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Article: Mapping the functional assessment of cancer therapy-general or -colorectal to SF-6D in Chinese patients with colorectal neoplasm

TitleMapping the functional assessment of cancer therapy-general or -colorectal to SF-6D in Chinese patients with colorectal neoplasm
Authors
Keywordscolorectal neoplasm
FACT-C
mapping
patient-reported outcomes
quality of life
SF-6D
Issue Date2012
PublisherWiley-Blackwell Publishing, Inc. The Journal's web site is located at http://www.wiley.com/bw/journal.asp?ref=1098-3015
Citation
Value In Health, 2012, v. 15 n. 3, p. 495-503 How to Cite?
AbstractObjectives: To map Functional Assessment of Cancer Therapy-General (FACT-G) and Functional Assessment of Cancer Therapy-Colorectal (FACT-C) subscale scores onto six-dimensional health state short form (derived from short form 36 health survey) (SF-6D) preference-based values in patients with colorectal neoplasm, with and without adjustment for clinical and demographic characteristics. These results can then be applied to studies that have used FACT-G or FACT-C to predict SF-6D utility values to inform economic evaluation. Methods: Ordinary least square regressions were estimated mapping FACT-G and FACT-C onto SF-6D by using cross-sectional data of 537 Chinese subjects with different stages of colorectal neoplasm. Mapping functions for SF-6D preference-based values were developed separately for FACT-G and FACT-C in four sequential models for addition of variables: 1) main-effect terms, 2) squared terms, 3) interaction terms, and 4) clinical and demographic variables. Predictive performance in each model was assessed by the R 2, adjusted R 2, predicted R 2, information criteria (Akaike information criteria and Bayesian information criteria), the root mean square error, the mean absolute error, and the proportions of absolute error within the threshold of 0.05 and 0.10. Results: Models including FACT variables and clinical and demographic variables had the best predictive performance measured by using R 2 (FACT-G: 59.98%; FACT-C: 60.43%), root mean square error (FACT-G: 0.086; FACT-C: 0.084), and mean absolute error (FACT-G: 0.065; FACT-C: 0.065). The FACT-C-based mapping function had better predictive ability than did the FACT-G-based mapping function. Conclusions: Models mapping FACT-G and FACT-C onto SF-6D reached an acceptable degree of precision. Mapping from the condition-specific measure (FACT-C) had better performance than did mapping from the general cancer measure (FACT-G). These mapping functions can be applied to FACT-G or FACT-C data sets to estimate SF-6D utility values for economic evaluation of medical interventions for patients with colorectal neoplasm. Further research assessing model performance in independent data sets and non-Chinese populations are encouraged. © 2012, International Society for Pharmacoeconomics and Outcomes Research (ISPOR).
Persistent Identifierhttp://hdl.handle.net/10722/152875
ISSN
2015 Impact Factor: 3.824
2015 SCImago Journal Rankings: 1.645
ISI Accession Number ID
Funding AgencyGrant Number
CRCG of the University of Hong Kong200907176135
Food and Health Bureau, HKSAR08090851
Funding Information:

Funding for this study was provided by Small Project Funding (Project code 200907176135) from CRCG of the University of Hong Kong and Health and Health Service Research Fund (HHSRF #08090851) of Food and Health Bureau, HKSAR.

