Included participantsNot included

GFR Decline as an Endpoint in Clinical Trials of CKD

Josef Coresh, MD, PhDG.W. Comstock Professor

of Epidemiology, Biostatistics & Medicine Johns Hopkins University

1

Josef Coresh, MD, PhD & Morgan Grams, MD, PhDCo-Principal Investigators (~70 cohorts including ~10 Million participants)

1. Criteria for assessing a surrogate outcomes in CKD

2. Using data to make progress Observational studies Clinical Trials Simulations

3. 2012 FDA Workshop Conclusions Using eGFR change as a surrogate outcome (57% reduction 30-40% reduction) with a major caveat (acute effects can nullify the paradigm)

4. Related work – 2018 FDA Workshop on change in albuminuria and GFR slopes

Outline

Am J Kidney Dis. 2014; 64(6):821-835

DEFINITION (since 2002)• CKD is defined as abnormalities of kidney structure or function, present for 3+ monthsSTAGING (CGA since 2013)• by cause (C), GFR category (G), and albuminuria category (A)

Progression data were limited• Decline in GFR category

• Certain drop (25+%) • Rapid 5+ ml/min/y• Confidence # yrs, # measures

• ACR small fluctuations are common

KDIGO 2012 – Evaluation & Mangement of CKD

• Biologic plausibility: whether surrogate is on pathophysiologic pathway leading to clinical outcome of interest (causal? necessary intermediate?)

• Strength and consistency of epidemiologic data supporting relationship between surrogate and clinical outcome of interest

• Prediction of treatment effects on surrogate from treatment effects on clinical outcome of interest (with drugs in the same/related pharmacologic class? with drugs from distinct pharmacologic classes/ regardless of the mechanism of the intervention?)

Assessing a Candidate Surrogate Endpoint

At present, no FDA guidance document contains a detailed discussion of the evidence needed to establish a “validated surrogate endpoint” supporting traditional approval, however FDA has stated that the standard is high.

Chronic Kidney Disease Prognosis Consortium~70 cohorts, ~10 million participants

Josef Coresh, MD, PhD & Morgan Grams, MD, PhDCo-PIs, CKD Prognosis Consortium

http://www.jhsph.edu/ckdpc

Included participantsNot included

AichiHiroshi YatsuyaKentaro YamashitaHideaki ToyoshimaKoji Tamakoshi

AKDN:Marcello TonelliBrenda HemmelgarnMatthew James Tanvir C Turin

ARIC:Josef CoreshKunihiro Matsushita Morgan GramsYingying Sang

AusDiab: Robert C Atkins Kevan R PolkinghorneSteven Chadban

Beaver Dam: Ronald Klein Barbara EK KleinKristine E Lee

Beijing:HaiYan WangLuxia Zhang Fang WangLi Zuo

China National Survey:Luxia ZhangLisheng LiuMinghui ZhaoFang WangJinwei Wang

CHS:Michael ShlipakCarmen PeraltaRonit Katz

CIRCS:Hiroyasu IsoAkihiko KitamuraTetsuya OhiraKazumasa Yamagishi

COBRA:Tazeen JafarMuhammad Islam Juanita Hatcher Neil PoulterNish Chaturvedi

ESTHER:Dietrich RothenbacherHermann Brenner Heiko MüllerBen Schöttker

Framingham:Caroline S Fox Shih-Jen Hwang James B MeigsAshish Uphadhay

Gubbio:Massimo Cirillo

HUNT: Stein HallanKnut AasarødCecilia M ØienMarie Radtke

Ibaraki:Fujiko IrieHiroyasu IsoToshimi SairenchiKazumasa Yamagishi

Jackson Heart Study:Adolfo CorreaCasey RebholzEbony BoulwareBessie Young

Japan Health Checkup:Tsuyoshi WatanabeKunihiro YamagataKunitoshi IsekiKouichi Asahi

JMS:Shizukiyo IshikawaYuichiro Yano

Korean Heart Study: Sun Ha JeeHeejin KimmYejin Mok

KSHS:Eliseo GuallarSeungho RyuYoosoo ChangJuhee ChoHocheol Shin

Maccabi:Gabriel ChodickVarda ShalevYair C BirnbaumAnat Bet-Or

MESA:Michael ShlipakMark J SarnakCarmen PeraltaRonit Katz Holly J Kramer

MRC Older People:Paul Roderick Dorothea Nitsch Astrid Fletcher Christopher Bulpitt

