PRecisiOn MEdicine to Target Frailty of Endocrine-metabolic Origin (PROMETEO)

November 22, 2022 updated by: Andrea M. Isidori, University of Roma La Sapienza
This is a multicenter, observational, retrospective and prospective study for the evaluation of precision medicine to target frailty of endocrine-metabolic origin, with a genetic study.

Study Overview

Status

Recruiting

Conditions

Detailed Description

Overall summary Frailty results from the lifelong accumulation of damage caused by age- and disease-related impairment of the repair network. The amount of cellular damage needed to alter function is uncertain and determined on an individual basis. Assessing cumulative dysfunction in different systems (hormonal, metabolic, immune, cardiovascular, and skeletal) is crucial as the relationship with frailty is nonlinear and not linked to the severity in one system. When subtle, declining functions reaches an aggregate crucial level, and frailty becomes evident. The frail individual is who, after a mild stressor event, undergoes a larger deterioration, which manifest as functional dependency (hospitalization), and who does not return to baseline homoeostasis (favoring polypharmacy). By implementing precision medicine, retrospective and prospective data collected in five referral centers covering densely populated regions in Italy, will be merged and thoroughly analyzed. This network aims at identifying novel biomarkers, predictors of treatment response, and simplified management for complex multiple endocrine comorbidities. The network will investigate emerging and highly prevalent disorders linked to frailty: the gonadal and adrenal, metabolic, neuroendocrine, skeletal. The network will generate scores and precision-medicine based algorithms for the fragile population, often excluded from clinical trials while absorbing most of healthcare expenditure.

Background Frailty is raising globally. Patients with multiple endocrine and metabolic comorbidities (MEDs) are at high risk for inappropriate prescriptions, with negative effects on health outcomes and costs. Endocrine and metabolic comorbidities often coexist with frailty being the common endpoint in patients requiring intensive medical care (falls, disability, hospitalization, and mortality). Concomitant multiple medications aggravate frailty by increasing the risk of interactions, adverse effects and reduce efficacy. The cost of supporting these high-risk population are no longer sustainable for the National Health System (NHS). The pathophysiology of frailty is poorly understood, but multiple endocrine dysfunctions are often associated. Dysregulation of the hypothalamic-pituitary-gonadal and adrenal axes are often associated with metabolic disease (Type 2 Diabetes Mellitus-T2D) as well as bone diseases. In 2018 data from the European Male Aging Study (EMAS) showed that both androgen and nonandrogenic anabolic hormones were independently associated with change in frailty status. Other studies showed that frailty was independently associated with chronically raised diurnal cortisol. Diabetes and osteoporosis (OP) are commonly associated with a significant health burden, especially in elderly individuals. Diabetes is also associated with a wide spectrum of comorbidities (cardiovascular disease, impairment of bone quality, hypogonadism, reduced quality of life, obesity). OP is a complex disorder whose pathogenesis is due to the interaction of various predisposing genetic and epigenetic factors regulating bone and mineral metabolism and non-skeletal risk factors that could influence the risk of fall. Genome-wide association studies (GWAS), epigenetic factors and circulating micro-RNA have opened new horizons for the discovery of genetic loci and variants associated with OP and fracture risk, identifying replicated genetic loci associated with OP. Circulating microRNA profiles have also a prognostic value making them attractive, blood-based, non-invasive biomarkers for prediction and staging of endocrine diseases. Moreover, evidence suggests that inflammation has a major role in the pathophysiology of frailty through an abnormal, low-grade inflammatory chronic response that is hyper-responsive to stimuli. Several inflammatory cytokines have been independently associated with frailty and a link was demonstrated between immune cell function and steroid hormone levels in the recently published DREAM trial. Response to therapy in T2D is often patient-related especially in frail patients. However specific biomarkers are needed for disease monitoring and prediction of disease progression or therapy response. Finally, pituitary diseases are associated with increased mortality and morbidity. This can be a direct effect of hormonal hypersecretion but also secondary to hypopituitarism (HP) caused by mass effect, or a direct consequence of trauma, as well as an important side effect of the treatment itself on pituitary lesions (novel immune check-point inhibitors). HP is globally under-diagnosed and insidious with tremendous effects on quality of life (QoL) as well. All the above mentioned and several other studies suggest an important role of the endocrine system on the development of frailty. It is very likely that comorbidities and drugs can accelerate the frailty of endocrine and metabolic origin. Finally, as concern inappropriate prescriptions, some algorithms were demonstrated particularly reliable. Combining clinical, epidemiological, social, hospital admissions and drug prescription data, has been proven a valid approach to identify inappropriate prescriptions due to drug ineffectiveness and to evaluate cost of polypharmacy.

