Endocrine DiseaseNCT07512609
Environment, Inflammation and Metabolic Diseases Study
An observational study of Endocrine Disease and Metabolic Disorders, run by Qifu Li at 1 site in China.
Trial summary
The aim is to establish an effective and practical early warning model for endocrine and metabolic diseases based on an environmental-gene-protein panoramic network, to uncover new mechanisms underlying the onset and progression of these diseases, and to screen for novel therapeutic targets. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Endocrine Disease, Metabolic Disorders, Hypertension
- What is being tested?
- observe
- How many people
- 8,000 participants
- Where
- 1 siteChina
- Study dates
- 25 Dec 2020to 31 Dec 2026
- How long will I take part?
- 5 Years
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: This study aims to establish a specialized resource database-the Chongqing Environment, Inflammation, and Metabolic Diseases Study (EIMDS). The cohort will include approximately 8,000 community-based individuals who have been followed up for over 10 years. Clinical, biochemical, and endpoint event assessments will be conducted every two years, along with the collection of blood and urine specimens
Who may be able to join
- All individuals who voluntarily participated in the physical examination
Who cannot join
- Participants with incomplete data
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
The First Affiliated Hospital of Chongqing Medical University
Chongqing
Yunyan Liao, MD, 15823939745, 2215133087@qq.com
About this study
The aim is to establish an effective and practical early warning model for endocrine and metabolic diseases based on an environmental-gene-protein panoramic network, to uncover new mechanisms underlying the onset and progression of these diseases, and to screen for novel therapeutic targets.
Read the detailed description
This study aims to establish a specialized resource database for metabolic diseases-the Chongqing Environment, Inflammation, and Metabolic Diseases Study (EIMDS). The cohort will include approximately 8,000 community-based individuals who have been followed up for over 5 years, with clinical, biochemical, and endpoint event assessments conducted every two years, along with the collection of blood and urine samples. Based on the EIMDS cohort,this study will explore the risk factors for endocrine and metabolic diseases from a population perspective. Furthermore, by employing technologies such as whole-transcriptome sequencing, proteomics and phosphoproteomics, ATAC-seq, and single-cell sequencing,this study aim to elucidate the molecular mechanisms underlying endocrine and metabolic diseases and identify potential drug targets.
- Being tested
- observe
- Keywords
- Endocrine Disease, Metabolic Disorders, Hypertension, Diabetes Mellitus
- Medical subject headings
- Endocrine System Diseases, Metabolic Diseases, Hypertension, Diabetes Mellitus
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
observeOther
A single observational cohort of study participants undergoing baseline biochemical screening for autonomous aldosterone secretion (AAS). No experimental interventions or treatments are administered. All participants receive standard clinical care and undergo standardized baseline assessments, including measurement of plasma aldosterone concentration (PAC) and plasma renin concentration (PRC) for AAS classification, as well as collection of demographic, clinical, biochemical, anthropometric data and biospecimens for proteomic analysis.
| Study group | Role | What they receive |
|---|---|---|
| hypertension group | Participants with hypertension Receives: Other: observe | |
| DM group | Participants with diabetes mellitus Receives: Other: observe | |
| AAS group | Participants with autonomous aldosterone secretion (AAS) Receives: Other: observe |
What is being measured
The primary outcome is the main question the study is designed to answer.
The prevalence of autonomous secretion of aldosterone
The primary outcome is the prevalence of autonomous aldosterone secretion at baseline. Autonomous aldosterone secretion is defined by plasma aldosterone concentration (PAC) ≥100 pg/mL combined with plasma renin concentration (PRC) ≤15 uIU/mL in study participants at enrollment. Prevalence will be calculated as the number of participants meeting the above biochemical criteria divided by the total enrolled participants in the target population, presented as percentage with corresponding 95% confidence interval.
Measured: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years
Secondary outcomes (3)
Identification of key risk factors associated with autonomous aldosterone secretion
To identify independent demographic, clinical, biochemical, and anthropometric risk factors associated with prevalent autonomous aldosterone secretion.Autonomous aldosterone secretion is biochemically defined as plasma aldosterone concentration ≥100 pg/mL and plasma renin concentration ≤15 uIU/mL. Multivariable regression analysis will be applied to evaluate significant associated factors; effect sizes (e.g., odds ratio) with 95% confidence intervals and P-values will be reported.
