Challenges of developing a Cardiovascular risk calculator for patients with rheumatoid arthritis

Cynthia S. Crowson, Silvia Rollefstad, George D. Kitas, Piet L.C.M. Van Riel, Sherine Gabriel, Anne Grete Semb

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Objective: Cardiovascular disease (CVD) risk calculators designed for use in the general population do not accurately predict the risk of CVD among patients with rheumatoid arthritis (RA), who are at increased risk of CVD. The process of developing risk prediction models involves numerous issues. Our goal was to develop a CVD risk calculator for patients with RA. Methods: Thirteen cohorts of patients with RA originating from 10 different countries (UK, Norway, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico) were combined. CVD risk factors and RA characteristics at baseline, in addition to information on CVD outcomes were collected. Cox models were used to develop a CVD risk calculator, considering traditional CVD risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration with 10-fold cross-validation. Results: A total of 5638 RA patients without prior CVD were included (mean age: 55 [SD: 14] years, 76% female). During a mean follow-up of 5.8 years (30139 person years), 389 patients developed a CVD event. Event rates varied between cohorts, necessitating inclusion of high and low risk strata in the models. The multivariable analyses revealed 2 risk prediction models including either a disease activity score including a 28 joint count and erythrocyte sedimentation rate (DAS28ESR) or a health assessment questionnaire (HAQ) along with age, sex, presence of hypertension, current smoking and ratio of total cholesterol to high-density lipoprotein cholesterol. Unfortunately, performance of these models was similar to general population CVD risk calculators. Conclusion: Efforts to develop a specific CVD risk calculator for patients with RA yielded 2 potential models including RA disease characteristics, but neither demonstrated improved performance compared to risk calculators designed for use in the general population. Challenges encountered and lessons learned are discussed in detail.

Original languageEnglish (US)
Article numbere0174656
JournalPLoS ONE
Volume12
Issue number3
DOIs
StatePublished - Mar 1 2017

Fingerprint

rheumatoid arthritis
cardiovascular diseases
Rheumatoid Arthritis
Cardiovascular Diseases
Rheumatoid Factor
risk factors
Population
erythrocyte sedimentation rate
prediction
Blood Sedimentation
Greece
Norway
South Africa
Mexico
Proportional Hazards Models
high density lipoprotein cholesterol
Sweden
Netherlands
Spain
HDL Cholesterol

All Science Journal Classification (ASJC) codes

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Crowson, C. S., Rollefstad, S., Kitas, G. D., Van Riel, P. L. C. M., Gabriel, S., & Semb, A. G. (2017). Challenges of developing a Cardiovascular risk calculator for patients with rheumatoid arthritis. PLoS ONE, 12(3), [e0174656]. https://doi.org/10.1371/journal.pone.0174656
Crowson, Cynthia S. ; Rollefstad, Silvia ; Kitas, George D. ; Van Riel, Piet L.C.M. ; Gabriel, Sherine ; Semb, Anne Grete. / Challenges of developing a Cardiovascular risk calculator for patients with rheumatoid arthritis. In: PLoS ONE. 2017 ; Vol. 12, No. 3.
@article{9862ee66b3de48f7a70af570b920c3ce,
title = "Challenges of developing a Cardiovascular risk calculator for patients with rheumatoid arthritis",
abstract = "Objective: Cardiovascular disease (CVD) risk calculators designed for use in the general population do not accurately predict the risk of CVD among patients with rheumatoid arthritis (RA), who are at increased risk of CVD. The process of developing risk prediction models involves numerous issues. Our goal was to develop a CVD risk calculator for patients with RA. Methods: Thirteen cohorts of patients with RA originating from 10 different countries (UK, Norway, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico) were combined. CVD risk factors and RA characteristics at baseline, in addition to information on CVD outcomes were collected. Cox models were used to develop a CVD risk calculator, considering traditional CVD risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration with 10-fold cross-validation. Results: A total of 5638 RA patients without prior CVD were included (mean age: 55 [SD: 14] years, 76{\%} female). During a mean follow-up of 5.8 years (30139 person years), 389 patients developed a CVD event. Event rates varied between cohorts, necessitating inclusion of high and low risk strata in the models. The multivariable analyses revealed 2 risk prediction models including either a disease activity score including a 28 joint count and erythrocyte sedimentation rate (DAS28ESR) or a health assessment questionnaire (HAQ) along with age, sex, presence of hypertension, current smoking and ratio of total cholesterol to high-density lipoprotein cholesterol. Unfortunately, performance of these models was similar to general population CVD risk calculators. Conclusion: Efforts to develop a specific CVD risk calculator for patients with RA yielded 2 potential models including RA disease characteristics, but neither demonstrated improved performance compared to risk calculators designed for use in the general population. Challenges encountered and lessons learned are discussed in detail.",
author = "Crowson, {Cynthia S.} and Silvia Rollefstad and Kitas, {George D.} and {Van Riel}, {Piet L.C.M.} and Sherine Gabriel and Semb, {Anne Grete}",
year = "2017",
month = "3",
day = "1",
doi = "https://doi.org/10.1371/journal.pone.0174656",
language = "English (US)",
volume = "12",
journal = "PloS one",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "3",

