PRecisiOn MEdicine to Target Frailty of Endocrine-metabolic Origin
NCT ID: NCT04856683
Last Updated: 2022-11-23
Study Results
Results pending
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
Recruitment Status
UNKNOWN
Total Enrollment
1100 participants
Study Classification
OBSERVATIONAL
Study Start Date
2020-08-10
Study Completion Date
2024-08-09
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
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.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Mitochondrial Genetics of Presbycusis
NCT03720964
Presbycusis
Age Related Hearing Loss
UNKNOWN
Nutraceuticals and Drug Treatment in Frail Older Adults
NCT04962841
Frailty
UNKNOWN
Epidemiological Observatory on the Health Conditions of Inpatients Aged 65 or Older at the INRCA Research Hospitals
NCT01397682
Aging
Inpatients
UNKNOWN
Comprehensive Geriatric Assessment in the Elderly Subjects (PROMISING)
NCT05822154
Ageing
Frailty
UNKNOWN
Frailty in Elderly Patients With COVID-19
NCT04412265
Covid19
COMPLETED
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
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.
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.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Frailty
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
Observational Model Type
COHORT
Study Time Perspective
OTHER
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
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)
No interventions assigned to this group
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
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.
* signed informed consent to participate in the study.
Minimum Eligible Age
18 Years
Eligible Sex
ALL
Accepts Healthy Volunteers
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
University of Roma La Sapienza
OTHER
Sponsor Role
lead
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Andrea M. Isidori
Full Professor
Responsibility Role
PRINCIPAL_INVESTIGATOR
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
Andrea M Isidori, Prof
Role: PRINCIPAL_INVESTIGATOR
Department of Experimental Medicine, "Sapienza" University of Rome
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Azienda Ospedaliero-Universitaria Careggi
Florence, , Italy
Site Status
RECRUITING
Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico
Milan, , Italy
Site Status
RECRUITING
Azienda Ospedaliero-Universitaria Policlinico Umberto I
Rome, , Italy
Site Status
RECRUITING
Ospedale San Giovanni Calibita-Fatebenefratelli Fondazione Fatebenefratelli per la Ricerca e la Formazione Sanitaria e Sociale
Rome, , Italy
Site Status
RECRUITING
Azienda Ospedaliero-Universitaria Senese
Siena, , Italy
Site Status
RECRUITING
Countries
Review the countries where the study has at least one active or historical site.
Italy
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Facility Contacts
Find local site contact details for specific facilities participating in the trial.
References
Explore related publications, articles, or registry entries linked to this study.
Chiodini I, Adda G, Scillitani A, Coletti F, Morelli V, Di Lembo S, Epaminonda P, Masserini B, Beck-Peccoz P, Orsi E, Ambrosi B, Arosio M. Cortisol secretion in patients with type 2 diabetes: relationship with chronic complications. Diabetes Care. 2007 Jan;30(1):83-8. doi: 10.2337/dc06-1267.
Reference Type
BACKGROUND
Finkelstein J, Friedman C, Hripcsak G, Cabrera M. Potential utility of precision medicine for older adults with polypharmacy: a case series study. Pharmgenomics Pers Med. 2016 Apr 15;9:31-45. doi: 10.2147/PGPM.S101474. eCollection 2016.
Reference Type
BACKGROUND
Joseph SM, Rich MW. Targeting Frailty in Heart Failure. Curr Treat Options Cardiovasc Med. 2017 Apr;19(4):31. doi: 10.1007/s11936-017-0527-5.
Reference Type
BACKGROUND
Morley JE. Hormones and Sarcopenia. Curr Pharm Des. 2017 Nov 28;23(30):4484-4492. doi: 10.2174/1381612823666161123150032.
