Academic Editors: Gianluca Rigatelli and Arrigo F.G. Cicero
Background: Elevated concentrations of low-density lipoprotein
cholesterol (LDL-C) are an important cause of recurrent cardiovascular events.
This study aimed to describe the distribution and achieved concentrations of
LDL-C among patients with myocardial infarction (MI), percutaneous coronary
intervention (PCI), stroke, or transient ischaemic attack (TIA) in Hong Kong.
Methods: Patients with a lipid test from a public hospital were
identified from the Clinical Database and Analysis Reporting System of the Hong
Kong Hospital Authority. Among patients with an inpatient hospitalization for MI,
PCI, stroke or TIA, between 2003 to 2016, the distribution of LDL-C levels and
the number (%) of patients achieving an absolute concentration of LDL-C
Despite the availability and affordability of statins, a large proportion of
high risk individuals in Asia have low-density lipoprotein cholesterol (LDL-C)
levels that remain above recommended treatment targets which contributes to the
burden of atherosclerotic cardiovascular disease (ASCVD) [1, 2, 3]. Current
guidelines from the American College of Cardiology/American Health Association
and European Society of Cardiology/European Atherosclerosis Society (ESC/EAS)
emphasize achieving an absolute LDL-C
Further reductions in LDL-C are now obtainable with the addition of ezetimibe or proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors to statin therapy. These nonstatin lipid-modifying drugs improve cardiovascular outcomes in secondary prevention of cardiovascular events [6, 7, 8], and are recommended for patients who do not achieve LDL-C targets on maximally tolerated doses of statins [4]. Guideline recommended nonstatin therapies have long been available in Hong Kong: ezetimibe (approved July 2003), evolocumab (approved May 2016), and alirocumab (approved October 2016) [9]. However, underuse of both statin and nonstatin lipid-modifying drugs in people with acute coronary syndrome (myocardial infarction (MI) or unstable angina) is a challenge in Hong Kong public hospitals: research conducted between 2009 to 2015 indicates that 25% of individuals with acute coronary syndrome did not receive statins by discharge and there was limited use of ezetimibe [10].
Emerging evidence suggests that achieving LDL-C treatment targets is also
associated with improve cardiovascular outcomes in individuals with recent
percutaneous coronary intervention (PCI) [11] and stroke or transient ischaemic
attack (TIA) [12, 13]. In the Stroke Prevention by Aggressive Reduction in
Cholesterol Levels (SPARCL) trial, atorvastatin 80 mg daily compared with placebo
reduced the risk of fatal or nonfatal stroke and overall vascular events in
individuals with a recent stroke or TIA and an LDL-C of 2.6–4.9 mmol/L [12, 14].
Targeting an LDL-C
We did a cohort study using electronic health record data from the Hong Kong Hospital Authority. The Hospital Authority is the statutory body responsible for public healthcare in Hong Kong; its hospitals have about 80% of the region’s hospital beds [15]. We extracted data from the Clinical Data and Administrative Reporting System (CDARS), to initially identify a cohort of patients who had a lipid test from 1 January 2004 to 3 March 2014 at the Queen Mary Hospital—the major acute care and specialist outpatient hospital within the Hong Kong West Cluster. The catchment area of the Queen Mary Hospital is the central and western part of Hong Kong Island. This geographic region includes approximately 7% of the Hong Kong population. CDARS contains records of diagnoses, medication dispensing, hospital admission and discharge, procedures, demographics, and laboratory tests. This study was approved by the Hong Kong West Cluster/HKU Institutional Review Board (Reference Number UW 14-334).
We defined the index date (time zero) as the earliest discharge date of an
inpatient diagnosis or procedure diagnosis ranking in the first through third
position, for MI, stroke or TIA, or PCI, between 1 January 2003 to 31 December
2016. Next, we excluded patients with a date of death on or before the index
date, those who did not have at least one LDL-C test result during the index
hospitalization (admission date to discharge date inclusive) or during 365 days
after hospital discharge, and those aged
We used several time windows to assess baseline variables (Supplementary Table 1). We used a one year look-back window to assess most baseline diagnoses, medication use, and laboratory tests. Exceptions included a prior history of MI, stroke or TIA, PCI, and coronary artery bypass graft surgery (CABG), for which we looked back until the start of all diagnosis and procedures data availability. We included descriptive variables, those required to calculate the TIMI (Thrombolysis in Myocardial Infarction) Risk Score for Secondary Prevention (TRS 2ºP), and those judged to be important confounders (Supplementary Table 1).
