Risk stratification based on J-ACCESS risk models with myocardial perfusion imaging: Risk versus outcomes of patients with chronic kidney disease
Risk stratification based on J-ACCESS risk models with myocardial perfusion imaging: Risk versus outcomes of patients with chronic kidney disease
Kenichi Nakajima 1 6
Satoko Nakamura 1 4 5
Hiroki Hase 1 2
Yasuchika Takeishi 1 3
Shigeyuki Nishimura 0 1
Yuhei Kawano 1 4
g Tsunehiko Nishimura 1
0 Saitama Medical University International Medical Center , Hidaka , Japan
1 Reprint requests: Tsunehiko Nishimura , MD, PhD , Graduate School of Medical Science, Kyoto Prefectural University of Medicine , 465 Kajiicho, Kawara-machi Hirokoji, Kamigyo-ku, Kyoto 602-8566 , Japan
2 Department of Nephrology, Toho University Ohashi Medical Center , Tokyo , Japan
3 Department of Cardiovascular Medicine, Fukushima Medical University , Fukushima , Japan
4 Division of Hypertension and Nephrology, National Cerebral and Cardiovascular Center , Suita , Japan
5 Kansai University of Welfare Sciences , Kashihara , Japan
6 Department of Nuclear Medicine, Kanazawa University Hospital , Kanazawa , Japan
Background. This study aimed to validate the accuracy of major-event risk models created in the multicenter J-ACCESS prognostic study in a new cohort of patients with chronic kidney disease (CKD). Methods and Results. Three multivariable J-ACCESS risk models were created to predict major cardiac events (cardiac death, non-fatal acute coronary syndrome, and severe heart failure requiring hospitalization): Model 1, four variables of age, summed stress score, left ventricular ejection fraction and diabetes; Model 2 with five variables including estimated glomerular filtration rate (eGFR, continuous); and Model 3 with categorical eGFR. The validation data used three-year (3y) cohort of patients with CKD (n = 526, major events 11.2%). Survival analysis of low (< 3%/3y), intermediate (3% to 9%/3y), and high (> 9%/3y)-risk groups showed good stratification by all three models (actual event rates: 3.1%, 9.9%, and 15.9% in the three groups with eGFR ‡ 15 mL/min/1.73 m2, P = .0087 (Model 2). However, actual event rates were equally high across all risk groups of patients with eGFR < 15 mL/min/ 2 1.73 m . Conclusion. The J-ACCESS risk models can stratify patients with CKD and eGFR ‡ 15 mL/min/1.73 m2, but patients with eGFR < 15 mL/min/1.73 m2 are potentially at high risk regardless of estimated risk values. (J Nucl Cardiol 2018)
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Funding This study was supported by grants from the Japan
Cardiovascular Research Foundation.
Coronary artery disease
Chronic kidney disease
Estimated glomerular filtration rate
Left ventricular ejection fraction
Summed stress score
Myocardial perfusion abnormalities and left
ventricular (LV) dysfunction can predict major cardiac
events, and single-photon emission-computed
tomography (SPECT) myocardial perfusion imaging (MPI) can
provide vital information for prognosis.1–4 Large-scale
single- and multi-center studies have found that a larger
defect size on MPI, LV dysfunction such as lower LV
ejection fraction (LVEF) and higher LV volumes are
generally associated with an increased incidence of
cardiovascular events. Therefore, these factors have
been included as statistically significant variables in
uniand multi-variable analyses even in Japanese
multicenter cohort studies.5–7 In addition, since associated
conditions such as diabetes and chronic kidney disease
(CKD) are also major predictors of cardiovascular
events, the estimation of clinical risk factors could play
an important role in clinical practice.7,8
Risk models for estimating cardiac events have
been developed using score-related event risks9 and
calculations of event risk (%).10,11 However, although
multifactorial effects on cardiovascular events have
been demonstrated, few studies have evaluated the
accuracy of these multivariable risk models to predict
such events in Japanese populations by comparing
predicted and actual outcomes.
