Literature DB >> 34950462

Polypharmacy and medication use in patients with chronic kidney disease with and without kidney replacement therapy compared to matched controls.

Manon J M van Oosten1, Susan J J Logtenberg2, Marc H Hemmelder3, Martijn J H Leegte4, Henk J G Bilo5, Kitty J Jager1, Vianda S Stel1.   

Abstract

BACKGROUND: This study aims to examine polypharmacy (PP) prevalence in patients with chronic kidney disease (CKD) Stage G4/G5 and patients with kidney replacement therapy (KRT) compared with matched controls from the general population. Furthermore, we examine risk factors for PP and describe the most commonly dispensed medications.
METHODS: Dutch health claims data were used to identify three patient groups: CKD Stage G4/G5, dialysis and kidney transplant patients. Each patient was matched to two controls based on age, sex and socio-economic status (SES) score. We differentiated between 'all medication use' and 'chronic medication use'. PP was defined at three levels: use of ≥5 medications (PP), ≥10 medications [excessive PP (EPP)] and ≥15 medications [hyper PP (HPP)].
RESULTS: The PP prevalence for all medication use was 87, 93 and 95% in CKD Stage G4/G5, dialysis and kidney transplant patients, respectively. For chronic medication use, this was 66, 70 and 75%, respectively. PP and comorbidity prevalence were higher in patients than in controls. EPP was 42 times more common in young CKD Stage G4/G5 patients (ages 20-44 years) than in controls, while this ratio was 3.8 in patients ≥75 years. Older age (64-75 and ≥75 years) was a risk factor for PP in CKD Stage G4/G5 and kidney transplant patients. Dialysis patients ≥75 years of age had a lower risk of PP compared with their younger counterparts. Additional risk factors in all patients were low SES, diabetes mellitus, vascular disease, hospitalization and an emergency room visit. The most commonly dispensed medications were proton pump inhibitors (PPIs) and statins.
CONCLUSIONS: CKD Stage G4/G5 patients and patients on KRT have a high medication burden, far beyond that of individuals from the general population, as a result of their kidney disease and a large burden of comorbidities. A critical approach to medication prescription in general, and of specific medications like PPIs and statins (in the dialysis population), could be a first step towards more appropriate medication use.
© The Author(s) 2021. Published by Oxford University Press on behalf of ERA-EDTA.

Entities:  

Keywords:  CKD; dialysis; health claims data; kidney transplantation; medication use; polypharmacy

Year:  2021        PMID: 34950462      PMCID: PMC8690067          DOI: 10.1093/ckj/sfab120

Source DB:  PubMed          Journal:  Clin Kidney J        ISSN: 2048-8505


INTRODUCTION

Polypharmacy (PP), defined as the concomitant use of medications by one individual, is a frequent phenomenon in clinical practice [1, 2]. Older age and multimorbidity are associated with the growing PP prevalence [2-4]. Chronic kidney disease (CKD) patients often have a large burden of comorbidities and commonly require a multitude of medications to prevent further progression of CKD, to treat its complications and to treat comorbidities [5]. This makes PP a part of their life [6-8]. PP puts patients at risk of medication-related problems, such as drug–drug interactions, suboptimal therapeutic response, a higher risk of adverse drug events and decreased medication adherence [5, 9]. Additionally, PP is associated with poorer quality of life, increased healthcare utilization with higher healthcare costs and a higher risk of morbidity and mortality [2, 10, 11]. Whether the poor outcomes associated with PP are merely a reflection of a person’s poor health remain unclear. Nevertheless, findings from previously published papers suggest an association between PP and mortality, even after adjustment for measured confounders such as comorbidities [12]. The prevalence of PP varies across countries and stages of CKD [6–8, 10, 13–17]. Current studies mostly report on elderly patients, only a few studies have used nationwide data and most studies lack a comparison with the general population [6, 7, 15]. This study aims to examine PP in patients with CKD Stage G4/G5 and patients on kidney replacement therapy (KRT) compared with matched general population controls of similar age, sex and socio-economic status (SES), while making use of a national health insurance database encompassing the complete known Dutch kidney disease population. Furthermore, we aim to determine risk factors for PP and commonly dispensed medications.

MATERIALS AND METHODS

Vektis insurance claims database

We used the Vektis database, which includes virtually all Dutch citizens [18]. Vektis contains reimbursement data on all medical procedures covered by the Health Insurance Act and demographic data such as sex, year of birth, area of residence, SES (Appendix 1) and date of death [19]. All hospital procedures in The Netherlands are reimbursed via physician claims called Diagnosis–Treatment Combinations (DBCs) [20]. Vektis also includes pharmacy dispensing data on anatomical therapeutic chemical code level, the defined daily dose (DDD) and the quantity of supplied medication per year. A DDD is a technical unit that reflects the assumed average maintenance dose per day for a medication used for its main indication [21]. The annual quantity supplied for a specific medication is a product of the DDD and the number of days a medication was dispensed. Information on over-the-counter medications and medications administered during a hospital admission or dialysis treatment are missing, since the costs for the latter are covered by the hospital DBC. Since health claims databases lack clinical data, we used proxies [e.g. pharmaceutical cost groups (PCGs)], to assess the prevalence and number of chronic conditions (Appendix 1) [22, 23]. Hospitalization, intensive care unit (ICU) admission and emergency room (ER) visits were identified by specific healthcare operation codes, an element of the DBC code (Appendix 1).

Study population

We selected adults (i.e. ≥20 years) with CKD Stage G4/G5 or on KRT using 2017 healthcare claims data. Patients were divided into three patient groups: CKD Stage G4/G5 [estimated glomerular filtration rate (eGFR) <30 mL/min/1.73 m2] without KRT, dialysis patients and kidney transplant patients. Patients were excluded if they switched between groups in 2017 (i.e. from CKD Stage G4/G5 to KRT and vice versa or between KRT modalities), if they died in 2017 or if matching was impossible (Figure 1).
FIGURE 1:

Flow chart study participants

Flow chart study participants

CKD Stage G4/G5 without KRT

We selected patients with a CKD Stage G4/G5 health claim on 1 January 2017. Since primary care does not have ‘disease-specific’ claims comparable to DBCs, we could not identify patients solely treated in primary care.

Dialysis

Patients with a health claim for dialysis on 1 January 2017 were selected regardless of dialysis modality.

Kidney transplantation

Patients with a health claim for kidney transplantation on 1 January 2017 were selected.

Control groups

Two controls per patient, matched for age, sex and SES (per quartile) were selected, provided they had no CKD-related healthcare claim.

PP

Medications with a cumulative annual DDD ≥15 (except for antibiotic treatment) and medications with a cumulative annual DDD ≥180 were selected. The first group (DDD ≥15) was further indicated as ‘all medication use’, to prevent inclusion of medication dispensed for a very short period, and the second cut-off (DDD ≥180) as ‘chronic medication use’. We defined PP at three levels: concurrent use of ≥5 medications (PP), ≥10 medications [excessive PP (EPP)] and ≥15 medications [hyper PP (HPP)]. For combination medications, the individual substances could not be extracted and therefore were counted as one.

Statistical analysis

To describe baseline characteristics we used means and standard deviations (SDs) for continuous variables and frequency distributions with percentages for categorical variables. To compare baseline characteristics between patients and controls we used the chi-squared test for categorical variables and the Mann–Whitney U-test for non-normally distributed continuous variables. We calculated the PP, EPP and HPP prevalences in all patient (sub)groups and controls and expressed them as percentages. These analyses were repeated in a sensitivity analysis, including all patients who died in 2017. Ratios were calculated by dividing the PP prevalence of patients by the respective prevalence in controls. Univariate and multivariate logistic regressions were used to analyse the association between the independent variables [e.g. age, sex and diabetes mellitus (DM)] and the outcome (i.e. EPP based on chronic medication use). The EPP prevalence was low (i.e. ≤15%) and therefore the rare disease assumption for logistic regression was met [24]. For the identification of confounders, we took the criteria for confounding into account [25]. Associations were expressed as odd ratios (ORs) with 95% confidence intervals (CIs). We considered a P-value <0.05 as statistically significant. Analyses were performed in SAS version 9.4 (SAS Institute, Cary, NC, USA).

RESULTS

Baseline characteristics

We included 27 573 individuals: 14 905 CKD Stage G4/G5 without KRT, 3872 dialysis and 8796 transplant patients, with mean ages of 75.6, 70.8 and 56.5 years, respectively (Table 1).
Table 1.

Baseline characteristics of CKD Stage G4/G5 without KRT, dialysis and kidney transplant patients and matched controls

CharacteristicsCKDDialysisKidney transplantation
Patients (n = 14 905)Matched controls (n = 29 810)P-valuePatients (n = 3872)Matched controls (n = 7744)P-valuePatients (n = 8796)Matched controls (n = 17 592)P-value
Age (years), median (25th–75th percentile)78.0 (70.0–84.0)78.0 (70.0–84.0)0.9974.0 (64.0–80.0)74.0 (64.0–80.0)1.0058.0 (48.8–67.0)58.0 (48.8–67.0)1.00
Age (years), mean (SD)75.6 (11.2)75.6 (11.2)0.9970.8 (13.2)70.8 (13.2)1.0056.5 (13.6)56.5 (13.6)1.00
Age (years), %
 20–441.81.84.54.519.619.6
 45–6412.212.222.522.548.448.4
 65–7425.025.025.825.824.624.6
 ≥7561.061.01.0047.347.31.007.57.51.00
Sex (male), %52.852.81.0058.858.81.0059.859.81.00
SES score, median (25th–75th percentile)−0.20 (−1.04–0.45)−0.18 (−1.01–0.45)0.16−0.35 (−1.21–0.33)−0.32 (−1.21–0.36)0.25−0.09 (−1.03–0.57)−0.11 (−1.01–0.57)0.61
Quartiles, %
 Q128.128.133.633.627.627.6
 Q226.526.526.626.624.924.9
 Q325.225.222.422.423.723.7
 Q420.220.21.0017.417.41.0023.923.91.00
No. of chronic conditions, mean (SD)1.92 (11.2)0.68 (0.98)<0.00011.86 (1.15)0.61 (0.96)<0.00011.46 (0.95)0.33 (0.71)<0.0001
Chronic conditions, %
 010.855.213.263.312.677.8
 125.921.024.319.345.714.1
 ≥263.423.8<0.000162.617.3<0.000141.78.1<0.0001
DM, %35.911.0<0.000131.19.8<0.000128.35.4<0.0001
Macrovascular disease, %17.75.2<0.000129.24.8<0.000111.32.4<0.0001
 Coronary artery disease, %8.74.3<0.000113.24.3<0.00016.02.5<0.0001
 Peripheral artery disease, %8.42.0<0.000116.91.8<0.00014.90.82<0.0001
 CVA/TIA, %2.51.7<0.00013.61.5<0.00011.60.67<0.0001
Malignancy, %13.77.4<0.000116.46.9<0.000119.23.6<0.0001
Hypertension, %88.035.7<0.000182.731.7<0.000186.617.2<0.0001
Hospitalization, %28.78.7<0.000152.37.8<0.000128.84.4<0.0001
ICU admittance, %2.60.78<0.00018.40.81<0.00012.50.35<0.0001
ER visit, %28.510.1<0.000149.59.2<0.000132.25.6<0.0001

Q: quartile; CVA/TIA: cerebrovascular accident/transient ischaemic attack.

