations
- Agostino Gemelli University Polyclinic (IT)
- Università Cattolica del Sacro Cuore (IT)
- Bambino Gesù Children's Hospital (IT)
- Corresponding author
- Sanfilippo, Maria Zoe
- ORCID
- Venue
- Frontiers in Oncology
- Publisher
- Frontiers Media SA
- Published
- 2021-03-29
- Volume
- 11
- Pages
- 621690-621690
- ISSN
- 2234-943X (ISSN-L)
- PMC
- PMC8039366
- OpenAlex
- W3140610630
- Cited by
- 13
- References
- 30
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 2 · 2023: 5 · 2022: 1
- FWCI
- 1.98
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Oncology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- PubliCatt (Università Cattolica del Sacro Cuore) (submittedVersion, other-oa)
- Topics
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pediatric Pain Management Techniques
- Social Sciences › Psychology › Social Psychology › Music Therapy and Health
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Childhood Cancer Survivors' Quality of Life
- Keywords
- pediatric radiotherapy, psychological distress, psychological support, treatment planning, cognitive impairment, RADAR project
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
