gms | German Medical Science

53. Kongress für Allgemeinmedizin und Familienmedizin

Deutsche Gesellschaft für Allgemeinmedizin und Familienmedizin (DEGAM)

Erlangen, 12. - 14.09.2019

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Development and validation of the PROPERmed instrument to identify older patients in general practice at risk of worsening health-related quality of life: an individual participant data meta-analysis (IPD-MA)

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  • Ana Isabel González-González - Goethe University, Institute of General Medicine, Deutschland
  • Andreas Meid - University Hospital, Department of Clinical Pharmacology and Pharmacoepidemiology, Deutschland
  • Truc Sophia Nguyen - Goethe University, Institute of General Medicine, Deutschland
  • Jeanet W. Blom - Leiden University Medical Center, Department of Public Health and Primary Care, Leiden, Niederlande
  • Marjan van den Akker - Goethe University, Institute of General Medicine, Deutschland
  • Karin Swart - Amsterdam UMC, Vrije Universiteit Amsterdam, Department of General Practice and Elderly Care Medicine, Amsterdam Public Health research institute, Amsterdam, Niederlande
  • Daniela Küllenberg de Gaudry - University of Freiburg Faculty of Medicine, Institute for Evidence in Medicine (for Cochrane Germany Foundation), Medical Center, Freiburg, Deutschland
  • Ulrich Thiem - Albertinen-Diakoniewerk, Deutschland
  • Kym Snell - Keele University, Centre for Prognosis Research. Research Institute for Primary Care & Health Sciences, Großbritannien
  • Walter Emil Haefeli - University Hospital, Department of Clinical Pharmacology and Pharmacoepidemiology, Deutschland
  • Rafael Perera - University of Oxford, Nuffield Department of Primary Care, Oxford, Großbritannien
  • Benno Flaig - Goethe University, Institute of General Medicine, Deutschland
  • Hans-Joachim Trampisch - Ruhr University, AMIB, Deutschland
  • Henrik Rudolf - Ruhr University, AMIB, Deutschland
  • Jörg Meerpohl - University of Freiburg Faculty of Medicine, Institute for Evidence in Medicine (for Cochrane Germany Foundation), Medical Center, Freiburg, Deutschland
  • Petra Elders - Amsterdam UMC, Vrije Universiteit Amsterdam, Department of General Practice and Elderly Care Medicine, Amsterdam Public Health research institute, Amsterdam, Niederlande
  • Frank Verheyen - Techniker Krankenkasse (TK), Deutschland
  • Ghainsom Kom - Techniker Krankenkasse (TK), Deutschland
  • Paul P. Glasziou - Bond University, Centre for Research in Evidence-Based Practice (CREBP), Australien
  • Ferdinand Michael Gerlach - Goethe University, Institute of General Medicine, Deutschland
  • Christiane Muth - Goethe University, Institute of General Medicine, Deutschland

53. Kongress für Allgemeinmedizin und Familienmedizin. Erlangen, 12.-14.09.2019. Düsseldorf: German Medical Science GMS Publishing House; 2019. DocSym4-02

doi: 10.3205/19degam219, urn:nbn:de:0183-19degam2190

Published: September 11, 2019

© 2019 González-González et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.

Outline

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Background: Aging populations are facing multimorbidity and polypharmacy, inappropriate prescriptions, and underuse, which may contribute towards worsening of health-related quality of life (wHRQoL). In heterogeneous primary care populations, it would be helpful to identify those patients at highest risk of wHRQoL, since they may benefit most from (complex) interventions to improve their well-being.

Objective: To develop and validate a prognostic model to predict wHRQoL (EQ-5D-3L index decrease ≥5%) at six-month follow-up in older patients in general practice with ≥1 chronic condition and ≥1 chronic medication.

Methods: We harmonized individual participant data (IPD) from five cluster-randomized trials from the Netherlands and Germany.The model was developed using logistic regression with a stratified-intercept to account for between-study heterogeneity in baseline risk. Variables were selected in complete cases and then refitted in multiply imputed data to obtain the final model equation. Predictive performance and generalisability were derived by bootstrap internal validation and internal-external cross-validation (IECV), respectively.

Results: We included 4,561 participants from 307 general practices. Mean age was 78 years, 58% women, 95% lived at home, 89% had low/medium educational level, an average of 3 chronic conditions, and 7 chronic prescriptions. Selected predictors were related to demographics (e.g., low level of education), disease and health status (e.g., coronary heart disease, functional impairment, depressive symptoms or pain), drug classes alone or interrelated with underlying diseases (internal performance: calibration slope of 0.93 [0.51;1.35] and c-statistics of 0.71 [0.69;0.72]; generalisability: pooled c-statistics in IECV loop of 0.69).

Discussion: The first IPD-based prediction model for wHRQL in older patients in general practice performed well in calibration, discrimination, and generalizability and may thus assist the identification of high-risk patients, though its feasibility needs to be tested.

Take home message for practical use: A prediction model including socio-demographics, conditions, and medications may identify older patients at risk for wHRQoL in general practice.