Baseline characteristics of CKD Stage G4/G5 without KRT, dialysis and kidney transplant patients and matched controls Q: quartile; CVA/TIA: cerebrovascular accident/transient ischaemic attack. Chronic comorbidity conditions were 2.9 times more prevalent in CKD Stage G4/G5 patients than in controls (1.92 versus 0.68), 3.0 times higher in dialysis patients (1.86 versus 0.61) and 4.4 times higher in transplant patients (1.46 versus 0.33). In all patient groups, the prevalence of DM, macrovascular disease and hypertension was significantly higher than in controls.

Number of dispensed medications

All medication use

The median number of dispensed medications was 10 for CKD Stage G4/G5 patients, 12 for dialysis patients and 11 for transplant patients compared with 1, 1 and 0 in controls, respectively (Figure 2).
FIGURE 2:

Total number of dispensed medication per percentage of CKD stage G4/G5 not on KRT patients, dialysis and kidney transplant patients versus matched controls; all medication use

Total number of dispensed medication per percentage of CKD stage G4/G5 not on KRT patients, dialysis and kidney transplant patients versus matched controls; all medication use

Chronic medication use

The median number of dispensed medications was six in all patient groups, compared with zero in controls (Figure 3).
FIGURE 3:

Total number of dispensed medication per percentage of CKD stage G4/G5 not on KRT patients, dialysis and kidney transplant patients versus matched controls; chronic medication use

Total number of dispensed medication per percentage of CKD stage G4/G5 not on KRT patients, dialysis and kidney transplant patients versus matched controls; chronic medication use Figure 4 presents the prevalence and ratio of PP in patients versus controls for ‘all medication use’ (left panel) and ‘chronic medication use’ (right panel). The results of the sensitivity analyses were consistent with the results of the main analyses (Appendix 2).
FIGURE 4:

Percentage and ratio of polypharmacy of CKD stage G4/G5 without KRT, dialysis and kidney transplant patients versus matched controls for (left) all medication use and (right) chronic medication use

Percentage and ratio of polypharmacy of CKD stage G4/G5 without KRT, dialysis and kidney transplant patients versus matched controls for (left) all medication use and (right) chronic medication use

Overall

The PP, EPP and HPP prevalences were 87.4, 56.6 and 22.8%, respectively, in patients with CKD Stage G4/G5; 93.4, 69.3 and 31.5%, respectively, in dialysis patients; and 94.8, 60.0 and 21.5%, respectively, in transplant patients (Figure 4). For all comparisons, the PP, EPP and HPP prevalences were much higher in patients than in controls, with ratios ranging from 2.6 (PP in CKD patients versus controls) to 23.9 (EPP in transplant patients versus controls). Overall, PP based on chronic medication use was less common than PP based on all medication use (Figure 4). The PP, EPP and HPP prevalences were 66.1, 13.3 and 0.9%, respectively, in CKD Stage G4/G5 patients; 70.0, 15.1 and 1.2%, respectively, in dialysis patients; and 75.0, 14.9 and 1.0%, respectively, in transplant patients. Ratios ranged from 3.7 (PP in CKD patients) to 25.8 (EPP in transplant patients).

Patient subgroups

Tables 2 and 3 show the prevalence and ratio of PP in patients versus controls for different subgroups and for ‘all’ and ‘chronic medication use’. Since the PP prevalence for ‘all medication use’ was very high and the HPP prevalence for ‘chronic medication use’ was very low, these results are not shown.
Table 2.

Percentage and ratio of PP (‘all medication use’) in different subgroups of CKD Stage G4/G5 without KRT patients (n = 14 905), dialysis patients (n = 3872) and kidney transplant patients (n = 8796) versus matched controls (n = 29 810, n = 7744 and n = 17 592, respectively)

All medication use
CKDDialysisKidney transplantation
EPP ≥10 drugsHPP ≥15 drugsEPP ≥10 drugsHPP ≥15 drugsEPP ≥10 drugsHPP ≥15 drugs
SubgroupsPatientsMatched controlsRatioPatientsMatched controlsRatioPatientsMatched controlsRatioPatientsMatched controlsRatioPatientsMatched controlsRatioPatientsMatched controlsRatio
PP overall, %56.612.04.722.83.07.669.310.46.731.52.611.960.04.014.921.50.9023.9
Age (years), %
 20–4423.00.5542.06.60.047.40.8754.719.738.50.4978.18.50.0998.0
 45–6445.13.114.416.20.6026.867.03.817.432.61.227.059.22.821.120.00.6928.8
 65–7456.77.67.523.31.614.974.07.69.736.41.919.173.46.810.831.01.323.1
 ≥7560.016.03.824.44.25.869.815.94.429.54.07.477.412.06.434.22.911.9
Sex, %
 Male56.611.74.821.92.87.769.19.97.031.22.512.359.13.815.619.70.7326.9
 Female56.712.44.623.93.27.469.511.16.332.12.811.461.44.414.024.21.121.1
SES, %
 Q158.413.74.224.73.76.768.711.95.829.43.29.362.44.414.023.31.122.2
 Q257.612.14.823.73.08.070.89.97.233.52.911.760.94.513.521.51.120.0
 Q355.411.24.921.82.87.967.69.47.232.62.314.160.13.716.421.60.6732.1
 Q454.510.65.120.42.58.270.39.77.331.61.817.856.33.416.519.40.7625.4
No. of chronic conditions, %
 06.20.6310.00.620.087.924.00.5543.55.321.30.21100.62.70.0473.9
 131.411.42.86.11.54.053.810.85.014.61.59.947.46.17.79.60.7213.3
 ≥275.546.61.633.413.32.584.845.91.843.613.63.285.537.02.340.29.54.2
DM, %78.142.51.837.912.43.086.941.02.151.113.03.986.029.72.941.67.45.7
Macrovascular disease, %79.047.51.739.715.32.684.645.21.948.214.73.389.836.02.549.47.96.3
 Coronary artery disease, %84.636.52.344.011.53.889.438.22.356.013.64.190.824.63.753.25.110.4
 Peripheral artery disease, %75.941.11.837.614.62.682.734.12.446.28.75.390.835.22.649.77.66.5
 CVA/TIA, %77.338.32.041.010.83.884.832.72.642.88.84.887.917.84.948.93.414.4
Malignancy, %66.427.82.429.88.83.474.225.52.938.66.36.167.018.43.628.04.16.8
Hypertension, %62.830.72.025.68.03.277.129.72.635.98.04.565.319.63.323.94.45.4
Hospitalization, %78.247.11.742.917.12.579.244.41.843.014.53.081.828.22.942.69.54.5
ICU admittance, %85.460.51.452.023.62.283.160.31.450.325.42.090.850.81.859.024.62.4
ER visit, %78.542.61.843.515.12.978.441.11.941.314.82.878.022.83.438.57.55.1
Table 3.

Percentage and ratio of PP (‘chronic medication use’) in different subgroups of CKD Stage G4/G5 without KRT patients (n = 14 905), dialysis patients (n = 3872) and kidney transplant patients (n = 8796) versus matched controls (respectively n = 29810, n = 7744 and n = 17 592)

Chronic medication use
CKDDialysisKidney transplantation
PP ≥5 drugsEPP ≥10 drugs PP ≥5 drugsEPP ≥10 drugsPP ≥5 drugsEPP ≥10 drugs
SubgroupsPatientsMatched controlsRatioPatientsMatched controlsRatioPatientsMatched controlsRatioPatientsMatched controlsRatioPatientsMatched controlsRatioPatientsMatched controlsRatio
PP overall, %66.117.83.713.31.59.070.015.84.415.11.510.475.06.711.314.90.5527.3
Age (years), %
 20–4428.10.738.53.350.90.958.75.256.20.52107.64.50.03154.0
 45–6456.55.310.611.80.5820.568.65.811.818.60.8023.177.04.616.814.70.3937.9
 65–7469.412.65.515.91.114.173.512.85.718.51.018.483.111.97.021.31.020.9
 ≥7567.723.02.912.91.87.070.623.63.012.62.25.885.018.84.522.41.416.4
Sex, %
 Male, %67.518.53.613.81.78.171.016.34.316.01.411.077.66.711.615.80.5628.1
 Female, %64.417.13.812.91.210.568.515.04.613.81.59.471.36.610.713.60.5226.0
SES, %
 Q168.319.73.514.81.97.669.417.34.015.41.98.275.97.610.016.40.6226.4
 Q266.817.93.713.81.58.971.215.84.515.61.610.076.47.510.215.90.4833.0
 Q364.717.33.712.81.111.370.214.84.816.31.213.473.65.912.514.50.5526.2
 Q463.615.94.011.51.29.769.414.54.812.50.8215.374.15.513.412.70.5224.3
No. of chronic conditions, %
 05.30.69.20.120.0111.118.90.444.10.2027.60.13210.00.18
 146.320.82.20.910.127.953.520.32.62.40.2012.271.111.86.04.30.0853.2
 ≥284.566.21.320.77.22.987.267.01.323.18.22.893.760.21.631.06.64.7
DM, %86.261.81.425.68.33.184.363.51.327.69.62.991.852.01.834.26.15.6
Macrovascular disease, %84.361.11.423.07.43.179.760.21.324.17.03.590.750.91.834.16.05.6
 Coronary artery disease, %87.851.51.725.86.34.188.149.71.831.98.23.993.339.42.438.23.99.7
 Peripheral artery disease, %83.652.31.622.97.63.074.650.01.520.42.97.090.852.41.734.28.34.1
 CVA/TIA, %78.744.81.818.34.24.374.640.71.819.61.811.183.025.43.328.4
Malignancy, %71.835.02.115.23.74.173.233.72.215.33.74.178.425.33.117.02.18.2
Hypertension, %73.245.91.615.14.03.877.645.51.717.54.43.980.833.52.417.02.95.8
Hospitalization, %76.745.41.720.05.53.672.143.21.718.16.32.981.730.72.722.55.04.5
ICU admittance, %77.352.81.516.48.22.069.654.01.322.19.52.379.355.71.428.19.82.9
ER visit, %77.444.51.720.15.13.971.242.11.718.25.63.280.524.33.321.73.26.9
Percentage and ratio of PP (‘all medication use’) in different subgroups of CKD Stage G4/G5 without KRT patients (n = 14 905), dialysis patients (n = 3872) and kidney transplant patients (n = 8796) versus matched controls (n = 29 810, n = 7744 and n = 17 592, respectively) Percentage and ratio of PP (‘chronic medication use’) in different subgroups of CKD Stage G4/G5 without KRT patients (n = 14 905), dialysis patients (n = 3872) and kidney transplant patients (n = 8796) versus matched controls (respectively n = 29810, n = 7744 and n = 17 592) In CKD Stage G4/G5 and in transplant patients, the EPP and HPP prevalences were highest in patients ≥75 years of age (CKD G4/G5: 60.0 and 24.4%; transplantation: 77.4 and 34.2%). EPP was 42.0 times more common in young CKD patients (ages 20–44 years) than in controls, and this ratio declined with age to 3.8 in patients ≥75 years (Tables 2). PP was more common in both patients and controls with chronic conditions, such as diabetes or macrovascular disease, with EP prevalence ranging from 78.1 to 89.8% in patient groups and 24.6 to 47.5% in controls. The highest PP prevalence (EPP 90.8%) was found in transplant patients with coronary artery disease. PP was most common in CKD patients (69.4%) and dialysis patients (73.5%) ages 65–74 years and in transplant patients (85.0%) ≥75 years of age. Ratios between patient and control groups decreased with increasing age. The prevalence of PP was high in patients with chronic conditions in all patient groups (Table 3).

