Development and validation of a prediction model of poor performance status and severe symptoms over time in cancer patients (PROVIEW+). (October 2021)
- Record Type:
- Journal Article
- Title:
- Development and validation of a prediction model of poor performance status and severe symptoms over time in cancer patients (PROVIEW+). (October 2021)
- Main Title:
- Development and validation of a prediction model of poor performance status and severe symptoms over time in cancer patients (PROVIEW+)
- Authors:
- Seow, Hsien
Tanuseputro, Peter
Barbera, Lisa
Earle, Craig C
Guthrie, Dawn M
Isenberg, Sarina R
Juergens, Rosalyn A
Myers, Jeffrey
Brouwers, Melissa
Tibebu, Semra
Sutradhar, Rinku - Other Names:
- Morin Lucas guest-editor.
Onwuteaka-Philipsen Bregje guest-editor. - 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%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. … (more)
- Is Part Of:
- Palliative medicine. Volume 35:Number 9(2021)
- Journal:
- Palliative medicine
- Issue:
- Volume 35:Number 9(2021)
- Issue Display:
- Volume 35, Issue 9 (2021)
- Year:
- 2021
- Volume:
- 35
- Issue:
- 9
- Issue Sort Value:
- 2021-0035-0009-0000
- Page Start:
- 1713
- Page End:
- 1723
- Publication Date:
- 2021-10
- Subjects:
- Cancer -- prognosis -- palliative care -- logistic model -- ADL -- depression -- dyspnea -- pain
Pain -- Treatment -- Periodicals
Cancer -- Palliative treatment -- Periodicals
Palliative Care -- Periodicals
Palliatieve behandeling
616.029 - Journal URLs:
- http://pmj.sagepub.com/ ↗
http://www.uk.sagepub.com/home.nav ↗
http://www.ingenta.com/journals/browse/arn/pm ↗ - DOI:
- 10.1177/02692163211019302 ↗
- Languages:
- English
- ISSNs:
- 0269-2163
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17630.xml