Literature DB >> 30836953

Potential life-years gained over a 5-year period by correcting DOPPS-identified modifiable practices in haemodialysis: results from the European MONITOR-CKD5 study.

Christian Combe1, Johannes Mann2, David Goldsmith3, Frank Dellanna4, Philippe Zaoui5, Gérard London6, Kris Denhaerynck7,8, Andriy Krendyukov9, Ivo Abraham10,11, Karen MacDonald7.   

Abstract

BACKGROUND: DOPPS reported that thousands of life-years could be gained in the US and Europe over 5 years by correcting six modifiable haemodialysis practices. We estimated potential life-years gained across 10 European countries using MONITOR-CKD5 study data.
METHODS: The DOPPS-based target ranges were used, except for haemoglobin due to label changes, as well as DOPPS-derived relative mortality risks. Percentages of MONITOR-CKD5 patients outside targets were calculated. Consistent with the DOPPS-based analyses, we extrapolated life-years gained for the MONITOR-CKD5 population over 5 years if all patients were within targets.
RESULTS: Bringing the 10 MONITOR-CKD5 countries' dialysis populations into compliance on the six practices results in a 5-year gain of 97,428 patient-years. In descending order, survival impact was the highest for albumin levels, followed by phosphate levels, vascular access, haemoglobin, dialysis adequacy, and interdialytic weight gain.
CONCLUSIONS: Optimal management of the six modifiable haemodialysis practices may achieve 6.2% increase in 5-year survival. TRIAL REGISTRATION: NCT01121237 . Clinicaltrials.gov registration May 12, 2010 (retrospectively registered).

Entities:  

Keywords:  Anaemia; Biosimilar epoetin alfa; Haemodialysis; Life-years; Modifiable haemodialysis practices

Mesh:

Year:  2019        PMID: 30836953      PMCID: PMC6402099          DOI: 10.1186/s12882-019-1251-z

Source DB:  PubMed          Journal:  BMC Nephrol        ISSN: 1471-2369            Impact factor:   2.388


Background

The Dialysis Outcomes and Practice Patterns Study (DOPPS) [1] reported [2] that an additional 143,617 patient life-years could be gained in the United States over a 5-year period if six modifiable haemodialysis practices were brought into best practice compliance. Four of the six modifiable haemodialysis practices (dialysis dose, phosphate control, improved anaemia, and partial correction of serum albumin) are supported by published guidelines [3-6] while reduced inter-dialytic weight gain [7, 8] and reduced use of catheters for vascular access [9-12] have been linked to mortality. These analyses were replicated for Belgium [13], Spain [14], France [15] and Sweden [16], except that albumin-corrected serum calcium was substituted for intradialytic weight gain. Here, we present a simulation of potential life-years gained by correcting these six practices across 10 European countries using data from the MONITOR-CKD5 study.

Methods

MONITOR-CKD5, a real-world, prospective, observational study on the treatment patterns and associated outcomes of renal anaemia management with Sandoz epoetin alfa biosimilar (commercially available as Binocrit®/Epoetin Alfa Hexal®; hereafter Binocrit®), included an evaluable sample of 2023 CKD5 patients from 114 centres in 10 European countries: Austria (6 centres), France (35), Germany (45), Italy (21), Poland (7), Romania (14), Slovenia (2), Spain (6), Switzerland (4), and the United Kingdom (4). Eligible were male or female CKD5 adult (age ≥ 18) patients on haemodialysis of original or grafted kidneys; diagnosed with renal anaemia; and treated with intravenous Binocrit®. The overall study methodology has been detailed elsewhere [17]. The original DOPPS methodology to estimate life-years gained from modifiable haemodialysis practices [2], as well as the methodology of the four country replications [13-16] and the MONITOR-CKD5 analyses are summarized in Table 1.
Table 1

Methodology

StudyCountry Countries Estimatedn (sample) for RR analysisMethod for RRn (sample) for “outside of range” analysisPopulation estimation sourcePopulation estimation methodCalculation of attributable patient-yearsEquation for calculating attributable patient-years^
Port et al. 2004 [2]USRandom sample (n = 17,245) from all 7 DOPPS I countries (N = 52,905)6 Cox proportional hazards models (one for each factor); a 7th Cox survival model was also used which adjusted for all six HD practices simultaneously. All models were adjusted for age, race, years of ESRD, country & 15 summary comorbid conditions (CAD, CHF, other cardiac disease, PVD, HTN, cerebrovascular disease, DM, lung disease, dyspnea, Hx cancer (active or inactive, excluding skin cancer), GI bleeding in past 12 months, neurologic disease, psychiatric disease, HIV/AIDS, and recurrent skin disease (including gangrene).1914 prevalent HD patients from US DOPPS II2001 US Renal Data System Annual Data ReportEstimation of the total US HD patient population in 2004 by extrapolation of 2001 data using a 6% annual growth rateThe expected gain in patient-years was calculated from the difference in the area under the 5-year survival curves between survival of the US haemodialysis population based on actual current death rates versus projected survival of the US haemodialysis population if all patients currently outside of the six practice guidelines were instead within them.PY = [(N0/L) * FD] + [(N1/L) * (t – (FD/L))],Assumptions:• t = 5 years• L = 0.251 if all patients outside of the target ranges for the six HD practices are brought within these target ranges• L = 0.30 if there is no change from the current proportion of patients outside the six target ranges• N0 = 313,000• N1 = 116,477
Jadoul et al. 2007 [13]Belgium>  20,000 (from all 12 DOPPS I and II countries)Same as US study except: 1 modifiable practice differed (substituted albumin-corrected serum calcium for IDWG); did not adjust for dyspnea538 prevalent HD patients from Belgian DOPPS IIOutpatient HD patient population reported in the 2001 Flemish-speaking and French-speaking registriesEstimation of the total Belgian HD patient population in 2006 by extrapolation of 2001 data using a 7.5% annual growth rateSame as US but on Belgian dataSame as US except:• L = 0.113 if all patients outside of the target ranges for the six HD practices are brought within these target ranges• L = 0.22 if there is no change from the current proportion of patients outside the six target ranges• N0 = 6373• N1 = 1591
Piera et al. 2007 [14]Spain>  20,000 (from all 12 DOPPS I and II countries)Same as US study except: 1 modifiable practice differed (substituted albumin-corrected serum calcium for IDWG); did not adjust for dyspnea613 from Spanish DOPPS IIInforme de la Sociedad Española de Nefrología de 2005Estimation of the total Spanish HD patient population in 2006 by extrapolation of 2005 data using a 5.1% annual growth rateSame as US but on Spanish dataSame as US except:• L = 0.099 if all patients outside of the target ranges for the six HD practices are brought within these target ranges• L = 0.170 if there is no change from the current proportion of patients outside the six target ranges• N0 = 20,920• N1 = 4902
Canaud et al. 2008 [15]France>  20,000 (from all 12 DOPPS I and II countries)Same as US study except: 1 modifiable practice differed (substituted albumin-corrected serum calcium for IDWG); did not adjust for dyspnea532 from French DOPPS IIBulletin Epidemiologique Hebdomadaire de 2005Estimation of the total French HD patient population in 2006 by extrapolation of 2005 data using a 5.3% annual growth rateSame as US but on French dataSame as US except:• L = 0.157 if all patients outside of the target ranges for the six HD practices are brought within these target ranges• L = 0.223 if there is no change from the current proportion of patients outside the six target ranges• N0 = 31,987• N1 = 6070
Wikström et al. 2010 [16]Sweden>  20,000 (from all 12 DOPPS I and II countries)Same as US study except: 1 modifiable practice differed (substituted albumin-corrected serum calcium for IDWG); did not adjust for dyspnea547 prevalent HD patients from Swedish DOPPS II2003 Swedish Renal RegistryEstimation of the total Swedish HD patient population in 2006 by extrapolation of 2003 data using a 4.5% annual growth rateSame as US but on Swedish dataSame as US except:• L = 0.180 if all patients outside of the target ranges for the six HD practices are brought within these target ranges• L = 0.274 if there is no change from the current proportion of patients outside the six target ranges• N0 = 2434• N1 = 769
MONITOR-CKD5AustriaFranceGermanyItalyPolandRomaniaSloveniaSpainSwitzerlandUnited Kingdom*Not applicableUtilizes published RR rates from various DOPPS studies (see Table 2 for details)2023 from MONITOR-CKD5Austria, Poland, Romania, Spain, Switzerland, UK: ERA-EDTA Registry 2014;France: REIN Rapport Annuel 2014;Germany: QuaSi-Niere-Bericht 2006–2007;Italy: RIDT Report 2011–2013;Slovenia: ERA-EDTA Registry 2013Estimation of the HD patient population in 2017 in the 10 countries participating in the MONITOR-CKD5 study by extrapolation of 2014 data (except for Germany for which 2006 data were available, and Italy and Slovenia for which 2013 data were available) using a 5% annual growth rateSame as US but on data from 10 European countriesSame as US except:L = 0.170 if all patients outside the target ranges for the six HD practices are brought within these target rangeL = 0.203 if there is no change from the current proportion of patients outside the six target rangesN0 = 303,517N1 = 66,597

* Included centres in England only.

^ where t total time period, FD fraction still on dialysis at time t, L annual rate of US haemodialysis patients lost from the haemodialysis population due to death or transfer to transplantation or peritoneal dialysis, N0 number of patients prevalent at the start of the 5-year time interval, N1 number of incident patients entering the haemodialysis patient population during each year, and PY projected total haemodialysis patient-years summed over the 5 years of the analysis period.

Methodology * Included centres in England only. ^ where t total time period, FD fraction still on dialysis at time t, L annual rate of US haemodialysis patients lost from the haemodialysis population due to death or transfer to transplantation or peritoneal dialysis, N0 number of patients prevalent at the start of the 5-year time interval, N1 number of incident patients entering the haemodialysis patient population during each year, and PY projected total haemodialysis patient-years summed over the 5 years of the analysis period.

Definition and Selection of Target Ranges for Modifiable Practices

We used the same target ranges set forth in the 2004 DOPPS analysis [2] for dialysis dose (Kt/V ≥ 1.2), phosphate control (serum phosphate ≤5.5 mg/dL), and fluid management (interdialytic weight gain ≤5.7%). For partial correction of serum albumin, we applied the range used in the Belgian [13], Spanish [14], and French [15] replications (≥4.0 g/dL). Best practice guidelines for anaemia management have changed since 2004 with more conservative haemoglobin targeting and individualized risk-based dosing of erythropoiesis-stimulating agents [5, 18, 19]. Hence, the original [2] haemoglobin target of ≥11 g/dL was reduced to ≥10 g/dL in our analysis. For the evaluation of catheter use for vascular access, all DOPPS-based analyses [2, 13–16] used a facility-level variable (percentage of catheter use at the centre-level). In the MONITOR-CKD5 study, vascular access was not collected as a facility-level but as a dichotomous patient-level variable. Some centres contributed small numbers of patients, hence determining centre percentages would have been subject to bias.