J-ACCESS prognostic studies have been ongoing in
Japan since 2001, and event risk models to estimate
major cardiac events, including cardiac death, non-fatal
myocardial infarction (MI) and severe heart failure (HF)
requiring hospitalization, have been created for clinical
applications.10 These J-ACCESS risk models
incorporated the risk factors of age, LVEF, and perfusion
defects under stress determined using summed stress
score (SSS), diabetes, and subsequently estimated
glomerular filtration rates (eGFR).11 The J-ACCESS-3
study was an independent multi-center study in Japan in
patients with CKD, and three-year outcomes were
evaluated in patients with eGFR \ 50 mL/min/
The hypothesis of the present study is that risk
estimated using the model from the J-ACCESS study
could be in agreement with the actual outcome of the
JACCESS-3 study, which was used as a validation
population. The present study also aimed to determine
the effect of eGFR on associations between risk models
Risk Models Created in J-ACCESS Study
where b(i) is a parameter estimate of a predictive
variable x(i). To create the logistic risk models, patients who
were censored alive within the 3 year follow-up were
Model 1: four-parameter model with
out eGFR. Multivariable logistic analysis of the 4,031
individuals showed that SSS (with four categorical variables of
0-3, 4-8, 9-12, and C 13 by a 20-segment model; revised later
to 0-3, 4-7, 8-11, and C 12 by a 17-segment model), LVEF,
age, and diabetes were significant variables (Table 2).10
Model 2: five-parameter model with con
tinuous eGFR. Subsequent analysis based on patients with
information about eGFR (n = 2,395) clarified the importance
of including CKD or eGFR. Therefore, all coefficients were
determined based on similar logistic analysis with five
variables (Table 2).11 SSS was classified as 0 (\ 8) and 1 (C 8).
Model 3: five-parameter model with cate
gorical eGFR and four SSS classes. Model 3 was
used in Heart Risk View software [Nihon Medi-Physics,
Tokyo, Japan], which was a revision of Model 2 that included
categorical variables and was intended for practical application
to clinical situations. The model included eGFR (mL/min/
1.73 m2) classified as 1 (\ 30), 2 (C 30, \ 45), 3
Derivation population Model 1
eGFR, estimated glomerular filtration rate; LVEF, left ventricular ejection fraction; SSS, summed stress score
(C 45, \ 60), 4 (C 60, \ 90), and 5 (C 90); and SSS was
classified as 0 (B 3), 1 (
), 2 (
), and 3 (C 12).
Patients in the Validation Population
The principal design and results of J-ACCESS-3 are
described elsewhere.14 A total of 549 patients were registered
from 62 institutions between 2009 and 2010. The inclusion
criteria included patients aged C 20 years who were scheduled
to undergo stress-rest electrocardiographic gated MPI due to
having suspected ischemic coronary artery disease (CAD),
eGFR \ 50 mL/min/1.73 m2, and one or more of the seven
risk factors for CAD (hypertension, diabetes, dyslipidemia,
peripheral vascular diseases, currently smoking, family history
of juvenile CAD, and history of ischemic stroke). Chronic
kidney disease was defined based on the Japanese equation for
eGFR (mL/min/1.73 m2).15 The exclusion criteria included
hemodialysis or peritoneal dialysis, severe valvular heart
disease requiring surgical treatment, cardiomyopathies, prior
diagnosis of angina pectoris or MI, and a history of
revascularization, percutaneous coronary intervention (PCI), or a
coronary artery bypass graft surgery. A total of 526 patients
who had complete sets of variables for the risk model were
Either 1-day (96%) or 2-day (4%) protocols were applied
in pharmacological stress MPI studies using a standard
protocol of 99mTc-tetrofosmin and Anger-type cameras.
Pharmacological stress studies proceeded using adenosine (91%),
dipyridamole, or adenosine triphosphate. The average
administered doses of 99mTc-tetrofosmin for the initial and second
studies were 312 and 689 MBq, respectively. Chest pain
(n = 7, 1.3%), ST depression (n = 3, 0.6%), atrioventricular
block (the second degree or worse) (n = 2, 0.4%), and serious
arrhythmia (n = 2, 0.4%) developed during the
pharmacological stress study. Both LVEF and LV volumes were quantified
using QGS software (Cedars-Sinai Medical Center, Los
Angeles, CA, USA).
Evaluation of MPI Findings
An interpretation committee comprising seven nuclear
cardiology experts objectively analyzed all data from standard
SPECT slices including SSS, SRS, and SDS. Thresholds for
defect scoring were based on a normal database derived from
the Japanese Society of Nuclear Medicine working group
Events During Follow-Up
The endpoints of the J-ACCESS-3 study were major
cardiac events comprising cardiac death, sudden cardiac death,
non-fatal MI, and hospitalization to treat HF. Sudden death
was defined as death of unknown cause at 24 hours after
occurrence. These major cardiac events were confirmed at each
institution based mainly on medical charts, along with written
questionnaires and telephone interviews. During the 3-year
follow-up, 4.8% and 3.6% of the patients were lost to the
JACCESS and J-ACCESS 3 studies, respectively.
The Institutional Review Boards of all participating
hospitals approved both the J-ACCESS and J-ACCESS-3
studies, both of which also complied with the Ethical
Guidelines for Epidemiological Research in Japan.14 All patients
provided written informed consent to participate in the study.
Data are expressed as mean ± standard deviation (SD) or
median and ranges for non-normal distribution. Continuous
variables were compared using T tests and analyses of
variance. Categorical data between groups were compared
using v2 tests. Since C-reactive protein (CRP) was one of the
major independent prognostic factors at a threshold of 0.3 mg/
mL,13 the frequency of high CRP was also examined in each
group. Calculated differences in cardiac event risks among
groups within the three models were compared using Kaplan–
Meier survival analysis. Appropriate thresholds for three
models were determined from the three risk groups of patients
by analyzing receiver-operating characteristics (ROC) curves
and histograms; \ 3%/3 years (1%/year) for low-risk patients
and [ 9% for high-risk patients (corresponding to the lower
and upper quartiles of the event risks). All data were
statistically analyzed using JMP software version 12.2 (SAS
Institute Inc., Cary, NC, USA). A P value of \ 0.05 was
considered to indicate a significant difference.
Demographics of Patients
Table 1 summarizes the background conditions for
the model-derivation groups and the J-ACCESS-3
study. The validation population did not include any
patients with a history of either MI or
revascularization. The eGFR values in Model 2 and J-ACCESS-3
were 67.3 ± 30.7 and 29.0 ± 12.8 mL/min/1.73 m2
(P \ .0001), respectively. The SSS, SRS, and SDS
were lower in J-ACCESS-3 than in the Model 2
derivation populations (P \ .0001 for all).
Major Cardiovascular Events
Out of 526 patients 59 (11.2%) patients developed
cardiac events, and 13 (2.5%) had cardiac or sudden
death. The events in these 59 patients comprised HF
treated upon admission (n = 42) sudden death (n = 6),
cardiac death (n = 3), death due to HF upon admission
(n = 3), non-fatal MI (n = 2), non-fatal MI and HF upon
admission (n = 2), and non-fatal MI and subsequent
cardiac death (n = 1). We found lower values for LVEF
(52.1% ± 14.8% vs 62.7% ± 14.7%, P \ .0001) and
eGFR (25.0 ± 12.4 vs 29.4 ± 12.7 mL/min/1.73 m2,
P = .026), and higher values for EDV (113.9 ± 43.6 vs
88.1 ± 38.3 mL, P = .0004), ESV (58.1 ± 35.3 vs
37.0 ± 30.2 mL, P = .0003), SSS (3.7 ± 6.7 vs
1.6 ± 3.2, P = .046), and SRS (2.8 ± 6.0 vs 0.9 ± 2.4,
P = .040), in a group that developed HF as the first
event (n = 45) compared with a group that did not
develop events (n = 466). The SDS did not significantly
differ between these groups (1.0 ± 2.1 vs 0.8 ± 1.8,
P = ns).
Renal events of hemodialysis and peritoneal
dialysis developed in 45 (8.6%) and 4 (0.8%) patients,
respectively. Patients with eGFR \ 15 mL/min/1.73 m2
(n = 99) showed more frequent renal events including
40 (40.4%) with hemodialysis and 4 (4.0%) with
Distribution of Risk Values Calculated by Three Models
The median risk values were 3.3% (range
0.2%36.6%), 5.3% (0.25%-44.2%), and 5.0% (0.25%-44.5%)
for Models 1, 2, and 3, respectively, and were highest for
Model 2 (Models 1 vs 2, and 1 vs 3, both P \ .0001;
Model 2 vs 3 P = .0041). High correlation was observed
for risk values between Models 1, 2, and 3 showing Risk
by Model 2 = 1.5 ? 1.21 9 Risk by Model 1
(R2 = 0.92, P \ .0001) and Risk by Model
2 = 0.40 ? 1.03 9 Risk by Model 3 (R2 = 0.97,
P \ .0001).
Estimation of Cardiac Event Risk by Models
1, 2, and 3 with Respect to eGFR
Table 2 shows parameter estimates for the three
JACCESS risk models.10,11 Figure 1 graphically shows
an example of differences in estimated risk in a 60-year
old patient with LVEF 50%. Event risk determined by
Model 1 was not influenced by the eGFR values defined
in the model, whereas calculated risk negatively
depended on eGFR in Models 2 and 3. These graphs also
indicated that the estimated risk was two-fold higher for
patients with high ([ 7) compared with low (B 7) SSS.
Furthermore, complication with diabetes mellitus also
increased risk two-fold.
ROC Analysis for Predicting Cardiac Events
Areas under the ROC curve (AUC) were 0.66 (95%
confidence of intervals [CI]: 0.58-0.73), 0.67
(0.590.73), and 0.66 (0.58-0.73) for Models 1, 2, and 3,
respectively, indicating that the models similarly
predicted low to high major cardiac event. Thresholds were
determined from the highest value for
sensitivity ? specificity - 1 at 4.3, 5.2, and 4.5% risk for
Models 1, 2, and 3, respectively.
Survival Analysis and Event Rates in Three
group was clearly separated by the three models among
those with eGFR C 15 mL/min/1.73 m2. The actual
event rate was the lowest among the low-risk (\ 3%)
patients in Model 2 (3.1%). In contrast, none of the three
models could stratify patients with eGFR \ 15 mL/min/
1.73 m2 (n = 99) into three risk groups (Figure 3C).
Frequency of High CRP in Risk Groups
The CRP values ranged from 0 to 10.1 (median, 0.1;
mean, 0.42 ± 0.98) mg/dL. Analyses of ROC curves
showed that the optimal cutoff to obtain the highest
sensitivity ? specificity - 1 was 0.3 (AUC = 0.62,
P = 0.0029). Figure 4 shows the frequency of high
CRP ([ 0.3 mg/mL) among patients at low,
intermediate, and high risk using Models 1, 2, and 3. The
frequency of high CRP was increased among patients
with eGFR C 15 mL/min/1.73 m2 depending on risk for
all models (P = .0004, .0003, and .0045 for Models 1, 2,
and 3, respectively). However, the frequency of elevated
CRP was high in all groups of patients with eGFR \
15 mL/min/1.73 m2 regardless of model type.
The present study demonstrated the validity of the
event risk models created by the J-ACCESS multi-center
cohort study and presently applied in Japan.10,11 The
estimation of major cardiovascular events has practical
roles for deciding optimal treatment strategies for
patients with suspected CAD.1,3,17 Actual event rates
were higher than the risk predicted by the model created
without eGFR but including eGFR improved risk
assessment by the models. However, the incidence of
cardiac events was higher regardless of predicted risk in
patients with eGFR \ 15 mL/min/1.73 m2, indicating a
limitation of the risk model for such patients.
J-ACCESS Risk Model
The J-ACCESS risk model validated herein was the
first risk model created in Japan to estimate major
cardiac events using quantitative gated stress-rest MPI.18
Based on multivariable logistic analysis, the model
included the four variables of age, LVEF, SSS, and
diabetes as predictor,10 and eGFR was subsequently
added.8,11 Because SDS did not reach statistical
significance in the multivariable analysis, it was not adopted
in the model. Since respectively categorizing SSS and
eGFR into four and five classes was considered
clinically practical, risk calculation software that included
these categorical variables was also created for clinical
applications. The uniqueness of these risk models was
that a multivariable logistics model provided major
cardiac event risks (%) for 3 years. Therefore,
agreement between the predicted risk and actual event rates
was a concern and required validation. The
modelderivation and validation populations differed insofar as
the latter group had lower eGFR, SSS, and SRS. That is,
our model was applied to patients with different
demographics. The safety of pharmacological stress in
patients with CKD was also confirmed.
Validity of the Risk Models
The validation study showed that any of the three
J-ACCESS risk models could stratify patients into
being at low, intermediate, or high risk of developing
major cardiac events. However, another important
aspect of the model was the identical predicted and
actual event rates (%). The risk of events predicted by
Model 1 was underestimated compared with actual
event rates (1%-3% vs 5.4% and 3%-9% vs 14.9%),
whereas Model 2 including eGFR predicted 1%-3%
and 3%-9% risk of events, compared with the actual
rates of 3.1% and 9.9%, respectively. These outcomes
were still slightly higher than the upper limit of the
predicted values with eGFR. Although Models 2 and 3
tended to be similar, the risk of events predicted by
Model 2 was 3.1%, which was lower than the 4.5%
predicted by Model 3 for low-risk patients. Therefore,
although the J-ACCESS risk model including eGFR
improved risk estimation (%/3 years), the actual
outcomes for patients with CKD remained underestimated
to some degree.
Estimated GFR as a Predictor of the Model
Predictive accuracy was quite different depending
on eGFR [ 15 (CKD stages 3a, 3b and 4 in the present
study) or \ 15 mL/min/1.73 m2 (stage 5), which was
selected because this threshold is a significant predictor
of survival in patients with CKD.13 Although the actual
event rate was near the upper limit or slightly higher
than the predicted rates in patients with C 15 mL/min/
1.73 m2, the rates were 3%-5% and 9%-13% for
lowand intermediate-risk patients, respectively, whose
predicted risk was apparently underestimated when eGFR
was \ 15 mL/min/1.73 m2. A comparison of Models 2
and 3 showed that Model 2 estimated lower risk for
lowrisk patients, and that the difference in outcome events
among the risk groups tended to be larger than that of
Model 3. This could be explained by differences
between the numerical and categorical applications of
variables; eGFR \ 30 mL/min/1.73 m2 was categorized
into one category in Model 3, but continuous in Model
2. These model structures might have caused the larger
difference in calculated risk at lower eGFR.
High-Risk Patients with Low eGFR
The underestimated risk among patients with CKD
stage 5 (eGFR \ 15 mL/min/1.73 m2) is an important
limitation of the present risk model. Since few patients
(3%) had stage 5 CKD (end-stage) in the
modelderivation group, the predictive accuracy of the model
might be less accurate with respect to this validation
group. Although the present study could not determine
the pathophysiological reasons for this phenomenon,
high CRP or an inflammatory reaction might have been
associated, which has also been noted in previous
studies. Potentially critical elements in the initiation,
progression, and rupture of plaque have become evident,
and anti-inflammatory and antioxidant therapies have
been sought.19 In fact, the distribution of event outcomes
and positive CRP were related in the present study
(Figures 3, 4), as CRP was elevated at the initiation of
dialysis treatment among some patients with CKD and it
is a predictor of cardiac events.20,21 Analysis of
relationships among metabolic syndrome, high-sensitivity
CRP, and CKD revealed that CRP is a powerful risk
factor for arterial stiffness, cardiovascular events, and
mortality.22 In the present validation population, the
high proportion of patients with severe HF requiring
hospitalization might be a result of these complex
backgrounds. Moreover, when renal events were
analyzed during the 3-year follow-up, 44 of 99 patients
required either hemodialysis or peritoneal dialysis.
Progression to renal insufficiency could exacerbate
cardiac function, leading to chronic HF. However, the
long-term effects of hemodialysis are beyond the scope
of the present study and will require a follow-up
investigation. Another factor might be associated with
sympathetic derangement in patients with severe CKD.
Cardiac 123I-metaiodobenzylguanidine uptake was low
among patients with low eGFR, and this contributed to
the high cardiac mortality risk among patients with
The present study included patients with CKD
stages 3 to 5, whereas the model-derivation population
included stages 1 to 5. Although stages 1 and 2 were not
included in the validation population, including low-risk
patients with an annual event rate of \ 1% (21% and
25% of patients determined by Models 2 and 3,
respectively), a wide range of risk was evaluated. A
recent validation of J-ACCESS Model 2 also found that
an event risk of 10% separated the prognosis of patients
with a mean eGFR of 67.4 ± 24.3 mL/min/1.73 m2.24
Therefore, although the present study focused on
patients with CKD, the J-ACCESS model could apply
even to patients with normal eGFR. In addition, further
validation studies are needed to clarify the relevance of
including additional variables such as CRP to enhance
Three J-ACCESS models were applied to assess
risk of major cardiac events among CKD patients in the
J-ACCESS-3 study. Although all risk models for major
cardiac events could stratify outcomes of patients with
CKD, the model that included eGFR was more
appropriate for these patients. Risk stratification was effective
for patients with stages 3a, 3b, and 4 CKD (eGFR C 15
mL/min/1.73 m2), whereas patients with stage 5 CKD
(eGFR \ 15 mL/min/1.73 m ) are potentially at high
risk across all estimated risk values.
We are grateful to CMIC PMS Co. Ltd., Osaka, for
statistical analysis of the data. The authors thank Norma
Foster for editorial assistance.
All authors declare no conflict of interest to disclose.
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