D PPS Dialysis Outcomes and Practice Patterns Study

Impact of Dialysis Prescriptions and Practices on Outcomes

Friedrich K. Port, MD, MSArbor Research Collaborative for Health

Ann Arbor, Michigan

ESRD State of the Art, Boston, MA. April 23-26, 2009

DOPPS Overview

• Prospective observational study, 1997 – 2011

• Representative HD samples in 12 countries

• Practice-patterns in dialysis facilities and outcomes

• 4 Phases: consistent data collection internationally

• DOPPS 2: Added focus on incident HD patients

• DOPPS 3: Added processes of care and nutrition

• DOPPS 4*: Added practice trends and MD opinions

• Goal: Improve Outcomes in Hemodialysis:

- Mortality, Morbidity, and Quality of Life

* 2009-2011 funded by Amgen, Kyowa Hakko Kirin, and Genzyme

Dallas Conference, 1989

• Held PJ, Brunner F, Odaka M, Garcia J, Port FK, Gaylin DS: Five-year survival for ESRD patients in the U.S., Europe, and Japan 1982-87. Am J Kidney Dis 1990; 15: 451-457.

• US survival is lower than EDTA or Japan: Why

– US captures all deaths, other registries don’t (?)

– US case mix or practices explain the differences

– Mortality differs in the general populations

– Were authors simply wrong?

Outline

• International outcome comparisons– Are outcomes differences real?– Can we explain outcomes difference?

• Dialysis prescription over the last 20 years

• Opportunities to improve practices in dialysis

– Treatment time, at same Kt/V

– Blood pressure

– Phosphorus

• Focusing analyses on Practice Patterns may improve evidence and have practical implications

5-Year Survival for ESRD Patients Based on Registries, Adjusted for Diabetes and Age

US EDTA US Japan

5-YearSurvival

(%)

Held et al. AJKD 15: 451, 1990U 277 99

3940

4854

0

20

40

60

Includes all dialysis and transplant patients

DOPPS I: Survival Among Hemodialysis Patients in Japan, Europe, and the United States:

50

60

70

80

90

100

0.0 1.0 2.0 3.0

Japan (ref)

Europe (RR=3.12)

US (RR=5.34)

DA Goodkin et al. JASN 14: 3270-3277, 2003

50

60

70

80

90

100

0.0 1.0 2.0 3.0

Japan (ref)

Europe (RR=2.84)

US (RR=3.78)

Survival (%)

Unadjusted Adjusted for demographics and comorbidities

Years Years

US/EU RR =1.33

Mortality in the General Population versus the Dialysis Patient Mortality

Nathan Levin’s Hypothesis: In international comparisons, higher dialysis patientmortality is partly explained by higher mortality in thegeneral population

Methods:Correlate WHO data with Registry + DOPPS data

Yoshino et al JASN 2006, 17:3510-3519

Relationship of All-Cause Mortality Rates Between Dialysis Patients (DP) and General Population (GP)

Yoshino et al JASN (2006)

Unadjusted:

Relationship of All-Cause Mortality Rates Between Dialysis Patients (DP) and General Population (GP)

Yoshino et al JASN (2006)

Adjusted for age in DP (overall median mean age [60.4 yr]) and GP (overall median percentage of population aged 65 yr [15.8%]). N=21 countries.

International Differences

• Differences confirmed for US versus EU using detailed adjustment for case mix and same data collection for death ascertainment

• Better outcomes in Japan may be exaggerated since selection to transplant of healthier patients is minimal in Japan

• Background mortality partially explains differences*

• Question: Do practice differences contribute?

Outcomes by Vascular Access Use:Problems with patient-based analyses

• Patients who use a catheter for dialysis tend to be sicker patients

• Patients using a catheter have higher mortality than patients using an AV fistula

• Is the higher mortality due to catheter use or due to the selection of sicker patients?

The use of catheters varies widely from facility to facility even when adjusted for case mix. This may be a practice pattern: In DOPPS we studied overall mortality in facilities by level of catheter use

Pisoni et al. AJKD 2009, 53: 475-491

RR of Death among Facility Patients per 20% more facility use of indicated access type

*DOPPS I+II, 1996-2004; n=27,892; adjusted for age, gender, black race, yrs with ESRD, 14 comorbidity classes, weight, other practice indicators (median treatment time, % of pts with S. Ca >10 mg/dl or S. PO4 >5.5 mg/dl) whether hosp unit, & accounted for facility clustering; stratified by study phase & region. Facility access use is adjusted for facility case-mix.