We inspected the distribution of each laboratory test and removed results with
missing numeric values. Because LDL-C is calculated according to the Friedewald
formula, we excluded any test results with values less than zero or reported as
unfit for calculating LDL-C due to triglycerides
For patients with multiple index diagnoses or procedures, we classified the index event for each patient into one of three mutually exclusive groups in hierarchical order: first as MI, second as stroke or TIA, and third as PCI.
Medication classes were identified using British National Formulary sections and specific medications were identified using drug item codes (Supplementary Table 1). Statins were classified into low-, moderate-, and high-intensity according to their average anticipated reduction in LDL-C [16]. We defined nonstatin lipid-modifying drugs as ezetimibe, fibrates, bile acid sequestrants, and PCSK9 inhibitors.
The TRS 2ºP uses nine clinical risk factors to estimate the
risk of cardiovascular death, myocardial infarction, and ischaemic stroke in
patients with a history of acute coronary syndrome [17]. Risk categories have
been defined as low (0 to 1 risk factors), intermediate (2 risk factors), and
high (
We defined the hypertension risk factor as having a diagnosis of hypertension
based on diagnosis codes or a baseline prescription for any antihypertensive
medication. Similarly, we defined the diabetes mellitus risk factor as having a
diagnosis of diabetes mellitus or a prescription for an antidiabetic medication.
Each TRS 2ºP risk factor contributed a weight of one, and the
total number of risk factors at baseline were summed. The remaining risk factors
that are not derived from other variables are the same as those in
Supplementary Table 1 (e.g., smoker, peripheral artery disease). We
described TRS 2ºP risk factors on a continuous scale and
categorically (0, 1, 2, and
Baseline (in-hospital) LDL-C was the primary exposure of interest and its
distribution was presented continuously and categorically. We classified LDL-C in
two ways. First, we created five categories:
The follow-up window for all outcomes was defined as one year after hospital
discharge. Follow-up LDL-C levels were assessed in five time windows: 30, 90,
180, and 365 days; and any time during the one year follow-up window. If a
patient had multiple LDL-C results during the window, we selected the latest
results farthest away from index date. For each follow-up window, we described
the distribution of LDL-C for the overall cohort and stratified by index event.
For patients with at least one baseline and one follow-up LDL-C level, we
calculated the percent reduction in LDL-C using the latest LDL-C level one year
after hospital discharge, defined as
Patient characteristics and LDL-C are presented as numbers and percentages,
means and standard deviations (SD), or medians and interquartile ranges (IQR), as
appropriate. We visualized the distribution of LDL-C within each follow-up window
according to index diagnosis using box plots. Achievement any time after
discharge of LDL-C
After application of the exclusion criteria, we included a total of 18417 patients with a diagnosis of MI, stroke or TIA, or PCI, between 1 January 2003 to 31 December 2016 (Fig . 1). Baseline characteristics of the included patients are shown Table 1. The majority of patients were male, Chinese, diagnosed with an index stroke or TIA while 56.4% had a diagnosis of hypertension and 31.9% had a diagnosis of diabetes. By hospital discharge 66.8% were prescribed a lipid-modifying drug. Statins were the most prescribed class of lipid-modifying drug and 70.0% of patients prescribed statins received a moderate-intensity statin.
Flowchart of patients who had a lipid test at the Queen Mary Hospital. MI, myocardial infarction; PCI, percutaneous coronary intervention; TIA, transient ischaemic attack.