Reference Type
BACKGROUND
Swiecicka A, Eendebak RJAH, Lunt M, O'Neill TW, Bartfai G, Casanueva FF, Forti G, Giwercman A, Han TS, Slowikowska-Hilczer J, Lean MEJ, Pendleton N, Punab M, Vanderschueren D, Huhtaniemi IT, Wu FCW, Rutter MK; European Male Ageing Study Group. Reproductive Hormone Levels Predict Changes in Frailty Status in Community-Dwelling Older Men: European Male Ageing Study Prospective Data. J Clin Endocrinol Metab. 2018 Feb 1;103(2):701-709. doi: 10.1210/jc.2017-01172.
Reference Type
BACKGROUND
Saad F, Rohrig G, von Haehling S, Traish A. Testosterone Deficiency and Testosterone Treatment in Older Men. Gerontology. 2017;63(2):144-156. doi: 10.1159/000452499. Epub 2016 Nov 18.
Reference Type
BACKGROUND
Ladapo JA, Budoff MJ, Sharp D, Kuo JZ, Huang L, Maniet B, Herman L, Monane M. Utility of a Precision Medicine Test in Elderly Adults with Symptoms Suggestive of Coronary Artery Disease. J Am Geriatr Soc. 2018 Feb;66(2):309-315. doi: 10.1111/jgs.15215. Epub 2017 Dec 6.
Reference Type
BACKGROUND
Ramaswami R, Bayer R, Galea S. Precision Medicine from a Public Health Perspective. Annu Rev Public Health. 2018 Apr 1;39:153-168. doi: 10.1146/annurev-publhealth-040617-014158. Epub 2017 Nov 20.
Reference Type
BACKGROUND
Kane AE, Gregson E, Theou O, Rockwood K, Howlett SE. The association between frailty, the metabolic syndrome, and mortality over the lifespan. Geroscience. 2017 Apr;39(2):221-229. doi: 10.1007/s11357-017-9967-9. Epub 2017 Mar 9.
Reference Type
BACKGROUND
Johar H, Emeny RT, Bidlingmaier M, Reincke M, Thorand B, Peters A, Heier M, Ladwig KH. Blunted diurnal cortisol pattern is associated with frailty: a cross-sectional study of 745 participants aged 65 to 90 years. J Clin Endocrinol Metab. 2014 Mar;99(3):E464-8. doi: 10.1210/jc.2013-3079. Epub 2014 Feb 24.
Reference Type
BACKGROUND
Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013 Mar 2;381(9868):752-62. doi: 10.1016/S0140-6736(12)62167-9. Epub 2013 Feb 8.
Reference Type
BACKGROUND
Isidori AM, Venneri MA, Graziadio C, Simeoli C, Fiore D, Hasenmajer V, Sbardella E, Gianfrilli D, Pozza C, Pasqualetti P, Morrone S, Santoni A, Naro F, Colao A, Pivonello R, Lenzi A. Effect of once-daily, modified-release hydrocortisone versus standard glucocorticoid therapy on metabolism and innate immunity in patients with adrenal insufficiency (DREAM): a single-blind, randomised controlled trial. Lancet Diabetes Endocrinol. 2018 Mar;6(3):173-185. doi: 10.1016/S2213-8587(17)30398-4. Epub 2017 Dec 8.
Reference Type
BACKGROUND
DeFronzo RA. Pathogenesis of type 2 diabetes mellitus. Med Clin North Am. 2004 Jul;88(4):787-835, ix. doi: 10.1016/j.mcna.2004.04.013.
Reference Type
BACKGROUND
Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998 Sep 12;352(9131):837-53.
Reference Type
BACKGROUND
Rossi MC, Nicolucci A, Arcangeli A, Cimino A, De Bigontina G, Giorda C, Meloncelli I, Pellegrini F, Valentini U, Vespasiani G; Associazione Medici Diabetologi Annals Study Group. Baseline quality-of-care data from a quality-improvement program implemented by a network of diabetes outpatient clinics. Diabetes Care. 2008 Nov;31(11):2166-8. doi: 10.2337/dc08-0469. Epub 2008 Aug 11.
Reference Type
BACKGROUND
Dujic T, Zhou K, Tavendale R, Palmer CN, Pearson ER. Effect of Serotonin Transporter 5-HTTLPR Polymorphism on Gastrointestinal Intolerance to Metformin: A GoDARTS Study. Diabetes Care. 2016 Nov;39(11):1896-1901. doi: 10.2337/dc16-0706. Epub 2016 Aug 4.
Reference Type
BACKGROUND
Guay C, Regazzi R. Circulating microRNAs as novel biomarkers for diabetes mellitus. Nat Rev Endocrinol. 2013 Sep;9(9):513-21. doi: 10.1038/nrendo.2013.86. Epub 2013 Apr 30.
Reference Type
BACKGROUND
Sebastiani G, Nigi L, Grieco GE, Mancarella F, Ventriglia G, Dotta F. Circulating microRNAs and diabetes mellitus: a novel tool for disease prediction, diagnosis, and staging? J Endocrinol Invest. 2017 Jun;40(6):591-610. doi: 10.1007/s40618-017-0611-4. Epub 2017 Feb 17.
Reference Type
BACKGROUND
Jamaluddin JL, Huri HZ, Vethakkan SR. Clinical and genetic predictors of dipeptidyl peptidase-4 inhibitor treatment response in Type 2 diabetes mellitus. Pharmacogenomics. 2016 Jun;17(8):867-81. doi: 10.2217/pgs-2016-0010. Epub 2016 Jun 1.
Reference Type
BACKGROUND
Catanzaro G, Besharat ZM, Chiacchiarini M, Abballe L, Sabato C, Vacca A, Borgiani P, Dotta F, Tesauro M, Po A, Ferretti E. Circulating MicroRNAs in Elderly Type 2 Diabetic Patients. Int J Endocrinol. 2018 Apr 10;2018:6872635. doi: 10.1155/2018/6872635. eCollection 2018.
Reference Type
BACKGROUND
Sherlock M, Ayuk J, Tomlinson JW, Toogood AA, Aragon-Alonso A, Sheppard MC, Bates AS, Stewart PM. Mortality in patients with pituitary disease. Endocr Rev. 2010 Jun;31(3):301-42. doi: 10.1210/er.2009-0033. Epub 2010 Jan 19.
Reference Type
BACKGROUND
Tanriverdi F, Schneider HJ, Aimaretti G, Masel BE, Casanueva FF, Kelestimur F. Pituitary dysfunction after traumatic brain injury: a clinical and pathophysiological approach. Endocr Rev. 2015 Jun;36(3):305-42. doi: 10.1210/er.2014-1065. Epub 2015 May 7.
Reference Type
BACKGROUND
Corsello SM, Barnabei A, Marchetti P, De Vecchis L, Salvatori R, Torino F. Endocrine side effects induced by immune checkpoint inhibitors. J Clin Endocrinol Metab. 2013 Apr;98(4):1361-75. doi: 10.1210/jc.2012-4075. Epub 2013 Mar 7.
Reference Type
BACKGROUND
Arosio M, Reimondo G, Malchiodi E, Berchialla P, Borraccino A, De Marinis L, Pivonello R, Grottoli S, Losa M, Cannavo S, Minuto F, Montini M, Bondanelli M, De Menis E, Martini C, Angeletti G, Velardo A, Peri A, Faustini-Fustini M, Tita P, Pigliaru F, Borretta G, Scaroni C, Bazzoni N, Bianchi A, Appetecchia M, Cavagnini F, Lombardi G, Ghigo E, Beck-Peccoz P, Colao A, Terzolo M; Italian Study Group of Acromegaly. Predictors of morbidity and mortality in acromegaly: an Italian survey. Eur J Endocrinol. 2012 Aug;167(2):189-98. doi: 10.1530/EJE-12-0084. Epub 2012 May 17.
Reference Type
BACKGROUND
Colao A, Ferone D, Marzullo P, Lombardi G. Systemic complications of acromegaly: epidemiology, pathogenesis, and management. Endocr Rev. 2004 Feb;25(1):102-52. doi: 10.1210/er.2002-0022.