Vascular Access Use and Mortality Risk Facility-Based Model

p<0.0001 p<0.0001Ref.

1.19

1.081.00

0.6

0.8

1

1.2

1.4

Catheters Grafts Fistulae

p=0.008p<0.0001 Ref.

1.45

1.311.24

1

1.07

1.14

1.38

1.26

11.14

0.5

0.75

1

1.25

1.5

0 20 40 60 80

Fac. Catheter Use(R2=0.95)

Fac. Graft Use(R2=0.966)

RR of death

% Adjusted Facility Access Use

Mortality Risk in Facilities that have Greater Use of Catheters or AV Grafts versus low use

Quintiles for Graft and Catheter Use

Mortality Risk for US versus European DOPPS is Largely Explained by Vascular Access Practice

All models were adjusted for age, gender, race, time on dialysis, 14 summary comorbid conditions, weight, unit type, facility median treatment time, facility % pts with serum phos > 5.5 and serum Ca> 10 mg/dl, and stratified by study phase; accounted for facility clustering effects. DOPPS I + II; n=24,398; *EUR=France, Germany, Italy, Spain, and UK.

0.5

1

1.5Adjusted for

Case Mix

1.00

EURUS

1.36 + Adjusted for Facility Vascular Access Practice

1.06

US

1.00

EUR

p<0.0001 p=0.43

RR of Death

International Differences

• Differences confirmed for US versus EU using detailed adjustment for case mix and same data collection for death ascertainment

• Better outcomes in Japan may be exaggerated since selection of healthier patients to transplant is minimal on Japan

• Background mortality partially explains differences

• Differences in vascular access practice explain most of the mortality differences between Europe and US: This points to an opportunity to improve vascular access care and outcomes in the US

Dialysis Prescription

• Kt/V Trends

• Treatment time (TT) and mortality risk (independent of Kt/V)

0.991.11

1.22

1.36 1.40 1.42 1.451.53

1.59 1.61 1.61

1.53

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

1986 '88 '90 '92 '94 '96 '98 2000 '02 '04 '06

sp Kt/V

U S R D S S p e c i a l S t u d i e sCMMS CMAS DMMS

U S D O P P S DOPPS 1 DOPPS 2 DOPPS 3

Mean Single-pool Kt/V in US HD Patients during the Past 20 Years

Year

Adapted from Port et al. CJASN 1:246-255, 2006

Cross-sections of patients by year

Mean and Median Patient Prescribed Treatment Time in the US, by DOPPS Phase*

211.7

221.5222.8

210

225 225

200

205

210

215

220

225

230

DOPPS 1 DOPPS 2 DOPPS 3

Minutes

*Prevalent Cross-section of patients in each phase, weighted to represent total facility sample size.

(n=3,856) (n=2,260) (n=1,814)

MeanMedian

Distribution of Facility Treatment Time by Country and Phase

175

200

225

250

275

300

325

350

II III II III II III I II III I II III I II III I II III I II III II III I II III I II III

Mean Facility Treatment Time (min)

PhaseANZ Be Ca Fr Ge It Ja Sp Sw UK US

Box-plots show the 25th to 75th percentiles (box) with median (line) and 5th and 95th percentiles (whiskers)

Mortality Risk by Average Facility Treatment Time as a Practice Pattern

1.19

1.10

1.00

0.6

0.8

1.0

1.2

1.4

< 210 210 - 240 240 +

Facility Average Treatment Time (minutes)

RR=0.96 per 15 minutes, p=0.03

*Adjusted 2-stage model (instrumental variable)

p=0.04 p=0.26 Ref.

RR Mortality*

Treatment Time and Mortality:Summary

• Patients treated with longer dialysis sessions have lower mortality risk at the same Kt/V (Saran et al 2008)

• Patients treated in dialysis facilities that use on average longer treatment times have lower mortality (this analysis focuses on the practice and minimizes bias due to patient health status)

• The agreement of these results enhances the level of evidence

Predialysis Systolic Blood Pressure and Mortality Risk

A New Analytical Approach Using Patient Exposure to Different Practices

100

110

120

130

140

150

160

170

180

N of facilities = 150 84 62

Med

ian

Fac

ilit

y P

re-d

ialy

sis

SB

P JapanNorth America

EU & ANZ

— Prevalent HD Patients — Facility Median Pre-dialysis SBP, by Region

Substantial Variation Between Facilities and Regions

*Based on initial prevalent cross section patients (n=8000) with ESRD >3 months in 296 facilities in DOPPS III (2005-2008). SBP=systolic blood pressure

