Better prediction of stroke in atrial fibrillation with incorporation of cancer in CHA2DS2VASC score

Brandon Bungo; Pulkit Chaudhury; Michael Arustamyan; Rishi Rikhi; Muzna Hussain; Patrick Collier; Mohamed Kanj; Alok A Khorana; Amgad Mentias; Rohit Moudgil

doi:10.1016/j.ijcha.2022.101072

Better prediction of stroke in atrial fibrillation with incorporation of cancer in CHA2DS2VASC score

Brandon Bungo, Pulkit Chaudhury, Michael Arustamyan, Rishi Rikhi, Muzna Hussain, Patrick Collier, Mohamed Kanj, Alok A Khorana, Amgad Mentias, Rohit Moudgil

Research output: Contribution to journal › Article › peer-review

14 Citations (Scopus)

15 Downloads (Pure)

Abstract

INTRODUCTION: Atrial fibrillation (AF) is associated with an increased risk of stroke. Despite evidence linking cancer and thrombosis, cancer is not part of the CHA2DS2VASc score.

HYPOTHESIS: Cancer is an independent risk factor for thromboembolic stroke in patients with AF.

METHOD: The SEER database was utilized to identify patients with lung, colon, breast, and prostate cancers with AF and no prior diagnosis of stroke and. compared to controls within the dataset. The primary endpoint was rates of stroke per 100 person-years. Cox regression modeling and a nested model comparing CHA2DS2VASc score (Model 1) with a complete model including cancer diagnosis (Model 2) were performed. Models were compared using Akaike Information Criterion (AIC) and Net Reclassification Index (NRI). A propensity-matched cohort with equivalent CHA2DS2VASc scores determining stroke-free survival was also performed.

RESULTS: A total of 101,185 patients were included in the analysis, with 48,242 in the Cancer and 52,943 in the Non-cancer Group. Stroke rate per 100 person-years was significantly higher in the Cancer Group. The CHA2DS2VASc model (Model 1) was compared against a model including cancer (Model 2) showing improved predictability as assessed by both NRI and AIC. Cox regression analysis calculated a hazard ratio of 1.085 for Cancer, which was comparable to age >75, female sex, and diabetes. Propensity matched Kaplan-Meier curve demonstrated a decreased probability of stroke-free survival in the Cancer Group.

CONCLUSION: Cancers increase the risk of stroke in patients with AF. Consideration should be given to the addition of cancer to the clinical scoring system.

Original language	English
Article number	101072
Journal	IJC Heart and Vasculature
Volume	41
Early online date	20 Jun 2022
DOIs	https://doi.org/10.1016/j.ijcha.2022.101072
Publication status	Published - Aug 2022
Externally published	Yes

Bibliographical note

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.ijcha.2022.101072Licence: CC BY-NC-ND

Better prediction of stroke in atrial fibrillation with incorporation of cancer in CHA2DS2VASC score: CCHA2DS2VASC score
Copyright 2022 the authors. This is an open access article published under a Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits distribution and reproduction for non-commercial purposes, provided the author and source are cited.
Final published version, 890 KBLicence: CC BY-NC-ND

Cardiovascular disease in patients with cancer or amyloidosis
Hussain, M. (Author), Collier, P. (Supervisor), Watson, C. (Supervisor) & Grieve, D. (Supervisor), Jul 2023
Student thesis: Doctoral Thesis › Doctor of Philosophy

Cite this

@article{1e0b9754d81c46b5891a97f652b2638a,

title = "Better prediction of stroke in atrial fibrillation with incorporation of cancer in CHA2DS2VASC score",

abstract = "INTRODUCTION: Atrial fibrillation (AF) is associated with an increased risk of stroke. Despite evidence linking cancer and thrombosis, cancer is not part of the CHA2DS2VASc score.HYPOTHESIS: Cancer is an independent risk factor for thromboembolic stroke in patients with AF.METHOD: The SEER database was utilized to identify patients with lung, colon, breast, and prostate cancers with AF and no prior diagnosis of stroke and. compared to controls within the dataset. The primary endpoint was rates of stroke per 100 person-years. Cox regression modeling and a nested model comparing CHA2DS2VASc score (Model 1) with a complete model including cancer diagnosis (Model 2) were performed. Models were compared using Akaike Information Criterion (AIC) and Net Reclassification Index (NRI). A propensity-matched cohort with equivalent CHA2DS2VASc scores determining stroke-free survival was also performed.RESULTS: A total of 101,185 patients were included in the analysis, with 48,242 in the Cancer and 52,943 in the Non-cancer Group. Stroke rate per 100 person-years was significantly higher in the Cancer Group. The CHA2DS2VASc model (Model 1) was compared against a model including cancer (Model 2) showing improved predictability as assessed by both NRI and AIC. Cox regression analysis calculated a hazard ratio of 1.085 for Cancer, which was comparable to age >75, female sex, and diabetes. Propensity matched Kaplan-Meier curve demonstrated a decreased probability of stroke-free survival in the Cancer Group.CONCLUSION: Cancers increase the risk of stroke in patients with AF. Consideration should be given to the addition of cancer to the clinical scoring system.",

