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Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis.


ABSTRACT: The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.

SUBMITTER: Paige E 

PROVIDER: S-EPMC5860526 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis.

Paige Ellie E   Barrett Jessica J   Pennells Lisa L   Sweeting Michael M   Willeit Peter P   Di Angelantonio Emanuele E   Gudnason Vilmundur V   Nordestgaard Børge G BG   Psaty Bruce M BM   Goldbourt Uri U   Best Lyle G LG   Assmann Gerd G   Salonen Jukka T JT   Nietert Paul J PJ   Verschuren W M Monique WMM   Brunner Eric J EJ   Kronmal Richard A RA   Salomaa Veikko V   Bakker Stephan J L SJL   Dagenais Gilles R GR   Sato Shinichi S   Jansson Jan-Håkan JH   Willeit Johann J   Onat Altan A   de la Cámara Agustin Gómez AG   Roussel Ronan R   Völzke Henry H   Dankner Rachel R   Tipping Robert W RW   Meade Tom W TW   Donfrancesco Chiara C   Kuller Lewis H LH   Peters Annette A   Gallacher John J   Kromhout Daan D   Iso Hiroyasu H   Knuiman Matthew M   Casiglia Edoardo E   Kavousi Maryam M   Palmieri Luigi L   Sundström Johan J   Davis Barry R BR   Njølstad Inger I   Couper David D   Danesh John J   Thompson Simon G SG   Wood Angela A  

American journal of epidemiology 20171001 8


The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD eve  ...[more]

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