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Using a Weekly Patient-Reported Outcome Questionnaire to Track Acute Toxicity in Patients Undergoing Pelvic Radiotherapy for Gynecologic Cancers

There are limited patient-reported outcome (PRO) data tracking changes in toxicity in patients actively undergoing radiotherapy. Between 2015–2019, acute toxicity was prospectively measured in 698 patients undergoing a 5-week course of pelvic radiotherapy for gynecologic cancers using a weekly PRO q...

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Detalles Bibliográficos
Autores principales: Chan, Matthew, Olson, Robert, Lapointe, Vincent, Hamm, Jeremy, Bachand, Francois, Holloway, Caroline, Parsons, Christina, Lim, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140006/
https://www.ncbi.nlm.nih.gov/pubmed/35621660
http://dx.doi.org/10.3390/curroncol29050270
Descripción
Sumario:There are limited patient-reported outcome (PRO) data tracking changes in toxicity in patients actively undergoing radiotherapy. Between 2015–2019, acute toxicity was prospectively measured in 698 patients undergoing a 5-week course of pelvic radiotherapy for gynecologic cancers using a weekly PRO questionnaire. Our questionnaire was able detect a pattern of onset and resolution of acute gastrointestinal (GI) and genitourinary (GU) toxicity in 27 out of 32 questions. Logistic regression analysis showed that increasing GI and GU toxicity at week 2 could predict for severe toxicity at week 5. However, due to a low number of severe events, univariate results could not be productively added to a multivariate model. We observed a >70% response rate for all sections of the questionnaire, except for questions on sexual and vaginal health, which had a 13% average response rate. By demonstrating that PRO data can be used to track acute toxicity during radiotherapy, there is a need to further examine how this tool may be implemented in the clinic to provide complex, adaptive care, such as early side effect management, and modifying radiation delivery in real-time.