Estimation of “Out of Range”

Table 2 presents the recommended targets for each modifiable factor for the original DOPPS study [2] and the replication studies [13-16] and the percentage of each study sample outside the target range. We calculated the valid percentages of patients outside the indicated range for the MONITOR-CKD5 evaluable sample (n = 2023).
Table 2

Modifiable practices: target ranges, percent of patients outside recommended range and associated relative risk of mortality

CountryKt/VPhosphateHbInter-Dialytic Weight GainAlbuminFacility Catheter UseAll 6 Factors
Target range% outside rangeRR if outside rangeTargetRange% outside rangeRR if outside rangeTarget Range% outside rangeRR if outside rangeTarget Range% outside rangeRR if outside rangeTarget Range% outside rangeRR if outside rangeTarget Range% outside rangeRR if outside range% inside rangeon all 6% outside rangeon ≥1RR ifoutside range on ≥1
US[2]≥1.212.1%1.16≤5.5 mg/dL49.2%1.11≥11 g/dL27.2%1.14≤5.7%12.5%1.22≥3.5 g/dL20.5%1.38≤7%50.0%1.238.7%91.3%1.33
Belgium[13]≥1.230.3%1.13≤1.5 mmol/L56.2%1.11≥11 g/dL33.6%1.20≥4.0 g/dL67.1%1.46≤10%91.1%1.20
Spain[14]≥1.222.7%1.13≤1.5 mmol/L63.5%1.11≥11 g/dL30.4%1.20≥4.0 g/dL71.4%1.46≤10%42.8%1.20
France[15]≥1.215.5%1.13≤1.8 mmol/L39.6%1.14≥11 g/dL40.5%1.20≥4.0 g/dL70.5%1.46≤10%33.4%1.20
Sweden[16]≥1.220.1%1.13≤1.8 mmol/L50.8%1.14≥11 g/dL23.8%1.20≥3.5 g/dL40.1%1.48≤10%88.2%1.20
MONITOR-CKD5 *≥1.217.1%1.13≤5.5 mg/dL38.5%1.14≥10 g/dL14.0%1.22≤5.7%7.8%1.22≥4.0 g/dL56.8%1.46Pt-level: fistula (native or synthetic) vs. catheter16.6%1.3215.5%84.5%1.33
Source of RR for MONITOR-CKD5Four European replications: Jadoul et al. 2007 [Ref 13], Piera et al. 2007 [Ref 14], Canaud et al. 2008 [Ref 15], Wikström et al. 2010 [Ref 16]Two European replications: Canaud et al. 2008 [Ref 15], Wikström et al. 2010 [Ref 16]Locatelli et al. 2004 [Ref 20]Port et al. 2004 [Ref 2]Three European replications: Jadoul et al. 2007 [Ref 13], Piera et al. 2007 [Ref 14], Canaud et al. 2008 [Ref 15]Pisoni et al. 2009 [Ref 21]RR if outside range on ≥1 modifiable factor extrapolated from Port et al. 2004 [Ref. 1] Tables 1 and 2 where RR = (overall mortality / mortality rate of patients outside of range) / % of patients outside range − % of patients inside range; % of patients inside range on all 6 factors obtained through personal communication with Arbor Research 23Sep2016

* Valid % reported

Hb haemoglobin, RR relative risk

Modifiable practices: target ranges, percent of patients outside recommended range and associated relative risk of mortality * Valid % reported Hb haemoglobin, RR relative risk

Selection of Mortality Relative Risk Values

In MONITOR-CKD5 patients were followed for up to 24 months, which is shorter than in DOPPS. Per expert opinion, except for haemoglobin and catheter use, we adopted the mortality RR values generated by the five country-specific analyses (Table 2) [2, 13–16] based on congruence in definition of target range between the MONITOR-CKD5 and these studies, and similarities in population. Due to guideline-recommended changes in Hb targets since 2004, the RR of 1.22 associated with Hb < 10 g/dL reported by Locatelli et al. was utilized [20]. This is an estimate adjusted for age, gender, comorbidities, mobility, malnourishment, ability to eat independently, years with end-stage renal disease (ESRD), country, and facility. Since MONITOR-CKD5 study measured catheter use at the patient level, the mortality RR adopted for this parameter was based on findings from a patient-level analysis of mortality risk associated with vascular access from DOPPS [21]; this estimate was adjusted for age, gender, race, years with ESRD, body weight, and comorbidities to reduce treatment-by-indication bias.