Measured: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years
Association of autonomous aldosterone secretion with chronic kidney disease and metabolic disorders
To evaluate the cross-sectional association between biochemically defined autonomous aldosterone secretion and chronic kidney disease as well as metabolic abnormalities in study participants at baseline. AAS is defined as plasma aldosterone concentration ≥100 pg/mL combined with plasma renin concentration ≤15 uIU/mL. Chronic kidney disease and metabolic disorders will be defined according to current clinical guidelines; relevant correlation and regression analyses will be performed to report effect sizes with 95% confidence intervals and P-values.
Measured: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years
Screening of key proteins, signaling pathways and potential biomarkers associated with autonomous aldosterone secretion using proteomic analysis
To explore differentially expressed key proteins, enriched signaling pathways and candidate molecular biomarkers correlated with biochemical autonomous aldosterone secretion (AAS) via quantitative proteomic technology. AAS is defined as plasma aldosterone concentration ≥100 pg/mL and plasma renin concentration ≤15 uIU/mL. Bioinformatics analyses including protein differential expression profiling, functional enrichment analysis and pathway annotation will be performed to identify core molecular targets and potential diagnostic biomarkers for AAS.
Measured: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Apr 2026
- Study start25 Dec 2020
- Primary completion31 Dec 2026 (estimated)
- Study completion31 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (17)Papers the sponsor has linked to this study.
- Other trials for Endocrine DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 8,000 participants (estimated)
- Target duration
- 5 Years
Sponsor and investigators
- Lead sponsor
- Qifu Li
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Qifu Li, Chongqing Medical University
- Investigators
- Qifu Li, MD, PhD, Chief Physician, Principal investigator, First Affiliated Hospital of Chongqing Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07512609
- Sponsor's protocol ID
- EIMDS
- Status last verified
- Apr 2026
- First submitted
- 20 Nov 2025
- Last updated
- 6 Apr 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Zhang PP, Han Q, Sheng MX, Du CY, Wang YL, Cheng XF, Xu HX, Li CC, Xu YJ. Identification of Circular RNA Expression Profiles in White Adipocytes and Their Roles in Adipogenesis. Front Physiol. 2021 Aug 19;12:728208. doi: 10.3389/fphys.2021.728208. eCollection 2021.
PubMed 34489740Guo X, Zhang Z, Zeng T, Lim YC, Wang Y, Xie X, Yang S, Huang C, Xu M, Tao L, Zeng H, Sun L, Li X. cAMP-MicroRNA-203-IFNgamma network regulates subcutaneous white fat browning and glucose tolerance. Mol Metab. 2019 Oct;28:36-47. doi: 10.1016/j.molmet.2019.07.002. Epub 2019 Jul 6.
PubMed 31327757Arner P, Kulyte A. MicroRNA regulatory networks in human adipose tissue and obesity. Nat Rev Endocrinol. 2015 May;11(5):276-88. doi: 10.1038/nrendo.2015.25. Epub 2015 Mar 3.
PubMed 25732520Mulatero P, Monticone S, Burrello J, Veglio F, Williams TA, Funder J. Guidelines for primary aldosteronism: uptake by primary care physicians in Europe. J Hypertens. 2016 Nov;34(11):2253-7. doi: 10.1097/HJH.0000000000001088.
PubMed 27607462Xu Z, Yang J, Hu J, Song Y, He W, Luo T, Cheng Q, Ma L, Luo R, Fuller PJ, Cai J, Li Q, Yang S; Chongqing Primary Aldosteronism Study (CONPASS) Group. Primary Aldosteronism in Patients in China With Recently Detected Hypertension. J Am Coll Cardiol. 2020 Apr 28;75(16):1913-1922. doi: 10.1016/j.jacc.2020.02.052.
PubMed 32327102Chen X, Mao Y, Hu J, Han S, Gong L, Luo T, Yang S, Qing H, Wang Y, Du Z, Mei M, Zheng L, Lv X, Tang Y, Zhao Q, Zhou Y, He JC, Li Q, Wang Z. Perirenal Fat Thickness Is Significantly Associated With the Risk for Development of Chronic Kidney Disease in Patients With Diabetes. Diabetes. 2021 Oct;70(10):2322-2332. doi: 10.2337/db20-1031. Epub 2021 Jun 22.