Reference Type
BACKGROUND
Graversen D, Vestergaard P, Stochholm K, Gravholt CH, Jorgensen JO. Mortality in Cushing's syndrome: a systematic review and meta-analysis. Eur J Intern Med. 2012 Apr;23(3):278-82. doi: 10.1016/j.ejim.2011.10.013. Epub 2011 Nov 15.
Reference Type
BACKGROUND
Clayton RN, Raskauskiene D, Reulen RC, Jones PW. Mortality and morbidity in Cushing's disease over 50 years in Stoke-on-Trent, UK: audit and meta-analysis of literature. J Clin Endocrinol Metab. 2011 Mar;96(3):632-42. doi: 10.1210/jc.2010-1942. Epub 2010 Dec 30.
Reference Type
BACKGROUND
Mancini T, Kola B, Mantero F, Boscaro M, Arnaldi G. High cardiovascular risk in patients with Cushing's syndrome according to 1999 WHO/ISH guidelines. Clin Endocrinol (Oxf). 2004 Dec;61(6):768-77. doi: 10.1111/j.1365-2265.2004.02168.x.
Reference Type
BACKGROUND
Tomlinson JW, Holden N, Hills RK, Wheatley K, Clayton RN, Bates AS, Sheppard MC, Stewart PM. Association between premature mortality and hypopituitarism. West Midlands Prospective Hypopituitary Study Group. Lancet. 2001 Feb 10;357(9254):425-31. doi: 10.1016/s0140-6736(00)04006-x.
Reference Type
BACKGROUND
Mazziotti G, Chiavistelli S, Giustina A. Pituitary diseases and bone. Endocrinol Metab Clin North Am. 2015 Mar;44(1):171-80. doi: 10.1016/j.ecl.2014.10.014. Epub 2014 Nov 4.
Reference Type
BACKGROUND
Mazziotti G, Doga M, Frara S, Maffezzoni F, Porcelli T, Cerri L, Maroldi R, Giustina A. Incidence of morphometric vertebral fractures in adult patients with growth hormone deficiency. Endocrine. 2016 Apr;52(1):103-10. doi: 10.1007/s12020-015-0738-z. Epub 2015 Oct 3.
Reference Type
BACKGROUND
Mazziotti G, Frara S, Giustina A. Pituitary Diseases and Bone. Endocr Rev. 2018 Aug 1;39(4):440-488. doi: 10.1210/er.2018-00005.
Reference Type
BACKGROUND
Johnson MD, Woodburn CJ, Vance ML. Quality of life in patients with a pituitary adenoma. Pituitary. 2003 Sep;6(2):81-7. doi: 10.1023/b:pitu.0000004798.27230.ed.
Reference Type
BACKGROUND
Webb SM, Crespo I, Santos A, Resmini E, Aulinas A, Valassi E. MANAGEMENT OF ENDOCRINE DISEASE: Quality of life tools for the management of pituitary disease. Eur J Endocrinol. 2017 Jul;177(1):R13-R26. doi: 10.1530/EJE-17-0041. Epub 2017 Mar 28.
Reference Type
BACKGROUND
Andela CD, Scharloo M, Ramondt S, Tiemensma J, Husson O, Llahana S, Pereira AM, Kaptein AA, Kamminga NG, Biermasz NR. The development and validation of the Leiden Bother and Needs Questionnaire for patients with pituitary disease: the LBNQ-Pituitary. Pituitary. 2016 Jun;19(3):293-302. doi: 10.1007/s11102-016-0707-4.
Reference Type
BACKGROUND
Sonino N, Fava GA. Psychiatric disorders associated with Cushing's syndrome. Epidemiology, pathophysiology and treatment. CNS Drugs. 2001;15(5):361-73. doi: 10.2165/00023210-200115050-00003.
