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The Prediction of Cardiac Events Using Contemporary Risk Prediction Models after Radiation Therapy for Head and Neck Cancer

Publication ,  Journal Article
Alvi, RM; Quinaglia, T; Spahillari, A; Suero-Abreu, GA; Hassan, MZO; Gongora, C; Gilman, HK; Nikolaidou, S; Sama, S; Wirth, LJ; Chan, AW ...
Published in: Cancers
August 1, 2022

This study aims to evaluate the efficacy of the Pooled Cohort Equation (PCE), U.S. Preventative Services Task Force (USPSTF), and Framingham Risk Score (FRS) models in predicting ASCVD events among patients receiving radiation therapy (RT) for head and neck cancer (HNCA). From a large cohort of HNCA patients treated with RT, ASCVD events were adjudicated. Observed vs. predicted ASCVD events were compared. We compared rates by statin eligibility status. Regression models and survival analysis were used to identify the relationship between predicted risk and post-RT outcomes. Among the 723 identified patients, 274 (38%) were statin-eligible based on USPSTF criteria, 359 (49%) based on PCE, and 234 (32%) based on FRS. During follow-up, 17% developed an ASCVD, with an event rate of 27 per 1000 person-years, 68% higher than predicted (RR 1.68 (95% CI: 1.02, 2.12), p < 0.001). In multivariable regression, there was no difference in event rates by statin eligibility status (p > 0.05). Post-RT, the observed event rate was higher than the predicted ASCVD risk across all grades of predicted risk (p < 0.05) and the observed risk of an ASCVD event was high even among patients predicted to have a low risk of ASCVD. In conclusion, current ASCVD risk calculators significantly underestimate the risk for ASCVD among patients receiving RT for HNCA.

Duke Scholars

Published In

Cancers

DOI

EISSN

2072-6694

Publication Date

August 1, 2022

Volume

14

Issue

15

Related Subject Headings

  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Alvi, R. M., Quinaglia, T., Spahillari, A., Suero-Abreu, G. A., Hassan, M. Z. O., Gongora, C., … Neilan, T. G. (2022). The Prediction of Cardiac Events Using Contemporary Risk Prediction Models after Radiation Therapy for Head and Neck Cancer. Cancers, 14(15). https://doi.org/10.3390/cancers14153651
Alvi, R. M., T. Quinaglia, A. Spahillari, G. A. Suero-Abreu, M. Z. O. Hassan, C. Gongora, H. K. Gilman, et al. “The Prediction of Cardiac Events Using Contemporary Risk Prediction Models after Radiation Therapy for Head and Neck Cancer.” Cancers 14, no. 15 (August 1, 2022). https://doi.org/10.3390/cancers14153651.
Alvi RM, Quinaglia T, Spahillari A, Suero-Abreu GA, Hassan MZO, Gongora C, et al. The Prediction of Cardiac Events Using Contemporary Risk Prediction Models after Radiation Therapy for Head and Neck Cancer. Cancers. 2022 Aug 1;14(15).
Alvi, R. M., et al. “The Prediction of Cardiac Events Using Contemporary Risk Prediction Models after Radiation Therapy for Head and Neck Cancer.” Cancers, vol. 14, no. 15, Aug. 2022. Scopus, doi:10.3390/cancers14153651.
Alvi RM, Quinaglia T, Spahillari A, Suero-Abreu GA, Hassan MZO, Gongora C, Gilman HK, Nikolaidou S, Sama S, Wirth LJ, Chan AW, Addison D, Neilan TG. The Prediction of Cardiac Events Using Contemporary Risk Prediction Models after Radiation Therapy for Head and Neck Cancer. Cancers. 2022 Aug 1;14(15).

Published In

Cancers

DOI

EISSN

2072-6694

Publication Date

August 1, 2022

Volume

14

Issue

15

Related Subject Headings

  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis