{"id":{"repo_id":"auckland-ms","oai_identifier":"oai:researchspace.auckland.ac.nz:2292/74758"},"canonical_url":"https://search.dev.ndltd.org/etd/auckland-ms/oai:researchspace.auckland.ac.nz:2292/74758","repository":{"repo_id":"auckland-ms","name":"University of Auckland","base_url":"https://researchspace.auckland.ac.nz/server/oai/request"},"display":{"title":"Developing and Updating Cardiovascular Disease Risk Prediction Equations: An Exploration of Key Methodological Questions","abstract":"Aim: This thesis explored a series of methodological questions about developing and updating cardiovascular disease (CVD) risk prediction equations for people without prior CVD. Methods: Using Health Contact Cohorts (HCCs) constructed by linking national administrative health databases, this thesis comprised four studies: i) an update of policy equations; ii) a description of CVD risk distribution in a contemporary national population; iii) a comparison of different risk horizons; iv) an analysis of treatment ‘drop-in’ (initiation during follow-up). Findings: New sex-specific 5-year equations, using a more recent primary prevention population, a broader age range, more disaggregated ethnicity classifications and additional predictors, showed improved discrimination and calibration than previous equations. Sex-ethnicity-specific equations had better calibration but inconsistent reclassification across ethnicities. Applying the new equations to 2.7 million individuals aged 30-79 years in 2023 found that 2% of women and 6% of men had a 5-year CVD risk ≥15%, the ‘strongly recommended’ treatment threshold. Māori, Pacific peoples and individuals in deprived or rural areas generally had higher risks. In the study comparing 5-year and 10-year equations, both horizons ranked mostly the same high-risk individuals in the top quintiles. In the study comparing 5-year and lifetime equations, 14% of the population (mostly people aged 30-49 years) were at ‘low 5-year but high lifetime’ risk. However, their cumulative risk remained <10% until age 60-65 years (women) and 55-60 years (men). The final study found that, among people untreated at baseline, blood pressure-lowering and/or lipid-lowering treatment drop-in accounted for 14% of follow-up time, increasing with age and baseline risk. Adjusting equations to account for lipid-lowering treatment drop-in had minimal impact on predicted risk. Conclusions: This thesis demonstrated that i) updating equations in a more contemporary population measurably improved performance; ii) 5-year and 10-year equations ranked people similarly, but the clinical utility of lifetime tools requires further evaluation; iii) medication drop-in is common, but has limited impact on predicted risk. Finally, inequities in CVD risk persist across ethnic groups and localities. Collectively, these findings have important implications for improving CVD risk prediction and the equity of CVD risk management in New Zealand and globally.","abstract_html":"Aim: This thesis explored a series of methodological questions about developing and updating cardiovascular disease (CVD) risk prediction equations for people without prior CVD. Methods: Using Health Contact Cohorts (HCCs) constructed by linking national administrative health databases, this thesis comprised four studies: i) an update of policy equations; ii) a description of CVD risk distribution in a contemporary national population; iii) a comparison of different risk horizons; iv) an analysis of treatment ‘drop-in’ (initiation during follow-up). Findings: New sex-specific 5-year equations, using a more recent primary prevention population, a broader age range, more disaggregated ethnicity classifications and additional predictors, showed improved discrimination and calibration than previous equations. Sex-ethnicity-specific equations had better calibration but inconsistent reclassification across ethnicities. Applying the new equations to 2.7 million individuals aged 30-79 years in 2023 found that 2% of women and 6% of men had a 5-year CVD risk ≥15%, the ‘strongly recommended’ treatment threshold. Māori, Pacific peoples and individuals in deprived or rural areas generally had higher risks. In the study comparing 5-year and 10-year equations, both horizons ranked mostly the same high-risk individuals in the top quintiles. In the study comparing 5-year and lifetime equations, 14% of the population (mostly people aged 30-49 years) were at ‘low 5-year but high lifetime’ risk. However, their cumulative risk remained &lt;10% until age 60-65 years (women) and 55-60 years (men). The final study found that, among people untreated at baseline, blood pressure-lowering and/or lipid-lowering treatment drop-in accounted for 14% of follow-up time, increasing with age and baseline risk. Adjusting equations to account for lipid-lowering treatment drop-in had minimal impact on predicted risk. Conclusions: This thesis demonstrated that i) updating equations in a more contemporary population measurably improved performance; ii) 5-year and 10-year equations ranked people similarly, but the clinical utility of lifetime tools requires further evaluation; iii) medication drop-in is common, but has limited impact on predicted risk. Finally, inequities in CVD risk persist across ethnic groups and localities. Collectively, these findings have important implications for improving CVD risk prediction and the equity of CVD risk management in New Zealand and globally.","abstract_has_math":false,"creators":["Liang, Jingyuan"],"institution":"ResearchSpace@Auckland","degree_name":"PhD","degree_level":"Doctoral","degree_discipline":"Population Health","degree_department":null,"school":null,"contributors":[],"advisors":["Poppe, Katrina","Jackson, Rod","Wells, Susan"],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026-02-26","date_published":"2026-02-26","updated_at":"2026-07-24T01:05:11Z","subjects":[],"languages":[],"rights":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."],"rights_urls":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2292/74758","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Poppe, Katrina","Jackson, Rod","Wells, Susan"]},{"key":"dc:creator","label":"Author","values":["Liang, Jingyuan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-02-25T23:14:26Z"]},{"key":"dc:date.issued","label":"Date","values":["2026-02-26"]},{"key":"dc:publisher","label":"Institution","values":["ResearchSpace@Auckland"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Population