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. 2025 Jun 17;85(23):2253-2266.
doi: 10.1016/j.jacc.2025.03.545.

Predicting Heart Failure Outcomes Using Patient-Reported Health Status: Real-World Validation of the KCCQ-12

Bassim R El-Sabawi  1 , Mohammed A Al-Garadi  2 , Bryan D Steitz  2 , Amy M Perkins  3 , Allison B McCoy  2 , Donald G Sengstack  2 , Robert A Greevy Jr  3 , Emily H Burnell  4 , Kelly H Schlendorf  1 , JoAnn Lindenfeld  1 , Lynne W Stevenson  1 , Deepak K Gupta  1 , John A Spertus  5 , Sean P Collins  6 , Michael E Matheny  7 , Justin M Bachmann  8
Affiliations

Predicting Heart Failure Outcomes Using Patient-Reported Health Status: Real-World Validation of the KCCQ-12

Bassim R El-Sabawi et al. J Am Coll Cardiol. .

Abstract

Background: The Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12), a patient-reported outcome measure for adults with heart failure, is associated with hospitalizations and mortality in clinical trials. Curated data sets from controlled trials differ substantially from pragmatic data collected from real-world settings, however, and few data exist on the KCCQ-12's predictive utility in clinical practice.

Objectives: This study sought to evaluate the predictive utility of the KCCQ-12 for hospitalizations and mortality when administered during outpatient heart failure care.

Methods: We conducted a cohort study of patients assigned the KCCQ-12 in heart failure clinics from July 2019 through March 2024. The primary exposure was KCCQ-12 Overall Summary (KCCQ-OS) score. The primary outcomes were 90-day hospitalization and cumulative mortality. Multivariable-adjusted associations were assessed using logistic regression and Cox proportional hazards models. Gradient boosting (XGBoost) and random survival forest machine learning models were used to evaluate KCCQ-OS feature importance in predicting 90-day hospitalizations and cumulative mortality, respectively.

Results: Among 4,406 patients assigned the KCCQ-12, 2,888 (66%) completed at least 1 questionnaire. The median KCCQ-OS score was 59.4 (Q1-Q3: 35.4-81.8). Patients with KCCQ-OS scores <25 had higher adjusted risks of 90-day hospitalization (OR: 3.49; 95% CI: 2.50-4.90) and cumulative mortality (HR: 3.09; 95% CI: 2.29-4.17) compared with those with scores ≥75. The KCCQ-OS score was the most important feature for predicting 90-day hospitalizations in the XGBoost model (area under the receiver-operating characteristic curve: 0.760; 95% CI: 0.706-0.811) and the most important feature for predicting cumulative mortality in the random survival forest model (C-index 0.783; 95% CI: 0.742-0.824) compared with other clinical, demographic, and laboratory variables. KCCQ-12 noncompletion was independently associated with increased 90-day hospitalization (OR: 1.72; 95% CI: 1.46-2.02) and 1-year mortality (HR: 1.52; 95% CI: 1.25-1.84) after adjusting for all variables in the primary analysis.

Conclusions: In outpatient heart failure care, lower KCCQ-OS scores were strongly associated with increased hospitalizations and mortality, with the greatest risk among patients with scores <25. Noncompletion of the KCCQ-12 was itself associated with worse outcomes. The KCCQ-OS score was the dominant predictor of 90-day hospitalizations and cumulative mortality in machine learning models, supporting the KCCQ-12 as a prognostic tool in routine clinical practice.

Keywords: health informatics; heart failure; machine learning; patient-reported outcomes; prognosis.

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Conflict of interest statement

Funding Support and Author Disclosures This material is based upon work supported by Career Development Award 1IK2HX003021 (Dr Bachmann) from the United States Department of Veterans Affairs, Health Services Research Service; Rapid-Cycle Research Award RI-RCIP-1812-002 (Dr Bachmann) from the Patient-Centered Outcomes Research Institute; and T32 HG008341 (Dr El-Sabawi) from the National Institutes of Health. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government. Dr Lindenfeld is a consultant for Abbott, Abiomed, Adona, Alleviant, Boston Scientific, CVRx, Edwards Lifesciences, Fire 1, Intershunt, Medtronic, Merck, Orchestra Biomed, VWave, Whiteswell, and Vascular Dynamics. Dr Gupta receives research support from the NIH; and is a consultant for Novo Nordisk. Dr Spertus has provided consultative services on patient-reported outcomes and evidence evaluation to Alnylam, AstraZeneca, Bayer, Janssen, Bristol Myers Squibb, Terumo, Cytokinetics, BridgeBio, VentricHealth, and Imbria; holds research grants from the National Institutes of Health, the Patient-Centered Outcomes Research Institute, the American College of Cardiology Foundation, Lexicon, Imbria, and Janssen; owns the copyright to the Seattle Angina Questionnaire, Kansas City Cardiomyopathy Questionnaire, and Peripheral Artery Questionnaire; and serves on the Board of Directors for Blue Cross Blue Shield of Kansas City. Dr Collins receives research support from NIH, PCORI, and DOD and is a consultant for Reprieve Cardiovascular, Prenosis, Abbott, Boehringer Ingelheim and Tosoh. Dr Bachmann’s spouse is employed by Amgen, Inc. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

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