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Article: Risk prediction scores for mortality, cerebrovascular, and heart disease among Chinese people with type 2 diabetes

TitleRisk prediction scores for mortality, cerebrovascular, and heart disease among Chinese people with type 2 diabetes
Authors
Issue Date2019
PublisherOxford University Press. The Journal's web site is located at https://academic.oup.com/jcem
Citation
The Journal of Clinical Endocrinology & Metabolism, 2019, v. 104 n. 12, p. 5823-5830 How to Cite?
AbstractContext: Risk scores for cardiovascular and mortality outcomes have not been commonly applied in Chinese populations. Objective: To develop and externally validate a set of parsimonious risk scores (HKU-SG) to predict the risk of mortality, cerebrovascular disease and ischemic heart disease among Chinese people with type 2 diabetes; and compare HKU-SG risk scores to other existing ones. Design: Retrospective population-based cohorts drawn from Hong Kong Hospital Authority health records from 2006 to 2014 for development and Singapore Ministry of Health records from 2008 to 2016 for validation. Separate 5-year risk scores were derived using Cox proportional hazards models for each outcome. Setting: Study participants were adults with type 2 diabetes aged 20 years or over, consisting of 678,750 participants from Hong Kong and 386,425 participants from Singapore. Main Outcome: Measures Performance was evaluated by discrimination (Harrell’s c-index), and calibration plots comparing predicted against observed risks. Results: All models had fair external discrimination. Among the risk scores for the diabetes population, ethnic-specific risk scores (HKU-SG and JADE) performed better than UKPDS and RECODe models. External validation of the HKU-SG risk scores for mortality, cerebrovascular disease and ischemic heart disease had corresponding c-indices of 0.778, 0.695, and 0.644. The HKU-SG models appeared well calibrated on visual plots, with predicted risks closely matching observed risks. Conclusions: The HKU-SG risk scores were developed and externally validated in two large Chinese population-based cohorts. The parsimonious use of clinical predictors compared to previous risk scores could allow wider implementation of risk estimation in diverse Chinese settings.
Persistent Identifierhttp://hdl.handle.net/10722/272083
ISSN
2023 Impact Factor: 5.0
2023 SCImago Journal Rankings: 1.899
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorQuan, J-
dc.contributor.authorPang, D-
dc.contributor.authorLi, TK-
dc.contributor.authorChoi, CH-
dc.contributor.authorSiu, SC-
dc.contributor.authorTang, SY-
dc.contributor.authorWat, NM-
dc.contributor.authorWoo, J-
dc.contributor.authorLau, ZY-
dc.contributor.authorTan, KB-
dc.contributor.authorLeung, GM-
dc.date.accessioned2019-07-20T10:35:21Z-
dc.date.available2019-07-20T10:35:21Z-
dc.date.issued2019-
dc.identifier.citationThe Journal of Clinical Endocrinology & Metabolism, 2019, v. 104 n. 12, p. 5823-5830-
dc.identifier.issn0021-972X-
dc.identifier.urihttp://hdl.handle.net/10722/272083-
dc.description.abstractContext: Risk scores for cardiovascular and mortality outcomes have not been commonly applied in Chinese populations. Objective: To develop and externally validate a set of parsimonious risk scores (HKU-SG) to predict the risk of mortality, cerebrovascular disease and ischemic heart disease among Chinese people with type 2 diabetes; and compare HKU-SG risk scores to other existing ones. Design: Retrospective population-based cohorts drawn from Hong Kong Hospital Authority health records from 2006 to 2014 for development and Singapore Ministry of Health records from 2008 to 2016 for validation. Separate 5-year risk scores were derived using Cox proportional hazards models for each outcome. Setting: Study participants were adults with type 2 diabetes aged 20 years or over, consisting of 678,750 participants from Hong Kong and 386,425 participants from Singapore. Main Outcome: Measures Performance was evaluated by discrimination (Harrell’s c-index), and calibration plots comparing predicted against observed risks. Results: All models had fair external discrimination. Among the risk scores for the diabetes population, ethnic-specific risk scores (HKU-SG and JADE) performed better than UKPDS and RECODe models. External validation of the HKU-SG risk scores for mortality, cerebrovascular disease and ischemic heart disease had corresponding c-indices of 0.778, 0.695, and 0.644. The HKU-SG models appeared well calibrated on visual plots, with predicted risks closely matching observed risks. Conclusions: The HKU-SG risk scores were developed and externally validated in two large Chinese population-based cohorts. The parsimonious use of clinical predictors compared to previous risk scores could allow wider implementation of risk estimation in diverse Chinese settings.-
dc.languageeng-
dc.publisherOxford University Press. The Journal's web site is located at https://academic.oup.com/jcem-
dc.relation.ispartofThe Journal of Clinical Endocrinology & Metabolism-
dc.rightsThis is a pre-copy-editing, author-produced PDF of an article accepted for publication in The Journal of Clinical Endocrinology & Metabolism following peer review. The definitive publisher-authenticated version The Journal of Clinical Endocrinology & Metabolism, 2019, v. 104 n. 12, p. 5823-5830 is available online at: https://academic.oup.com/jcem/article-abstract/104/12/5823/5528893?redirectedFrom=fulltext-
dc.titleRisk prediction scores for mortality, cerebrovascular, and heart disease among Chinese people with type 2 diabetes-
dc.typeArticle-
dc.identifier.emailQuan, J: jquan@hku.hk-
dc.identifier.emailLeung, GM: gmleung@hku.hk-
dc.identifier.authorityQuan, J=rp02266-
dc.identifier.authorityLeung, GM=rp00460-
dc.description.naturepostprint-
dc.identifier.doi10.1210/jc.2019-00731-
dc.identifier.scopuseid_2-s2.0-85073577958-
dc.identifier.hkuros299014-
dc.identifier.volume104-
dc.identifier.issue12-
dc.identifier.spage5823-
dc.identifier.epage5830-
dc.identifier.isiWOS:000508237600015-
dc.publisher.placeUnited States-
dc.identifier.issnl0021-972X-

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