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Development and validation of a prediction model of poor performance status and severe symptoms over time in cancer patients (PROVIEW+).
- Source :
- Palliative Medicine; Oct2021, Vol. 35 Issue 9, p1713-1723, 11p
- Publication Year :
- 2021
-
Abstract
- Background: Predictive cancer tools focus on survival; none predict severe symptoms. Aim: To develop and validate a model that predicts the risk for having low performance status and severe symptoms in cancer patients. Design: Retrospective, population-based, predictive study Setting/Participants: We linked administrative data from cancer patients from 2008 to 2015 in Ontario, Canada. Patients were randomly selected for model derivation (60%) and validation (40%). Using the derivation cohort, we developed a multivariable logistic regression model to predict the risk of an outcome at 6 months following diagnosis and recalculated after each of four annual survivor marks. Model performance was assessed using discrimination and calibration plots. Outcomes included low performance status (i.e. 10–30 on Palliative Performance Scale), severe pain, dyspnea, well-being, and depression (i.e. 7–10 on Edmonton Symptom Assessment System). Results: We identified 255,494 cancer patients (57% female; median age of 64; common cancers were breast (24%); and lung (13%)). At diagnosis, the predicted risk of having low performance status, severe pain, well-being, dyspnea, and depression in 6-months is 1%, 3%, 6%, 13%, and 4%, respectively for the reference case (i.e. male, lung cancer, stage I, no symptoms); the corresponding discrimination for each outcome model had high AUCs of 0.807, 0.713, 0.709, 0.790, and 0.723, respectively. Generally these covariates increased the outcome risk by >10% across all models: lung disease, dementia, diabetes; radiation treatment; hospital admission; pain; depression; transitional performance status; issues with appetite; or homecare. Conclusions: The model accurately predicted changing cancer risk for low performance status and severe symptoms over time. [ABSTRACT FROM AUTHOR]
- Subjects :
- DEMENTIA risk factors
MENTAL depression risk factors
DIABETES risk factors
CANCER patient psychology
EXPERIMENTAL design
WELL-being
APPETITE
PREDICTIVE tests
PAIN
RESEARCH methodology
RESEARCH methodology evaluation
FUNCTIONAL status
LUNG diseases
RETROSPECTIVE studies
LUNG tumors
PATIENTS
RISK assessment
SEVERITY of illness index
DYSPNEA
HOSPITAL admission & discharge
TREATMENT effectiveness
DESCRIPTIVE statistics
PREDICTION models
STATISTICAL sampling
LOGISTIC regression analysis
STATISTICAL models
BREAST tumors
DISEASE risk factors
DISEASE complications
Subjects
Details
- Language :
- English
- ISSN :
- 02692163
- Volume :
- 35
- Issue :
- 9
- Database :
- Complementary Index
- Journal :
- Palliative Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 153180597
- Full Text :
- https://doi.org/10.1177/02692163211019302