Characteristic | Patients (n = 18417) | |
Demographics | ||
Male (%) | 11102 (60.3) | |
Age, years (mean (SD)) | 70.0 (12.9) | |
Age |
7429 (40.3) | |
Nationality (%) | ||
Chinese | 17170 (93.2) | |
Other | 462 (2.5) | |
Missing | 785 (4.3) | |
Hospital Authority cluster of residence (%) | ||
HKW | 12912 (70.1) | |
HKE | 2518 (13.7) | |
KW | 1174 (6.4) | |
KE | 588 (3.2) | |
NTE | 431 (2.3) | |
NTW | 381 (2.1) | |
KC | 349 (1.9) | |
Unknown | 64 (0.3) | |
Index event | ||
Myocardial infarction | 3637 (19.7) | |
PCI | 4096 (22.2) | |
Stroke or TIA | 10684 (58.0) | |
Year of diagnosis (%) | ||
2003 | 349 (1.9) | |
2004 | 1366 (7.4) | |
2005 | 1453 (7.9) | |
2006 | 1411 (7.7) | |
2007 | 1455 (7.9) | |
2008 | 1506 (8.2) | |
2009 | 1573 (8.5) | |
2010 | 1596 (8.7) | |
2011 | 1666 (9.0) | |
2012 | 1628 (8.8) | |
2013 | 1589 (8.6) | |
2014 | 1104 (6.0) | |
2015 | 902 (4.9) | |
2016 | 819 (4.4) | |
Length of index admission, days (mean (SD)) | 7.7 (14.7) | |
Laboratory tests | ||
LDL-C, mmol/L (mean (SD)) | 2.8 (1.0) | |
Total cholesterol, mmol/L (mean (SD)) | 4.7 (1.1) | |
HDL-C, mmol/L (mean (SD)) | 1.2 (0.4) | |
non–HDL-C, mmol/L (mean (SD)) | 3.5 (1.1) | |
Triglycerides, mmol/L (median [IQR]) | 1.2 [0.9, 1.6] | |
MDRD eGFR (mL/min/1.73 m |
69.6 (26.0) | |
Diagnoses and procedures | ||
Hypertension (%) | 10388 (56.4) | |
Diabetes mellitus (%) | 5876 (31.9) | |
Heart failure (%) | 1585 (8.6) | |
Smoking (%) | 342 (1.9) | |
Kidney disease (%) | 981 (5.3) | |
Myocardial infarction (%) | 471 (2.6) | |
PCI (%) | 531 (2.9) | |
CABG (%) | 272 (1.5) | |
Stroke or TIA (%) | 1156 (6.3) | |
Peripheral artery disease (%) | 270 (1.5) | |
Medications | ||
Lipid-modifying drug (%) | 12295 (66.8) | |
Statin (%) | 12082 (65.6) | |
Nonstatin lipid-modifying drug (%) | 690 (3.7) | |
Statin and nonstatin lipid-modifying drug (%) | 481 (2.6) | |
Fibrate (%) | 599 (3.3) | |
Ezetimibe (%) | 72 (0.4) | |
PCSK9 inhibitor (%) | 1 (0.0) | |
Bile acid sequestrant (%) | 22 (0.1) | |
Antiplatelet drug (%) | 15535 (84.4) | |
Antihypertensive (%) | 15613 (84.8) | |
Antidiabetic drug (%) | 5866 (31.9) | |
Statin drug (%) | ||
Atorvastatin | 2103 (17.4) | |
Fluvastatin | 89 (0.7) | |
Pravastatin | 6 (0.0) | |
Rosuvastatin | 1281 (10.6) | |
Simvastatin | 8603 (71.2) | |
Statin intensity (%) | ||
Low | 1859 (15.4) | |
Moderate | 8463 (70.0) | |
High | 1760 (14.6) | |
TRS 2°P risk factors | ||
Number (median [IQR]) | 2.0 [1.0, 3.0] | |
0 risk factors | 1201 (6.5) | |
1 risk factor | 4804 (26.1) | |
2 risk factors | 5576 (30.3) | |
6836 (37.1) | ||
CABG, coronary artery bypass graft surgery; eGFR, estimated glomerular filtration rate; HDL-C, high-density lipoprotein cholesterol; HKW, Hong Kong West; HKE, Hong Kong East; IQR, interquartile range; KC, Kowloon Central; KE, Kowloon East; KW, Kowloon West; LDL-C, low-density lipoprotein cholesterol; MDRD, Modification of Diet in Renal Disease; non–HDL-C, non–high-density lipoprotein cholesterol; NTW, New Territories West; NTE, New Territories East; PCI, percutaneous coronary intervention; PCSK9, Proprotein Convertase Subtilisin/Kexin type 9; SD, standard deviation; TIA, transient ischaemic attack; TRS 2ºP, TIMI (Thrombolysis in Myocardial Infarction) Risk Score for Secondary Prevention. |
For each time window, the distribution of LDL-C stratified by index event is
shown in Fig. 2. Most patients had an LDL-C result available at hospital
discharge and during follow-up (Supplementary Table 2). The proportion
of patients with a baseline LDL-C was 75.9% among patients with MI, 52.7% with
PCI, and 83.0% with stroke or TIA. Overall, 1849 (10.0%) of patients had an
LDL-C
Distribution of low-density lipoprotein cholesterol concentrations stratified by index event. We assessed low-density lipoprotein concentrations at baseline (during the index hospitalization), and at 30, 90, 180, and 365 days after hospital discharge, or any time during one year of follow-up.