}

Challenges of developing a Cardiovascular risk calculator for patients with rheumatoid arthritis. / Crowson, Cynthia S.; Rollefstad, Silvia; Kitas, George D.; Van Riel, Piet L.C.M.; Gabriel, Sherine; Semb, Anne Grete.

In: PLoS ONE, Vol. 12, No. 3, e0174656, 01.03.2017.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Challenges of developing a Cardiovascular risk calculator for patients with rheumatoid arthritis

AU - Crowson, Cynthia S.

AU - Rollefstad, Silvia

AU - Kitas, George D.

AU - Van Riel, Piet L.C.M.

AU - Gabriel, Sherine

AU - Semb, Anne Grete

PY - 2017/3/1

Y1 - 2017/3/1

N2 - Objective: Cardiovascular disease (CVD) risk calculators designed for use in the general population do not accurately predict the risk of CVD among patients with rheumatoid arthritis (RA), who are at increased risk of CVD. The process of developing risk prediction models involves numerous issues. Our goal was to develop a CVD risk calculator for patients with RA. Methods: Thirteen cohorts of patients with RA originating from 10 different countries (UK, Norway, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico) were combined. CVD risk factors and RA characteristics at baseline, in addition to information on CVD outcomes were collected. Cox models were used to develop a CVD risk calculator, considering traditional CVD risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration with 10-fold cross-validation. Results: A total of 5638 RA patients without prior CVD were included (mean age: 55 [SD: 14] years, 76% female). During a mean follow-up of 5.8 years (30139 person years), 389 patients developed a CVD event. Event rates varied between cohorts, necessitating inclusion of high and low risk strata in the models. The multivariable analyses revealed 2 risk prediction models including either a disease activity score including a 28 joint count and erythrocyte sedimentation rate (DAS28ESR) or a health assessment questionnaire (HAQ) along with age, sex, presence of hypertension, current smoking and ratio of total cholesterol to high-density lipoprotein cholesterol. Unfortunately, performance of these models was similar to general population CVD risk calculators. Conclusion: Efforts to develop a specific CVD risk calculator for patients with RA yielded 2 potential models including RA disease characteristics, but neither demonstrated improved performance compared to risk calculators designed for use in the general population. Challenges encountered and lessons learned are discussed in detail.

AB - Objective: Cardiovascular disease (CVD) risk calculators designed for use in the general population do not accurately predict the risk of CVD among patients with rheumatoid arthritis (RA), who are at increased risk of CVD. The process of developing risk prediction models involves numerous issues. Our goal was to develop a CVD risk calculator for patients with RA. Methods: Thirteen cohorts of patients with RA originating from 10 different countries (UK, Norway, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico) were combined. CVD risk factors and RA characteristics at baseline, in addition to information on CVD outcomes were collected. Cox models were used to develop a CVD risk calculator, considering traditional CVD risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration with 10-fold cross-validation. Results: A total of 5638 RA patients without prior CVD were included (mean age: 55 [SD: 14] years, 76% female). During a mean follow-up of 5.8 years (30139 person years), 389 patients developed a CVD event. Event rates varied between cohorts, necessitating inclusion of high and low risk strata in the models. The multivariable analyses revealed 2 risk prediction models including either a disease activity score including a 28 joint count and erythrocyte sedimentation rate (DAS28ESR) or a health assessment questionnaire (HAQ) along with age, sex, presence of hypertension, current smoking and ratio of total cholesterol to high-density lipoprotein cholesterol. Unfortunately, performance of these models was similar to general population CVD risk calculators. Conclusion: Efforts to develop a specific CVD risk calculator for patients with RA yielded 2 potential models including RA disease characteristics, but neither demonstrated improved performance compared to risk calculators designed for use in the general population. Challenges encountered and lessons learned are discussed in detail.

UR - http://www.scopus.com/inward/record.url?scp=85016152504&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85016152504&partnerID=8YFLogxK

U2 - https://doi.org/10.1371/journal.pone.0174656

DO - https://doi.org/10.1371/journal.pone.0174656

M3 - Article

VL - 12

JO - PloS one

JF - PloS one

SN - 1932-6203

IS - 3

M1 - e0174656

ER -