25th = 131 mmHg 75th = 145 mmHg

25th = 142 mmHg 75th = 153 mmHg

25th = 147 mmHg 75th = 161 mmHg

0

5

10

15

20

25

30

35

<100 100-110 110-120 120-130 130-140 140-150 150-160 160-170 170-180 ≥180

% of Pts in Facilities

Pre-Dialysis SBP (mmHg)

* 22,559 initial prevalent cross section patients with ESRD duration > 180 days from 919 facilities in DOPPS I, II, III

Within-Facility Distribution of Pre-Dialysis SBP* Substantial Variation Across a Wide BP Range

1.03

0.97

1.01

0.99

1.00

1.151.15

0.89

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.071.06

1.00

1.011.01

1.07 1.05 1.06

0.85

0.90

0.95

1.00

1.05

1.10

1.15

1.20

Pre-HD Systolic BP and All-Cause Mortality

RR of death§

Patient Level BP

110 120 130 140 150 160 170 180

Pt achieved pre-dialysis SBP (mmHg)

Ref

Facility Level BPRR for an additional 10% of patients

compared to the ref categoryRR of death§

110 120 130 140 150 160 170 180

*P<0.05

*

Pre-dialysis SBP Group (mmHg)

Ref

* *

*

§ 21,388 prevalent HD, 919 facilities Excludes patients with SBP <110 mm Hg. Cox models adjusted for age, gender, black race, BMI, vintage, study phase, hemoglobin, s. albumin, phosphorus, creatinine, ferritin, PTH, intra-dialysis weight loss, treatment time, catheter use, 13 comorbidities, stratified by country and accounted for facility clustering. Facility level model also adjusted for facility mean levels of intra-dialysis weight loss, dialysate sodium, and treatment time (min), % of catheter use and % pts in albumin, Hgb, Kt/V, and phosphate guidelines. No meaningful change with the addition of anti-hypertensive medications to the models, or with the addition of pts with SBP<110.

*

*

1.06 1.05

0.96

1

1.04

1.08

1.12

Facility Predialysis Systolic BP and All-Cause Mortality

Pre-dialysis SBP (mmHg)

Facility Level Mortality RR per an additional 10% of patients by category compared to the reference

Ref

* *

RR of death

110-129 130-160 >160

* p <0.05

Predialysis Blood Pressure Levels and Survival: Summary

• Optimal target BP has been difficult to identify, because BP is influenced by health status

• Facility-based analyses provide insights by minimizing bias due to patient health status, and by taking advantage of the large between-facility variation in BP as a likely reflection of practices or MD opinion

• Our data show that:

– Patients treated at facilities where more patients have low pre-dialysis SBP (110-130 mmHg) have higher mortality risk

– Patients treated at facilities where more patients have high pre-dialysis SBP (>160 mmHg) have higher mortality risk

Predialysis Blood Pressure Levels and Survival: Conclusion

• These facility-level findings suggest that both higher predialysis SBP (>160 mmHg) and lower SBP (<130 mmHg) are associated with elevated mortality risk

• The present results are not consistent with KDOQI Guidelines (SBP <140 mmHg)

• A clinical trial is needed to identify optimal predialysis SBP goals

Serum Phosphorus and Mortality Risk

Patient-based analyses

and

Practice-based analyses

Practices of Better Control of High Phosphorus and Mortality Risk

BACKGROUND:

• Patient level analyses showing higher mortality in patients with high P levels may be confounded, if sicker patients have higher P levels

• The new KDIGO Guidelines recommend control “toward normal P levels” since randomized trials are lacking

• Since randomization to poor P control is not feasible, can we make observational studies more informative?

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.5mg/dl

HR

Mortality Risk by Phosphorus CategoriesPatient-Level Analyses, Among Patients on HD > 180 days

CardiovascularAll-cause

Cox models used all DOPPS (n=25,529) and adjusted for age, sex, race, BMI, years on ESRD, 13 comorbid conditions, facility clustering. Hazard ratios and 95% confidence intervals (whiskers) for all-cause (events n=5,857) and cardiovascular mortality (n events=1,930)

Tentori et al. AJKD 2008

Variation in Facility-Level Serum Phosphorus

Facility % of PatientsN=899 facilities

0

10

20

30

40

50

60

<3.5 3.5-5 5-6 6-7 >7Serum Phosphorus (mg/dl)

The % of patients having a serum PO4 of >7 mg/dl varies from 3% in some facilities to 40% of patients in other facilities.

