The potential for a generally applicable mapping model between QLQ-C30 and SF-6D in patients with different cancers: a comparison of regression-based methods.
Purpose: To establish and compare generalized or "global" mapping relationships between QLQ-C30 and SF-6D, applicable across different cancer types.Methods: Patients (N = 671) with breast, myeloma, colorectal, lymphoma, bone marrow, prostate, lung and gastroenteric cancer were randomly split into es...
| Publicado en: | Quality of Life Research Vol. 24; no. 6; pp. 1535 - 1545 |
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| Autor principal: | |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Jun2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109744293&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109744293 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09629343 GPQ jtl: Quality of Life Research issn: 09629343 maglogo: N pubinfo: dt: Jun2015 vid: 24 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 109744293 NLM25391489 2013040573 10.1007/s11136-014-0857-7 NLM25391489 109744293 ppf: 1535 ppct: 10 formats: fmt: @attributes: type: P tig: atl: The potential for a generally applicable mapping model between QLQ-C30 and SF-6D in patients with different cancers: a comparison of regression-based methods. aug: au: Kontodimopoulos, Nick sug: ab: Purpose: To establish and compare generalized or "global" mapping relationships between QLQ-C30 and SF-6D, applicable across different cancer types.Methods: Patients (N = 671) with breast, myeloma, colorectal, lymphoma, bone marrow, prostate, lung and gastroenteric cancer were randomly split into estimation (75%) and validation (25%) datasets. SF-6D was estimated from QLQ-C30 scores via ordinary least squares, generalized linear models and median (least-absolute deviations) regression approaches, and with Bayesian additive regression kernels. Predictive ability was assessed with root mean square error, mean absolute error and proportions of predictions with absolute errors >0.05 and >0.1, whereas explanatory power with adjusted R (2) or equivalent fit measures. Two external samples (breast and colorectal cancer) were used to further test the models.Results: The QLQ-C30's global health item, the physical, emotional and social functioning scales, and the fatigue, pain and diarrhea symptom scales were significant predictors (p < 0.05 or better) in all models. Negligible deviations in models' performance were observed. All models overpredicted utilities for patients in worst health and underpredicted them for those in better health (p < 0.01 or better). Regarding external validation, performance was better in the colorectal cancer than in the breast cancer sample.Conclusions: This study has provided evidence to support the use of "global" mapping models to predict SF-6D utilities from QLQ-C30 in patients with different cancers. Testing with diverse patient samples is required to confirm the generalizability (or not) of mapping models across cancer conditions. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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