Gastrointestinal mucositis.

Dorothy M K Keefe; Rachel J Gibson; Martin Hauer-Jensen

doi:10.1053/j.soncn.2003.10.007

Home/Archive/PubMed

PubMed · 15038516

Gastrointestinal mucositis.

Dorothy M K Keefe·Rachel J Gibson·Martin Hauer-Jensen

View original source ↗Export metadata ↓

Abstract

OBJECTIVE: To review the management of radiotherapy- and chemotherapy-induced gastrointestinal mucositis. DATA SOURCE: Articles and research studies. CONCLUSION: Gastrointestinal damage is becoming a common dose-limiting toxicity. However, there is only limited research into the mechanism and possible treatment of this toxicity. IMPLICATIONS FOR NURSING PRACTICE: It is important to document the frequency and severity of gastrointestinal mucositis, and to alleviate symptoms wherever possible.

Explore related subjects

Antineoplastic Agents Gastrointestinal Diseases Humans Mouth Mucosa Neoplasms Nurse's Role Nursing Assessment Oncology Nursing Radiotherapy Stomatitis Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.Review

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Dorothy M K Keefe, Rachel J Gibson, Martin Hauer-Jensen. 2004. Gastrointestinal mucositis.. https://doi.org/10.1053/j.soncn.2003.10.007

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2021

Deep generative neural network for accurate drug response imputation.

Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outcome. In this study, we develop a deep variational autoencoder (VAE) model to compress thousands of genes into latent vectors in a low-dimensional space. We then demonstrate that these encoded vectors could accurately impute drug response, outperform standard signature-gene based approaches, and appropriately control the overfitting problem. We apply rigorous quality assessment and validation, including assessing the impact of cell line lineage, cross-validation, cross-panel evaluation, and application in independent clinical data sets, to warrant the accuracy of the imputed drug response in both cell lines and cancer samples. Specifically, the expression-regulated component (EReX) of the observed drug response achieves high correlation across panels. Using the well-trained models, we impute drug response of The Cancer Genome Atlas data and investigate the features and signatures associated with the imputed drug response, including cell line origins, somatic mutations and tumor mutation burdens, tumor microenvironment, and confounding factors. In summary, our deep learning method and the results are useful for the study of signatures and markers of drug response.

Antineoplastic Agents↗

PubMed2008

Favorable response of intraommaya topotecan for leptomeningeal metastasis of neuroblastoma after intravenous route failure.

A 3-year-old male, diagnosed with stage 4 neuroblastoma, developed recurrent leptomeningeal metastasis after multi-modality treatment including multi-agent chemotherapy, surgery, high dose chemotherapy plus stem cell rescue, cis-retinoic acid and intravenous (IV) topotecan. He then received intraommaya (IO) topotecan three times weekly (maximum dose; 0.4 mg). A complete response was achieved by a resolution of malignant cells in cerebrospinal fluid and resolution leptomeningeal enhancement by brain MRI. Treatment toxicities included low-grade fever and minimal headache. The duration of treatment response from IO topotecan was 18 weeks. The survival time from CNS recurrence in this patient was 13 months. We suggest IO topotecan be considered for neoplastic meningitis of tumors with known sensitivity to topotecan.

Antineoplastic Agents↗

PubMed2008

Mobilization of Ph chromosome-negative peripheral blood stem cells in a child with chronic myeloid leukemia after imatinib-induced complete molecular remission.

Chronic myelogenous leukemia (CML) is rare in the pediatric population. Allogeneic stem cell transplant remains the only curative therapy; however, identifying a fully matched donor is not always possible. Imatinib mesylate has been shown to induce hematologic and cytogenetic response in adults and children with CML. We describe a child who achieved molecular remission with imatinib mesylate. BCR-ABL negative peripheral blood stem cells (PBSC) were successfully collected after mobilization with filgrastim.

Antineoplastic Agents↗