Population Estimation

Haemodialysis prevalent and incident counts for the 10 countries in MONITOR-CKD5 are presented in Table 3. Data for 7 of the 10 countries were obtained from the 2014 ERA-EDTA Registry Annual Report [22] Slovenia was included in the 2013 [23] but not the 2014 ERA-EDTA Report; hence, 2013 data were utilized. Neither Germany nor Italy are included in the ERA-EDTA Registry. The most recent and sufficiently detailed data from their respective national databases were used instead, which were 2006 data for Germany [24] and 2013 data for Italy [25]. Country-level prevalent and incident counts were extrapolated from year of data to 2017 using an annual growth rate of 5%. However, this growth rate was not included in the calculation of projected life-years over the 5 years, thus providing a conservative, lower-bound estimation of life-years gained.
Table 3

Haemodialysis prevalent and incident counts

CountriesSourceYear of DataHD Prevalent CountHD Incident CountExtrapolation to 2017
HD Prevalent CountHD Incident Count
AustriaERA-EDTA Registry 20141201439738144599.24942.31
France °ERA-EDTA Registry 20141201441,314832147,826.129632.60
GermanyNierenersatztherapie in Deutschland 2006–20072200663,41316,260108,457.1127,809.96
ItalyRegistro Italiano di Dialisi e Trapianto Report 2011–20133201341,006824149,843.2210,017.40
Poland ERA-EDTA Registry 20141 (Section B, aggregated data)4201419,345395422,394.264577.25
Romania ^ERA-EDTA Registry 20141201414,686253817,000.882938.05
Slovenia ††ERA-EDTA Registry 20135201313492091639.72254.04
Spain ~ERA-EDTA Registry 20141201421,517423624,908.624903.70
SwitzerlandERA-EDTA Registry 20141 (Section B, aggregated data)201426366633051.50767.51
United Kingdom, England only ° *ERA-EDTA Registry 20141201420,556410723,796.144754.37

° Incident counts are estimated (see ERA-EDTA Registry: Annual Report 2014 for methods[22])

† Incidence data for Poland not reported; incident count imputed

^ Overall prevalence of RRT is underestimated by approximately 3% due to an estimated 30% underreporting of patients living on a functioning graft

†† Slovenia not included in ERA-EDTA Registry 2014, so 2013 ERA-EDTA data used[23]

~ Counts for Spain are sums of the following:

* Patients younger than 20 years of age are not reported

1 ERA-EDTA Registry: Annual Report 2014 [Ref 22]

2 Computed from 2006 dialysis prevalence (808 pmp X 95.2%HD) and incidence (213 pmp X 92.6%HD) rates from Nierenersatztherapie in Deutschland: Bericht über Dialysebehandlung und Nierentransplantation in Deutschland 2006-2007 [Ref 24] and 2006 population data (82,437,995) from Eurostat (http://ec.europa.eu/eurostat/)

3 Computed from 2013 dialysis prevalence (760 pmp X 90.4%HD) and incidence (160 pmp X 86.3%HD) rates from Registro Italiano Dialisi e Trapianto: Report 2011-2013 [Ref 25] and 2013 population data (59,685,227) from Eurostat (http://ec.europa.eu/eurostat/)

4 Prevalent count from ERA-EDTA Registry 2014¹ (Section B, aggregated data), incidence not reported; incident count imputed as Poland's HD prevalent count [19,345] X average percentage of HD incident count/HD prevalent count of 9 countries with complete data [0.2044]

5 ERA-EDTA Registry: Annual Report 2013 [Ref 23]

* Patients younger than 20 years of age are not reported

1 ERA-EDTA Registry: Annual Report 2014 [22]

2 Computed from 2006 dialysis prevalence (808 pmp X 95.2%HD) and incidence (213 pmp X 92.6%HD) rates from Nierenersatztherapie in Deutschland: Bericht über Dialysebehandlung und Nierentransplantation in Deutschland 2006–2007 [24] and 2006 population data (82,437,995) from Eurostat (http://ec.europa.eu/eurostat/)

3 Computed from 2013 dialysis prevalence (760 pmp X 90.4%HD) and incidence (160 pmp X 86.3%HD) rates from Registro Italiano Dialisi e Trapianto: Report 2011–2013 [25] and 2013 population data (59,685,227) from Eurostat (http://ec.europa.eu/eurostat/)

4 Prevalent count from ERA-EDTA Registry 20141 (Section B, aggregated data), incidence not reported; incident count imputed as Poland’s HD prevalent count [19,345] X average percentage of HD incident count/HD prevalent count of 9 countries with complete data [0.2044]

5 ERA-EDTA Registry: Annual Report 2013 [23]

Haemodialysis prevalent and incident counts ° Incident counts are estimated (see ERA-EDTA Registry: Annual Report 2014 for methods[22]) † Incidence data for Poland not reported; incident count imputed ^ Overall prevalence of RRT is underestimated by approximately 3% due to an estimated 30% underreporting of patients living on a functioning graft †† Slovenia not included in ERA-EDTA Registry 2014, so 2013 ERA-EDTA data used[23] ~ Counts for Spain are sums of the following: * Patients younger than 20 years of age are not reported 1 ERA-EDTA Registry: Annual Report 2014 [Ref 22] 2 Computed from 2006 dialysis prevalence (808 pmp X 95.2%HD) and incidence (213 pmp X 92.6%HD) rates from Nierenersatztherapie in Deutschland: Bericht über Dialysebehandlung und Nierentransplantation in Deutschland 2006-2007 [Ref 24] and 2006 population data (82,437,995) from Eurostat (http://ec.europa.eu/eurostat/) 3 Computed from 2013 dialysis prevalence (760 pmp X 90.4%HD) and incidence (160 pmp X 86.3%HD) rates from Registro Italiano Dialisi e Trapianto: Report 2011-2013 [Ref 25] and 2013 population data (59,685,227) from Eurostat (http://ec.europa.eu/eurostat/) 4 Prevalent count from ERA-EDTA Registry 2014¹ (Section B, aggregated data), incidence not reported; incident count imputed as Poland's HD prevalent count [19,345] X average percentage of HD incident count/HD prevalent count of 9 countries with complete data [0.2044] 5 ERA-EDTA Registry: Annual Report 2013 [Ref 23] * Patients younger than 20 years of age are not reported 1 ERA-EDTA Registry: Annual Report 2014 [22] 2 Computed from 2006 dialysis prevalence (808 pmp X 95.2%HD) and incidence (213 pmp X 92.6%HD) rates from Nierenersatztherapie in Deutschland: Bericht über Dialysebehandlung und Nierentransplantation in Deutschland 2006–2007 [24] and 2006 population data (82,437,995) from Eurostat (http://ec.europa.eu/eurostat/) 3 Computed from 2013 dialysis prevalence (760 pmp X 90.4%HD) and incidence (160 pmp X 86.3%HD) rates from Registro Italiano Dialisi e Trapianto: Report 2011–2013 [25] and 2013 population data (59,685,227) from Eurostat (http://ec.europa.eu/eurostat/) 4 Prevalent count from ERA-EDTA Registry 20141 (Section B, aggregated data), incidence not reported; incident count imputed as Poland’s HD prevalent count [19,345] X average percentage of HD incident count/HD prevalent count of 9 countries with complete data [0.2044] 5 ERA-EDTA Registry: Annual Report 2013 [23]

