Work

Predicting acute odynophagia during lung cancer radiotherapy using observations derived from patient-centred nursing care

Year: 2018

Type: article

Abstract: During radiotherapy, lung cancer patients commonly experience pain while swallowing (odynophagia) of food and drink. Observations from patient-centred nursing practice have been used to generate predictive models for odynophagia needing prescription pain medication during external beam lung radiotherapy for non-small cell and small-cell lung cancer. Three multivariate logistic models were evaluated in repeat cross-validation: a manual-stepwise model and two supervised machine learning models. Overall predictive performance was good. Correct classification rates ranged from 0.82 to 0.84, and areas under the receiver operator curve ranged from 0.83 to 0.85. Model sensitivity (range: 0.92-0.97) was higher than model specificity (range: 0.58-0.63). Further validation of the models in clinical context is required. A predictive model for pain medication for odynophagia prior to commencement of radiotherapy would support Radiotherapy Technologists Nurses (RTNs) in directing nursing interventions towards patients at risk.

Source: Technical Innovations & Patient Support in Radiation Oncology

DOI: 10.1016/j.tipsro.2018.01.002

Authors: Karina Olling, Dorte Wendelboe Nyeng, Leonard Wee

Institution: Vejle Sygehus

Language: English

Topic: Dysphagia Assessment and Management

Subfield: Speech and Hearing

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,410