Reference Type
BACKGROUND
van Aken MO, Pereira AM, Biermasz NR, van Thiel SW, Hoftijzer HC, Smit JW, Roelfsema F, Lamberts SW, Romijn JA. Quality of life in patients after long-term biochemical cure of Cushing's disease. J Clin Endocrinol Metab. 2005 Jun;90(6):3279-86. doi: 10.1210/jc.2004-1375. Epub 2005 Mar 1.
Reference Type
BACKGROUND
Carosi G, Malchiodi E, Ferrante E, Sala E, Verrua E, Profka E, Giavoli C, Filopanti M, Beck-Peccoz P, Spada A, Mantovani G. Hypothalamic-Pituitary Axis in Non-Functioning Pituitary Adenomas: Focus on the Prevalence of Isolated Central Hypoadrenalism. Neuroendocrinology. 2015;102(4):267-273. doi: 10.1159/000430815. Epub 2015 Apr 29.
Reference Type
BACKGROUND
Terzolo M, Reimondo G, Berchialla P, Ferrante E, Malchiodi E, De Marinis L, Pivonello R, Grottoli S, Losa M, Cannavo S, Ferone D, Montini M, Bondanelli M, De Menis E, Martini C, Puxeddu E, Velardo A, Peri A, Faustini-Fustini M, Tita P, Pigliaru F, Peraga G, Borretta G, Scaroni C, Bazzoni N, Bianchi A, Berton A, Serban AL, Baldelli R, Fatti LM, Colao A, Arosio M; Italian Study Group of Acromegaly. Acromegaly is associated with increased cancer risk: a survey in Italy. Endocr Relat Cancer. 2017 Sep;24(9):495-504. doi: 10.1530/ERC-16-0553. Epub 2017 Jul 14.
Reference Type
BACKGROUND
Ronchi CL, Giavoli C, Ferrante E, Verrua E, Bergamaschi S, Ferrari DI, Corbetta S, Montefusco L, Arosio M, Ambrosi B, Spada A, Beck-Peccoz P. Prevalence of GH deficiency in cured acromegalic patients: impact of different previous treatments. Eur J Endocrinol. 2009 Jul;161(1):37-42. doi: 10.1530/EJE-09-0222. Epub 2009 Apr 7.
Reference Type
BACKGROUND
Giavoli C, Profka E, Verrua E, Ronchi CL, Ferrante E, Bergamaschi S, Sala E, Malchiodi E, Lania AG, Arosio M, Ambrosi B, Spada A, Beck-Peccoz P. GH replacement improves quality of life and metabolic parameters in cured acromegalic patients with growth hormone deficiency. J Clin Endocrinol Metab. 2012 Nov;97(11):3983-8. doi: 10.1210/jc.2012-2477. Epub 2012 Aug 17.
Reference Type
BACKGROUND
Chiodini I, Mascia ML, Muscarella S, Battista C, Minisola S, Arosio M, Santini SA, Guglielmi G, Carnevale V, Scillitani A. Subclinical hypercortisolism among outpatients referred for osteoporosis. Ann Intern Med. 2007 Oct 16;147(8):541-8. doi: 10.7326/0003-4819-147-8-200710160-00006.
Reference Type
BACKGROUND
Chiodini I, Torlontano M, Scillitani A, Arosio M, Bacci S, Di Lembo S, Epaminonda P, Augello G, Enrini R, Ambrosi B, Adda G, Trischitta V. Association of subclinical hypercortisolism with type 2 diabetes mellitus: a case-control study in hospitalized patients. Eur J Endocrinol. 2005 Dec;153(6):837-44. doi: 10.1530/eje.1.02045.
Reference Type
BACKGROUND
Zhukouskaya VV, Eller-Vainicher C, Gaudio A, Cairoli E, Ulivieri FM, Palmieri S, Morelli V, Orsi E, Masserini B, Barbieri AM, Polledri E, Fustinoni S, Spada A, Fiore CE, Chiodini I. In postmenopausal female subjects with type 2 diabetes mellitus, vertebral fractures are independently associated with cortisol secretion and sensitivity. J Clin Endocrinol Metab. 2015 Apr;100(4):1417-25. doi: 10.1210/jc.2014-4177. Epub 2015 Jan 15.
