A predictor finding study found patient-reported outcomes improve the prediction of mortality of incident dialysis patients

Kidney International, vol. 109, pp. 1025–1035

Abstract

INTRODUCTION: Prognostic models for mortality in patients receiving dialysis primarily use clinical predictors like age, comorbidities and laboratory markers. Studies in other fields suggest that patient-reported outcomes (PROs), like pain and fatigue, can be predictors of survival. Therefore, we aimed to assess the added value of PROs to predict mortality in incident dialysis patients. METHODS: Data from NECOSAD (1956 individuals) were used, and analyses were replicated in the EQUAL (415 individuals) and NECOSAD 65+ (862 individuals) studies. A base model for two-year mortality containing clinical predictors was extended using PROs (mental component score, physical component score, general health perception, depressive symptoms, number of symptoms, symptom burden, fatigue and pain). Logistic regression was used, and the added predictive performance of the PROs was evaluated using the area under the curve (AUC), measures of calibration, Brier score, likelihood ratio tests, reclassification tables, net reclassification indices, integrated discrimination improvements, and decision curve analyses. We also examined different combinations of predictors, and each PRO individually. RESULTS: Within two years, mortality rates were 22.9%, 24.3%, and 37.1% in NECOSAD, EQUAL, and NECOSAD 65+, respectively. The base model yielded optimism-corrected AUCs of 0.806, 0.781 and 0.699, which improved to 0.826, 0.878 and 0.746 after adding the PROs. Improvement of the calibration, Brier scores, and comparative measures confirmed their predictive value. The mental and physical component score, and symptom burden had the most consistent strong performance across all cohorts. CONCLUSIONS: PROs improved prognostic models for mortality of patients receiving incident dialysis, even when added to an already well-performing model of clinical predictors.

Authors 15

1. Jet Milders corresponding Aachen Department of Clinical Epidemiology

   Leiden University Medical Center

   Affiliation as printed

   Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: jetmil98@hotmail.com

2. Roemer J. Janse Aachen Department of Clinical Epidemiology

   Leiden University Medical Center

   Affiliation as printed

   Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands

3. Willem Jan W. Bos Aachen

   Leiden University Medical Center · St. Antonius Ziekenhuis

   Affiliation as printed

   Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands; Department of Internal Medicine, St. Antonius Hospital, Nieuwegein, the Netherlands

4. Fergus John Caskey

   University of Bristol

   Affiliation as printed

   Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK

5. Claudia Torino

   National Research Council

   Affiliation as printed

   Institute of Clinical Physiology, National Research Council, Reggio Calabria, Italy

6. Antonio Demetrio Vilasi

   National Research Council

   Affiliation as printed

   Institute of Clinical Physiology, National Research Council, Reggio Calabria, Italy

7. Maciej Szymczak

   Wroclaw Medical University

   Affiliation as printed

   Clinical Department of Nephrology, Transplantation Medicine and Internal Diseases, Wroclaw Medical University, Wroclaw, Poland

8. Christiane Drechsler

   University of Würzburg · Universitätsklinikum Würzburg

   Affiliation as printed

   Department of Clinical Research and Epidemiology, Comprehensive Heart Failure Center, University Hospital of Würzburg, Würzburg, Germany

9. C. Wanner

   University of Würzburg · Universitätsklinikum Würzburg

   Affiliation as printed

   Department of Clinical Research and Epidemiology, Comprehensive Heart Failure Center, University Hospital of Würzburg, Würzburg, Germany

10. Maria Pippias

    University of Bristol

    Affiliation as printed

    Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Renal Unit, North Bristol National Health Service Trust, Bristol, UK

11. Kitty J. Jager

    Amsterdam UMC Location University of Amsterdam · Amsterdam Public Health · Amsterdam University Medical Centers · University of Amsterdam

    Affiliation as printed

    European Renal Association Registry, Department of Medical Informatics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands; Quality of Care Research Program, Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Amsterdam, the Netherlands

12. Nicholas C Chesnaye

    Amsterdam UMC Location University of Amsterdam · Amsterdam Public Health · Amsterdam University Medical Centers · University of Amsterdam

    Affiliation as printed

    European Renal Association Registry, Department of Medical Informatics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands; Quality of Care Research Program, Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Amsterdam, the Netherlands

13. Marie Evans

    Karolinska University Hospital · Karolinska Institutet

    Affiliation as printed

    Renal Unit, Department of Clinical Intervention and Technology (CLINTEC), Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden

14. Friedo W. Dekker Aachen Department of Clinical Epidemiology

    Leiden University Medical Center

    Affiliation as printed

    Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands

15. Merel van Diepen Aachen Department of Clinical Epidemiology

    Leiden University Medical Center

    Affiliation as printed

    Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands