Anti-platelet Precision Medicine to Prevent Stroke Early Progression and Recurrence (PRECISE)
Conditions: Stroke
Sponsor: Asan Medical Center

      
 
 
                                           Confidential                             
 
 
Clinical Study Protocol 
 
 
 
 
 
Anti-platelet Precision Medicine to Prevent Stroke Early Progression and 
Recurrence (PRECISE) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Confidentiality Statement 
This document contains confidential information that must not be disclosed to anyone other than 
the principal investigator, investigators, the IRB and national regulatory authorities without prior 
written consent of the sponsor, except to obtain informed written consent to participate in the 
study from those providing the information of what is intended to be observed in the study. 
Protocol Number 
PRECISE 
Protocol Version 
3.1 
Version Date 
July 23, 2018 
Study Center 
Asan Medical Center and 21 Other  
Institutions 
Study Coordinator 
Dong-Wha Kang, Dept. of Neurology, Asan  
Medical Center 

      
 
 
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※ PROTOCOL SYNOPSIS 
Study title 
Anti-platelet Precision Medicine to Prevent Stroke Early Progression and 
Recurrence (PRECISE) 
Study phase and 
design 
Pragmatic, 
multi-center, 
non-interventional, 
non-random 
trial 
based 
on 
prospective observational study 
Study center 
Asan Medical Center and 21 other institutions 
Study coordinator 
Dong-Wha Kang of Department of Neurology, Asan Medical Center  
Study sponsor 
Dong-Wha Kang of Department of Neurology, Asan Medical Center 
Study funder 
Chong Kun Dang Holdings 
Study objectives 
Primary objectives: To predict the clinical prognosis according to the antiplatelet 
treatment regime (aspirin as first-line treatment or in combination with 
clopidogrel), develop an AI that will search for and retrieve similar cases to each 
patient, and assess benefits of the technology: 
1) To establish a stroke clinical-imaging library (big data) and develop Deep 
Learning-based AI that understands the relationship between anti-platelet 
agents and prognosis (progression or recurrence). AI will present the 
probability of stroke progression or recurrence following each treatment 
regime. AI will also help physicians make treatment decisions by searching 
for and retrieving existing cases with similar clinical conditions to the patients 
concerned. 
2) To prove AI’s merit in predicting prognosis by applying it to different patient 
groups. 
 
Secondary objective: To analyze practical results of antiplatelet agents: 
The aspirin alone group and the clopidogrel plus aspirin group will be compared 
against each other directly to help find the link between early progression and 
recurrence of stroke. Although this is a non-randomized trial, different statistical 
methodologies, including propensity score matching (PSM) should address 
confidence issues.   
Study subjects  
 
Acute ischemic stroke patients: 
Transient ischemic attack with confirmed acute ischemic stroke by brain imaging 

      
 
 
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Inclusion criteria 
1) Male and/or female subjects who are aged 19 or over. 
2) Patients with acute noncardiac stroke or transient ischemic attack within 72 
hours of the onset (in the case of a transient ischemic attack, presence of 
ischemic/ischemic lesion on DWI or PWI). 
3) Patients whose informed consent document within 72 hours of onset was 
signed and submitted. 
4) Patients who were treated with aspirin alone or aspirin plus clopidogrel 
resinate following stroke. 
Exclusion criteria 
1) Patients who need anticoagulants for cardiac ischemic stroke or other 
reasons. 
2) Patients who suffered severe stroke (National Institutes of Health Stroke 
Scale> 16). 
3) Patients who received emergency remission therapies such as tPA and 
thrombolysis. 
4) Patients with neurological deterioration prior to signing an informed written 
consent document. 
5) Patients who have undergone patency procedures (surgery or stent 
insertion) in the cerebrovascular or carotid arteries following stroke or are 
expected to do so. 
6) Patients who are scheduled to undergo major surgery. 
7) Patients who developed stroke during procedure/surgery. 
8) Patients with recent history (in the past three months) of cerebral 
hemorrhage. 
9) Patients with active internal bleeding. 
10) Patients with severe anemia (Hb <10 g / dL) or bleeding tendency (platelet 
<100,000 / uL or PT-INR> 1.7). 
11) When a patient’s life expectancy is less than 6 months due to other systemic 
disease.  
Number of target 
study subjects 
 
Aspirin alone 
group 
Aspirin + 
Clopidogrel 
resinate group 
Total No. of 
target subjects 
No. of subjects  
1,000 
1,000 
2,000 
Study duration 
1)  Study duration: Approximately 36 months from IRB approval (subject to 
change depending on subject enrollment speed) 
2) Study duration for each subject: 90 days (± 15 days) 
Study drug and 
dose 
Study drug 
Route of administration/dose 
Aspirin (monotherapy or 
concomitant therapy) 
75~100mg once per day, initial loading dose of 
300~500mg/d is allowed 

      
 
 
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Clopidogrel resinate 
(Concomitant therapy) 
75mg once per day, initial loading dose of  
300mg/d is allowed 
Study description 
This is a pragmatic, multi-center, non-interventional, non-randomized prospective 
observational study. 
 