Calculation of Attributable Patient-Years

We replicated the Port et al. [2] methodology for estimating potential life-years gained using the MONITOR-CKD5 proportions of patients out of range for each practice, the current population statistics for the 10 countries in the study, and the published relative risks associated with each practice. Based on the estimated percentages of patients falling outside the target ranges of the six modifiable practices and the mortality risk associated with each, Port el al. extrapolated to the US haemodialysis population for a 5-year period to quantify potential life-years gained [2]. Projections were obtained by computing the difference in the area under the 5-year survival curve between the general survival of haemodialysis patients based on the actual mortality rate and the estimated survival if patients outside targets were brought into target range on the six modifiable factors based. The projected total haemodialysis patient-years summed over the 5 years of the analysis period PY is defined as. PY = [(N/L) * FD] + [(N/L) * (t–(FD/L))] (Eq. 1). where t is the total time period in years, FD the fraction still on dialysis at t, L the annual rate of haemodialysis patients lost from the haemodialysis population due to death or transfer to transplantation or peritoneal dialysis, N the number of patients prevalent at the start of the 5-year time interval, and N the number of incident patients entering the haemodialysis population during each year. PY is calculated for status quo (PY), where none of the patients outside the target range are brought into compliance; for each modifiable factor i assuming all patients are brought into compliance (PY where i = Kt/V, phosphate, Hb, interdialytic weight gain, albumin, AVF/graft); and for the condition that all patients are brought into compliance on all six factors (PY). From Eq. 1, we estimated the potential patient-years gained over the 5-year time interval ∆PY, for a given modifiable factor and aggregated across all six factors, as the difference between PY (the projected total patient-years summed over 5 years) and the corresponding PY for the ith factor or PY for the six factors aggregated; or. ∆PY = PY - PY (Eq. 2). and ∆PY = PY - PY (Eq. 3).

Ethics

The MONITOR-CKD5 study protocol was approved by the ethical review committees of participating centres in accordance with national laws and regulations. Written informed consent was obtained from all participating patients.

Consort

N/A; this is not a clinical trial but a simulation study.

Results

Patients

A total of 2086 patients were enrolled yielding an evaluable enrolment sample of 2023 patients. Details of patient enrolment and disposition have been reported elsewhere [26] as have been centre-level and interim patient-level results [27]. Most patients (40.6%) were treated in Germany, followed by Romania (18.6%) and Italy (15.3%), accounting together for 74.4% of the study population. The sample was predominantly male (59.3%), virtually completely Caucasian (96.2%), with median age of 68 years (range 20–93). Median time on dialysis was 2.1 years (range 0–35). Most patients (82.5%) had been treated with another ESA at enrolment, therefore can be considered in the maintenance phase of renal anaemia management, and were switched to Binocrit®. Mean (±SD) Hb at enrolment was 11.09(±1.14)g/dL and 68.0% of patients had Hb values in the 10-12 g/dL range. In terms of the six modifiable factors, as can be calculated from Tables 2, 82.9% were within target range for Kt/V (≥1.2), 61.5% had adequate phosphate control (serum phosphate ≤5.5 mg/dL), 86.0% had Hb ≥ 10 g/dL, 92.2% had interdialytic weight gain ≤5.7, 43.2% had partial correction of serum albumin (≥4.0 g/dL), and 83.4% had vascular access via either an arteriovenous fistula or graft.

Estimated Patient Life-Years Gained

Table 4 summarizes the patient life-years gained over five years, estimated per Eqs. 1 through 3 above, if respectively an optimal 100% (or suboptimal 50%) of patients falling outside of the recommended target range on the six modifiable practices were brought into compliance. Results are reported for each modifiable factor separately, as well as for all 6 factors combined. The baseline for the 10 MONITOR-CKD5 countries is the estimated 303,517 haemodialysis patients for 2017. This baseline is adjusted upward for the estimated 66,597 incident cases added over the 5-year period, adjusted downward for the variable annual death rate in general and associated with compliance with each factor, and further adjusted downward for the fixed annual loss rate to peritoneal dialysis or transplant.
Table 4

Project patient-years gained based on relative risk for compliance with recommended targets (over 5 years)

