TY - JOUR
T1 - Development and internal validation of prediction models for colorectal cancer survivors to estimate the 1-year risk of low health-related quality of life in multiple domains
AU - Révész, Dóra
AU - van Kuijk, Sander M.J.
AU - Mols, Floortje
AU - van Duijnhoven, Fränzel J.B.
AU - Winkels, Renate M.
AU - Hoofs, Huub
AU - Kant, IJ.
AU - Smits, Luc J.
AU - Breukink, Stéphanie O.
AU - van de Poll-Franse, Lonneke V.
AU - Kampman, Ellen
AU - Beijer, Sandra
AU - Weijenberg, Matty P.
AU - Bours, Martijn J.L.
PY - 2020/3/12
Y1 - 2020/3/12
N2 - Background: Many colorectal cancer (CRC) survivors experience persisting health problems post-treatment that compromise their health-related quality of life (HRQoL). Prediction models are useful tools for identifying survivors at risk of low HRQoL in the future and for taking preventive action. Therefore, we developed prediction models for CRC survivors to estimate the 1-year risk of low HRQoL in multiple domains. Methods: In 1458 CRC survivors, seven HRQoL domains (EORTC QLQ-C30: Global QoL; cognitive, emotional, physical, role, social functioning; fatigue) were measured prospectively at study baseline and 1 year later. For each HRQoL domain, scores at 1-year follow-up were dichotomized into low versus normal/high. Separate multivariable logistic prediction models including biopsychosocial predictors measured at baseline were developed for the seven HRQoL domains, and internally validated using bootstrapping. Results: Average time since diagnosis was 5 years at study baseline. Prediction models included both non-modifiable predictors (age, sex, socio-economic status, time since diagnosis, tumor stage, chemotherapy, radiotherapy, stoma, micturition, chemotherapy-related, stoma-related and gastrointestinal complaints, comorbidities, social inhibition/negative affectivity, and working status) and modifiable predictors (body mass index, physical activity, smoking, meat consumption, anxiety/depression, pain, and baseline fatigue and HRQoL scores). Internally validated models showed good calibration and discrimination (AUCs: 0.83-0.93). Conclusions: The prediction models performed well for estimating 1-year risk of low HRQoL in seven domains. External validation is needed before models can be applied in practice.
AB - Background: Many colorectal cancer (CRC) survivors experience persisting health problems post-treatment that compromise their health-related quality of life (HRQoL). Prediction models are useful tools for identifying survivors at risk of low HRQoL in the future and for taking preventive action. Therefore, we developed prediction models for CRC survivors to estimate the 1-year risk of low HRQoL in multiple domains. Methods: In 1458 CRC survivors, seven HRQoL domains (EORTC QLQ-C30: Global QoL; cognitive, emotional, physical, role, social functioning; fatigue) were measured prospectively at study baseline and 1 year later. For each HRQoL domain, scores at 1-year follow-up were dichotomized into low versus normal/high. Separate multivariable logistic prediction models including biopsychosocial predictors measured at baseline were developed for the seven HRQoL domains, and internally validated using bootstrapping. Results: Average time since diagnosis was 5 years at study baseline. Prediction models included both non-modifiable predictors (age, sex, socio-economic status, time since diagnosis, tumor stage, chemotherapy, radiotherapy, stoma, micturition, chemotherapy-related, stoma-related and gastrointestinal complaints, comorbidities, social inhibition/negative affectivity, and working status) and modifiable predictors (body mass index, physical activity, smoking, meat consumption, anxiety/depression, pain, and baseline fatigue and HRQoL scores). Internally validated models showed good calibration and discrimination (AUCs: 0.83-0.93). Conclusions: The prediction models performed well for estimating 1-year risk of low HRQoL in seven domains. External validation is needed before models can be applied in practice.
KW - Cancer survivors
KW - Colorectal cancer
KW - Internal validation
KW - Model development
KW - Prediction models
KW - Quality of life
UR - https://doi.org/10.6084/m9.figshare.c.4892781
U2 - 10.1186/s12911-020-1064-9
DO - 10.1186/s12911-020-1064-9
M3 - Article
C2 - 32164641
AN - SCOPUS:85081923845
SN - 1472-6947
VL - 20
JO - BMC Medical Informatics and Decision Making
JF - BMC Medical Informatics and Decision Making
M1 - 54
ER -