Mt. Sinai BioMe:Erwin BottingerGirish Nadkarni

NHANES III:Brad Astor Josef Coresh Kunihiro Matsushita

NIPPON:Hirotsugu UeshimaAkira OkayamaKatsuyuki MiuraSachiko Tanaka

Ohasama:Takayoshi Ohkubo Hirohito MetokiMasaaki Nakayama Masahiro KikuyaYutaka Imai

Okinawa 83 & 93:Kunitoshi Iseki

Ontario ICES-KDT:Amit GargEric McArthur

PREVEND:Ron T Gansevoort Paul E de Jong Hans Hillege

Rancho Bernardo:Simerjot K JassalElizabeth Barrett-Connor Jaclyn Bergstrom

REGARDS:David G Warnock Paul MuntnerSuzanne Judd Orlando Gutierrez

CKD-PC (GP cohorts)Rotterdam:

Sanaz SedaghatM Arfan IkramEwout J HoornAbbas Dehghan

SCREAM:Juan-Jesus CarreroAbdul Rashid Qureshi

SEED:Tien Yin WongCharumathi SabanyagamChing-Yu ChengWan Gen Yip

Taiwan:Chi-Pang Wen Sung-Feng Wen Chwen-Keng TsaoMin-Kuang Tsai

Takahata:Tsuneo KontaAtsushi HirayamaKazunobu Ichikawa

TLGS Iran:Farzad Hadaegh, Mohammadhassan MirboloukFereidoun Azizi

Tromsø:Marit D SolbuBjørn O Eriksen

ULSAM:Johan ÄrnlövLars LannfeltAnders Larsson

ADVANCE:Mark Woodward John Chalmers Stephen MacMahonHisatomi Arima

CARE:Marcello TonellFrank Sacks Gary Curhan

KEEP: Allan J CollinsJoseph A VassalottiSuying Li Shu-Cheng Chen

KP Hawaii:Brian J Lee

MRFIT:Areef IshaniJames Neaton

NZDCS:C Raina ElleyTim KenealySimon MoyesJohn CollinsPaul Drury

Pima Indian:Robert G NelsonWilliam C Knowler

SMART:Frank Visseren

ZODIAC:Henk J BiloHanneke JoostenNanne KleefstraKlaas H GroenierIefke Drion

AASK:Jackson Wright Lawrence Appel Tom GreeneBrad C Astor

British Columbia CKD: Adeera Levin Ognjenka Djurdjev

CanPREDDICTAdeera LevinOgnjenka Djurdjev

CARE FOR HOMeGunnar HeineSarah SeilerAdam Sawada

CCF:Sankar NavaneethanJoseph NallyJesse Schold

CKD-JAC:Masafumi FukagawaShoichi MaruyamaTakayuki HamanoTakeshi HasegawaNaohiko Fujii

CRIB:David C Wheeler Martin J Landray Jonathan N TownendJonathan Emberson

CRIC:Lawrence AppelHarold FeldmanChi-Yuan Hsu

CRISIS:Philip A KalraJames RitchieRaman MaharajanHelen AldersonBeverly Lane

GCKD:Kai-Uwe EckardtAnna KottgenStephanie Titze

GeisingerAlex R ChangRobert PerkinsH Les Kirchner

GLOMMS 2:Corri BlackAngharad Marks Nicholas FluckGordon Prescott

Gonryo CKDSadayoshi ItoMasaaki NakayamaMariko Miyazaki

Hong Kong CKD:Angela Yee Moon WangSharon CheungSharon WongJessie ChuHenry Wu

KP Northwest: David H Smith Eric S Johnson Micah L ThorpJessica Weinstein

MASTERPLAN: Jack F WetzelsPeter J Blankestijn Arjan D van Zuilen

MDRD: Mark SarnakAndrew S LeveyLesley InkerVandana Menon

MMKD:Florian KronenbergBarbara KolleritsEberhard Ritz

Nanjing CKD:Haitao Zhang

Nefrona:Jose M ValdivielsoElvira FernandezAngels BetriuMarcelino Bermudez-Lopez

NephroTest:Marc Froissart Benedicte Stengel Marie Metzger Jean-Philippe HaymannPascal HouillierMartin Flamant

NRHP-URU:Pablo RiosNelson MazzuchiLiliana GadolaVerónica LamadridLaura Sola

CKD-PC (HR/CKD cohorts)PSPA:

Olivier MoranneCecile CouchoudCecile Vigneau

PSP-CKD:Nigel BrunskilRupert Major

RENAAL: Hiddo J L HeerspinkBarry Brenner Dick de Zeeuw

SRR-CKDMarie Evans

STENO CKD: Peter RossingHans-Henrik Parving

Sunnybrook:David NaimarkNavdeep Tangri

VA/RCAV:Csaba P KovesdyKamyar Kalantar-Zadeh

West of Scotland CKD: Patrick B MarkJamie P TraynorColin C GeddesPeter C Thomson

CKD Progression: A Focus on Future Risk

Adjust for first eGFR

First eGFR

8

Baselineperiod

Follow-up for ESRD

150

120

90

60

30

eGFR

ml/

min

/1.7

3m2

(A)

150

120

90

60

30 (B)

Last eGFR

45

Clinical Trial Perspective:Equal starting point

• Question: Is more rapid CKD progression (B vs. A) associated with higher subsequent risk of ESRD?

• Analyze each participating cohort: model % change in eGFR using a spline• Meta-analyze across cohorts: random effects meta-analysis• Examine heterogeneity: Forest Plots and Meta-Regression

Adjust for last eGFR

First eGFR

Last eGFR

Baselineperiod

Follow-up for ESRD

150

120

90

60

30 (A)

150

120

90

60

30

(B)

45eGFR

ml/

min

/1.7

3m2

Clinician Perspective: at last visit extrapolate past history

ESRD

45

ESRD

Am J Kidney Dis. 2014; 64(6):821-835

Participating Cohorts: Description by Baseline Kidney Function

During the baseline period After the baseline period

Participants,N

Serum creatinine,

n (IQR)

ESRD events, n

Follow-up Mean (SD),

yearsBaseline eGFR <60

Baseline eGFR 60+

Baseline eGFR <60

Baseline eGFR 60+

Baseline 19 cohorts 9 cohorts 19 cohorts 9 cohorts1 year 487,213 1,043,401 2 (2-3) 11,236 1,109 3.12 years 383,216 957,949 3 (3-5) 7,548 992 2.43 years 255,795 824,405 5 (5-5) 4,087 1,085 2.0

Variable Mean MeanBaseline eGFR 48 90Age 74 52% Female 23 52% Black 6 1Total Cholesterol 5 5Systolic BP 135 132% DM 38 16% Hx of CVD 33 6

Adjustment variables at baseline

JAMA 2014;311: 2518-31

31.4 (21.6, 45.7)

10.1 (8.1, 12.5)5.3 (4.5, 6.2)

2.9 (2.5, 3.3)

Ref.

0.30.30.30.30.30.30.30.30.30.3 0.70.70.70.70.70.70.70.70.70.7 1.51.51.51.51.51.51.51.51.51.5 3.43.43.43.43.43.43.43.43.43.46.96.96.96.96.96.96.96.96.96.9

12121212121212121212

25252525252525252525

1616161616161616161612121212121212121212 10101010101010101010

4.84.84.84.84.84.84.84.84.84.8

-4-202468

1012

.2

1

5

25

125

625

PAR

, %

Adj

uste

d H

R

-70 -60 -50 -40 -30 -20 -10 0 10 20 30 40Percent change of eGFR

55.7 (22.7, 136.7)

15.1 (8.7, 26.3)

6.6 (3.8, 11.5)

2.8 (1.8, 4.3)

Ref.