MeasureCurrent statisticsKt/V ≥ 1.2Phosphate ≤ 5.5 mg/dLHb ≥ 10 g/dLIDWG ≤ 5.7%Albumin  ≥ 4.0 g/dlAVF or graft v. catheterAll 6 Factors
Annual death rate0.150 10.1467 20.1423 20.1455 20.1475 20.1189 20.1424 20.1173 2
Annual rate of other loss30.0530.0530.0530.0530.0530.0530.0530.053
L (Total loss rate)0.2030.2000.1950.1990.2000.1720.1950.170
T55555555
N0 4303,517303,517303,517303,517303,517303,517303,517303,517
N1 566,59766,59766,59766,59766,59766,59766,59766,597
FD0.637600.631640.623430.629380.632980.576680.623630.57321
PY1,563,2211,572,5401,585,2731,576,0471,570,4431,655,5651,584,9671,660,650
Potential patient years gained
if 100% brought within target931922,05212,826722292,34421,74697,4296
if 50% brought within target7450110,6516195348844,60110,50347,057

Hb haemoglobin, IDWG inter-dialytic weight gain, AVF arterio-venous fistula, L annual rate of US haemodialysis patients lost from the haemodialysis population due to death or transfer to transplantation or peritoneal dialysis, t total time period, N number of patients prevalent at the start of the 5-year time interval, N number of incident patients entering the haemodialysis patient population during each year, FD fraction still on dialysis at time t, PY projected total haemodialysis patient years summed over the 5 years of the analysis period

1 From ERA-EDTA Registry: Annual Report 2014. Table B.6.7.a. Unadjusted 1-year survival (cohort 2008–2012): incident dialysis patients (from day 91).

2 Mortality rate of pts. inside range = overall mortality / ((% of patients outside range * RR) + % of patients in range)

3 Other loss to peritoneal dialysis or transplant assumed to be 5.3%

4 N0 assumed to be 303,517 based upon population estimates for countries participating in MONITOR-CKD5 [Table 3]

5 N1 assumed to be 66,597 based upon population estimates for countries participating in MONITOR-CKD5 [Table 3]

6 Patient-years gained if all 6 factors in target range is less than the sum of the years gained on the 6 individual factors since the modifiable practices are not mutually exclusive (i.e. patients can be outside target range on ≥1 factor)

7 Adjusted to 0.4830 of potential years gained if 100% brought within target (i.e. not .50, due to results of sensitivity analysis; personal communication with Arbor Research)

Project patient-years gained based on relative risk for compliance with recommended targets (over 5 years) Hb haemoglobin, IDWG inter-dialytic weight gain, AVF arterio-venous fistula, L annual rate of US haemodialysis patients lost from the haemodialysis population due to death or transfer to transplantation or peritoneal dialysis, t total time period, N number of patients prevalent at the start of the 5-year time interval, N number of incident patients entering the haemodialysis patient population during each year, FD fraction still on dialysis at time t, PY projected total haemodialysis patient years summed over the 5 years of the analysis period 1 From ERA-EDTA Registry: Annual Report 2014. Table B.6.7.a. Unadjusted 1-year survival (cohort 2008–2012): incident dialysis patients (from day 91). 2 Mortality rate of pts. inside range = overall mortality / ((% of patients outside range * RR) + % of patients in range) 3 Other loss to peritoneal dialysis or transplant assumed to be 5.3% 4 N0 assumed to be 303,517 based upon population estimates for countries participating in MONITOR-CKD5 [Table 3] 5 N1 assumed to be 66,597 based upon population estimates for countries participating in MONITOR-CKD5 [Table 3] 6 Patient-years gained if all 6 factors in target range is less than the sum of the years gained on the 6 individual factors since the modifiable practices are not mutually exclusive (i.e. patients can be outside target range on ≥1 factor) 7 Adjusted to 0.4830 of potential years gained if 100% brought within target (i.e. not .50, due to results of sensitivity analysis; personal communication with Arbor Research) The estimated potential patient-years gained over the 5-year period at status quo (PY) is 1,563,221. At the singular modifiable factor level, bringing all patients into Kt/V compliance yields 9319 additional patient-years over PY (for a total of 1,572,540); into phosphate compliance an additional 22,052 patient-years (1,585,273); into Hb compliance an additional 12,826 patient-years (1,576,047); into interdialytic weight gain compliance an additional 7222 patient-years (1,570,443); into albumin compliance an additional 92,344 patient-years (1,655,565); and into vascular access compliance an additional 21,746 patient-years (1,584,967). On the aggregate, bringing all patients into compliance on all six modifiable factors results in an incremental gain of 97,428 patient-years for a total of 1,660,650 patient-years (note that years gained if all 6 factors in target range is less than the sum of the years gained on the 6 individual factors since the modifiable practices are not mutually exclusive; i.e. patients can be outside target range on ≥1 factor).