Hypothesis and Significance Dysregulation of glucocorticoid secretion and hypogonadism due to primary adrenal or gonadal disorders are independent contributors to frailty and failure to treat effectively cardiovascular, metabolic and bone diseases. Prompt restoration of gonadal and adrenal function, when altered, can reduce the need for multi-drug prescription necessary to target high blood pressure, cardiovascular remodeling, osteoporosis and diabetes mellitus.

Less than 50% of patients with T2D had good glycemic control, understanding the mechanisms of Dipeptidyl peptidase-4 (DPP4) inhibitors and Glucagon-like peptide 1 (GLP1)-receptor agonist therapy is needed to predict the response to treatment. Genetic analysis and circulating microRNA profiling may help choosing the appropriate glucose-lowering drugs in T2D patients.

The high prevalence of pituitary and neuroendocrine disorders has a significant impact on morbidity, mortality and QoL. Tailoring diagnostic and therapeutic strategies will lead to early diagnosis of these diseases and their complications allowing to select the best long-term management.

A correlation between genetic and epigenetic risk of OP and fragility fractures (FF), two major components of frailty, is hypothesized and the investigators aim to identify early the subjects at higher risk and predict their response to anti-fracture drug.

Some complex endocrine disorders require extensive use of healthcare resources. Health Care Utilization (HCU) data offer accurate information on the prevalence, incidence, and duration of drugs use providing a comprehensive picture of the therapeutic habits. Linking prescription and clinical-administrative data could allow this network to investigate the inappropriate prescription patterns and the association with worse clinical outcomes.

Implications of the Study The case load of hospital care, diagnostic procedures and drug costs for non-communicable diseases is exceeding sustainability in all countries with a negative impact on public health system. The exponential rise in costs is due to the ageing of the population, prevalence of chronic disorders, improved acute care and new expensive drugs. Rationalization of expenditures is mandatory. Personalize diagnostic procedures, therapeutic approaches and management of comorbidities in highly prevalent disorders is only the immediately sustainable approach. The endocrine and metabolic disorders offer the ideal model to quantify the advantages of shifting from a non-personalized approached to precision etiological treatment strategies. This can lead to a rapid and substantial decline in cost expenditure in terms of number of hospital access, prescribed investigations, and inappropriate medication use. Expected outcomes is a reduction of NIH cost due to saving in 1) polypharmacy and 2) reduced hospitalization for the greater efficacy of drugs prescribed using and personalized algorithm, 3) reduced side effects due to multiple-drug interactions.

Study Type

Observational

Enrollment (Anticipated)

1100

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • Italy
      • Florence, Italy, 50134
        • Recruiting
        • Azienda Ospedaliero-Universitaria Careggi
      • Milan, Italy, 20122
        • Recruiting
        • Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico
      • Rome, Italy, 00161
        • Recruiting
        • Azienda Ospedaliero-Universitaria Policlinico Umberto I
        • Contact:
      • Rome, Italy, 00186
        • Recruiting
        • Ospedale San Giovanni Calibita-Fatebenefratelli Fondazione Fatebenefratelli per la Ricerca e la Formazione Sanitaria e Sociale
      • Siena, Italy, 53100
        • Recruiting
        • Azienda Ospedaliero-Universitaria Senese

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

16 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Patients with endocrine and metabolic diseases (hypothalamic-pituitary-gonadal and adrenal diseases, type 2 diabetes mellitus and bone diseases).

Retrospective cohort of 1100 subjects randomly selected from the 2000 on-file, after matching inclusion criteria.

Prospective cohort of 378 subjects from the 1100 patients recruited in the retrospective phase.

