Cargando…

Development of prediction tools for diarrhea and rash in breast cancer patients receiving lapatinib in combination with capecitabine

Lapatinib and capecitabine (L-CAP) is effective in HER-2 positive patients with metastatic breast cancer (MBC). However, moderate to severe diarrhea and rash (≥ grade 2) are problematic dose limiting toxicities. Since risk may vary over the course of therapy, we developed repeated measures models to...

Descripción completa

Detalles Bibliográficos
Autores principales: Dranitsaris, George, Lacouture, Mario E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4173070/
https://www.ncbi.nlm.nih.gov/pubmed/25216762
http://dx.doi.org/10.1007/s10549-014-3126-0
_version_ 1782336132207345664
author Dranitsaris, George
Lacouture, Mario E.
author_facet Dranitsaris, George
Lacouture, Mario E.
author_sort Dranitsaris, George
collection PubMed
description Lapatinib and capecitabine (L-CAP) is effective in HER-2 positive patients with metastatic breast cancer (MBC). However, moderate to severe diarrhea and rash (≥ grade 2) are problematic dose limiting toxicities. Since risk may vary over the course of therapy, we developed repeated measures models to predict the risk of ≥ grade 2 diarrhea and rash prior to each cycle of L-CAP. Data from 197 patients who received the L-CAP as part of a clinical trial were reviewed (Cameron, Breast Cancer Res Treat 112:533–543, 2008). Generalized estimating equations were used to develop the risk models using a backward elimination process. Risk scoring algorithms were then derived from the final model coefficients. Finally, a receiver operating characteristic curve (ROC) analysis was undertaken to measure the predictive accuracy of the scoring algorithms. Patient age, presence of skin metastases at baseline, treatment being initiated in the spring, earlier cycles, and grade I diarrhea in the prior cycle were identified as being significant predictors for ≥ grade 2 diarrhea. The ROC analysis indicated good predictive accuracy for the diarrhea algorithm with an area under the curve of 0.78 (95 %CI: 0.72–0.82). Prior to each cycle of therapy, patients with risk scores > 125 units would be considered at high risk for developing ≥ grade 2 diarrhea. A similar prediction index was also derived in the case of ≥ grade 2 rash. Our models provide patient-specific risk information that could be helpful in assessing the risks and benefits of L-CAP in the MBC patients.
format Online
Article
Text
id pubmed-4173070
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Springer US
record_format MEDLINE/PubMed
spelling pubmed-41730702014-09-26 Development of prediction tools for diarrhea and rash in breast cancer patients receiving lapatinib in combination with capecitabine Dranitsaris, George Lacouture, Mario E. Breast Cancer Res Treat Epidemiology Lapatinib and capecitabine (L-CAP) is effective in HER-2 positive patients with metastatic breast cancer (MBC). However, moderate to severe diarrhea and rash (≥ grade 2) are problematic dose limiting toxicities. Since risk may vary over the course of therapy, we developed repeated measures models to predict the risk of ≥ grade 2 diarrhea and rash prior to each cycle of L-CAP. Data from 197 patients who received the L-CAP as part of a clinical trial were reviewed (Cameron, Breast Cancer Res Treat 112:533–543, 2008). Generalized estimating equations were used to develop the risk models using a backward elimination process. Risk scoring algorithms were then derived from the final model coefficients. Finally, a receiver operating characteristic curve (ROC) analysis was undertaken to measure the predictive accuracy of the scoring algorithms. Patient age, presence of skin metastases at baseline, treatment being initiated in the spring, earlier cycles, and grade I diarrhea in the prior cycle were identified as being significant predictors for ≥ grade 2 diarrhea. The ROC analysis indicated good predictive accuracy for the diarrhea algorithm with an area under the curve of 0.78 (95 %CI: 0.72–0.82). Prior to each cycle of therapy, patients with risk scores > 125 units would be considered at high risk for developing ≥ grade 2 diarrhea. A similar prediction index was also derived in the case of ≥ grade 2 rash. Our models provide patient-specific risk information that could be helpful in assessing the risks and benefits of L-CAP in the MBC patients. Springer US 2014-09-13 2014 /pmc/articles/PMC4173070/ /pubmed/25216762 http://dx.doi.org/10.1007/s10549-014-3126-0 Text en © The Author(s) 2014 https://creativecommons.org/licenses/by-nc/4.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Epidemiology
Dranitsaris, George
Lacouture, Mario E.
Development of prediction tools for diarrhea and rash in breast cancer patients receiving lapatinib in combination with capecitabine
title Development of prediction tools for diarrhea and rash in breast cancer patients receiving lapatinib in combination with capecitabine
title_full Development of prediction tools for diarrhea and rash in breast cancer patients receiving lapatinib in combination with capecitabine
title_fullStr Development of prediction tools for diarrhea and rash in breast cancer patients receiving lapatinib in combination with capecitabine
title_full_unstemmed Development of prediction tools for diarrhea and rash in breast cancer patients receiving lapatinib in combination with capecitabine
title_short Development of prediction tools for diarrhea and rash in breast cancer patients receiving lapatinib in combination with capecitabine
title_sort development of prediction tools for diarrhea and rash in breast cancer patients receiving lapatinib in combination with capecitabine
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4173070/
https://www.ncbi.nlm.nih.gov/pubmed/25216762
http://dx.doi.org/10.1007/s10549-014-3126-0
work_keys_str_mv AT dranitsarisgeorge developmentofpredictiontoolsfordiarrheaandrashinbreastcancerpatientsreceivinglapatinibincombinationwithcapecitabine
AT lacouturemarioe developmentofpredictiontoolsfordiarrheaandrashinbreastcancerpatientsreceivinglapatinibincombinationwithcapecitabine