Discussion

Using as baseline the estimated 303,517 haemodialysis patients estimated to be alive in 2017 in the 10 European countries that participated in the MONITOR-CKD5 study, and adjusting this upward for growth in this patient population and downward for mortality and transition to peritoneal dialysis or transplantation, we projected that the 5-year period starting in 2017 would yield a net total of 1,563,221 patient-years under the haemodialysis practice patterns observed in the study. However, as the DOPPS investigators have shown for several countries [2, 13–16], mortality in haemodialysis patients could potentially be reduced and life expectancy increased by focusing on six modifiable factors: dialysis quality (Kt/V), managing phosphate, haemoglobin, and albumin levels, reducing interdialytic weight gain (or, alternately managing calcium), and minimizing catheter use for vascular access. If all haemodialysis patients in the 10 MONITOR-CKD5 countries were brought into the target range of these six modifiable practice patterns, an additional 97,429 patient life-years would hypothetically be gained over the 5-year period starting in 2017. This corresponds to a 6.2% increase in 5-year survival. In comparison, the corresponding rates from the country-specific DOPPS analyses of the modifiable practices are, in ascending order, 8.2% for the US, 13.1% for France, 14.7% for Spain, 17.8% for Sweden, and 22.5% for Belgium [2, 13–16]. The differences in rates may be due to sample size. However, considering that these simulation analyses cover a time span of approximately 15 years, this variation in rates may also suggest significant improvements having been achieved in haemodialysis care over time [28]. Though we chose not to perform country-specific analyses, with collectively 25.3% of MONITOR-CKD5 patients being treated in Central and Eastern European countries, our lower rate in life-years gained underscores the advances in the quality of haemodialysis care made across all European regions. This is also evident from the loss rates used in the various analyses. Consistent with their time period and country, Port et al. [2] assumed a 24.0% annual death rate and 6.5% annual rate of other loss (transition or peritoneal analysis or transplantation), for a total loss rate of 30.5%. In the four country-specific DOPPS analyses [13-16], the annual death rates ranged from 17.1 to 24.3%, the annual other loss rates from a gain of 2.1% to a loss of 5.3%, for total loss rates between 17.0 and 27.4% In our ten-country European analysis, these rates were 15.0% (death-related), 5.3% (other), and 20.3% (total). With the historical trends of fewer patients outside of the recommended range on each of the modifiable practices and decreasing mortality rates in dialysis populations, there is a diminishing opportunity for further improvement and, hence, smaller gains in potential life years. Yet, there is still room for improvement. While the percentage of patients out of range have decreased across all six modifiable practices, only 15% of patients in the MONITOR-CKD5 study were in range on all six. The historical differences are also evident at the level of the individual practice patterns. In the Port et al. [2] analysis, reducing catheter use was associated with the greatest gain in patient life-years (with the highest potential gains in the USA), followed by increasing serum albumin levels (a measure of nutritional status and inflammation), and phosphate control. In our analysis, the greatest gains in theoretical patient life-years were achieved by targeting patient’s serum albumin level followed, remotely, by phosphate control and vascular access. In the country-specific DOPPS analyses (which did not include interdialytic weight gain but serum calcium level instead), albumin levels and catheter use were the modifiable factors that prevailed in impact, followed by calcium levels and, variably, phosphate and Hb levels. Despite these differences in rates, all analyses converged on the importance of bringing albumin levels into target range, assuring vascular access by means of fistula or graft, and mineral control. That dialysis quality contributed only modestly to survival in all analyses may reflect the longstanding acceptance of the Kt/V ≥ 1.2 standard. One notable challenge for clinicians is that while serum albumin exerts the most influence on mortality in these models in terms of relative risk, it is perhaps the most resistant of the six practices to therapeutic intervention, since it is linked to different factors, mainly inflammation and nutritional status [29]. Mortality risks attributable to the six modifiable practice patterns have not been systematically evaluated in randomized controlled trials (RCT); though a RCT of an established practice such as dialysis quality of Kt/V ≥ 1.2 versus < 1.2 would be ethically untestable. Hence, estimating preventable mortality and associated life-years gained as a function of modifiable practices may be appropriate as secondary endpoints in randomized trials. Further, the role of patient adherence, in particular to dietary restrictions, phosphate binders, and dialysis regimen, should be examined in future studies [30-32]. Our analyses have limitations. Like DOPPS, MONITOR-CKD5 is a non-controlled study. The use of patient-level versus facility-level data for catheter use may introduce treatment-by-indication bias especially in terms of patient age, comorbid conditions, and disease severity. The adjusted mortality risk associated with patient-level vascular access data utilized in our study [21] reduced such confounding but some residual bias cannot be excluded. Countries in MONITOR-CKD5 differed in some of the modifiable practices MONITOR-CKD5 [28]. The estimation of life-years gained using the MONITOR-CKD5 aggregate sample may conceal specific countries where opportunities for larger gains exist. Not being part of the ERA-EDTA Registry, national reports were used for Germany and Italy. The MONITOR-CKD5 patient population was virtually Caucasian with minimal racial/ethnic variation.

Conclusions

Replicating and extending the DOPPS analyses [2, 13–16] to the population in MONITOR-CKD5, we estimated in this hypothetical simulation that bringing all haemodialysis patients of the countries included in this study within the target range of six modifiable practices would yield a 6.2% increase in patient life-years over 5 years. An additional 97,429 life-years might be gained if, in descending order of survival impact, haemodialysis patients could be maintained at albumin levels ≥4.0 g/dL and phosphate levels ≤5.5 mg/dL, have vascular access by means of fistula or graft, have haemoglobin maintained at ≥10 g/dL, receive dialysis at Kt/V ≥ 1.2, and have their interdialytic weight gain limited to ≤5.7%. It is reassuring that compared to the original DOPPS papers, potential gains linked to quality improvement have decreased, reflecting better achievement of recommended therapeutic goals. Supplementary List of all Ethical Review Committees for MONITOR-CKD5. (DOCX 99 kb)
Spain, Andalusia4115795
Spain, Aragon °529105
Spain, Asturias °44793
Spain, Basque country789159
Spain, Cantabria *19643
Spain, Castile & León °*1078217
Spain, Castile-La Mancha *826196
Spain, Catalonia °4227889
Spain, Extremadura °590106
Spain, Galicia1540292
Spain, Community of Madrid2576593
Spain, Region of Murcia950158
Spain, Navarre °*25161
Spain, Valencian region3403529

* Patients younger than 20 years of age are not reported

1 ERA-EDTA Registry: Annual Report 2014 [Ref 22]

2 Computed from 2006 dialysis prevalence (808 pmp X 95.2%HD) and incidence (213 pmp X 92.6%HD) rates from Nierenersatztherapie in Deutschland: Bericht über Dialysebehandlung und Nierentransplantation in Deutschland 2006-2007 [Ref 24] and 2006 population data (82,437,995) from Eurostat (http://ec.europa.eu/eurostat/)

3 Computed from 2013 dialysis prevalence (760 pmp X 90.4%HD) and incidence (160 pmp X 86.3%HD) rates from Registro Italiano Dialisi e Trapianto: Report 2011-2013 [Ref 25] and 2013 population data (59,685,227) from Eurostat (http://ec.europa.eu/eurostat/)

4 Prevalent count from ERA-EDTA Registry 2014¹ (Section B, aggregated data), incidence not reported; incident count imputed as Poland's HD prevalent count [19,345] X average percentage of HD incident count/HD prevalent count of 9 countries with complete data [0.2044]

5 ERA-EDTA Registry: Annual Report 2013 [Ref 23]

  22 in total

Review 1.  Oral phosphate binders in patients with kidney failure.

Authors:  Marcello Tonelli; Neesh Pannu; Braden Manns
Journal:  N Engl J Med       Date:  2010-04-08       Impact factor: 91.245

Review 2.  Target haemoglobin to aim for with erythropoiesis-stimulating agents: a position statement by ERBP following publication of the Trial to reduce cardiovascular events with Aranesp therapy (TREAT) study.

Authors:  Francesco Locatelli; Pedro Aljama; Bernard Canaud; Adrian Covic; Angel De Francisco; Iain C Macdougall; Andrzej Wiecek; Raymond Vanholder
Journal:  Nephrol Dial Transplant       Date:  2010-06-29       Impact factor: 5.992

3.  Type of vascular access and mortality in U.S. hemodialysis patients.

Authors:  R K Dhingra; E W Young; T E Hulbert-Shearon; S F Leavey; F K Port
Journal:  Kidney Int       Date:  2001-10       Impact factor: 10.612

4.  A pharmacoepidemiological study of the multi-level determinants, predictors, and clinical outcomes of biosimilar epoetin alfa for renal anaemia in haemodialysis patients: background and methodology of the MONITOR-CKD5 study.

Authors:  Loreto Gesualdo; Gérard London; Matthew Turner; Christopher Lee; Karen Macdonald; David Goldsmith; Adrian Covic; Philippe Zaoui; Christian Combe; Johannes Mann; Frank Dellanna; Michael Muenzberg; Ivo Abraham
Journal:  Intern Emerg Med       Date:  2011-05-18       Impact factor: 3.397

Review 5.  The challenge of controlling phosphorus in chronic kidney disease.

Authors:  Jorge B Cannata-Andía; Kevin J Martin
Journal:  Nephrol Dial Transplant       Date:  2015-03-13       Impact factor: 5.992

6.  Fluid retention is associated with cardiovascular mortality in patients undergoing long-term hemodialysis.

Authors:  Kamyar Kalantar-Zadeh; Deborah L Regidor; Csaba P Kovesdy; David Van Wyck; Suphamai Bunnapradist; Tamara B Horwich; Gregg C Fonarow
Journal:  Circulation       Date:  2009-01-26       Impact factor: 29.690

7.  Health status as a potential mediator of the association between hemodialysis vascular access and mortality.

Authors:  Vanessa Grubbs; Haimanot Wasse; Eric Vittinghoff; Barbara A Grimes; Kirsten L Johansen
Journal:  Nephrol Dial Transplant       Date:  2013-11-13       Impact factor: 5.992

8.  DOPPS estimates of patient life years attributable to modifiable hemodialysis practices in the United States.

Authors:  Friedrich K Port; Ronald L Pisoni; Jennifer L Bragg-Gresham; Sudtida S Satayathum; Eric W Young; Robert A Wolfe; Philip J Held
Journal:  Blood Purif       Date:  2004       Impact factor: 2.614

9.  Risk-based individualisation of target haemoglobin in haemodialysis patients with renal anaemia in the post-TREAT era: theoretical attitudes versus actual practice patterns (MONITOR-CKD5 study).

Authors:  Loreto Gesualdo; Christian Combe; Adrian Covic; Frank Dellanna; David Goldsmith; Gérard London; Johannes F Mann; Philippe Zaoui; Matthew Turner; Mike Muenzberg; Karen MacDonald; Ivo Abraham
Journal:  Int Urol Nephrol       Date:  2015-04-17       Impact factor: 2.370

10.  Long-term treatment with biosimilar epoetin-α (HX575) in hemodialysis patients with renal anemia: real-world effectiveness and safety in the MONITOR-CKD5 study
.

Authors:  Gérard London; Johannes Mann; David Goldsmith; Christian Combe; Frank Dellanna; Philippe Zaoui; Nadja Hoebel; Andriy Krendyukov; Karen MacDonald; Ivo Abraham
Journal:  Clin Nephrol       Date:  2018-01       Impact factor: 0.975

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