The number of patients with a hospital discharge LDL-C concentration
Number with LDL-C |
Number (%) with follow-up LDL-C | |
Overall | 11934 | 2214 (18.6) |
Stroke or TIA | 7981 | 1069 (13.4) |
Myocardial infarction | 2359 | 725 (30.7) |
PCI | 1594 | 420 (26.3) |
LDL-C, low-density lipoprotein cholesterol; PCI, percutaneous coronary intervention; TIA, transient ischaemic attack. |
Table 3 presents the baseline characteristics and percent reduction of LDL-C
from baseline, stratified according to an LDL-C of 1.8 mmol/L by 365 days after
hospital discharge, after excluding 5654 patients missing a follow-up LDL-C test.
A larger proportion of patients who achieved an LDL-C of
Characteristic | |||
Male (%) | 3058 (66.6) | 4990 (61.1) | |
Age, years (mean (SD)) | 69.7 (12.3) | 68.2 (12.3) | |
Index event (%) | |||
Myocardial infarction | 1288 (28.1) | 1744 (21.3) | |
PCI | 1542 (33.6) | 2122 (26.0) | |
Stroke or TIA | 1761 (38.4) | 4306 (52.7) | |
Percent reduction in LDL-C from baseline (mean (SD)) | –35.5 (27.7) | –8.7 (35.4) | |
LDL-C, mmol/L (mean (SD)) | 2.5 (0.9) | 3.1 (1.0) | |
Total cholesterol, mmol/L (mean (SD)) | 4.3 (1.1) | 4.9 (1.2) | |
HDL-C, mmol/L (mean (SD)) | 1.1 (0.4) | 1.2 (0.4) | |
non–HDL-C, mmol/L (mean (SD)) | 3.2 (1.0) | 3.7 (1.1) | |
Triglycerides, mmol/L (median [IQR]) | 1.2 [0.9, 1.7] | 1.3 [0.9, 1.7] | |
MDRD eGFR (mL/min/1.73 m |
67.3 (25.9) | 69.9 (25.4) | |
Hypertension (%) | 2745 (59.8) | 4577 (56.0) | |
Diabetes mellitus (%) | 1916 (41.7) | 2718 (33.3) | |
Heart failure (%) | 468 (10.2) | 697 (8.5) | |
Smoking (%) | 125 (2.7) | 159 (1.9) | |
Kidney disease (%) | 317 (6.9) | 451 (5.5) | |
Myocardial infarction (%) | 148 (3.2) | 220 (2.7) | |
PCI (%) | 142 (3.1) | 289 (3.5) | |
CABG (%) | 103 (2.2) | 144 (1.8) | |
Stroke or TIA (%) | 242 (5.3) | 510 (6.2) | |
Peripheral artery disease (%) | 87 (1.9) | 110 (1.3) | |
Lipid-modifying drug (%) | 4032 (87.8) | 5658 (69.2) | |
Statin (%) | 4005 (87.2) | 5525 (67.6) | |
Nonstatin lipid-modifying drug (%) | 205 (4.5) | 381 (4.7) | |
Statin and nonstatin lipid-modifying drug (%) | 178 (3.9) | 251 (3.1) | |
Fibrate (%) | 177 (3.9) | 323 (4.0) | |
Ezetimibe (%) | 23 (0.5) | 44 (0.5) | |
PCSK9 inhibitor (%) | 0 (0.0) | 1 (0.0) | |
Bile acid sequestrant (%) | 6 (0.1) | 16 (0.2) | |
Antiplatelet drug (%) | 4261 (92.8) | 6923 (84.7) | |
Antihypertensive (%) | 4178 (91.0) | 7078 (86.6) | |
Antidiabetic drug (%) | 1942 (42.3) | 2735 (33.5) | |
Statin drug (%) | |||
Atorvastatin | 728 (18.2) | 1033 (18.7) | |
Fluvastatin | 12 (0.3) | 45 (0.8) | |
Pravastatin | 1 (0.0) | 5 (0.1) | |
Rosuvastatin | 628 (15.7) | 525 (9.5) | |
Simvastatin | 2636 (65.8) | 3917 (70.9) | |
Statin intensity (%) | |||
Low | 542 (13.5) | 870 (15.7) | |
Moderate | 2694 (67.3) | 3856 (69.8) | |
High | 769 (19.2) | 799 (14.5) | |
TRS 2°P risk factors | |||
Number (median [IQR]) | 2.0 [1.0, 3.0] | 2.0 [1.0, 3.0] | |