0.10.10.10.10.10.10.10.10.10.1 0.20.20.20.20.20.20.20.20.20.2 0.40.40.40.40.40.40.40.40.40.4 1.21.21.21.21.21.21.21.21.21.2 3.23.23.23.23.23.23.23.23.23.2

12121212121212121212

2020202020202020202015151515151515151515

8.68.68.68.68.68.68.68.68.68.63.73.73.73.73.73.73.73.73.73.7

34343434343434343434

0

10

20

30

40

Perc

enta

ge o

f pop

ulat

ion

-70 -60 -50 -40 -30 -20 -10 0 10 20 30 40Percent change of eGFR

Adjusted Hazard Ratio (HR) of ESRD and Subsequent to % Change in eGFR during a 2-year baseline period

Doub

ling

of se

rum

cr

eatin

ine

Doub

ling

of se

rum

cr

eatin

ine

-30% eGFR

eGFR<60 eGFR≥60

JAMA 2014;311: 2518-31

31.4 (21.6, 45.7)

10.1 (8.1, 12.5)5.3 (4.5, 6.2)

2.9 (2.5, 3.3)

Ref.

0.30.30.30.30.30.30.30.30.30.3 0.70.70.70.70.70.70.70.70.70.7 1.51.51.51.51.51.51.51.51.51.5 3.43.43.43.43.43.43.43.43.43.46.96.96.96.96.96.96.96.96.96.9

12121212121212121212

25252525252525252525

1616161616161616161612121212121212121212 10101010101010101010

4.84.84.84.84.84.84.84.84.84.8

-4-202468

1012

.2

1

5

25

125

625

PAR

, %

Adj

uste

d H

R

-70 -60 -50 -40 -30 -20 -10 0 10 20 30 40Percent change of eGFR

55.7 (22.7, 136.7)

15.1 (8.7, 26.3)

6.6 (3.8, 11.5)

2.8 (1.8, 4.3)

Ref.

0.10.10.10.10.10.10.10.10.10.1 0.20.20.20.20.20.20.20.20.20.2 0.40.40.40.40.40.40.40.40.40.4 1.21.21.21.21.21.21.21.21.21.2 3.23.23.23.23.23.23.23.23.23.2

12121212121212121212

2020202020202020202015151515151515151515

8.68.68.68.68.68.68.68.68.68.63.73.73.73.73.73.73.73.73.73.7

34343434343434343434

0

10

20

30

40

Perc

enta

ge o

f pop

ulat

ion

-70 -60 -50 -40 -30 -20 -10 0 10 20 30 40Percent change of eGFR

Adjusted Hazard Ratio (HR) of ESRD and Subsequent to % Change in eGFR during a 2-year baseline period

Doub

ling

of se

rum

cr

eatin

ine

Doub

ling

of se

rum

cr

eatin

ine

-30% eGFR

eGFR<6012% 39%

% population attributable risk eGFR≥607% 23%

JAMA 2014;311: 2518-31

NOTE: Weights are from random effects analysis

Overall (I-squared = 79.9%, p = 0.000)

Study

Maccabi

NZDCS

MRFIT

ID

Sunnybrook

VA_CKD

Pima

AKDN_dipstick

ADVANCE

BC_CKD

6.61 (3.74, 11.68)

Hazard

20.49 (11.32, 37.08)

9.87 (5.43, 17.96)

1.53 (0.81, 2.90)

Ratio (95% CI)

3.32 (0.72, 15.25)

10.12 (6.00, 17.07)

9.13 (3.95, 21.12)

6.47 (2.83, 14.76)

6.07 (1.73, 21.26)

4.34 (1.77, 10.63)

100.00

%

12.72

12.69

12.44

Weight

7.17

13.13

11.18

11.26

8.60

10.81

6.61 (3.74, 11.68)

Hazard

20.49 (11.32, 37.08)

9.87 (5.43, 17.96)

1.53 (0.81, 2.90)

Ratio (95% CI)

3.32 (0.72, 15.25)

10.12 (6.00, 17.07)

9.13 (3.95, 21.12)

6.47 (2.83, 14.76)

6.07 (1.73, 21.26)

4.34 (1.77, 10.63)

100.00

%

12.72

12.69

12.44

Weight

7.17

13.13

11.18

11.26

8.60

10.81

1.5 1 2 4 8 16 32First eGFR60

for 30% decline in eGFR in 2 yearsRelative risk of End-Stage Renal Disease

NOTE: Weights are from random effects analysis

Overall (I-squared = 62.8%, p = 0.000)