Risk factors for PP

Table 4 presents the unadjusted and adjusted association between patient demographics and disease-related variables and EPP (≥10 medications, ‘chronic medication use’). Below we discuss the fully adjusted models if adjustment for potential confounders was possible.
Table 4.

Unadjusted and adjusted analysis of variables associated with PP (defined as ≥10 medications for chronic medication use) in CKD Stage G4/G5 without KRT patients, dialysis patients and kidney transplant patients, using logistic regression

CKDDialysisKidney transplantation
UnadjustedAge-, sex-, SES-adjusted modelFully adjusted modelUnadjustedAge-, sex-, SES-adjusted modelFully adjusted modelUnadjustedAge-, sex-, SES-adjusted modelFully adjusted model
VariablesOR95% CIOR95% CIOR95% CIOR95% CIOR95% CIOR95% CIOR95% CIOR95% CIOR95% CI
Age categories (years)
  20–64Ref.Ref.Ref.
 65–741.571.33–1.85NAbNAb1.160.92–1.46NAbNAb3.692.89–4.71NAbNAb
  ≥751.241.06–1.44NAbNAb0.740.59–0.91NAbNAb5.884.60–7.51NAbNAb
Age (continuous, per 10 years)1.010.96–1.05NAbNAb0.960.90–1.03NAbNAb1.511.44–1.59NAbNAb
Sex
 FemaleRef.Ref.Ref.
 Male1.080.98–1.19NAbNAb1.180.99–1.42NAbNAb1.191.05–1.34NAbNAb
SES (categories)
 Q11.341.17–1.55NAbNAb1.280.97–1.68NAbNAb1.341.13–1.59NAbNAb
 Q21.231.07–1.43NAbNAb1.290.97–1.72NAbNAb1.291.09–1.54NAbNAb
 Q31.140.98–1.32NAbNAb1.361.02–1.82NAbNAb1.160.97–1.39NAbNAb
 Q4Ref.Ref.Ref.
DM5.004.51–5.544.984.50–5.52NAb3.643.04–4.363.693.08–4.43NAb6.595.81–7.485.594.91–6.36NAb
Vascular disease2.362.12–2.622.362.12–2.632.01c1.80–2.252.462.06–2.952.492.08–2.992.08c1.72–2.513.643.14–4.222.862.45–3.332.51c2.14–2.96
Hospitalization2.101.91–2.312.101.90–2.311.35d1.17–1.551.661.38–1.991.661.39–1.991.13 d0.90–1.422.161.91–2.441.991.76–2.251.29 d1.09–1.52
ICU admittance1.290.98–1.691.280.98–1.690.64e0.47–0.861.681.27–2.211.661.26–2.191.10 e0.81–1.492.291.70–3.101.991.46–2.711.10 e0.78–1.55
ER visit2.121.92–2.332.111.92–2.331.69f1.53–1.881.621.35–1.941.631.37–1.961.34 f1.11–1.622.091.85–2.352.011.78–2.271.76 f1.54–2.00

The overall PP rates (for PP defined as ≥10 medications for chronic medication use) are considered rare enough to reasonably allow for the rare disease assumption for logistic regression.

For this variable, no confounders could be identified considering the criteria for confounding (NA: not applicable).

Model adjusted for age, sex, SES and DM.

Model adjusted for age, sex, SES, DM, vascular disease and ER visits.

Model adjusted for age, sex, SES, DM, vascular disease, hospitalization and ER visits.

Model adjusted for age, sex, SES, DM and vascular disease.

Unadjusted and adjusted analysis of variables associated with PP (defined as ≥10 medications for chronic medication use) in CKD Stage G4/G5 without KRT patients, dialysis patients and kidney transplant patients, using logistic regression The overall PP rates (for PP defined as ≥10 medications for chronic medication use) are considered rare enough to reasonably allow for the rare disease assumption for logistic regression. For this variable, no confounders could be identified considering the criteria for confounding (NA: not applicable). Model adjusted for age, sex, SES and DM. Model adjusted for age, sex, SES, DM, vascular disease and ER visits. Model adjusted for age, sex, SES, DM, vascular disease, hospitalization and ER visits. Model adjusted for age, sex, SES, DM and vascular disease. Patients ages 65–74 years [OR 1.57 (95% CI 1.33–1.85)] and ≥75 years [OR 1.24 (95% CI 1.06–1.44)] had a higher EPP risk compared with patients ages 20–64 years. In addition, an SES score in the lowest two quartiles compared with an SES score in the highest quartile [OR 1.34 (95% CI 1.17–1.55) versus OR 1.23 (95% CI 1.07–1.43)], diabetes [OR 4.98 (95% CI 4.51–5.54)] or vascular disease [OR 2.01 (95% CI 2.12–2.62)], as well as hospitalization [OR 1.35 (95% CI 1.17–1.55)] and an ER visit [OR 1.69 (95% CI 1.53–1.88)] were significantly associated with PP. Patients ≥75 years of age had a lower risk of EPP [OR 0.74 (95% CI 0.59–0.91)] compared with patients ages 20–64 years. The most pronounced risk factors for EPP in dialysis patients were diabetes [OR 3.69 (95% CI 3.08–4.43)] and vascular disease [OR 2.08 (95% CI 1.72–2.51)]. Patients ages 65–74 years [OR 3.69 (95% CI 2.89–4.71)] and ≥75 years [OR 5.88 (95% CI 4.60–7.51)] had a higher EPP risk compared with patients ages 20–64 years. In addition, being male [OR 1.19 (95% CI 1.05–1.34)], having an SES score in the lowest two quartiles compared with an SES score in the highest quartile [OR 1.34 (95% CI 1.13–1.59) versus OR 1.29 (95% CI 1.09–1.54)], diabetes [OR 5.59 (95% CI 4.91–6.36)] or vascular disease [OR 2.51 (95% CI 2.14–2.96)], hospitalization [OR 1.29 (95% CI 1.09–1.52)] and an ER visit [OR 1.76 (95% CI 1.54–2.00)] were significantly associated with EPP.

Dispensed medication classes

Table 5 shows the most commonly dispensed chronic medication. Proton pump inhibitors (PPIs) were among the most commonly dispensed medications in patients, with ≥50% of patients using a PPI versus 8–19% of controls. Also, statins were commonly dispensed (53, 51 and 40% in CKD Stage G4/G5, transplant and dialysis patients, respectively). Dispensed medication classes for all medication use are shown in Appendix 3. Of note, 3–12% of CKD patients with DM do not use antidiabetic medication, whereas 17–19% of controls with DM are diet-controlled (Appendix 3, Table A1). Furthermore, 63–75% of CKD patients with DM chronically use antidiabetic medication compared with 61–65% of controls (Table 5).
Table 5.

Percentage of most commonly dispensed medication classes of CKD Stage G4/G5 without KRT patients, dialysis patients and kidney transplant patients and matched controls: medication classes defined for chronic medication use

Chronic medication use
CKDDialysisKidney transplantation
Patients, %Matched controls, %Patients, %Matched controls, %Patients, %Matched controls, %
Medication classes(n = 14 905)(n = 29 810)(n = 3872)(n = 7744)(n = 8796)(n = 17 592)
Cardiovascular drugs
 ACE inhibitors23.611.111.410.424.65.3
 ARB27.99.813.27.917.64.8
 Beta-blockers29.19.125.17.929.63.7
 Calcium channel blockers39.89.329.78.543.44.2
 Diuretics43.110.144.38.619.13.8
Statins52.819.339.518.350.810.2
PPIs51.919.465.516.854.08.2
Vitamin D analogues50.612.543.49.948.54.7
Antithrombotic agents45.219.250.317.229.67.6
 Platelet aggregation inhibitors38.815.344.613.923.96.2
 Vitamin K antagonist5.62.16.31.84.30.67
 Heparin0.270.140.440.100.470.06
 DOAC/NOAC1.11.90.031.61.40.76
Antidiabetics25.86.619.66.421.33.5
 Insulin15.82.114.82.111.21.0
 Metformin2.24.70.034.89.22.6
 Sulphonylurea derivative10.32.94.52.57.11.5

ACE: angiotensin-converting enzyme; ARB: angiotensin II receptor blocker; DOAC/NOAC: direct oral anticoagulant/novel oral anticoagulant.

Percentage of most commonly dispensed medication classes of CKD Stage G4/G5 without KRT patients, dialysis patients and kidney transplant patients and matched controls: medication classes defined for chronic medication use ACE: angiotensin-converting enzyme; ARB: angiotensin II receptor blocker; DOAC/NOAC: direct oral anticoagulant/novel oral anticoagulant.

DISCUSSION

This study using Dutch health claims data demonstrates that PP is highly prevalent in CKD Stage G4/G5 patients and patients with KRT compared with the general population. Since multimorbidity is one of the driving factors of PP, we must note that chronic comorbid conditions were three to four times more prevalent in patients than in controls. In our study, PP prevalence based on ‘all medication use’ ranged from 87% in CKD Stage G4/G5 to 94–95% in dialysis and transplant patients. The prevalence was lower for chronic medication use. Older age was an important risk factor for PP in CKD Stage G4/G5 and transplant patients, whereas dialysis patients ≥75 years of age had a lower risk of PP compared with younger counterparts. For all patients, additional risk factors were lower SES, DM, vascular disease, hospitalization and an ER visit during the year. The PP prevalence ratio between patients and controls declined with age. The most commonly dispensed medications were PPIs and statins, with more than half of patients using these medications.

Strengths and limitations

The main strength of this article is the use of a health claims database with almost complete national coverage of Stage G4/G5 CKD patients, by which we could study CKD Stage G4/G5 and KRT patients in the same cohort and compare them with the general population. Pharmacy dispensing data were complete and contained all medication dispensed by the pharmacy. This in contrast to other studies that used data from patient questionnaires, which heavily relies on patient memory. Another strength of pharmacy dispensing data is that they only include prescribed medication that was actually dispensed and do not cover prescribed medications that were never collected at the pharmacy. Although information on medication adherence is often missing in studies describing medication use, the regular dispensing of medication in a health claims database is an indirect yet strong indication that the medication was routinely taken. We must consider several limitations. First, although the identification of dialysis and transplant patients is accurate using health claims data [26], we were unable to identify patients with CKD treated in primary care, being mostly elderly patients [27]. Furthermore, data on medication adherence are missing. In addition, we were unable to identify medication given during dialysis sessions. Therefore the PP levels of dialysis patients reported in this study are likely an underestimation of their actual medication burden. Finally, the estimation of chronic conditions in our study was based on proxies that are vulnerable to inaccuracy.

Prevalence of PP

The comparison of the prevalence of PP with other studies is challenging due to the substantial differences in patient selection, definition of PP and data collection. Almost all previously performed studies collected cross-sectional medication data via patient reports or medical charts. Our study is unique in that we used pharmacy dispensing data, which enabled us to monitor all dispensed medication. The availability of the annual quantity of supplied medications makes it possible to differentiate between all and chronic medication use. The considerably higher PP prevalence based on all medication use compared with chronic medication use suggests that patients often receive short-term medication or experience medication changes. Although PP prevalence based on chronic medication use better reflects the structural medication burden, this type of medication use is not reported in other studies. Therefore we can only discuss our findings on the PP prevalence in the perspective of other studies on all medication use. Current literature describes PP prevalence in different stages of CKD, using different definitions of PP and mainly in elderly patients. Two studies describe PP prevalence in CKD Stage G4/G5 patients. Of these, Schmidt et al. [6] reported a PP prevalence of 92% (eGFR <30mL/min/1.73 m2). Hayward et al. [15] describe prevalences of 91% (≥5 medications) and 43% (≥10 medications) in a group of elderly (age >65 years) patients (eGFR <20 mL/min/1.73 m2) of different European countries. Within the subset of Dutch patients in this study, a prevalence of 91% (≥5 medications) and 43% (≥10 medications) was described. All results are comparable to our findings. Lower PP prevalence was found in patients with CKD Stages G1–G3 [6-8]. It is well known that dialysis patients have a high medication burden [13, 28, 29]. A pooled analysis reported that dialysis patients use 12 different medications [10, 29]. We report a median of 12 medications. A study from Saudi Arabia with 95 haemodialysis patients reported a 98% PP prevalence (>5 medications) [16], which is comparable to our PP prevalence. A Canadian study reported that 93.1% of elderly haemodialysis patients (age ≥65 years) used five or more medications [10]. No previous studies have reported on EP and HP prevalence and we are the first study in a much larger cohort of dialysis patients of all ages. A high pill burden is also described in transplant patients, ranging from 7 to 32 pills per day, depending on the time period after transplantation [30-32]. An Argentinean study described a mean of 7.8 different medications, while we describe a median of 10 different medications [33]. Only one Polish study reported PP prevalence in a much smaller group of 136 transplant patients as 56% (5–9 medications) and 17% (≥10 medications) [17]. We demonstrated a considerably higher PP and EP prevalence in our larger cohort of transplant patients.

Comparison with the general population

To our knowledge, this is the first study comparing the PP prevalence of CKD Stage G4/G5 patients and KRT patients with a matched control group from the general population. We demonstrate that PP prevalence is already substantially higher in young patients compared with controls, probably reflecting the high number of comorbidities in CKD patients already at a young age. The ratio of PP between patients and controls decreases with increasing age, because medication use increases more with age in the general population than it does in patients [34]. We confirm a positive association between PP and older age in CKD Stage G4/G5 and transplant patients [6, 8, 17, 35]. The inverse association between PP and age ≥75 years in dialysis patients may suggest some reluctance to prescribe medication in the elderly dialysis patient with limited life expectancy and being at high risk for medication-related problems. We confirm that the presence of chronic conditions like DM and cardiovascular disease are risk factors for PP in all patients [6, 10, 16, 36]. Next, we described a positive association between low SES and PP for CKD Stage G4/G5 and transplant patients, in line with other studies [6, 8]. A possible explanation is that individuals with a low SES often have low health literacy and are more vulnerable to comorbid illness. Lastly, we are the first to demonstrate a positive association between PP and hospitalization or an ER visit. We hypothesize that patients with an indication for an ER visit or hospital admission likely have severe comorbid conditions or complications of their CKD for which they need additional medication prescriptions. Moreover, PP itself may be associated with hospitalization in the elderly population [37, 38], although this was not confirmed elsewhere [39].

Medication dispensing

The increased cardiovascular risk of CKD patients is reflected in the high number of medications to prevent or treat cardiovascular conditions. Recent guidelines recommend statin prescription to CKD Stage G4/G5 patients [40]. Although (almost) all CKD Stage G4/G5 patients would be expected to fulfil the criteria for statin prescription, only half of the patients in our study used statins. Conversely, several studies question the benefit of statin therapy for dialysis patients [41-43]. Guidelines suggest that statins should not be routinely ‘initiated’, though they should be continued when patients already use statins when initiating dialysis treatment [44]. We suggest a critical evaluation of statin treatment in dialysis patients to reduce some of the medication burden. This also may be the case for PPIs [45]. More than 50% of CKD Stage G4/G5 and transplant patients, and even >65% of dialysis patients, used a PPI in our study. Previous studies reported PPI use of 30, 50 and 52% in haemodialysis patients and 33, 49 and 62% in CKD Stage G4/G5 patients, respectively [10, 15, 36]. The literature reports that the indication for PPI use in dialysis patients was unknown >25% of the time [46]. Since the long-term use of PPIs can have negative consequences, deprescribing of PPIs should be considered [47].

CONCLUSION

Our study demonstrates that patients with CKD Stage G4/G5 and patients on KRT have a very high medication burden, far beyond that of individuals from the general population. Important PP risk factors are age, SES, DM, vascular disease, hospitalization and an ER visit. Medication treatment of CKD patients is a challenging balance between the benefits of pharmacotherapy for the treatment of kidney disease and comorbidities and the disadvantages of potentially inappropriate prescribing or adverse drug interaction [48]. Although physicians often check whether the prescribed medication is appropriate in their patient, it is not easy to minimize the medication burden. As directed by the Hippocratic Oath, physicians strive for optimal treatment of their patients, while avoiding those twin traps of overtreatment and therapeutic nihilism. Undertreatment has been repeatedly associated with unfavourable outcomes in dialysis patients [49]. Despite the fact that therapeutic nihilism should be avoided at all times, we propose that a critical approach to the prescription of specific medications like PPIs in all CKD patients and statins in the dialysis population could be a first step towards more appropriate medication use. Finding a proper balance between potentially beneficial medication and needless use of medications with adverse effects will remain a challenge.

FUNDING

This work is financed by a grant from the Dutch Kidney Foundation.

CONFLICT OF INTEREST STATEMENT

None declared.

DATA AVAILABILITY STATEMENT

The Vektis database used for this study can only be accessed by contacting Vektis (see www.vektis.nl).

Definition of DM

Diagnosis code
Internal medicine
313.221DM without secondary complications
313.222DM with secondary complications
313.223DM chronic pump therapy
ATC code
A10Drugs used in diabetes
Primary care activity code
11602Multidisciplinary care T2DM—head tariff
13029Diabetes medical support per year
13030Diabetes regulation—insulin therapy
400001Multidisciplinary care T2DM—organization and infrastructure

ATC, anatomical therapeutic chemical.

Definition of macrovascular disease
Diagnosis codeVariable
Cardiology
313.101Symptomatic ischaemic heart disease1
313.102Instable angina, myocardial infarction1
313.121CVA/TIA3
313.123Aneurysm2
313.124Atherosclerosis of the extremities/peripheral artery disease2
313.129Aneurysm and other arterial vascular malformations2
Surgery
303.403Aneurysm thoracic aorta (including rupture)2
303.405Aneurysm iliac aorta2
303.406Aneurysm abdominal aorta, rupture2
303.409Vascular malformations abdomen/pelvis2
303.410Vascular damage upper extremity2
303.412Peripheral arterial occlusive disease Stage 1, arm2
303.416Aneurysm lower extremity2
303.418Peripheral arterial occlusive disease Stage 2, intermittent claudication2
303.419Peripheral arterial occlusive disease Stage 3, rest pain2
303.420Peripheral arterial occlusive disease Stage 4, gangrene2
303.427Crural ulcer2
303.431Buerger’s disease2
303.432Diabetic foot2
303.439Other peripheral artery disease2
Cardiology
320.2Thoracic pain, possible angina pectoris1
320.3Angina pectoris, no ischaemia detected yet1
320.4Angina pectoris, ischaemia detected1
320.5Ischaemia without angina pectoris (silent ischaemia)1
320.7Unstable/progressive angina pectoris1
320.9Acute myocardial infarction (q/non-q) anterior wall1
320.11Acute myocardial infarction (q/non-q) elsewhere1
320.13Follow-up after myocardial infarction1
320.15Follow-up after PTCA and/or CABG1
320.202Angina pectoris, stable1
320.203Angina pectoris, unstable1
320.204ST elevation myocardial infarction1
320.205Non ST elevation myocardial infarction1
320.801Follow-up after acute coronary syndrome1
320.802Follow-up after PTCA and/or CABG and/or ablation1
Neurology
330.1101Subarachnoid haemorrhage3
330.1102Intracerebral haemorrhage3
330.1103Intracranial haemorrhage (sub/epidural)3
330.1111Cerebral ischaemia3
330.1112TIA (including amaurosis fugax)3
Physical medicine and rehabilitation
327.0313CVA3
Cardiothoracic surgery
328.2320Coronary artery bypass graft (CABG), venous grafts and maximum 1 arterial graft1
328.2400CABG (≥2 arterial grafts)1
328.2415CABG (1 arterial graft) + mitral valve replacement1
328.2425CABG (1 arterial graft) + aortic valve replacement1
328.2470Left ventricular plasty + CABG1
328.2550CABG + MVR ± tricuspid valve replacement1
328.2555CABG (2 arterial grafts) + MVR1
328.2560CABG (1 arterial graft) + AVR + MVR1
328.2570CABG (2 arterial grafts) + AVR1
328.2585CABG + hypertrophic obstructive cardiomyopathy1
328.2630Ventricular tachycardia + CABG1
328.2635Maze + CABG1
328.2640Ventricular septal rupture + CABG1
328.2645MVR + AVR + CABG1
328.2650MVR + CABG (2 arterial grafts)1
328.2655AVR + CABG + hypertrophic obstructive cardiomyopathy1
328.2665Aortic root + CABG1
328.2720Aortic dissection ± CABG1
328.2740Aortic ascending + CABG1
328.2770Aortic root + CABG + MVR1
328.2775Aortic dissection B/conservative2
328.2785Maze + CABG or AVR + MVR ± TVR1
328.2810Thoracoabdominal aneurysm2
328.3210Carotid endarterectomy2
328.3320Acute aortic aneurysm2
Geriatric medicine
335.263CVA/TIA3
Definition of malignancies
Diagnosis code
Ophthalmology
301.358Tumour of the orbit
Ear Nose Throat
302.20Vestibular schwannoma
302.21Malignant tumour ear
302.60Malignant oral cavity tumour Stages 1 and 2
302.61Malignant oral cavity tumour Stages 3 and 4
302.62Malignant oropharyngeal tumour Stages 1 and 2
302.63Malignant oropharyngeal tumour Stages 3 and 4
302.64Malignant hypopharyngeal tumour Stages 1 and 2
302.65Malignant hypopharyngeal tumour Stages 3 and 4
302.66Malignant laryngeal tumour Stages 1 and 2
302.67Malignant laryngeal tumour Stages 3 and 4
302.68Malignant nasopharyngeal tumour Stages 1 and 2
302.69Malignant nasopharyngeal tumour Stages 3 and 4
302.72Malignant tumour salivary gland
302.84Malignant tumour throat
302.88Malignant skin tumour head/throat
Surgery
303.303Malignant neoplasm thyroid
303.306Malignant neoplasm salivary glands
303.313Neoplasm bronchus, lung
303.314Neoplasm mediastinum/pleura (mesothelioma)
303.315Malignant neoplasm oesophagus
303.318Malignant neoplasm breast
303.319Malignant neoplasm oesophagus/gastric cardia
303.330Malignant neoplasm stomach
303.331Malignant neoplasm gall bladder
303.332Malignant neoplasm pancreas/bile ducts
303.333Malignant neoplasm colon (excluding sigmoid/rectum)
303.334Malignant neoplasm rectosigmoid transition zone
303.335Malignant neoplasm rectum
303.346Malignant neoplasm stomach, excluding gastric cardia
303.347Peritoneal carcinomatosis caused by colorectal carcinoma without metastasis
303.348Neoplasm liver (including metastasis)
303.349Other malignant neoplasms abdomen
303.350Malignant melanoma of the skin
303.352Malignant neoplasm soft tissue
303.353Hogdkin lymphoma, non-Hodgkin lymphoma (NHL)
303.357Germ cell tumour
303.358Neuroblastoma
303.359Other oncological diagnosis
303.360Metastasis bone
303.363Malignant neoplasm bone (excluding metastasis)
303.367Malignant neoplasm liver (including metastasis)
303.370Wilms tumour
Plastic surgery
304.35Excision tumours with axial flap reposition, or with frozen tissue section, >5 or large malignant tumours
304.509Malignant tumour, not in functional area (FA)
304.511Malignant tumour in FA wherefore transposition or transplantation <1%
304.513Excision tumour wherefore transposition or transplantation in FA 1–3% or non-FA >3%, 2–5 tumours
Orthopaedic surgery
305.1110Metastasis in bone
305.1140Malignant neoplasm bone
305.1150Malignant neoplasm soft tissue
Urology
306.40Malignant neoplasm prostate
306.45Malignant neoplasm prostate with lymph nodes
306.48Malignant neoplasm prostate (orchidectomy)
306.50Penile cancer
306.92Penile cancer with lymph nodes
Gynaecology
307.M11Malignant neoplasm vulva
307.M12Malignant neoplasm vagina
307.M13Malignant neoplasm cervix
307.M14Malignant neoplasm endometrium
307.M15Malignant neoplasm myometrium
307.M16Malignant neoplasm of ovarian/fallopian tube
307.M17Chorionic carcinoma
307.M99Malignant neoplasm other
Neurosurgery
308.1810Neurosurgical part of stereotactic radiotherapy
Dermatology
310.14Malignant dermatosis
Internal medicine
313.214Malignant neoplasm thyroid
313.264Malignant neoplasm adrenal gland
313.291Multiple endocrine neoplasia syndrome
313.621Malignant neoplasm, small cell carcinoma bronchus
313.622Malignant neoplasm, large cell carcinoma bronchus
313.623Thymoma
313.624Malignant neoplasm pleura
313.629Other thoracic malignancies not further specified
313.751Hodgkin lymphoma
313.752NHL low grade
313.753NHL intermediate grade/high grade
313.754Multiple myeloma/primary amyloidosis
313.755Monoclonal gammopathy
313.756Acute lymphoid leukaemia
313.757Chronic lymphoid leukaemia, Waldenström’s and Hairy cell leukaemia
313.761Acute myeloid leukaemia/Refractory anaemia with excess blasts (RAEB) in transformation
313.762RAEB
313.771Chronic myeloid leukaemia
313.773Chronic myelomonocytic leukaemia
313.801Malignant neoplasm head–throat
313.802Malignant neoplasm central nervous system (primary)
313.811Malignant neoplasm breast
313.821Malignant neoplasm ovarium
313.822Malignant neoplasm cervix
313.823Malignant neoplasm endometrium
313.831Malignant neoplasm testicle
313.832Malignant neoplasm prostate
313.833Malignant neoplasm urinary tract
313.834Malignant neoplasm kidney/Grawitz
313.839Other malignant neoplasm in urogenital tract
313.841Malignant neoplasm bone and articular cartilage
313.842Malignant neoplasm skin/melanoma
313.843Malignant neoplasm soft tissue
313.899Malignant neoplasm not further specified
313.904Malignant neoplasm oesophagus/gastric cardia
313.914Malignant neoplasm stomach (excluding gastric cardia)
313.927Malignant neoplasm colorectal
313.964Malignant neoplasm pancreas
313.979Other malignancies digestive tract
Gastroenterology
318.307Oesophagus/cardia malignancy
318.407Stomach cancer, excluding gastric cardia cancer
318.408Lymphoma
318.610Colorectal cancer
731.312Malignant neoplasm liver
313.735Cholangiocarcinoma
313.810Oncological treatment in case of gastrointestinal malignancy
313.906Oncology, not gastrointestinal
Pulmonology
322.1303Non-small-cell lung carcinoma
322.1304Small-cell lung carcinoma
322.1305Mesothelioma
322.1308Metastasis of tumour elsewhere
Neurology
330.202Primary malignant neoplasm intracranial
330.203Secondary neoplasm intracranial (metastasis)
330.213Secondary neoplasm extracranial (metastasis)
330.223Secondary spinal neoplasm (metastasis)
330.233Secondary neoplasm extraspinal/epidural/spine (metastasis)
330.241Leptomeningeal malignancy
330.242Primary leptomeningeal malignancy
330.243Secondary leptomeningeal malignancy
330.251Paraneoplastic condition
330.299Other neuro-oncology
Radiotherapy
361.101Head and neck cancer and thyroid cancer
361.102Gastrointestinal cancer
361.103Lung and other intrathoracic cancer
361.104Bone and soft tissue cancer
361.105Breast cancer
361.106Gynaecological cancer
361.107Urological cancer
361.108Tumour in central nervous system
361.109Other malignant conditions
361.110Haematological cancer
361.111Unknown primary tumour
361.302Screening of late effects of cancer treatment

Definition of hypertension

Diagnosis code
Internal medicine
313.311Hypertension
Cardiology
320.902Hypertension
ATC code
C02Antihypertensives
C03Diuretics
C04Peripheral vasodilators
C07Beta-blocking agents
C08Calcium channel blockers
C09Agents acting on the renin–angiotensin system
Definition of hospitalization
Hospital activity code
190218Nursing day
Following care product codes were excluded
979002140Kidney transplantation with hospital admittance
979002141Kidney transplantation
979002142Living-donor kidney transplantation with hospital admittance
979002143Living-donor kidney transplantation
979002052Transplantation of kidney and pancreas
979002053Transplantation of kidney and pancreas with hospital admittance
979002036Transplantation of pancreas
979002037Transplantation of pancreas with hospital admittance
979002136Liver transplantation with hospital admittance
979002137Liver transplantation
979002139Partial liver transplantation
979002159Care for transplantation recipient with maximum of 13 nursing days
979002160Care for transplantation recipient with 14–28 nursing days
979002161Care for transplantation recipient with 29–56 nursing days
979002162Care for transplantation recipient with more than 56 nursing days
979002214Liver transplantation or transplantation of liver and kidney with hospital admittance
979002215Liver transplantation or transplantation of liver and kidney
979002297Pancreas transplantation
979002299Deceased-donor kidney transplantation with more than 28 nursing days
979002300Deceased-donor kidney transplantation with maximum of 28 nursing days
979002302Living-donor kidney transplantation with more than 28 nursing days
979002303Living-donor kidney transplantation with maximum of 28 nursing days
979002305Combined organ transplantation with more than 28 nursing days
979002306Combined organ transplantation with maximum of 28 nursing days

Definition of ICU admission

Hospital declaration code
039611Extracorporeal membrane oxygenation treatment supplement
190125ICU treatment day supplement Group 1
190126ICU admittance supplement Group 1—registration on first day on ICU
190127ICU ventilator supplement Group 1
190128ICU dialysis supplement Group 1
190129ICU consult
190130Interhospital critical care transport (<2 h)
190131Interhospital critical care transport (≥2 h)
190132Medical ICU (MICU) transport (<2 h)
190133MICU transport (≥2 h)
190134ICU treatment day supplement Group 2
190135ICU admittance supplement Group 2—registration on first day on ICU
190136ICU ventilator supplement Group 2
190137ICU dialysis supplement Group 2
190141ICU treatment day supplement Group 3
190142ICU admittance supplement Group 3—registration on first day on ICU
190143ICU ventilator supplement Group 3
190144ICU dialysis supplement Group 3
190150Neonatal ICU
190151Paediatric ICU
190153ICU treatment day—light care
190154ICU treatment day—medium care
190155ICU treatment day—heavy care
190156Dialysis supplement—per ICU day
190157ICU day—Type 1
190158ICU day—Type 1

Definition of ER visits

Hospital declaration code
190015Emergency care contact on an emergency department
190016Emergency care contact outside the emergency department, elsewhere in the hospital
Defined PCGs 2019
Description
1Acromegaly
2Asthma
3Autoimmune disorders (based on add-on)
4Cancer I (based on add-on)
5Cancer II (based on add-on)
6Central nervous system disorders: multiple sclerosis
7Central nervous system disorders: other
8Chronic anticoagulant use
9Chronic pain excluding opioids
10COPD/heavy asthma
11COPD/heavy asthma (based on add-on)
12Crohn’s disease/ulcerative colitis
13Cystic fibrosis/pancreas enzymes
14Depression
15DM Type Ia, with hypertension
16DM Type Ib, without hypertension
17DM Type IIa, with hypertension
18DM Type IIb, without hypertension
19Epilepsy
20Extreme high costs Cluster 1 (based on pharmacy claims and add-on)
21Extreme high costs Cluster 2 (based on add-on)
22Extreme high costs Cluster 3 (based on add-on)
23Glaucoma
24Growth disorders (based on add-on)
25Heart diseases
26HIV/AIDS
27Hormone sensitive tumours
28Immunoglobulin therapy (based on add-on)
29Neuropathic pain
30Parkinson’s disease
31Psoriasis
32Psychosis and addiction (excluding nicotin)
33Pulmonary (arterial) hypertension
34Renal disorders
35Rheumatoid arthritis
36Thyroid disorders
37Transplantation
Appendix Table A1.

DDDs for acromegaly

ATC codeOral
H01AX0110 mg
H01CB020.7 mg
H01CB033 mg
H01CB051.2 mg
Table A2.

DDDs for asthma

ATC codeInhalation (aerosol)Inhalation (powder)Inhalation (solution)OralParenteralRectal
R03AC020.8 mg0.8 mg10 mg
R03AC032 mg2 mg20 mg
R03AC120.1 mg0.1 mg
R03AC1324 μg24 μg
R03AK064 doses2 doses
R03AK072–4 doses
R03AK084 doses
R03AK0101 dose
R03AK0112–4 doses
R03AK0122 doses
R03BA010.8 mg0.8 mg1.5 mg
R03BA020.8 mg0.8 mg1.5 mg
R03BA050.6 mg0.6 mg1.5 mg
R03BA080.16 mg
R03BC0140 mg80 mg80 mg
R03BC038 mg
R03CC0212 mg12
R03DC0310 mg

Restriction: only if there is no ATC code for chronic obstructive pulmonary disease (COPD)/heavy asthma or COPD/heavy asthma (based on add-on).

Table A3.

DDDs for autoimmune diseases (based on add-on)

ATC codeParentalOralSubcutaneous
L04AA2427 mg
L04AA2625 mg
L04AA2910 mg
L04AA3260 mg
L04AA335.4 mg
L04AA374 mg
L04AB017 mg
L04AB023.75 mg
L04AB042.9 mg
L04AB0514 mg
L04AB061.66 mg
L04AC03100 mg
L04AC05540 μg
L04AC0720 mg
L04AC082.7 mg
L04AC1010 mg
L04AC1137 mg
L04AC1215 mg
L04AC132.9 mg
L04AC1414.3 mg

Based on additional reimbursements or add-ons: expensive or orphan drugs.

Table A4.

ATC codes for cancer I (based on add-on)

ATC codeName
L01AA01Cyclofosfamide
L01AA02Chloorambucil
L01AA03Melfalan
L01AA09Bendamustine
L01AB01Busulfan
L01AC01Thiotepa
L01AD02Lomustine
L01AX03Temozolomide
L01BA04Pemetrexed
L01BB03Tioguanine
L01BB05Fludarabine
L01BB06Clofarabine
L01BB07Nelarabine
L01BC01Cytarabine
L01BC03Tegafur
L01BC05Gemcitabine
L01BC06Capecitabine
L01BC07Azacitidine
L01BC08Decitabine
L01BC53Tegafur and Gimeracil and Oteracil
L01BC59Trifluridine and Tipiracil
L01CA01Vinblastine
L01CA02Vincristine
L01CA04Vinorelbine
L01CB01Etoposide
L01CB02Teniposide
L01CD01Paclitaxel
L01CD02Docetaxel
L01CD04Cabazitaxel
L01CX01Trabectedine
L01DB01Doxorubicine
L01DB03Epirubicine
L01DB06Idarubicine
L01DB07Mitoxantron
L01DB11Pixantron
L01DC01Bleomycine
L01DC03Mitomycine
L01XA01Cisplatine
L01XA03Oxaliplatine
L01XB01Procarbazine
L01XCAvelumab
L01XCdinutuximab Beta
L01XC02Rituximab
L01XC03Trastuzumab
L01XC06Cetuximab
L01XC07Bevacizumab
L01XC08Panitumumab
L01XC10Ofatumumab
L01XC11Ipilimumab
L01XC12Brentuximab Vedotine
L01XC13Pertuzumab
L01XC14Trastuzumab-Emtansine
L01XC15Obinutuzumab
L01XC17Nivolumab
L01XC18Pembrolizumab
L01XC19Blinatumomab
L01XC21Ramucirumab
L01XC22Necitumumab
L01XC23Elotuzumab
L01XC24Daratumumab
L01XC26Inotuzumab Ozogamicine
L01XC27Olaratumab
L01XC32Azetolizumab
L01XD05Temoporfine
L01XE01Imatinib
L01XE02Gefitinib
L01XE03Erlotinib
L01XE04Sunitinib
L01XE05Sorafenib
L01XE06Dasatinib
L01XE07Lapatinib
L01XE08Nilotinib
L01XE09Temsirolimus
L01XE10Everolimus
L01XE11Pazopanib
L01XE12Vandetanib
L01XE13Afatinib
L01XE14Bosutinib
L01XE15Vemurafenib
L01XE16Crizotinib
L01XE17Axitinib
L01XE18Ruxolitinib
L01XE21Regorafenib
L01XE23Dabrafenib
L01XE24Ponatinib
L01XE25Trametinib
L01XE26Cabozantinib
L01XE27Ibrutinib
L01XE28Ceritinib
L01XE29Lenvatinib
L01XE31Nintedanib
L01XE33Palbociclib
L01XE35Osimertinib
L01XE38Cobimetinib
L01XE39Midostaurine
L01XE42Ribociclib
L01XX01Amsacrine
L01XX02Asparaginase
L01XX05Hydroxycarbamide
L01XX11Estramustine
L01XX14Tretinone
L01XX17Topotecan
L01XX19Irinotecan
L01XX23Mitotaan
L01XX24Pegasparagase
L01XX25Bexaroteen
L01XX27Arseentrioxide
L01XX32Bortezomib
L01XX35Anagrelide
L01XX41Eribuline
L01XX42Panobinostat
L01XX43Vismodegib
L01XX44Aflibercept
L01XX45Carfilzomib
L01XX46Olaparib
L01XX47Idelalisib
L01XX50Ixazomib
L01XX51Talimogeen Laherparepvec
L01XX52Venetoclax
L02BB04Enzalutamide
L02BX03Abirateron
L03AX16Plerixafor
L04AX02Thalidomide
L04AX04Lenalidomide
L04AX06Pomalidomide
V10XX02Ibritumomab-Tiuxetan
V10XX03Radium-223 Dichloride

Based on additional reimbursements or add-ons: expensive or orphan drugs.

DDD not applicable; instead, the number of health claims are counted.

Table A5.

ATC codes for cancer II (based on add-on)

ATC codeName
L01AX04Dacarbazine
L01BB02Mercaptopurine
L01BB03Tioguanine
L01BC02Fluorouracil
L03AC01Aldesleukine
V10XX04lutetium Oxotreotide

Based on additional reimbursements or add-ons: expensive or orphan drugs.

DDD not applicable; instead, the number of health claims are counted.

Restriction: only if there is no ATC code for cancer I.

Table A6.

DDDs for central nervous system disorders: multiple sclerosis

ATC codeOralParenteral
L03AB074.3 mg
L03AB084 milIU
L03AB138.9 μg
L03AX1320 μg
L04AA270.5 mg
L04AA3114 mg
N07XX09480 mg

milIU, million international units.

Table A7.

DDDs for central nervous system disorders: other

ATC codeOralParenteral
A07AA11600 mg
M03BX0150 mg0.55 mg
M03BX0212 mg
N07XX020.1 g

Restriction: only if there is no ATC code for central nervous system disorders: multiple sclerosis

Table A8.

DDDs for chronic anticoagulant use

ATC-codeOral
B01AA043 mg
B01AA075 mg
B01AE070.3 g
B01AF0120 mg
B01AF0210 mg
B01AF0360 mg

Restriction: only if there is no ATC code for chronic obstructive pulmonary disease (COPD)/heavy asthma, COPD/heavy asthma (based on add-on), heart diseases and pulmonary (arterial) hypertension.

Table A9.

DDDs for chronic pain excluding opioids

ATC-codeOralRectalParenteralTransdermal
M01AA01300 mg
M01AB01100 mg100 mg100 mg
M01AB05100 mg100 mg100 mg
M01AB16200 mg
M01AB55100 mg
M01AC0120 mg20 mg20 mg
M01AC0615 mg15 mg15 mg
M01AE011.2 g1.2 g1.2 g
M01AE02500 mg500 mg
M01AE03150 mg150 mg150 mg
M01AE11600 mg600 mg
M01AE1775 mg75 mg
M01AE52500 mg
M01AH01200 mg
M01AH0560 mg
M01AX011 g
N01BX044 g
N06AA0975 mg75 mg
N06AX2160 mg

Restriction: only if there is no ATC code for neuropathic pain.

Table A10.

DDDs for chronic obstructive pulmonary disease (COPD)/heavy asthma

ATC codeOralInhalation (aerosol)Inhalation (powder)Inhalation (solution)ParentalRectal
R03AC18150 μg
R03AC195 μg
R03AL016 doses3 doses
R03AL026 doses7.5 mL
R03AL031 dose
R03AL041 dose
R03AL052 doses
R03AL062 doses
R03AL094 doses
R03BB010.12 mg0.12 mg0.3 mg
R03BB0410 μg5 μg
R03BB05664 μg
R03BB0644 μg
R03BB0755 μg
R03DA040.4 g0.4 g0.4 g

Restriction: only if there is no ATC code for COPD/heavy asthma (based on add-on).

Table A11.

DDDs for chronic obstructive pulmonary disease (COPD)/heavy asthma (based on add-on)

ATC codeParental
R03DX0516 mg
R03DX087.5 mg
R03DX093.6 mg

Based on additional reimbursements or add-ons: expensive or orphan drugs.

Table A12.

DDDs for Crohn’s disease/ulcerative colitis

ATC codeOralRectal
A07EA04100 mL
A07EA069 mg1 tablet
A07EC021.5 g1.5 g
A07EC031 g

Restriction: only if there is no ATC code for autoimmune diseases.

Table A13.

DDDs for cystic fibrosis/pancreas enzymes

ATC codeInhalation (powder)Inhalation (solution)Oral
A09AA024–6 tablets/capsules
J01GB01112 mg0.3 g
J01XB013 milIU
R05CB132.5 mg
R07AX304 tablets

milIU: million international units.

Table A14.

DDDs for depression

ATC codeOralParenteral
N06AA020.1 g0.1 g
N06AA040.1 g0.1 g
N06AA1075 mg30 mg
N06AA120.1 g0.1 g
N06AA160.15 g
N06AA210.1 g0.1 g
N06AB0320 mg
N06AB0420 mg20 mg
N06AB0520 mg
N06AB0650 mg
N06AB080.1 g
N06AB1010 mg
N06AF0360 mg
N06AF0410 mg
N06AG020.3 g
N06AX0360 mg
N06AX050.3 g
N06AX1130 mg
N06AX120.3 Ga
N06AX160.1 g
N06AX2225 mg
N06AX2610 mg

Restriction: only if there is no ATC code for psychoses and addiction.

Drugs used to quit smoking excluded.

Table A15.

DDDs for DM Type I, DM Type Ia (>90 DDDs hypertension) or DM Type Ib (≤90 DDDs hypertension)

ATC codeParenteral
A10AB0140 IU
A10AB0440 IU
A10AB0540 IU
A10AB0640 IU
A10AC0140 IU
A10AD0140 IU
A10AD0440 IU
A10AD0540 IU
A10AD0640 IU
A10AE0440 IU
A10AE0540 IU
A10AE0640 IU
A10AE5440 IU
A10AE5640 IU
Table A16.

DDDs for DM Type II, DM Type IIa (>90 DDDs hypertension) or DM Type IIb (≤90 DDDs hypertension)

ATC codeOralParenteralParenteral depot
A10BA022 g
A10BB0110 mg
A10BB031.5 g
A10BB0960 mg
A10BB122 mg
A10BD022 tablets
A10BD052 tablets
A10BD072 tablets
A10BD082 tablets
A10BD102 tablets
A10BD112 tablets
A10BD152 tablets
A10BD162 tablets
A10BD202 tablets
A10BF010.3 g
A10BG0330 mg
A10BH010.1 g
A10BH020.1 g
A10BH035 mg
A10BH055mg
A10BJ0115 μg286 μg
A10BJ021.2 mg
A10BJ0320 μg
A10BJ050.16 mg
A10BK0110 mg
A10BK02200 mg
A10BK0317.5 mg
A10BX024 mg

Restriction: Only if there is no ATC code for DM Type I (Ia or Ib).

Table A17.

DDDs for epilepsy

ATC-codeOralParenteralRectal
N03AA020.1 g0.1 g
N03AA031.25 g
N03AB020.3 g0.3 g
N03AD011.25 g
N03AE018 mg8 mg
N03AF011 g1 g
N03AF021 g
N03AF031.4 g
N03AG011.5 g1.5 g1.5 g
N03AG042 g
N03AX030.4 g
N03AX090.3 g
N03AX102.4 g
N03AX110.3 g
N03AX141.5 g1.5 g
N03AX150.2 g
N03AX171 g
N03AX180.3 g0.3 g
N03AX210.9 g
NO3AX228 mg
NO3AX23100 mg100 mg
N05BA0920mg
Table A18.

ATC codes for extremely high costs, Cluster 1 (based on pharmacy claims and add-on)

ATC codeName
A16AA05Cargluminezuur
A16AB02Imiglucerase
A16AB03Agalsidase Alfa
A16AB04Agalsidase Beta
A16AB10Velaglucerase Alfa
A16AX06Miglustat
B01AC09Epoprostenol
B01AC21Treprostinil
N07XX08Tafamidis

Based on additional reimbursements or add-ons: expensive or orphan drugs.

DDD not applicable; instead, the number of health claims are counted.

Table A19.

ATC codes for extreme high costs, Cluster 2 (based on add-on)

ATC codeName
A16AB05Laronidase
L04AA25Eculizumab

Based on additional reimbursements or add-ons: expensive or orphan drugs.

DDD not applicable; instead, the number of health claims are counted.

Table A20.

ATC codes for extreme high costs, Cluster 2 (based on add-on)

ATC codeName
A16AB07Alglucosidase Alfa
A16AB08Galsulfase
A16AB09Idursulfase

Based on additional reimbursements or add-ons: expensive or orphan drugs.

DDD not applicable; instead, the number of health claims are counted.

Table A21.

DDDs for glaucoma

ATC-codeOralParenteralOcular
S01EA030.3 mL
S01EA050.2 mL
S01EB010.4/40 mL/mg
S01EC010.75 g0.75 g
S01EC030.3 mL
S01EC040.2 mL
S01EC540.2 mL
S01ED010.2 mL
S01ED020.2 mL
S01ED030.2 mL
S01ED050.2 mL
S01ED510.1/0.2 mL
S01ED540.3 mL
S01EE010.1 mL
S01EE030.1 mL
S01EE040.1 mL
S01EE050.3mL
Table A22.

ATC codes and DDDs for growth disorders (based on add-on)

ATC-codeParenteral
H01AC012 IU
H01AC032 mg

Based on additional reimbursements or add-ons: expensive or orphan drugs.

Table A23.

DDDs for heart diseases

ATC- codeOralOral (aerosol)ParenteralSublingualTransdermal
C01AA050.25 mg0.25 mg
C01BA011.2 g
C01BA030.4 mg0.4 mg
C01BB013 g
C01BC030.3 g0.3 g
C01BC040.2 g0.2 g
C01BD010.2 g0.2 g
C01CE0250 mg
C01CE031 g
C01DA025 mg2.5 mg10 mg2.5 mg5 mg
C01DA0860 mg20 mg10 mg20 mg0.1 g
C01DA1440 mg
C01DX1640 mg
C01EB1710mg
C03CA0140 mg40 mg
C03CA021 mg1 mg
C09DX042 tablets
Table A24.

ATC codes and DDDs for HIV/AIDS

ATC-codeOralParenteral
J05AE011.8 g
J05AE022.4 g
J05AE031.2 g
J05AE071.4 g
J05AE080.3 g
J05AE091 g
J05AE101.2 g
J05AF010.6 g0.6 g
J05AF020.4 g
J05AF0480 mg
J05AF050.3 g
J05AF060.6 g
J05AF070.245 g
J05AF090.2 g
J05AG010.4 g
J05AG030.6 g
J05AG040.4 g
J05AG0525 mg
J05AR012 tablets
J05AR021 tablet
J05AR031 tablet
J05AR042 tablets
J05AR061 tablet
J05AR081 tablet
J05AR091 tablet
J05AR100.8 g
J05AR131 tablet
J05AR141 tablet
J05AR171 tablet
J05AR181 tablet
J05AR191 tablet
J05AX070.18 g
J05AX080.8 g
J05AX090.6 g
J05AX1250 mg
V03AX03150 mg
Table A25.

DDDs for hormone-sensitive tumours

ATC-codeOralParenteralParenteral depotImplantationNasal
L02AB010.16 g
L02AB021 g1 g
L02AE011.5 mg0.11 mg1.2 mg
L02AE021mg0.134 mg60 μg
L02AE030.129 mg
L02AE050.137 mg
L02BA0120 mg
L02BA038.3 mg
L02BB010.75 g
L02BB020.3 g
L02BB0350 mg
L02BG031 mg
L02BG042.5 mg
L02BG0625 mg
L02BX013.6 mg
L02BX022.7 mg

Restriction: only if there is no ATC code for cancer I or cancer II.

Table A26.

ATC codes for immunoglobulin therapy (based on add-on)

ATC codeName
J06BA02Immunoglobuline i.v.

Based on additional reimbursements or add-ons: expensive or orphan drugs.

DDD not applicable; instead, the number of health claims are counted.

Table A27.

DDDs for neuropathic pain

ATC-codeOral
N03AX121.8 g
N03AX160.3 g
Table A28.

DDDs for Parkinson’s disease

ATC-codeOralParenteralTransdermal
N04BA020.6 g
N04BA030.45 g
N04BB010.2 g
N04BC0140 mg
N04BC023 mg
N04BC046 mg
N04BC052.5 mg
N04BC0720 mg
N04BC096 mg
N04BD015 mg
N04BD021 mg
N04BD0375 mg
N04BX010.45 g
N04BX021 g
Table A29.

ATC codes and DDDs for psoriasis

ATC-codeOralTransdermal
D05AC011 g or mg or mL
D05AX021 g or mg or mL
D05AX031 g or mg or mL
D05AX521 g or mg or mL
D05BA0210 mg
D05BB0235 mg
D05BX120 mg
D05BX51120 mg

Restriction: only if there is no ATC code for autoimmune disorders.

Table A30.

DDDs for psychosis and addiction (excluding nicotin)

ATC-codeOralParenteralParenteral depotRectalSublingual
N05AA010.3 g0.1 g0.3 g
N05AB0210 mg1 mg
N05AB0330 mg10 mg7 mg16 mg
N05AC0150 mg20 mg
N05AD018 mg8 mg3.3 mg
N05AD050.2 g
N05AD0610 mg10 mg3.3 mg
N05AE0316 mg
N05AE0560 mg
N05AF016 mg4 mg
N05AF030.3 g50 mg
N05AF0530 mg30 mg15 mg
N05AG010.7 mg
N05AG024 mg
N05AG036 mg
N05AH020.3 g0.3 g
N05AH0310 mg10 mg10 mg
N05AH040.4 g
N05AL010.8 g0.8 g
N05AX085 mg2.7 mg
N05AX1215 mg15 mg13.3 mg
N05AX136 mg2.5 mg
N07BB010.2 g
N07BB032 g
N07BB0450 mg
N07BB0518 mg
N07BC018 mg
N07BC0225 mg25 mg
N07BC518mg
Table A31.

DDDs for pulmonary (arterial) hypertension

ATC-codeOralParenteralInhalation
B01AC1150 μg150 μg
B01AC271.8 mg
C02KX01250 mg
C02KX027.5 mg
C02KX0410 mg
C02KX054.5 mg
G04BE0350 mg
G04BE0810 mg
Table A32.

DDDs for rheumatoid arthritis

ATC-codeOralParenteralRectal
A07EC012 g2 g
L01BA013.571 mg
L04AA1320 mg
L04AX032.5 mg3.571 mg
M01CB012.4 mg
M01CC010.5 g
P01BA020.516 g

Restriction: Only if there is no ATC code for auto-immune disorders.

Table A33.

DDDs for thyroid disorders

ATC-codeOralParenteral
H03AA010.15 mg0.15mg
H03AA0260 μg60 μg
H03BA020.1 g
H03BB0115 mg
H03BB0210 mg
CKDDialysisKidney transplantation
Main analysis (n = 14 905)Sensitivity analysis (n = 17 198)Main analysis (n = 3872)Sensitivity analysis (n = 17 198)Main analysis (n = 8796)Sensitivity analysis (n = 9087)
All medication use, %
PP≥5 drugs87.485.293.489.894.894.4
EPP≥10 drugs56.755.869.366.260.060.4
HPP≥15 drugs22.823.131.529.921.522.2
Chronic medication use
PP≥5 drugs66.160.870.060.975.073.8
EPP≥10 drugs13.312.015.112.714.914.7
HPP≥15 drugs0.850.741.21.01.01.0
Table A1.

Percentage of most commonly prescribed dispensed medication classes of CKD stage G4/G5 not on KRT, dialysis and kidney transplant patients and matched controls; medication classes defined for all medication use

All medication use
CKDDialysisKidney transplantation
Patients, %Matched controls, %Patients, %Matched controls, %Patients, %Matched controls, %
Medication classes(n = 14 905)(n = 29 810)(n = 3872)(n = 7744)(n = 8796)(n = 17 592)
Cardiovascular drugs
 ACE inhibitors30.013.016.811.931.56.1
 ARB31.410.716.78.920.85.1
 Beta-blockers56.619.161.316.656.48.1
 Calcium channel blockers44.110.835.99.847.94.9
 Diuretics51.014.245.711.826.15.
Statins61.322.748.221.463.512.0
PPIs56.922.871.019.858.210.1
Vitamin D analogues73.315.176.211.965.35.7
Antithrombotic agents64.525.370.521.539.59.6
 Platelet aggregation inhibitors41.716.449.614.726.26.8
 Vitamin K antagonist24.26.726.95.012.31.5
 Heparin3.01.24.41.14.10.7
 DOAC/NOAC2.12.90.082.42.51.1
Antidiabetics31.88.827.58.027.44.5
 Insulin19.92.622.02.615.21.3
 Metformin6.47.20.316.615.03.8
 Sulphonureumderivate13.23.66.83.18.81.8
 SGLT2 inhibitors0.090.050.090.130.06
 DPP-4 inhibitors2.90.341.80.271.10.15
 GLP-1 analogues0.280.060.100.140.140.11
Antibiotics39.419.051.916.854.312.5
Cinacalcet2.20.0423.50.038.20.01
Osteoporosis prophylaxis
 Bisfosfonates2.02.60.281.98.50.81
 Calcium derivates15.36.422.44.826.62.1
Urate-lowering therapy25.41.917.21.614.60.88
Phosphate binders12.10.0278.50.053.00.02
Haematopoietic
 Irona14.21.64.61.27.10.54
 EPOa18.80.134.70.125.40.01
Opioids8.63.213.22.86.71.5

Intravenous iron and EPO therapy were not included in this study.

SGLT2: sodium–glucose-cotransporter 2; DPP-4: dipeptidylpeptidase-4; GLP-1: glucagon-like peptide-1; EPO: erythropoietin.

Table A2.

Percentage of most commonly prescribed dispensed medication classes of CKD stage G4/G5 not on KRT, dialysis and kidney transplant patients and matched controls; medication classes defined for chronic use (complement to in main article)

Chronic medication use
CKDDialysisKidney transplantation
Patients (%)Matched controls (%)Patients (%)Matched controls (%)Patients (%)Matched controls (%)
Medication classes(n = 14,905)(n = 29,810)(n = 3,872)(n = 7,744)(n = 8,796)(n = 17,592)
Antidiabetics
 SGLT2 inhibitors0.050.020.060.080.02
 DPP-4 inhibitors2.10.281.20.190.760.09
 GLP-1 analogues0.190.040.080.120.070.11
Antibiotics0.400.170.800.191.40.10
Cinacalcet0.980.0212.74.5
Osteoporosis prophylaxis
 Bisfosfonates1.42.10.081.56.20.65
 Calcium derivates10.74.815.23.618.21.5
Urate-lowering therapy7.70.812.90.775.50.35
Phosphate binders1.644.60.28
Hematopoietics
 Irona3.40.351.00.361.20.05
 EPO8.10.080.850.082.26
Opioids1.70.582.00.521.20.34

Intravenous iron and EPO therapy were not included in this study.

DOAC/NOAC: direct oral anticoagulant/novel oral anticoagulant; SGLT2: sodium-glucose-cotransporter 2; DPP-4: dipeptidylpeptidase-4; GLP-1: glucagon-like peptide-1; EPO: erythropoietin.

  44 in total

1.  Pharmacy costs groups: a risk-adjuster for capitation payments based on the use of prescribed drugs.

Authors:  L M Lamers
Journal:  Med Care       Date:  1999-08       Impact factor: 2.983

2.  Confounding: what it is and how to deal with it.

Authors:  K J Jager; C Zoccali; A Macleod; F W Dekker
Journal:  Kidney Int       Date:  2007-10-31       Impact factor: 10.612

3.  Evaluation of the adequacy of drug prescriptions in patients with chronic kidney disease: results from the CKD-REIN cohort.

Authors:  Solène M Laville; Marie Metzger; Bénédicte Stengel; Christian Jacquelinet; Christian Combe; Denis Fouque; Maurice Laville; Luc Frimat; Carole Ayav; Elodie Speyer; Bruce M Robinson; Ziad A Massy; Sophie Liabeuf
Journal:  Br J Clin Pharmacol       Date:  2018-09-24       Impact factor: 4.335

Review 4.  Health outcomes associated with polypharmacy in community-dwelling older adults: a systematic review.

Authors:  Terri R Fried; John O'Leary; Virginia Towle; Mary K Goldstein; Mark Trentalange; Deanna K Martin
Journal:  J Am Geriatr Soc       Date:  2014-12       Impact factor: 5.562

Review 5.  The Role of Deprescribing in Older Adults with Chronic Kidney Disease.

Authors:  Laura K Triantafylidis; Chelsea E Hawley; Laura P Perry; Julie M Paik
Journal:  Drugs Aging       Date:  2018-11       Impact factor: 3.923

6.  Pill burden, adherence, hyperphosphatemia, and quality of life in maintenance dialysis patients.

Authors:  Yi-Wen Chiu; Isaac Teitelbaum; Madhukar Misra; Essel Marie de Leon; Tochi Adzize; Rajnish Mehrotra
Journal:  Clin J Am Soc Nephrol       Date:  2009-05-07       Impact factor: 8.237

7.  Prescribed drugs and polypharmacy in healthcare service users in South Korea: an analysis based on National Health Insurance Claims data.

Authors:  Hae-Young Park; Hyun-Nam Ryu; Mi Kyong Shim; Hyun Soon Sohn; Jin-Won Kwon
Journal:  Int J Clin Pharmacol Ther       Date:  2016-05       Impact factor: 1.366

8.  Strategies for reducing polypharmacy and other medication-related problems in chronic kidney disease.

Authors:  Nancy A Mason; Jodie L Bakus
Journal:  Semin Dial       Date:  2009-09-11       Impact factor: 3.455

9.  Rosuvastatin and cardiovascular events in patients undergoing hemodialysis.

Authors:  Bengt C Fellström; Alan G Jardine; Roland E Schmieder; Hallvard Holdaas; Kym Bannister; Jaap Beutler; Dong-Wan Chae; Alejandro Chevaile; Stuart M Cobbe; Carola Grönhagen-Riska; José J De Lima; Robert Lins; Gert Mayer; Alan W McMahon; Hans-Henrik Parving; Giuseppe Remuzzi; Ola Samuelsson; Sandor Sonkodi; D Sci; Gultekin Süleymanlar; Dimitrios Tsakiris; Vladimir Tesar; Vasil Todorov; Andrzej Wiecek; Rudolf P Wüthrich; Mattis Gottlow; Eva Johnsson; Faiez Zannad
Journal:  N Engl J Med       Date:  2009-03-30       Impact factor: 91.245

10.  The burden of comorbidity in people with chronic kidney disease stage 3: a cohort study.

Authors:  Simon D S Fraser; Paul J Roderick; Carl R May; Natasha McIntyre; Christopher McIntyre; Richard J Fluck; Adam Shardlow; Maarten W Taal
Journal:  BMC Nephrol       Date:  2015-12-01       Impact factor: 2.388

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1.  Chronic prescription of antidepressant medication in patients with chronic kidney disease with and without kidney replacement therapy compared with matched controls in the Dutch general population.

Authors:  Manon J M van Oosten; Dan Koning; Susan J J Logtenberg; Martijn J H Leegte; Henk J G Bilo; Marc H Hemmelder; Kitty J Jager; Vianda S Stel
Journal:  Clin Kidney J       Date:  2021-12-03
  1 in total

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