0 risk factors | 162 (3.5) | 471 (5.8) | |
1 risk factor | 1052 (22.9) | 2332 (28.5) | |
2 risk factors | 1420 (30.9) | 2519 (30.8) | |
1957 (42.6) | 2850 (34.9) | ||
ABG, coronary artery bypass graft surgery; eGFR, estimated glomerular filtration rate; HDL-C, high-density lipoprotein cholesterol; IQR, interquartile range; LDL-C, low-density lipoprotein cholesterol; MDRD, Modification of Diet in Renal Disease; non–HDL-C, non–high-density lipoprotein cholesterol; PCI, percutaneous coronary intervention; PCSK9, Proprotein Convertase Subtilisin/Kexin type 9; SD, standard deviation; TIA, transient ischaemic attack; TRS 2ºP, TIMI (Thrombolysis in Myocardial Infarction) Risk Score for Secondary Prevention. |
Achieved LDL-C targets during follow-up, the distribution of LDL-C, and the
percent reduction in LDL-C according to index year are shown in Table 4. Despite
a similar percent reduction in LDL-C over the study period, the absolute mean
achieved LDL-C concentrations, and the proportion of patients achieving either an
LDL-C
Index year | Number with follow-up LDL-C | Number (%) with follow-up LDL-C |
Number with in-hospital and follow-up LDL-C | Number (%) with |
Number (%) with |
Mean (SD) follow-up LDL-C, mmol/L | Mean LDL-C % reduction |
2003 | 290 | 58 (20.0) | 44 | 5 (11.4) | 2 (4.5) | 2.64 (0.92) | –17.7 |
2004 | 777 | 173 (22.3) | 435 | 62 (14.3) | 31 (7.1) | 2.46 (0.87) | –14.4 |
2005 | 821 | 187 (22.8) | 526 | 68 (12.9) | 43 (8.2) | 2.50 (0.90) | –14.9 |
2006 | 790 | 175 (22.2) | 544 | 69 (12.7) | 47 (8.6) | 2.41 (0.82) | –13.9 |
2007 | 874 | 207 (23.7) | 623 | 64 (10.3) | 45 (7.2) | 2.38 (0.80) | –14.1 |
2008 | 973 | 299 (30.7) | 715 | 92 (12.9) | 66 (9.2) | 2.23 (0.77) | –17.7 |
2009 | 1100 | 369 (33.5) | 752 | 126 (16.8) | 86 (11.4) | 2.15 (0.72) | –20.0 |
2010 | 1138 | 455 (40.0) | 697 | 142 (20.4) | 109 (15.6) | 2.09 (0.77) | –21.3 |
2011 | 1258 | 490 (39.0) | 809 | 149 (18.4) | 116 (14.3) | 2.06 (0.74) | –20.8 |
2012 | 1247 | 506 (40.6) | 821 | 165 (20.1) | 123 (15.0) | 2.03 (0.71) | –20.8 |
2013 | 1197 | 545 (45.5) | 781 | 167 (21.4) | 141 (18.1) | 1.97 (0.71) | –22.6 |
2014 | 891 | 438 (49.2) | 507 | 102 (20.1) | 89 (17.6) | 1.93 (0.71) | –21.4 |
2015 | 752 | 336 (44.7) | 450 | 73 (16.2) | 66 (14.7) | 1.96 (0.67) | –15.4 |
2016 | 655 | 353 (53.9) | 425 | 63 (14.8) | 56 (13.2) | 1.86 (0.70) | –14.7 |
LDL-C, low-density lipoprotein cholesterol. |
Using a large cohort of Chinese individuals, we described LDL-C levels
in-hospital and one year after discharge, and report important clinical
characteristics such as the use of statin and nonstatin lipid-modifying drugs and
the TRS 2ºP. During one year of follow-up, 75% of patients did
not achieve an LDL-C
Our findings align with a previous study of patients with acute coronary
syndrome who underwent PCI in Hong Kong between 2009 to 2015. Wang et al.