author = "Brandon Bungo and Pulkit Chaudhury and Michael Arustamyan and Rishi Rikhi and Muzna Hussain and Patrick Collier and Mohamed Kanj and Khorana, {Alok A} and Amgad Mentias and Rohit Moudgil",

note = "{\textcopyright} 2022 Published by Elsevier B.V.",

year = "2022",

month = aug,

doi = "10.1016/j.ijcha.2022.101072",

language = "English",

volume = "41",

journal = "IJC Heart and Vasculature",

issn = "2352-9067",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - Better prediction of stroke in atrial fibrillation with incorporation of cancer in CHA2DS2VASC score

AU - Bungo, Brandon

AU - Chaudhury, Pulkit

AU - Arustamyan, Michael

AU - Rikhi, Rishi

AU - Hussain, Muzna

AU - Collier, Patrick

AU - Kanj, Mohamed

AU - Khorana, Alok A

AU - Mentias, Amgad

AU - Moudgil, Rohit

PY - 2022/8

Y1 - 2022/8

N2 - INTRODUCTION: Atrial fibrillation (AF) is associated with an increased risk of stroke. Despite evidence linking cancer and thrombosis, cancer is not part of the CHA2DS2VASc score.HYPOTHESIS: Cancer is an independent risk factor for thromboembolic stroke in patients with AF.METHOD: The SEER database was utilized to identify patients with lung, colon, breast, and prostate cancers with AF and no prior diagnosis of stroke and. compared to controls within the dataset. The primary endpoint was rates of stroke per 100 person-years. Cox regression modeling and a nested model comparing CHA2DS2VASc score (Model 1) with a complete model including cancer diagnosis (Model 2) were performed. Models were compared using Akaike Information Criterion (AIC) and Net Reclassification Index (NRI). A propensity-matched cohort with equivalent CHA2DS2VASc scores determining stroke-free survival was also performed.RESULTS: A total of 101,185 patients were included in the analysis, with 48,242 in the Cancer and 52,943 in the Non-cancer Group. Stroke rate per 100 person-years was significantly higher in the Cancer Group. The CHA2DS2VASc model (Model 1) was compared against a model including cancer (Model 2) showing improved predictability as assessed by both NRI and AIC. Cox regression analysis calculated a hazard ratio of 1.085 for Cancer, which was comparable to age >75, female sex, and diabetes. Propensity matched Kaplan-Meier curve demonstrated a decreased probability of stroke-free survival in the Cancer Group.CONCLUSION: Cancers increase the risk of stroke in patients with AF. Consideration should be given to the addition of cancer to the clinical scoring system.

AB - INTRODUCTION: Atrial fibrillation (AF) is associated with an increased risk of stroke. Despite evidence linking cancer and thrombosis, cancer is not part of the CHA2DS2VASc score.HYPOTHESIS: Cancer is an independent risk factor for thromboembolic stroke in patients with AF.METHOD: The SEER database was utilized to identify patients with lung, colon, breast, and prostate cancers with AF and no prior diagnosis of stroke and. compared to controls within the dataset. The primary endpoint was rates of stroke per 100 person-years. Cox regression modeling and a nested model comparing CHA2DS2VASc score (Model 1) with a complete model including cancer diagnosis (Model 2) were performed. Models were compared using Akaike Information Criterion (AIC) and Net Reclassification Index (NRI). A propensity-matched cohort with equivalent CHA2DS2VASc scores determining stroke-free survival was also performed.RESULTS: A total of 101,185 patients were included in the analysis, with 48,242 in the Cancer and 52,943 in the Non-cancer Group. Stroke rate per 100 person-years was significantly higher in the Cancer Group. The CHA2DS2VASc model (Model 1) was compared against a model including cancer (Model 2) showing improved predictability as assessed by both NRI and AIC. Cox regression analysis calculated a hazard ratio of 1.085 for Cancer, which was comparable to age >75, female sex, and diabetes. Propensity matched Kaplan-Meier curve demonstrated a decreased probability of stroke-free survival in the Cancer Group.CONCLUSION: Cancers increase the risk of stroke in patients with AF. Consideration should be given to the addition of cancer to the clinical scoring system.

U2 - 10.1016/j.ijcha.2022.101072

DO - 10.1016/j.ijcha.2022.101072

M3 - Article

C2 - 35757148

SN - 2352-9067

VL - 41

JO - IJC Heart and Vasculature

JF - IJC Heart and Vasculature

M1 - 101072

ER -

Better prediction of stroke in atrial fibrillation with incorporation of cancer in CHA2DS2VASC score

Abstract

Bibliographical note

UN SDGs

Access to Document

Fingerprint

Student theses

Cardiovascular disease in patients with cancer or amyloidosis

Cite this