Description

Inclusion Criteria:

  • presence of endocrine and metabolic diseases (hypothalamic-pituitary-gonadal and adrenal diseases, type 2 diabetes mellitus, and bone diseases);
  • signed informed consent to participate in the study.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Other

Cohorts and Interventions

Group / Cohort
Patients with endocrine and metabolic diseases
Patients with endocrine and metabolic diseases (hypothalamic-pituitary-gonadal and adrenal diseases, type 2 diabetes mellitus and bone diseases)

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Composite Clinical Score
Time Frame: Baseline
To derive a Composite Clinical Score able to identify endocrine fragile patients (occurrence of at least one of the following events: falls, disability, hospitalization, and mortality within the previous 18-months).
Baseline
Prediction of frailty
Time Frame: Baseline
Validation of Composite Clinical Score to predict frailty occurrence
Baseline

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Peripheral blood mononuclear cell subpopulations
Time Frame: Baseline
Number of cells (number per mm3) of peripheral blood mononuclear cell subpopulations
Baseline
Molecular profiling
Time Frame: Baseline
Circulating miRNA in blood samples from patients with adrenal and gonadal diseases
Baseline
Steroid profiling
Time Frame: Baseline
Steroid metabolites assessed by liquid chromatography-mass spectrometry (LC-MS/MS)
Baseline
Measure of vascular flows though contrast enhanced ultrasound in endocrine glands
Time Frame: Baseline
Coupling vascular glandular inflow with hormonal outflow
Baseline
Measure of liver vascular inflow through 4 dimensional (4D)-flow MRI
Time Frame: Baseline
Coupling liver vascular inflow with liver glucocorticoid metabolism
Baseline
Serotonin Transporter 5-HTTLPR polymorphism
Time Frame: Baseline
To study the effects of Serotonin Transporter 5-HTTLPR polymorphism on gastrointestinal intolerance to metformin in a population of T2D subjects and its relationship with glycometabolic control
Baseline
Circulating microRNAs
Time Frame: Baseline and post 6 months
To evaluate circulating microRNAs in blood samples from patients with T2D before and after GLP1-receptor agonist or DPP4 inhibitors therapy, in order to identify markers predicting treatment response, therapeutic efficacy and side effects
Baseline and post 6 months
Gene polymorphisms
Time Frame: Baseline and post 6 months
To evaluate gene polymorphisms in blood samples from patients with T2D before and after GLP1-RA or DPP4 inhibitors therapy, in order to identify markers predicting treatment response, therapeutic efficacy and side effects
Baseline and post 6 months
Cardio-metabolic stratification risk
Time Frame: Baseline
To elaborate a risk stratification approach for cardiovascular, metabolic and cerebrovascular outcomes in pituitary patients aimed to personalize treatment and follow-up in pituitary diseases.
Baseline
Psychological function
Time Frame: Baseline
Psychological function assessed by QoL questionnaire in pituitary diseases
Baseline
Osteoporosis stratification risk
Time Frame: Baseline
Gene analysis to elaborate a risk screening panel for osteoporosis
Baseline
Epigenetic biomarkers
Time Frame: Baseline
To individuate possible serum epigenetic biomarkers of osteoporosis status and fragility fractures risk
Baseline
Multiple endocrine and metabolic comorbidities
Time Frame: Baseline
To identify patients with multiple endocrine and metabolic comorbidities and assess the incidence of major clinical events using regional registries
Baseline
Inappropriate therapeutic regimen
Time Frame: Baseline
To individuate inappropriate therapeutic regimen (drug prescriptions or suboptimal adherence) in patients with multiple endocrine and metabolic comorbidities
Baseline

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of Roma La Sapienza

Investigators

  • Principal Investigator: Andrea M Isidori, Prof, Department of Experimental Medicine, "Sapienza" University of Rome

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

August 10, 2020

Primary Completion (Anticipated)

August 1, 2023

Study Completion (Anticipated)

August 9, 2024

Study Registration Dates

First Submitted

April 13, 2021

First Submitted That Met QC Criteria

April 19, 2021

First Posted (Actual)

April 23, 2021

Study Record Updates

Last Update Posted (Actual)

November 23, 2022

Last Update Submitted That Met QC Criteria

November 22, 2022

Last Verified

November 1, 2022

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • PROMETEO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Frailty

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in El Salvador

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

3
Subscribe