Facility-Level Serum Phosphorus versusAll-Cause and CV Mortality Risks

Among Patients on HD > 180 days

0.8

0.9

1

1.1

1.2

1.3

Phosphorus (mg/dl) category

HR associated with 10% more patients in the phosphorus

category

All-Cause Cardiovascular

≤3.5 3.6-5.0 5.1-6.0 6.1-7.0 >7.0

Hazard ratios and 95% confidence intervals (whiskers) for all-cause (events n=5,857) and cardiovascular mortality (events n=1,930). Models (n=20,561) were stratified by study phase and region and adjusted for facility clustering effect; baseline patient age, sex, race, BMI, time on ESRD, 13 comorbid conditions, hemoglobin, albumin, normalized protein catabolic rate, single-pool Kt/V, prior parathyroidectomy, and vitamin D prescription; the percentage of patients at a facility with serum calcium <8.5, 8.6-10, and >10 mg/dL; and the percentage of patients at a facility with serum PTH <100, 101-300, 301-600, and >600 pg/mL.

Tentori et al AJKD 2008

Ref

+95% C.I.

Can we use Principles of Randomization in Observational

Studies?

If patients are assigned randomly to facilities: If patients are assigned randomly to facilities: YesYes

• Instrumental variables may reduce treatment by indication bias

• This is useful when large differences in practice are observed

• In DOPPS, we use facility-level treatment variables as instrumental variables

Facility-Level Treatment Variables Rationale in DOPPS Design

• Patients usually select dialysis facilities by factors independent of their own medical condition – e.g. by proximity to home

• Average treatment patterns differ substantially among facilities, in part due to provider opinion or preferences

Facility-Level Treatment Variables

• Since variations in treatment preferences are likely “random” with respect to medical condition, this provides a “natural experiment” with advantages similar to randomization in a clinical trial

• Randomization provides balance across both Randomization provides balance across both measured and measured and ununmeasured confoundersmeasured confounders

Facility-Level Treatment Variables as Instrumental Variables: Caveats

• Other treatment practices may vary together with the treatment of interest

– Action: We adjust also for other treatment practices

• Unmeasured treatment practices may be confounders

– Action: We measure many practices

Impact of Dialysis Prescriptions and Practices on Outcomes: Summary

• The DOPPS approach has allowed identification of opportunities to improve practices and outcomes, e.g.– Treatment time (>4 hours thrice weekly)– Systolic Blood pressure (130-160 mmHg pre-dialysis)

– Phosphorus (Avoid PO4 >6 mg/dl)

• International outcome differences are confirmed and the US-Euro difference is largely explained by case-mix and vascular access: Need to improve vascular access

• The instrumental variable approach is useful when based on large differences in actual clinical practice

Acknowledgements

• Thanks to participating DOPPS facilities for their data submission and dedication, and to patients for completing questionnaires

• DOPPS is supported by scientific research grants without restrictions on publications from

– Amgen (1996-2011)

– Kyowa Hakko Kirin (1999-2011 in Japan)

– Genzyme (2009-2011)

Tightness of Hgb Control* and Mortality Risk

Among Facility Patients

* measured as facility standard deviation of Hgb levels

0

10

20

30

40

50

6 8 10 12 14 16

Hemoglobin (g/dl)

Facility with Std Dev = 1.0 g/dl

Some facilities may have larger variation (standard deviation) in patient hemoglobin levels. This may be due to: (1) greater comorbidity and variation in ESA-responsiveness among patients in some facilities

(2) differences in facility practices that impact anemia control

Facility Hgb Standard Deviation

Patients (%)

Facility with Std Dev = 3.0 g/dl

(measure of “tightness of Hgb control” among facility patients)

0.34.7

12.1

23.6 24.9

17.4

10.3

3.9 2.9

0

10

20

30

40

<0.6 0.6-0.8 0.8-1.0 1.0-1.2 1.2-1.4 1.4-1.6 1.6-1.8 1.8-2.0 >2.0

Facilities (%)

Facility Standard Deviation (g/dl) for Hgb Levels among Facility Patients

Variation in Facility Hemoglobin Standard Deviation

n=921 facilities, DOPPS I, II, and III;Facility Hgb Std Dev based upon a prevalent cross-section of study patients in a facility at start of each DOPPS phase on dialysis > 180 days