Reference Type
BACKGROUND
Ralston SH. Genetic determinants of susceptibility to osteoporosis. Curr Opin Pharmacol. 2003 Jun;3(3):286-90. doi: 10.1016/s1471-4892(03)00033-x.
Reference Type
BACKGROUND
Richards JB, Zheng HF, Spector TD. Genetics of osteoporosis from genome-wide association studies: advances and challenges. Nat Rev Genet. 2012 Jul 18;13(8):576-88. doi: 10.1038/nrg3228.
Reference Type
BACKGROUND
Arden NK, Baker J, Hogg C, Baan K, Spector TD. The heritability of bone mineral density, ultrasound of the calcaneus and hip axis length: a study of postmenopausal twins. J Bone Miner Res. 1996 Apr;11(4):530-4. doi: 10.1002/jbmr.5650110414.
Reference Type
BACKGROUND
Eisman JA. Genetics of osteoporosis. Endocr Rev. 1999 Dec;20(6):788-804. doi: 10.1210/edrv.20.6.0384.
Reference Type
BACKGROUND
Andrew T, Antioniades L, Scurrah KJ, Macgregor AJ, Spector TD. Risk of wrist fracture in women is heritable and is influenced by genes that are largely independent of those influencing BMD. J Bone Miner Res. 2005 Jan;20(1):67-74. doi: 10.1359/JBMR.041015. Epub 2004 Oct 25.
Reference Type
BACKGROUND
Rocha-Braz MG, Ferraz-de-Souza B. Genetics of osteoporosis: searching for candidate genes for bone fragility. Arch Endocrinol Metab. 2016 Aug;60(4):391-401. doi: 10.1590/2359-3997000000178.
Reference Type
BACKGROUND
Ioannidis JP, Ralston SH, Bennett ST, Brandi ML, Grinberg D, Karassa FB, Langdahl B, van Meurs JB, Mosekilde L, Scollen S, Albagha OM, Bustamante M, Carey AH, Dunning AM, Enjuanes A, van Leeuwen JP, Mavilia C, Masi L, McGuigan FE, Nogues X, Pols HA, Reid DM, Schuit SC, Sherlock RE, Uitterlinden AG; GENOMOS Study. Differential genetic effects of ESR1 gene polymorphisms on osteoporosis outcomes. JAMA. 2004 Nov 3;292(17):2105-14. doi: 10.1001/jama.292.17.2105.
Reference Type
BACKGROUND
Ralston SH, Uitterlinden AG, Brandi ML, Balcells S, Langdahl BL, Lips P, Lorenc R, Obermayer-Pietsch B, Scollen S, Bustamante M, Husted LB, Carey AH, Diez-Perez A, Dunning AM, Falchetti A, Karczmarewicz E, Kruk M, van Leeuwen JP, van Meurs JB, Mangion J, McGuigan FE, Mellibovsky L, del Monte F, Pols HA, Reeve J, Reid DM, Renner W, Rivadeneira F, van Schoor NM, Sherlock RE, Ioannidis JP; GENOMOS Investigators. Large-scale evidence for the effect of the COLIA1 Sp1 polymorphism on osteoporosis outcomes: the GENOMOS study. PLoS Med. 2006 Apr;3(4):e90. doi: 10.1371/journal.pmed.0030090. Epub 2006 Feb 21.