PubMed 34593536Hu J, Yang S, Zhang A, Yang P, Cao X, Li X, Goswami R, Wang Y, Luo T, Liao K, Cheng Q, Xiao X, Li Q. Abdominal Obesity Is More Closely Associated With Diabetic Kidney Disease Than General Obesity. Diabetes Care. 2016 Oct;39(10):e179-80. doi: 10.2337/dc16-1025. Epub 2016 Aug 18. No abstract available.
PubMed 27538755Hu J, Hu Y, Hertzmark E, Yuan C, Liu G, Stampfer MJ, Rimm EB, Hu FB, Wang M, Sun Q. Weight Change, Lifestyle, and Mortality in Patients With Type 2 Diabetes. J Clin Endocrinol Metab. 2022 Feb 17;107(3):627-637. doi: 10.1210/clinem/dgab800.
PubMed 34741524Bao Y, Han J, Hu FB, Giovannucci EL, Stampfer MJ, Willett WC, Fuchs CS. Association of nut consumption with total and cause-specific mortality. N Engl J Med. 2013 Nov 21;369(21):2001-11. doi: 10.1056/NEJMoa1307352.
PubMed 24256379Hu FB, Satija A, Manson JE. Curbing the Diabetes Pandemic: The Need for Global Policy Solutions. JAMA. 2015 Jun 16;313(23):2319-20. doi: 10.1001/jama.2015.5287. No abstract available.
PubMed 25996138Hu Y, Zong G, Liu G, Wang M, Rosner B, Pan A, Willett WC, Manson JE, Hu FB, Sun Q. Smoking Cessation, Weight Change, Type 2 Diabetes, and Mortality. N Engl J Med. 2018 Aug 16;379(7):623-632. doi: 10.1056/NEJMoa1803626.
PubMed 30110591Ley SH, Hamdy O, Mohan V, Hu FB. Prevention and management of type 2 diabetes: dietary components and nutritional strategies. Lancet. 2014 Jun 7;383(9933):1999-2007. doi: 10.1016/S0140-6736(14)60613-9.
PubMed 24910231Tobias DK, Pan A, Jackson CL, O'Reilly EJ, Ding EL, Willett WC, Manson JE, Hu FB. Body-mass index and mortality among adults with incident type 2 diabetes. N Engl J Med. 2014 Jan 16;370(3):233-44. doi: 10.1056/NEJMoa1304501.
PubMed 24428469Chan JC, Malik V, Jia W, Kadowaki T, Yajnik CS, Yoon KH, Hu FB. Diabetes in Asia: epidemiology, risk factors, and pathophysiology. JAMA. 2009 May 27;301(20):2129-40. doi: 10.1001/jama.2009.726.
PubMed 19470990Grontved A, Hu FB. Television viewing and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality: a meta-analysis. JAMA. 2011 Jun 15;305(23):2448-55. doi: 10.1001/jama.2011.812.
PubMed 21673296
Study at a glance
From the registry record, last updated by the sponsor on 6 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Environment, Inflammation and Metabolic Diseases Study
- ClinicalTrials.gov ID
- NCT07512609
- Acronym / sponsor ID
- EIMDS
- Keywords
- Endocrine Disease, Metabolic Disorders, Hypertension, Diabetes Mellitus
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 8,000 participants (estimated)
- Lead sponsor
- Qifu LiUniversity, hospital or other
- Study start
- 25 Dec 2020 (actual)
- Primary completion
- 31 Dec 2026 (estimated)
- Study completion
- 31 Dec 2026 (estimated)
- First posted
- 6 Apr 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The aim is to establish an effective and practical early warning model for endocrine and metabolic diseases based on an environmental-gene-protein panoramic network, to uncover new mechanisms underlying the onset and progression of these diseases, and to screen for novel therapeutic targets.