 
Study procedures 
This is a prospective study of patients with acute stroke or transient ischemic 
attack within 72 hours of symptom onset. It is to mainly observe the patients’ 
prognosis following the prescription of clopidogrel resinate and aspirin, collect 
relevant data and create big data for stroke. Based on this data, an AI, using 
various advanced statistical methodologies and deep learning techniques will be 
developed, and offer information regarding stroke prognosis by extracting 
markers that are characteristic of the relationship between stroke and the study 
drug.  
 
These analyses and results will include information on which drug regimen will 
better prevent the progression or recurrence of stroke by considering individual 
patient conditions. This is a pragmatic trial based on the prescription and 
treatment processes of routine clinical practice. Thus, there is no major restriction 
and with only the minimum exclusion criteria in place, it does not hinder usual 
clinical practices. Therefore, selecting and changing a patient’s antiplatelet 
agents should be a rational medical judgment made by the patient's attending 
physician. The study will proceed without any major change in the sequence of 
routine clinical examinations, prescriptions, treatments, observations, etc. 
Provided, the process of storing and analyzing relevant information will be added 
to each study procedure in accordance with study methodologies and conditions 
no other special efforts or limitations will be required. 
 
The data will be collected prospectively, and the AI will generate brain imaging 
data and prognostic indicators for 3-months after stroke has occurred. The 
performance of the AI will be verified with independent test sets. 
Dropout criteria 
Because the subjects will receive usual stroke care practice, there will be no 
subject withdrawal or dropout due to issues related to the study description and 
design. 
However, if a research subject withdraws his/her consent to participate in the 
study (informed consent to have his/her personal information utilized), 
participation of the research subject will be suspended, and the data concerned 

      
 
 
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will not be used in the study. 
Endpoints 
Primary study endpoints 
AI will learn and predict the occurrence of the following outcome variables (up to 
3 months after stroke onset) according to the antiplatelet regimen (aspirin alone, 
or aspirin plus clopidogrel). An independent investigator, without knowledge of 
individual patient treatment regimens, will evaluate the same outcome variables 
separately and compare the results with those predicted by the AI: 
1) Neurological deterioration 
2) New ischemic stroke 
3) Symptomatic hemorrhagic transformation of an ischemic stroke 
4) Symptomatic intracranial hemorrhage 
5) Myocardial infarction 
6) Coronary revascularization without myocardial infarction 
7) Major hemorrhage other than intracranial hemorrhage (life threatening or 
non-life-threatening) 
8) Minor hemorrhage other than intracranial hemorrhage 
9) Ischemic vascular death 
10) Hemorrhagic vascular death 
11) Other serious adverse events 
 
Secondary study endpoints 
A direct comparison between the aspirin alone group and the aspirin and 
clopidogrel combination therapy group for the incidence of 11 outcome variables 
evaluated by an independent investigator at the primary endpoints will be 
conducted.  
Statistical 
Methodology 
General principle 
All the enrolled study subjects whose results are confirmed will be subject to 
analysis, and they will be selected and classified according to the study 
methodologies and objectives prior to analysis. During the study period, data will 
be regularly checked and managed so that the number of datasets and their 
levels will be maintained appropriately. 
 
Analyses of endpoints 
Analysis of primary endpoints 
1) The stroke clinical and imaging library (big data), that includes all the 

      
 
 
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clinical/imaging information related to clinical prognoses, will be established, 
and based on a deep learning algorithm, AI that has learned the relationship 
between antiplatelet agents and the following prognostic information will be 
developed. 
2) A probability of prognosis according to each treatment option prior to using 
antiplatelet agents will be offered. This information will help physicians select 
an antiplatelet agent by searching for and retrieving similar cases that match 
each patient. 
3) The stroke clinic and imaging library (big data) regarding the effect of 
antiplatelet agents that are being prescribed mainly to stroke patients in the 
clinical setting and the prognostic information of the patients concerned will 
be constructed. The relationship and prognostic features of antiplatelet 
agents in preventing early progression and recurrence of stroke will be 
extracted and analyzed from the “Big Data.” 
4) The development of AI using deep learning techniques will provide the basis 
for analysis of internal and external variables of stroke. This technique will 
change the model composition in line with the features and numbers 
extracted from the data. The depth and structure of the model will segment 
and materialize the characteristics of the target subjects and will be 
accompanied by the optimal design and verification processes of the model 
to simultaneously consider clinical/image information. 
5) The research analysis using the trained AI that will be developed will need to 
have its results clearly verified as to their quality/accuracy. The delivered 
outcome will be used directly or indirectly by physicians, but the performance 
and reliability of the results that will be generated are of significant 
importance. Therefore, the AI will learn and have its performance assessed 
based on the data that will continue to accumulate throughout this study. 
However, because of the features of deep learning technology, training and 
verification, using the same data may cause major issues such as overfitting. 
Therefore, a new dataset will be created to evaluate the performance of the 
AI. 
 
Analysis of secondary endpoints 
1) The propensity score matching (PSM) technique will be used to select either 
the aspirin monotherapy, or the clopidogrel resinate and aspirin combination 
therapy group which have matched important clinical/imaging parameters 
that affect the prognosis of stroke. 

      
 
 
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2) Compare the prognosis of each treatment group to determine which 
prescription method is superior.