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Electronically monitored medication adherence in idiopathic pulmonary fibrosis: prevalence, predictors and outcomes

Anouk Delameillieure, Wim A. Wuyts, Antoine Pironet, Fabienne Dobbels
ERJ Open Research 2022 8: 00030-2022; DOI: 10.1183/23120541.00030-2022
Anouk Delameillieure
1Dept of Chronic Diseases and Metabolism, Laboratory of Respiratory Diseases and Thoracic Surgery, KU Leuven, Leuven, Belgium
2Dept of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium
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Wim A. Wuyts
1Dept of Chronic Diseases and Metabolism, Laboratory of Respiratory Diseases and Thoracic Surgery, KU Leuven, Leuven, Belgium
3Dept of Respiratory Diseases, Unit for Interstitial Lung Diseases, University Hospitals Leuven, Leuven, Belgium
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Antoine Pironet
4AARDEX Group, Seraing, Belgium
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Fabienne Dobbels
2Dept of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium
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  • For correspondence: fabienne.dobbels@kuleuven.be
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  • FIGURE 1
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    FIGURE 1

    Study visits and variables.

  • FIGURE 2
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    FIGURE 2

    Study flowchart (n=55). “Study discontinuation” refers to the patients who had a data collection point planned but discontinued the study (e.g. deceased, medication switch).“No data collection” refers to the patients who did not have a new data collection point planned and thus ended the study as anticipated (e.g. due to the prospective inclusion and design of the study).

  • FIGURE 3
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    FIGURE 3

    Chronology plots of four participants. Chronology plots allow us to visualize any missing or extra drug intake, drug holidays, timing of intake, consistency in timing and taking and discontinuation. Dates are shown on the x-axis (calendar) and time (24-h clock) is shown on the y-axis. Three daily pirfenidone doses at mealtime are recommended for idiopathic pulmonary fibrosis patients: coloured dots are bottle openings (i.e. presuming medication intake): purple (morning dose), green (midday dose) and yellow (evening dose). The grey bars are points where no medication intake (i.e. opening bottle) are monitored and the red lines refer to study visits. a) Participant one took pirfenidone at times that varied greatly and missed several doses, especially at the end of the monitoring. The patient had 78.2% of days with correct dosing of pirfenidone. This reflects a poor implementation pattern. The patient stopped using the bottle without discontinuing the treatment. b) Patient two had two registered non-monitoring periods at the beginning of treatment, yet the plot shows two additional periods for which no reason was provided (i.e. considered as long drug holidays). Also, multiple intakes were missed, including short drug holidays. During the monitored period, the patient only had 59.4% of correct dosing days. c) Patient three had a regular timing adherence and only missed two doses during the monitoring period of 10 months. More specifically, the patient had 99.3% of correct dosing days. d) Patient four had similar adherence pattern as patient three but showed issues in taking adherence early after treatment initiation and especially for the timing point at the midday meal. During the monitored period, the patient had 94.8% of correct dosing days.

  • FIGURE 4
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    FIGURE 4

    Lasagna plot of the study cohort. The rows represent the individual participants, and the columns indicate the days. Each white rectangle represents a non-monitored day, each purple rectangle represents a day with no intake, and each colored rectangle represents a day with 1, 2, 3 or more than 3 intakes. The binary variable Zij is equal to 1 for days depicted in green and 0 for days depicted in purple, blue, turquoise and yellow. It is undefined for days depicted in white.

Tables

  • Figures
  • Supplementary Materials
  • TABLE 1

    Sociodemographic and clinical characteristics (n=55)

    Baseline (Visit 1)
    Sex n (%)
     Male42 (76.4)
     Female13 (23.6)
    Age years
     Mean±sd71.1±8.2
     Range50–87
     Median (IQR)72 (10)
    Ethnicity Caucasian n (%)55 (100)
    Marital status n (%)
     Partner47 (85.5)
     No partner8 (14.5)
    Education level n (%)
     Lower education13 (23.6)
     Moderate education28 (50.9)
     Higher education14 (25.5)
    DLCO % predicted n54
     Mean±sd58.1±14.7
     Range24.2–111
     Median (IQR)58.5 (18.3)
    FVC % predicted n54
     Mean±sd88±18.3
     Range50–126
     Median (IQR)88 (29)

    IQR: interquartile range; DLCO: diffusing capacity of the lung for carbon monoxide; FVC: forced vital capacity.