Detailed description
This study aims to establish a specialized resource database for metabolic diseases-the Chongqing Environment, Inflammation, and Metabolic Diseases Study (EIMDS). The cohort will include approximately 8,000 community-based individuals who have been followed up for over 5 years, with clinical, biochemical, and endpoint event assessments conducted every two years, along with the collection of blood and urine samples. Based on the EIMDS cohort,this study will explore the risk factors for endocrine and metabolic diseases from a population perspective. Furthermore, by employing technologies such as whole-transcriptome sequencing, proteomics and phosphoproteomics, ATAC-seq, and single-cell sequencing,this study aim to elucidate the molecular mechanisms underlying endocrine and metabolic diseases and identify potential drug targets.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 5 Years
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| hypertension group | – | Other: observeParticipants with hypertension |
| DM group | – | Other: observeParticipants with diabetes mellitus |
| AAS group | – | Other: observeParticipants with autonomous aldosterone secretion (AAS) |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- This study aims to establish a specialized resource database-the Chongqing Environment, Inflammation, and Metabolic Diseases Study (EIMDS). The cohort will include approximately 8,000 community-based individuals who have been followed up for over 10 years. Clinical, biochemical, and endpoint event assessments will be conducted every two years, along with the collection of blood and urine specimens
Key inclusion criteria (1 listed)
- All individuals who voluntarily participated in the physical examination
Key exclusion criteria (1 listed)
- Participants with incomplete data
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| observeA single observational cohort of study participants undergoing baseline biochemical screening for autonomous aldosterone secretion (AAS). No experimental interventions or treatments are administered. All participants receive standard clinical care and undergo standardized baseline assessments, including measurement of plasma aldosterone concentration (PAC) and plasma renin concentration (PRC) for AAS classification, as well as collection of demographic, clinical, biochemical, anthropometric data and biospecimens for proteomic analysis. | Other | AAS group, DM group, hypertension group |
Primary outcome
The prevalence of autonomous secretion of aldosterone
Time frame: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years
The primary outcome is the prevalence of autonomous aldosterone secretion at baseline. Autonomous aldosterone secretion is defined by plasma aldosterone concentration (PAC) ≥100 pg/mL combined with plasma renin concentration (PRC) ≤15 uIU/mL in study participants at enrollment. Prevalence will be calculated as the number of participants meeting the above biochemical criteria divided by the total enrolled participants in the target population, presented as percentage with corresponding 95% confidence interval.
3 secondary outcomes
Identification of key risk factors associated with autonomous aldosterone secretion
Time frame: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years
Association of autonomous aldosterone secretion with chronic kidney disease and metabolic disorders
Time frame: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years
Screening of key proteins, signaling pathways and potential biomarkers associated with autonomous aldosterone secretion using proteomic analysis
Time frame: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Apr 2026.
- Background: PubMed 34489740Zhang PP, Han Q, Sheng MX, Du CY, Wang YL, Cheng XF, Xu HX, Li CC, Xu YJ. Identification of Circular RNA Expression Profiles in White Adipocytes and Their Roles in Adipogenesis. Front Physiol. 2021 Aug 19;12:728208. doi: 10.3389/fphys.2021.728208. eCollection 2021.
- Background: PubMed 31327757Guo X, Zhang Z, Zeng T, Lim YC, Wang Y, Xie X, Yang S, Huang C, Xu M, Tao L, Zeng H, Sun L, Li X. cAMP-MicroRNA-203-IFNgamma network regulates subcutaneous white fat browning and glucose tolerance. Mol Metab. 2019 Oct;28:36-47. doi: 10.1016/j.molmet.2019.07.002. Epub 2019 Jul 6.
- Background: PubMed 25732520Arner P, Kulyte A. MicroRNA regulatory networks in human adipose tissue and obesity. Nat Rev Endocrinol. 2015 May;11(5):276-88. doi: 10.1038/nrendo.2015.25. Epub 2015 Mar 3.
- Background: PubMed 27607462Mulatero P, Monticone S, Burrello J, Veglio F, Williams TA, Funder J. Guidelines for primary aldosteronism: uptake by primary care physicians in Europe. J Hypertens. 2016 Nov;34(11):2253-7. doi: 10.1097/HJH.0000000000001088.
- Background: PubMed 32327102Xu Z, Yang J, Hu J, Song Y, He W, Luo T, Cheng Q, Ma L, Luo R, Fuller PJ, Cai J, Li Q, Yang S; Chongqing Primary Aldosteronism Study (CONPASS) Group. Primary Aldosteronism in Patients in China With Recently Detected Hypertension. J Am Coll Cardiol. 2020 Apr 28;75(16):1913-1922. doi: 10.1016/j.jacc.2020.02.052.