References
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DC FieldValueLanguage
dc.contributor.authorWong, CKHen_HK
dc.contributor.authorLam, CLKen_HK
dc.contributor.authorRowen, Den_HK
dc.contributor.authorMcGhee, SMen_HK
dc.contributor.authorMa, KPen_HK
dc.contributor.authorLaw, WLen_HK
dc.contributor.authorPoon, JTCen_HK
dc.contributor.authorChan, Pen_HK
dc.contributor.authorKwong, DLWen_HK
dc.contributor.authorTsang, Jen_HK
dc.date.accessioned2012-07-16T09:51:05Z-
dc.date.available2012-07-16T09:51:05Z-
dc.date.issued2012en_HK
dc.identifier.citationValue In Health, 2012, v. 15 n. 3, p. 495-503en_HK
dc.identifier.issn1098-3015en_HK
dc.identifier.urihttp://hdl.handle.net/10722/152875-
dc.description.abstractObjectives: To map Functional Assessment of Cancer Therapy-General (FACT-G) and Functional Assessment of Cancer Therapy-Colorectal (FACT-C) subscale scores onto six-dimensional health state short form (derived from short form 36 health survey) (SF-6D) preference-based values in patients with colorectal neoplasm, with and without adjustment for clinical and demographic characteristics. These results can then be applied to studies that have used FACT-G or FACT-C to predict SF-6D utility values to inform economic evaluation. Methods: Ordinary least square regressions were estimated mapping FACT-G and FACT-C onto SF-6D by using cross-sectional data of 537 Chinese subjects with different stages of colorectal neoplasm. Mapping functions for SF-6D preference-based values were developed separately for FACT-G and FACT-C in four sequential models for addition of variables: 1) main-effect terms, 2) squared terms, 3) interaction terms, and 4) clinical and demographic variables. Predictive performance in each model was assessed by the R 2, adjusted R 2, predicted R 2, information criteria (Akaike information criteria and Bayesian information criteria), the root mean square error, the mean absolute error, and the proportions of absolute error within the threshold of 0.05 and 0.10. Results: Models including FACT variables and clinical and demographic variables had the best predictive performance measured by using R 2 (FACT-G: 59.98%; FACT-C: 60.43%), root mean square error (FACT-G: 0.086; FACT-C: 0.084), and mean absolute error (FACT-G: 0.065; FACT-C: 0.065). The FACT-C-based mapping function had better predictive ability than did the FACT-G-based mapping function. Conclusions: Models mapping FACT-G and FACT-C onto SF-6D reached an acceptable degree of precision. Mapping from the condition-specific measure (FACT-C) had better performance than did mapping from the general cancer measure (FACT-G). These mapping functions can be applied to FACT-G or FACT-C data sets to estimate SF-6D utility values for economic evaluation of medical interventions for patients with colorectal neoplasm. Further research assessing model performance in independent data sets and non-Chinese populations are encouraged. © 2012, International Society for Pharmacoeconomics and Outcomes Research (ISPOR).en_HK
dc.languageengen_US
dc.publisherWiley-Blackwell Publishing, Inc. The Journal's web site is located at http://www.wiley.com/bw/journal.asp?ref=1098-3015en_HK
dc.relation.ispartofValue in Healthen_HK
dc.subjectcolorectal neoplasmen_HK
dc.subjectFACT-Cen_HK
dc.subjectmappingen_HK
dc.subjectpatient-reported outcomesen_HK
dc.subjectquality of lifeen_HK
dc.subjectSF-6Den_HK
dc.titleMapping the functional assessment of cancer therapy-general or -colorectal to SF-6D in Chinese patients with colorectal neoplasmen_HK
dc.typeArticleen_HK
dc.identifier.emailLaw, WL: lawwl@hkucc.hku.hken_HK
dc.identifier.emailPoon, JTC: tcjensen@hkucc.hku.hken_HK
dc.identifier.authorityLaw, WL=rp00436en_HK
dc.identifier.authorityPoon, JTC=rp01603en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jval.2011.12.009en_HK
dc.identifier.pmid22583460-
dc.identifier.scopuseid_2-s2.0-84861174578en_HK
dc.identifier.hkuros200927en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84861174578&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume15en_HK
dc.identifier.issue3en_HK
dc.identifier.spage495en_HK
dc.identifier.epage503en_HK
dc.identifier.eissn1524-4733-
dc.identifier.isiWOS:000303940600013-
dc.publisher.placeUnited Statesen_HK
dc.relation.projectA Study on Health-related Quality of Life of patients with Colorectal Neoplasm and Cost-Effectiveness Analysis of Colorectal Cancer Screening in Hong Kong-
dc.identifier.scopusauthoridWong, CKH=36465969200en_HK
dc.identifier.scopusauthoridLam, CLK=54880690600en_HK
dc.identifier.scopusauthoridRowen, D=8929127200en_HK
dc.identifier.scopusauthoridMcGhee, SM=55116663500en_HK
dc.identifier.scopusauthoridMa, KP=55219892400en_HK
dc.identifier.scopusauthoridLaw, WL=7103147867en_HK
dc.identifier.scopusauthoridPoon, JTC=7005903722en_HK
dc.identifier.scopusauthoridChan, P=47661052600en_HK
dc.identifier.scopusauthoridKwong, DLW=54890371000en_HK
dc.identifier.scopusauthoridTsang, J=55220707000en_HK

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