    • TABLE 2

      Overview of the summary statistics of the implementation metrics

      Implementation metricRange %Median % (IQR)
      Proportion of prescribed drug taken (taking adherence)47–10198 (5)
      Proportion of days with the correct number of doses taken (correct dosing)18–10092 (10)
      Proportion of drug holidays0–2.40 (0)
      Proportion of too short dosing intervals (timing adherence)0–7.91.5 (2.1)
    • TABLE 3

      Link between implementation and outcomes

      Implementation metricOutcome
      FVC (p-value)DLCO (p-value)EQ-Health Index (p-value)K-BILD breathlessness (p-value)K-BILD psychological (p-value)K-BILD symptoms (p-value)K-BILD total (p-value)
      Proportion of prescribed drug taken (taking adherence)0.126 (0.53)0.161 (0.53)−0.073 (0.77)25.1 (0.30)31.6 (0.21)44.9 (0.13)17.7 (0.24)
      Proportion of days with the correct number of doses taken (correct dosing)0.304 (0.03#)0.223 (0.22)0.106 (0.59)33.2 (0.09)7.89 (0.66)27.5 (0.20)17.1 (0.13)
      Proportion of too short dosing intervals−1.621 (0.00#)−1.531 (0.01#)−0.596 (0.28)−73.5 (0.11)16.3 (0.70)−97.2 (0.05)−28.8 (0.29)
      Proportion of drug holidays−0.626 (0.87)−0.903 (0.85)1.329 (0.79)71.8 (0.86)108 (0.78)305 (0.50)54.8 (0.82)

      The table contains the slopes of the random intercept models linking implementation to outcomes. The slopes are dimensionless. FVC: forced vital capacity; DLCO: diffusing capacity of the lung for carbon monoxide; K-BILD: The King's Brief Interstitial Lung Disease questionnaire. #: significance at the 0.05 level.

      • TABLE 4

        Predictors of taking adherence

        Predictor of dosing adherenceCoefficient (dimensionless)p-value
        Univariate analyses
         Individual predictors measured only at baseline
          Age0.880.63
          Marital status−0.230.85
          Health literacy0.001
         Individual predictors measured longitudinally with time as covariate
          Time−1.230.01
          Intention to be adherent−1.890.52
          Time−0.970.04
          Number of side-effects reported−0.550.57
          Time−0.960.04
          Self-reported omission of pirfenidone−1.410.02*
          TimeNot converged
          Depression
          Time−1.020.04
          Barriers to adherence−0.430.43
          Time−1.050.11
          Knowledge about pirfenidone2.120.03*
        Prediction models (multivariate analyses)
         Model with predictors measured only at baseline
          Age1.120.57
          Marital status−0.370.78
          Health literacy0.010.99
         Model with predictors measured longitudinally
          Time−1.210.04*
          Intention to be adherentNot selected
          Number of side-effects reportedNot selected
          Self-reported omission of pirfenidone−1.600.02*
          Depression0.040.98
          Barriers to adherenceNot selected
          Knowledge about pirfenidoneNot selected

        The variables which were not selected did not sufficiently improve the quality of the model. *: significance at the 0.05 level.

        Supplementary Materials

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        • Supplementary Material

          Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author.

          Supplementary material 00030-2022.SUPPLEMENT

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        Electronically monitored medication adherence in idiopathic pulmonary fibrosis: prevalence, predictors and outcomes
        Anouk Delameillieure, Wim A. Wuyts, Antoine Pironet, Fabienne Dobbels
        ERJ Open Research Jul 2022, 8 (3) 00030-2022; DOI: 10.1183/23120541.00030-2022

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        Electronically monitored medication adherence in idiopathic pulmonary fibrosis: prevalence, predictors and outcomes
        Anouk Delameillieure, Wim A. Wuyts, Antoine Pironet, Fabienne Dobbels
        ERJ Open Research Jul 2022, 8 (3) 00030-2022; DOI: 10.1183/23120541.00030-2022
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