Health"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["PhD"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Auckland"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/2292/74758"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Aim: This thesis explored a series of methodological questions about developing and updating cardiovascular disease (CVD) risk prediction equations for people without prior CVD. Methods: Using Health Contact Cohorts (HCCs) constructed by linking national administrative health databases, this thesis comprised four studies: i) an update of policy equations; ii) a description of CVD risk distribution in a contemporary national population; iii) a comparison of different risk horizons; iv) an analysis of treatment ‘drop-in’ (initiation during follow-up). Findings: New sex-specific 5-year equations, using a more recent primary prevention population, a broader age range, more disaggregated ethnicity classifications and additional predictors, showed improved discrimination and calibration than previous equations. Sex-ethnicity-specific equations had better calibration but inconsistent reclassification across ethnicities. Applying the new equations to 2.7 million individuals aged 30-79 years in 2023 found that 2% of women and 6% of men had a 5-year CVD risk ≥15%, the ‘strongly recommended’ treatment threshold. Māori, Pacific peoples and individuals in deprived or rural areas generally had higher risks. In the study comparing 5-year and 10-year equations, both horizons ranked mostly the same high-risk individuals in the top quintiles. In the study comparing 5-year and lifetime equations, 14% of the population (mostly people aged 30-49 years) were at ‘low 5-year but high lifetime’ risk. However, their cumulative risk remained <10% until age 60-65 years (women) and 55-60 years (men). The final study found that, among people untreated at baseline, blood pressure-lowering and/or lipid-lowering treatment drop-in accounted for 14% of follow-up time, increasing with age and baseline risk. Adjusting equations to account for lipid-lowering treatment drop-in had minimal impact on predicted risk. Conclusions: This thesis demonstrated that i) updating equations in a more contemporary population measurably improved performance; ii) 5-year and 10-year equations ranked people similarly, but the clinical utility of lifetime tools requires further evaluation; iii) medication drop-in is common, but has limited impact on predicted risk. Finally, inequities in CVD risk persist across ethnic groups and localities. Collectively, these findings have important implications for improving CVD risk prediction and the equity of CVD risk management in New Zealand and globally."]},{"key":"dc:title","label":"Title","values":["Developing and Updating Cardiovascular Disease Risk Prediction Equations: An Exploration of Key Methodological Questions"]}]}],"canonical_facts":{"dc:contributor.advisor":["Poppe, Katrina","Jackson, Rod","Wells, Susan"],"dc:creator":["Liang, Jingyuan"],"dc:date.accessioned":["2026-02-25T23:14:26Z"],"dc:date.issued":["2026-02-26"],"dc:description.abstract":["Aim: This thesis explored a series of methodological questions about developing and updating cardiovascular disease (CVD) risk prediction equations for people without prior CVD. Methods: Using Health Contact Cohorts (HCCs) constructed by linking national administrative health databases, this thesis comprised four studies: i) an update of policy equations; ii) a description of CVD risk distribution in a contemporary national population; iii) a comparison of different risk horizons; iv) an analysis of treatment ‘drop-in’ (initiation during follow-up). Findings: New sex-specific 5-year equations, using a more recent primary prevention population, a broader age range, more disaggregated ethnicity classifications and additional predictors, showed improved discrimination and calibration than previous equations. Sex-ethnicity-specific equations had better calibration but inconsistent reclassification across ethnicities. Applying the new equations to 2.7 million individuals aged 30-79 years in 2023 found that 2% of women and 6% of men had a 5-year CVD risk ≥15%, the ‘strongly recommended’ treatment threshold. Māori, Pacific peoples and individuals in deprived or rural areas generally had higher risks. In the study comparing 5-year and 10-year equations, both horizons ranked mostly the same high-risk individuals in the top quintiles. In the study comparing 5-year and lifetime equations, 14% of the population (mostly people aged 30-49 years) were at ‘low 5-year but high lifetime’ risk. However, their cumulative risk remained <10% until age 60-65 years (women) and 55-60 years (men). The final study found that, among people untreated at baseline, blood pressure-lowering and/or lipid-lowering treatment drop-in accounted for 14% of follow-up time, increasing with age and baseline risk. Adjusting equations to account for lipid-lowering treatment drop-in had minimal impact on predicted risk. Conclusions: This thesis demonstrated that i) updating equations in a more contemporary population measurably improved performance; ii) 5-year and 10-year equations ranked people similarly, but the clinical utility of lifetime tools requires further evaluation; iii) medication drop-in is common, but has limited impact on predicted risk. Finally, inequities in CVD risk persist across ethnic groups and localities. Collectively, these findings have important implications for improving CVD risk prediction and the equity of CVD risk management in New Zealand and globally."],"dc:identifier.uri":["https://hdl.handle.net/2292/74758"],"dc:publisher":["ResearchSpace@Auckland"],"dc:rights":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."],"dc:rights.uri":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"],"dc:title":["Developing and Updating Cardiovascular Disease Risk Prediction Equations: An Exploration of Key Methodological Questions"],"dc:type":["Thesis"],"thesis:degree_discipline":["Population Health"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["PhD"],"thesis:institution_name":["The University of Auckland"]},"updated_at":"2026-07-24T01:05:11Z"}