The mean facility Hgb level did not significantly correlate with

the facility Std Deviation of Hgb

Facility Std Deviation in Hemoglobin Levels and Mortality Risk

1.001.08

1.181.23

0.60

0.80

1.00

1.20

1.40

< 1.1 1.1 - 1.35 1.35 - 1.7 > 1.7

Relative Risk of death

Ref

Adjusted for age, gender, black race, years with ESRD, body mass index, 14 comorbidity classes and facility mean Hgb level; stratified by country and phase; accounted for facility clustering effects; n=23,245, DOPPS 1 to 3. Facility hgb std dev based upon facility prevalent cross-section, pts on dialysis > 180 days

Facility Std Dev for Hgb Levels

p=0.10

RR= 1.10 per 0.5 unit higher Std Dev (p=0.001)Adjusted for Facility Mean Hgb Levels

p=0.0003 p=0.003

Facility Std Dev in Hemoglobin Levels and Mortality Risk

1.001.06

1.161.27

0.60

0.80

1.00

1.20

1.40

< 1.1 1.1 - 1.35 1.35 - 1.7 > 1.7

Relative Risk of death

Ref

Adjusted for age, gender, black race, years with ESRD, body mass index, 14 comorbidity classes and facility mean Hgb level and the facility practice of treatment time, Kt/V, catheter use, serum Ca and PO4, and mean ESA dose; stratified by country and phase; accounted for facility clustering effects; n=23,245, DOPPS 1 to 3. Facility hgb std dev based upon facility prevalent cross-section, pts on dialysis > 180 days

Facility Std Dev (g/dl) for Hgb Levels

p=0.23

RR= 1.11 per 0.5 unit higher Std Dev (p=0.002) Adjusted for Facility Mean Hgb Level plus adjusted for 6 other facility practices

p=0.002 p=0.0008

Average Std Deviation in Hemoglobin by Country & DOPPS Phase*

*Baseline prevalent cross-section of patients on dialysis > 180 days for each country & phase. Restricted to facility with at least 12 observations

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

DOPPS I DOPPS II DOPPS III

Japan

ANZ

SwedenUS

France

Germany

Italy

UK

Spain

Belgium

CanadaUK

Japan

Ave of Facility Std Dev, g/dl

Practices Associated with Tighter Hgb Control at Facility Level

• Having a narrower Hgb target range• Adjusting ESA dose more often (at least monthly)

• Checking Hgb levels more often (at least weekly)

• Prescribing ESAs for more patients (higher %)

• Giving ESA i.v. rather than subcutaneously

Tighter Hgb Control at Facility Level*

Summary

Tighter Control of Hemoglobin at the Facility Level

• is associated with lower adjusted mortality at the facility

• is associated with certain practice patterns

• appears to be feasible according to the observed improvements over time in most countries

* i.e. smaller standard deviation of Hgb across patients

Distribution of Facility Mean TT, by Region and Phase

180

200

220

240

260

280

300

DOPPS I DOPPS II DOPPS I DOPPS II DOPPS I DOPPS II

TT (Minutes)

Europe Japan US

n = 546 facilitiesTT=Treatment Time

* * * *#

* p <0.05 vs US of same phase# p <0.05 vs US DOPPS I

Saran et al. KI 69: 1222-8, 2006

Hospitalization Risk by Facility Catheter UseMedian Facility = 18% of Patients Use Catheters

Relative Risk (95% CI)

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

28 +

18 - 28

13 - 18

9 - 13

28 +

18 - 28

13 - 18

9 - 13Infection-Related Hospitalization

Access-Related Hospitalization

RR=1.79 (p<0.0001) per 20%Higher Facility Catheter Use

RR=1.33 (p=0.008) per 20%Higher Facility Catheter Use

1.07

1.03

1.28

1.56

1.24

1.18

1.64

2.56

Facility (%)

Reference = AVF; adjusted for case mix and AV Graft use

Hospitalization Risk by Facility Graft UseMedian Facility = 32% of Patients Use Grafts

Relative Risk (95% CI)

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5

50 +

32 - 50

23 - 32

15 - 23

50 +

32 - 50

23 - 32

15 - 23

Infection-Related Hospitalization

Access-Related Hospitalization

RR=1.29 (p<0.0001) per 20%Higher Facility Graft Use

RR=1.11 (p=0.008) per 20%Higher Facility Graft Use

1.30

1.28

1.33

1.51

1.38

1.61

1.75

2.32

Facility (%)

Reference = AVF; adjusted for case mix and Catheter use

100

110

120

130

140

150

160

170

180

Facility Target Pre-Dialysis Systolic BP by Medical Director Survey

By Region

* DOPPS III Medical Director Survey. N = 236 facilities

SBP Target (mmHg)

N of facilities 119 57 60

25th = 140 mmHg 75th = 160

mmHg

Japan North AmericaEU & ANZ