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Med. Biol."],"published-print":{"date-parts":[[2026,7,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Background.<\/jats:italic>\n                    FAST-Forward trial has established the characteristics of 5-fraction breast cancer treatments that produce the same local cancer control as the standard 15-fraction schedule, while maintaining its safety level.\n                    <jats:italic>Aim.<\/jats:italic>\n                    To adapt a Monte Carlo (MC) simulation tool, previously used to study the surgery-to-radiotherapy delay effect on head and neck tumor control, to simulate breast cancer trials and apply it to reproduce FAST-Forward trial outcomes.\n                    <jats:italic>Methods.<\/jats:italic>\n                    The updated MC tool incorporates the linear-quadratic model for estimating the cell survival fraction for different dose fractions, as well as a component that simulates tumor bed boost. Model parameters have been evaluated for the three FAST-Forward trial arms.\n                    <jats:italic>Results.<\/jats:italic>\n                    The importance of the number of patients in the samples and the role played by the tumor bed boost have been studied. Sample size is a key factor, as the actual number of patients participating in the trial introduces uncertainties that could explain the paradox that the 26 Gy regimen achieves greater tumor control than the 27 Gy regimen. The boost model implemented has showed up as a consistent and robust procedure to simulate the empirical situation.\n                    <jats:italic>Conclusions.<\/jats:italic>\n                    The MC tool provides a good description of the trends observed in the trial, making it a very useful tool for investigating the characteristics of any treatment regimen. The findings further suggest that the observed variability across treatment arms may be influenced, at least in part, by sample size effects, which should be taken into account when interpreting the outcomes.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/ae8737","type":"journal-article","created":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T22:52:33Z","timestamp":1783464753000},"page":"145009","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Monte Carlo simulation tool to analyze breast cancer trial outcomes: application to FAST-Forward trial"],"prefix":"10.1088","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4813-6472","authenticated-orcid":true,"given":"Laura","family":"Quintero","sequence":"first","affiliation":[{"name":"Universidad de Granada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3257-360X","authenticated-orcid":false,"given":"Dami\u00e1n","family":"Guirado","sequence":"additional","affiliation":[{"name":"Unidad de Radiof\u00edsica, Hospital Universitario Cl\u00ednico San Cecilio"},{"name":"Instituto de Investigaci\u00f3n Biosanitaria ibs.GRANADA"},{"name":"CIBER de Epidemiolog\u00eda y Salud P\u00fablica (CIBERESP)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1962-6217","authenticated-orcid":true,"given":"Antonio M","family":"Lallena","sequence":"additional","affiliation":[{"name":"Universidad de Granada"},{"name":"Instituto de Investigaci\u00f3n Biosanitaria ibs.GRANADA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,7,20]]},"reference":[{"key":"pmbae8737bib1","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.radonc.2011.06.026","type":"journal-article","article-title":"First results of the randomised UK FAST trial of radiotherapy hypofractionation for treatment of early breast cancer (CRUKE\/04\/015)","volume":"100","author":"Agrawal","year":"2011","journal-title":"Radiother. 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