ArticlePloS one2017
Patients in palliative care-Development of a predictive model for anxiety using routine data.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- What gets measured in palliative care? A review and synthesis of routine data collection in 16 countries.Health policy OPEN · 2025Review
- Emergency palliative cancer care: anxiety and midazolam.BMC palliative care · 2025Article
- Predicting Anxiety in Routine Palliative Care Using Bayesian-Inspired Association Rule Mining.Frontiers in digital health · 2021Article
- The prevalence, grouping, and distribution of stressors and their association with anxiety among hospitalized patients.PloS one · 2021Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAnxiety is one of the most common psychological symptoms in patients in a palliative care situation. This study aims to develop a predictive model for anxiety using data from the standard documentation routine.
methodsData sets of palliative care patients collected by the German quality management benchmarking system called Hospice and Palliative Care Evaluation (HOPE) from 2007 to 2011 were randomly divided into a training set containing two-thirds of the data and a test set with the remaining one-third. We dichotomized anxiety levels, proxy rated by medical staff using the validated HOPE Symptom and Problem Checklist, into two groups with no or mild anxiety versus moderate or severe anxiety. Using the training set, a multivariable logistic regression model was developed by backward stepwise selection. Predictive accuracy was evaluated by the area under the receiver operating characteristic curve (AUC) based on the test set.
resultsAn analysis of 9924 data sets suggests a predictive model for anxiety in patients receiving palliative care which contains gender, age, ECOG, living situation, pain, nausea, dyspnea, loss of appetite, tiredness, need for assistance with activities of daily living, problems with organization of care, medication with sedatives/anxiolytics, antidepressants, antihypertensive drugs, laxatives, and antibiotics. It results in a fair predictive value (AUC = 0.72).
conclusionsRoutinely collected data providing individual-, disease- and therapy-related information contain valuable information that is useful for the prediction of anxiety risks in patients receiving palliative care. These findings could thus be advantageous for providing appropriate support for patients in palliative care settings and should receive special attention in future research.
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