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Utilizing risk prediction tools such as nomograms may be beneficial in predicting severe oral complications such as mucositis.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>A study was performed using the National Inpatient Samples Database 2018 to investigate individuals admitted to the hospital for autologous HSCT. The nomogram tool was employed to predict oral ulcerative mucositis (UM), utilizing a logistic regression model with the variables age, gender, race, total body irradiation (TBI), and fluid and electrolyte disorders (fed), and further we applied our findings in 2021 autologous HSCT cohorts and 2018 allogenic HSCT cohorts.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>A total of 1560 patients who encountered UM were identified among 10,700 patients who underwent HSCT. The analysis showed that a 30-year-old White female patient who undergoes HSCT has a 28.2% risk of developing UM, 95%CI: 17.1\u201342.9%, who also undertook TBI, and had fed. On the other hand, a 20-year-old White female patient who undergoes HSCT has a risk score of 28.9% (95%CI: 17.6\u201346.0%), who also underwent TBI, and had fed. Additionally, Black female patient with TBI and fed of the same age of 20 or 30 who undergoes HSCT along with TBI has a risk score of 29.3% (95%CI: 17.3\u201345.1%), and 27.7%; 95%CI: 16.8\u201342.0%. The application in 2021 and 2018 cohorts showed similar trends, UM risk higher in allogenic cohorts with 47.2% risk (95%CI: 37.7\u201357.09%) in a White female, having weight loss and TBI.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>This report shows that younger age group, females, Whites, and those who are expected to receive TBI and having fed could be considered to be at a higher risk for developing severe mucositis. Thus, routine use of nomogram can help identify those requiring enhanced preventive oral care for reducing the oral complications such as UM.\n<\/jats:p>\n          <\/jats:sec>","DOI":"10.1007\/s00520-025-09691-4","type":"journal-article","created":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T17:15:13Z","timestamp":1751390113000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Guided supportive care may benefit from predicting cancer treatment-induced toxicity\u2014a methodology paper on utilization of nomograms to predict severe oral mucositis, Part I"],"prefix":"10.1007","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1033-6627","authenticated-orcid":false,"given":"Poolakkad S.","family":"Satheeshkumar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joel B.","family":"Epstein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deepshikha","family":"Kewlani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roberto","family":"Pili","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,1]]},"reference":[{"key":"9691_CR1","unstructured":"Bell A, Kasi A (2023) Oral mucositis. 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