[10] found that of these patients 11.3% received high-intensity
statins, 26.8% did not receive a statin, and only 0.2% received ezetimibe. The
proportion of patients with MI and PCI with a baseline and follow-up LDL-C
We were particularly interested in the availability of in-hospital and follow-up LDL-C levels; missing lipid test patterns could identify gaps in monitoring patient response to lipid treatment. When examining the availability of LDL-C tests at baseline and during follow-up, a similar number of patients had an LDL-C level during their index hospitalization, but the proportion with follow-up levels increased from around 55% in 2004 to 80% in 2016. Further investigation is needed to understand the delay in obtaining follow-up LDL-C levels as nearly 30% of patients did not have a measured LDL-C within one year of the index event. It is possible that a group of patients with missing LDL-C values transfer their care to the private sector, leave Hong Kong, or obtain a follow-up LDL-C after 12 months, and would thus have a missing follow-up LDL-C result in our analysis.
Differences in achieved LDL-C levels exist when comparing Hong Kong to other
countries. LDL-C levels during follow-up may have narrower distribution in our
cohort compared with data from the United Kingdom. About 1.8% of patients in
this study had LDL-C levels which remained
This study has several limitations. Although calculated LDL-C remains the primary target for lipid modification in clinical practice guidelines, it becomes more inaccurate at low LDL-C and high triglyceride values [5]. The assessment of lipid-modifying drug effectiveness using the Friedewald formula could be confounded in some individuals because of the lack of fitness of calculated LDL-C in these contexts. The TRS 2ºP has only been validated in patients following acute coronary syndrome, and not with a diagnosis of stroke or TIA, thus the risk predictors of TRS 2ºP may not be completely applicable to all patients in our cohort. Initial lipid test data were identified only for one hospital. The Queen Mary Hospital is an important referral hospital in Hong Kong, which could cause selection bias of more severe or complex cases. CDARS only includes data from the Hospital Authority, and thus excludes private healthcare data. For example, after discharge patients could obtain follow-up prescriptions and laboratory testing at private hospitals or clinics. Finally, selection bias may also occur for patients who die after hospital discharge and prior to their first follow-up LDL-C result. However, only 913 patients died and had no recorded follow-up LDL-C level, which represents only 16% of the patients with no follow-up LDL-C results. The eligibility criteria were limited to patients who had a lipid test at a single hospital and we did not differentiate haemorrhagic and ischaemic stroke in our inclusion criteria, resulting in a more heterogeneous group of patients with stroke. To address these limitations, our research group is currently conducting an up-to-date assessment of LDL-C target achievement in all patients diagnosed with ASCVD (i.e., ischaemic heart disease, ischaemic stroke, TIA, and peripheral vascular disease) in the Hospital Authority from 2010 to 2020, regardless of whether a lipid test has been measured.
Between 2003 to 2016, there was vast under-treatment of ASCVD with
lipid-modifying drugs in Hong Kong, with only 25% of patients in this study
achieving a contemporary target LDL-C of
CWS, EWC, and JEB conceptualized the study; JEB did the formal analysis, and VKCY and JZ cross-checked the analysis; CWS and EWC acquired the funding, provided resources, and supervised the study; JEB, VKCY, JZ, CSLC, CWS, ICKW, and EWC interpreted the results; JEB wrote the first draft and VKCY, JZ, CSLC, ICKW, and EWC critically reviewed and edited the manuscript for intellectual content.
Ethics approval for this study was obtained from the Hong Kong West Cluster/HKU Institutional Review Board, reference number UW 14-334. Informed consent for this study was waived by the institutional review board.
JEB was supported by the Hong Kong Research Grants Council as a recipient of the Hong Kong PhD Fellowship Scheme.
This research was funded by Amgen Asia Holdings Limited, Hong Kong SAR, China, grant number RS190135. The authors drafted the initial protocol based on the funder’s objectives. The protocol underwent review and revision following feedback from the funder, and was approved by both the funder and the authors. The funder had the opportunity to review the manuscript and provide non-binding comments prior to submission for publication.
CSLC, EWC, and ICKW report grants from Amgen. CSLC received a grant from Hong Kong Innovation and Technology Commission outside of the submitted work. All other authors declare no competing interests.
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