CCF

MDRDMRFIT

ID

RENAAL

VA_CKD

CRIB

AASK

MASTERPLAN

KPNW

BC_CKD

Geisinger

NZDCS

GLOMMS1

NephroTest

Sunnybrook

ADVANCEAKDN_dipstick

KP Hawaii

Maccabi

Study

5.32 (4.52, 6.26)

5.36 (3.53, 8.12)

3.48 (2.66, 4.55)9.52 (1.54, 59.04)

Ratio (95% CI)

4.25 (1.42, 12.70)

6.40 (5.75, 7.13)

9.45 (3.62, 24.70)

4.99 (3.43, 7.27)

9.37 (4.84, 18.13)

23.94 (5.49, 104.38)

4.36 (3.64, 5.22)

5.22 (3.56, 7.66)

2.79 (1.73, 4.49)

4.27 (1.73, 10.52)

5.76 (3.05, 10.88)

6.23 (3.44, 11.29)

4.21 (0.80, 22.17)4.67 (3.04, 7.16)

25.94 (4.04, 166.37)

6.76 (5.37, 8.51)

Hazard

100.00

6.89

9.340.75

Weight

1.88

11.89

2.34

7.52

4.10

1.11

10.84

7.39

6.04

2.58

4.31

4.69

0.896.71

0.72

10.03

%

5.32 (4.52, 6.26)

5.36 (3.53, 8.12)

3.48 (2.66, 4.55)9.52 (1.54, 59.04)

Ratio (95% CI)

4.25 (1.42, 12.70)

6.40 (5.75, 7.13)

9.45 (3.62, 24.70)

4.99 (3.43, 7.27)

9.37 (4.84, 18.13)

23.94 (5.49, 104.38)

4.36 (3.64, 5.22)

5.22 (3.56, 7.66)

2.79 (1.73, 4.49)

4.27 (1.73, 10.52)

5.76 (3.05, 10.88)

6.23 (3.44, 11.29)

4.21 (0.80, 22.17)4.67 (3.04, 7.16)

25.94 (4.04, 166.37)

6.76 (5.37, 8.51)

Hazard

100.00

6.89

9.340.75

Weight

1.88

11.89

2.34

7.52

4.10

1.11

10.84

7.39

6.04

2.58

4.31

4.69

0.896.71

0.72

10.03

%

1.5 1 2 4 8 16 32First eGFR<60

for 30% decline in eGFR in 2 yearsRelative risk of End-Stage Renal Disease

12

19 studies with eGFR<60 9 studies with eGFR 60+

Adj. Hazard Ratio of ESRD after a 30% Decline in eGFR over 2-yearsForest Plot Showing Consistency Across Studies

5.32 (4.52, 6.26) 6.61 (3.74, 11.68)

2014 Publications Series for CKD Clinical Trials

Am J Kidney Dis. 2014; 64(6):848-859

Am J Kidney Dis. 2014; 64(6):860-866

Am J Kidney Dis. 2014; 64(6):867-879

JAMA 2014;311: 2518-31

Cohorts

Simulations

Clinical Trials – Intention to Treat

Clinical Trials - Observational

Am J Kidney Dis. 2014; 64(6):821-835

Conference Report - SUMMARY

Clinical Trials – Support using 30-40% Decline 37 randomized trials BUT Data are Limited

• Nice correlation across studies between: Hazard ratio alternativeoutcome (for 30-40% eGFR decline) hazard ratio for established outcome (doubling of serum creatinine or ESRD)

Am J Kidney Dis. 2014; 64(6):848-859

Simulations – Support using 30-40% Decline BUT Warn about Acute Effects

Am J Kidney Dis. 2014; 64(6): 821-835

Inflated Type 1 Error – False Positive Benefit

Inflated Type 1 Error – False Positive Harm

Type 1 Error Acceptable and Power Improved

Acute Effects

Summary of Evidence from All SourcesObservational Studies, Trials, Simulations

• Based on a series of meta-analyses of cohorts and clinical trials and simulations of trial designs and analytic methods, the workshop concluded that a confirmed decline in estimated GFR of 30% over 2 to 3 years may be an acceptable surrogate end point in some circumstances, but the pattern of treatment effects on GFR must be examined, specifically acute effects on estimated GFR. – An estimated GFR decline of 40% may be more broadly acceptable

than a 30% decline across a wider range of baseline GFRs and patterns of treatment effects on GFR.