- Background: PubMed 34593536Chen X, Mao Y, Hu J, Han S, Gong L, Luo T, Yang S, Qing H, Wang Y, Du Z, Mei M, Zheng L, Lv X, Tang Y, Zhao Q, Zhou Y, He JC, Li Q, Wang Z. Perirenal Fat Thickness Is Significantly Associated With the Risk for Development of Chronic Kidney Disease in Patients With Diabetes. Diabetes. 2021 Oct;70(10):2322-2332. doi: 10.2337/db20-1031. Epub 2021 Jun 22.
- Background: PubMed 27538755Hu J, Yang S, Zhang A, Yang P, Cao X, Li X, Goswami R, Wang Y, Luo T, Liao K, Cheng Q, Xiao X, Li Q. Abdominal Obesity Is More Closely Associated With Diabetic Kidney Disease Than General Obesity. Diabetes Care. 2016 Oct;39(10):e179-80. doi: 10.2337/dc16-1025. Epub 2016 Aug 18. No abstract available.
- Background: PubMed 34741524Hu J, Hu Y, Hertzmark E, Yuan C, Liu G, Stampfer MJ, Rimm EB, Hu FB, Wang M, Sun Q. Weight Change, Lifestyle, and Mortality in Patients With Type 2 Diabetes. J Clin Endocrinol Metab. 2022 Feb 17;107(3):627-637. doi: 10.1210/clinem/dgab800.
- Background: PubMed 24256379Bao Y, Han J, Hu FB, Giovannucci EL, Stampfer MJ, Willett WC, Fuchs CS. Association of nut consumption with total and cause-specific mortality. N Engl J Med. 2013 Nov 21;369(21):2001-11. doi: 10.1056/NEJMoa1307352.
- Background: PubMed 25996138Hu FB, Satija A, Manson JE. Curbing the Diabetes Pandemic: The Need for Global Policy Solutions. JAMA. 2015 Jun 16;313(23):2319-20. doi: 10.1001/jama.2015.5287. No abstract available.
- Background: PubMed 30110591Hu Y, Zong G, Liu G, Wang M, Rosner B, Pan A, Willett WC, Manson JE, Hu FB, Sun Q. Smoking Cessation, Weight Change, Type 2 Diabetes, and Mortality. N Engl J Med. 2018 Aug 16;379(7):623-632. doi: 10.1056/NEJMoa1803626.
- Background: PubMed 24910231Ley SH, Hamdy O, Mohan V, Hu FB. Prevention and management of type 2 diabetes: dietary components and nutritional strategies. Lancet. 2014 Jun 7;383(9933):1999-2007. doi: 10.1016/S0140-6736(14)60613-9.
- Individual participant dataSharing planned: No
Related trials for Endocrine Disease
RecruitingObservational study
Early Tracking of Childhood Health Determinants (ETCHED) Study
Diabetes Mellitus, Obesity
Active, not recruitingObservational study
EFFECT OF HYBRID CLOSED-LOOP SYSTEMS ON CARDIOVASCULAR MARKERS IN TYPE 1 DIABETES.
Type 1 Diabetes
Not yet recruitingPhase 1
Hepatic Artery Infusion of Carfilzomib in Participants With Liver Metastatic Disease Previously Treated With Hepatic Artery Infusion Pump Therapy
Colorectal Neoplasms, Neoplasms
Active, not recruitingPhase 2
Enhancement of Neurocognitive Functions by Hippocampal Sparing Radiotherapy
Radiation of Neurocranial Region
Active, not recruiting
Effect of the Thrive AI Health App on Lifestyle Behaviors and Quality of Life
Diabetes Type 2, Overweight or Obesity
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Qifu Li, MD, PhD, Chief Physician principal investigator
First Affiliated Hospital of Chongqing Medical University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Endocrine Disease and Metabolic Disorders, run by Qifu Li at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 6 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Qifu Li, MD, PhD, Chief Physician (+8618696676815 ext. 023-89011554, liqifu@yeah.net), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The prevalence of autonomous secretion of aldosterone (time frame: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07512609, which also lists 17 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Apr 2026.