– However, there are other circumstances in which these end points could lead to a reduction in statistical power or erroneous conclusions regarding benefits or harms of interventions.

– We encourage careful consideration of these alternative end points in the design of future clinical trials.

Summary of 5 papers : Am J Kidney Dis. 2014; 64(6):821-835Favorable editorials by FDA & EMA

Conclusions

• Meaningful CKD progression can be understood in the context of its prediction of future risk & surrogacy– eGFR decline of 30%-40% is a useful outcomes and surrogate for

CKD progression (with caveats)

• Ongoing work (FDA meeting 2018: data + discussion papers)

• Surrogacy speaks only to efficacy not safety which may relate to off-target effects

Acknowledgements

• CKD-EPI Collaboration (eGFR & trials)

• CKD Prognosis Consortium (NKF & KDIGO) • Consortium - a group formed to undertake an enterprise beyond the resources of any one member

• NKF, FDA and Workshop Attendees• International collaborations• Johns Hopkins co-investigators & staff

Thank you!

EXTRA SLIDES

NKF Workshop Report

2018 Preliminary Datato be presented at ASN

Figures

GFR Slope ESKD Risk Associations(ESKD HR and CI for 0.75 ml/min/1.73 m2 per year difference)

Least Square Mean Regression Linear Mixed Models RegressionBaseline eGFR <60

1-year 0.88 (0.86, 0.91) 0.80 (0.77, 0.83)2-year 0.80 (0.78, 0.82) 0.71 (0.69, 0.74)3-year 0.71 (0.69, 0.74) 0.64 (0.60, 0.67)

Baseline eGFR >601-year 0.93 (0.92, 0.94) 0.77 (0.74, 0.80)2-year 0.85 (0.83, 0.87) 0.70 (0.68, 0.73)3-year 0.77 (0.74, 0.80) 0.67 (0.64, 0.69)

*LSM; empirical: beta coefficient from linear regression of eGFR on time. LMM; best linear unbiased prediction from linear mixed models. All eGFR values within a given observation period (1-, 2-, 3- years +/- 30%) were used to estimate slope coefficient.

Treatment Effect on the Clinical vs. Slope Surrogate: Meta-Regression of 47 trial interventions

.06 .12 .25 .5 1 2 4 8 16ACR fold change

.06 .12 .25 .5 1 2 4 8 16PCR fold change

Albuminuria Change ESKD Risk Associations(ESKD HR and CI for 30% ACR or PCR Decrease)

Empiric* Adjusted for Regression Dilution (Median Reliability)**

ACR1-year 0.82 (0.74-0.91) 0.75 (0.64-0.87)2-year 0.83 (0.74-0.94) 0.78 (0.66-0.92)3-year 0.80 (0.71-0.90) 0.76 (0.65-0.87)

PCR1-year 0.86 (0.76-0.97) 0.80 (0.67-0.95)2-year 0.77 (0.68-0.87) 0.69 (0.58-0.83)3-year 0.74 (0.61-0.89) 0.68 (0.54-0.86)

*Adjusted for age, sex, race/ethnicity (blacks vs. non-blacks), systolic blood pressure, total cholesterol, diabetes, history of cardiovascular disease, current smoking, former smoking, and first eGFR and albuminuria. **Based on estimates for ACR and PCR in 19 studies. Median (IQR 25th to 75th percentile) reliability estimates (λ) for 1, 2 and 3 year change were 0.677 (0.533-0.770), 0.721 (0.650-0.808) and 0.789 (0.713-0.852). The same reliability estimates were used for ACR and PCR.

Treatment Effect on the Clinical vs. Slope Surrogate: Meta-Regression of 39 trial interventions

FDA meeting 2018: Data + discussion ASN 2018 + papers in progress

• ACR change can be a reasonably likely surrogate endpoint for kidney disease progression in many Phase III RCTs and can be a valid surrogate endpoint in some Phase III RCTs, but its appropriateness varies by disease and by intervention. It is most appropriate for diseases characterized by albuminuria and for interventions in which reducing albuminuria is hypothesized to be one of the mechanisms of action. A large treatment effect (a 20-30% reduction in GMR ACR) is likely to be necessary to assure a significant treatment effect on the clinical endpoint

• eGFR slopes are impressively predictive and correlated with clinical trial outcomes meeting criteria for a valid surrogate (with the caveat that acute effects complicate the analysis and interpretation)

Planning Committee

Advisors StakeholdersIncluding patients

Workshop Attendees

Operations Committee

Analytic Group

SponsorsNKF, FDA, EMA

GFR Slopes - Trials• Acute treatment effects are common and

vary by intervention.• Treatment effects on total and chronic

slope are less precise at shorter follow up intervals.

• At 3 years, treatment effects on chronic slope approach effect on total slope.

• Strong relationships of treatment effect on the clinical endpoint and treatment effect on slope at 3 years. Stronger for total slope than chronic slope.

• Consistency across baseline eGFR, ACR, disease and intervention, but insufficient power for definitive evaluation.

• Relationships weaken but persist at 2 years, but deteriorate greatly at 1 year

• Slope reduction of 0.5-1.0 ml/min/1.73 m2 per year has HR of 0.6-0.7 for treatment effect on clinical endpoint and PPV of 97.5% for HR <1.0.

Albuminuria Change – Trials (1)

• Moderately strong relationship.• Relationship is stronger for the

subgroup with ACR > 30 mg/g, but limited power to assess statistical significance.

• Consistency across baseline eGFR, ACR, disease and intervention, but insufficient power for definitive evaluation.

• 30-40% ACR reduction is associated with HR of 0.6-0.7 for treatment effect on clinical endpoint and PPV of 97.5% for HR <1.0.

Utility vs. ValidityHigher power (smaller

sample size, shorter follow up) compared

to Scrdoubling

Strong biologic

plausibility, strong

associations with clinical

endpoint, preserves low type 1 error

Both criteria depend on nature of treatment effect, duration of follow up, baseline GFR, size and direction of acute effects and trial duration.

Circumstances in which the proposed alternative surrogates may not be applicable (1)

• Effects of the interventions on non-GFR determinants of serum creatinine– Measure other filtration markers (cystatin C, etc)– Measure GFR

• Acute effects– No easy answer, will require modifications to clinical trial

design, generally on a case-by-case basis– Omission of pre-randomization GFR (inclusion of only on-

treatment GFR) would be a violation of RCT intention-to-treat analysis; justification should be specific to the intervention and disease

Relationship between Decline in eGFR andRise in Serum Creatinine or Cystatin C

• Mathematical transformations based on Scr or Scys coefficient in GFR estimating equations

• For CKD-EPI equations: Scr -1.209 (above the knots, Scr0.7 in women and Scr 0.9 in men)Scys -1.328 (above the knot, Scys0.8 in women and men)

eGFRdecline

x↑Scr x↑Scys

75% 3.15 2.8467% 2.50 2.3057% 2.01 1.8950% 1.77 1.6940% 1.53 1.4730% 1.34 1.3125% 1.27 1.2420% 1.20 1.1810% 1.09 1.08

Scorecard for eGFR decline >30% and >40%Analysis Results Comment

Cohorts

Relative risk for ESRD is strong (HR >4) Yes Consistent across cohorts and baseline eGFR

Excess risk is substantial (>10-50% for 30% decline in eGFR)

Yes Varies by baseline eGFR and follow-up interval

Trials

Relative risk for ESRD is strong (HR >4) Yes Consistent among trials

Treatment effect precision is greater than for Scr doubling

Yes Greater with longer duration of follow up

Treatment effect HR (with confirmation) is is similar to Scr doubling (within 10%)

Yes Consistent among interventions except diet (non-GFR effect) and except RASB vs. CCB with 30% (acute effects)

Simulations

Acceptable type 1 errors in simulations with null treatment effects

Yes Substantial savings for shorter trials and high baseline GFR. Inflated type I error in some settings with moderate and large acute effects(more with 30%)

Power stronger than Scr doubling (smaller samples size or shorter follow-up)