Reference Type
BACKGROUND
Uitterlinden AG, Ralston SH, Brandi ML, Carey AH, Grinberg D, Langdahl BL, Lips P, Lorenc R, Obermayer-Pietsch B, Reeve J, Reid DM, Amedei A, Bassiti A, Bustamante M, Husted LB, Diez-Perez A, Dobnig H, Dunning AM, Enjuanes A, Fahrleitner-Pammer A, Fang Y, Karczmarewicz E, Kruk M, van Leeuwen JP, Mavilia C, van Meurs JB, Mangion J, McGuigan FE, Pols HA, Renner W, Rivadeneira F, van Schoor NM, Scollen S, Sherlock RE, Ioannidis JP; APOSS Investigators; EPOS Investigators; EPOLOS Investigators; FAMOS Investigators; LASA Investigators; Rotterdam Study Investigators; GENOMOS Study. The association between common vitamin D receptor gene variations and osteoporosis: a participant-level meta-analysis. Ann Intern Med. 2006 Aug 15;145(4):255-64. doi: 10.7326/0003-4819-145-4-200608150-00005.
Reference Type
BACKGROUND
Langdahl BL, Uitterlinden AG, Ralston SH, Trikalinos TA, Balcells S, Brandi ML, Scollen S, Lips P, Lorenc R, Obermayer-Pietsch B, Reid DM, Armas JB, Arp PP, Bassiti A, Bustamante M, Husted LB, Carey AH, Perez Cano R, Dobnig H, Dunning AM, Fahrleitner-Pammer A, Falchetti A, Karczmarewicz E, Kruk M, van Leeuwen JP, Masi L, van Meurs JB, Mangion J, McGuigan FE, Mellibovsky L, Mosekilde L, Nogues X, Pols HA, Reeve J, Renner W, Rivadeneira F, van Schoor NM, Ioannidis JP; APOSS investigators; DOPS investigators; EPOS investigators; EPOLOS investigators; FAMOS investigators; LASA investigators; ERGO investigators; GENOMOS Study. Large-scale analysis of association between polymorphisms in the transforming growth factor beta 1 gene (TGFB1) and osteoporosis: the GENOMOS study. Bone. 2008 May;42(5):969-81. doi: 10.1016/j.bone.2007.11.007. Epub 2007 Dec 3.
Reference Type
BACKGROUND
van Meurs JB, Trikalinos TA, Ralston SH, Balcells S, Brandi ML, Brixen K, Kiel DP, Langdahl BL, Lips P, Ljunggren O, Lorenc R, Obermayer-Pietsch B, Ohlsson C, Pettersson U, Reid DM, Rousseau F, Scollen S, Van Hul W, Agueda L, Akesson K, Benevolenskaya LI, Ferrari SL, Hallmans G, Hofman A, Husted LB, Kruk M, Kaptoge S, Karasik D, Karlsson MK, Lorentzon M, Masi L, McGuigan FE, Mellstrom D, Mosekilde L, Nogues X, Pols HA, Reeve J, Renner W, Rivadeneira F, van Schoor NM, Weber K, Ioannidis JP, Uitterlinden AG; GENOMOS Study. Large-scale analysis of association between LRP5 and LRP6 variants and osteoporosis. JAMA. 2008 Mar 19;299(11):1277-90. doi: 10.1001/jama.299.11.1277.
Reference Type
BACKGROUND
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
PROMETEO
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.
The Effect of Frailty and Other Geriatric Syndromes on the Prognosis of Elderly Patients With Acute Coronary Syndrome
NCT04580706
UNKNOWN
The InChianti Follow-Up Study
NCT01331512
COMPLETED
Nutrition and Frailty in Older Persons
NCT01433211
COMPLETED
Improving Quality of Life in Frail, Older Patients with Hematological Cancer Through Geriatric Assessment and Treatment - a Pilot Study
NCT06689332
COMPLETED
NA
Remote Monitoring to Prevent Frailty Progression in the Elderly
NCT05173870
RECRUITING
Screening of the Frailty Degree in the Emergency Department Short Stay Unit
NCT04812834
UNKNOWN
INSPIRE: Feasibility of a Community-based Integrated Care Model for Older Adults Living at Home
NCT05302310
COMPLETED
Biological MArkers of FRAilty in Elderly Subjects
NCT02816580
COMPLETED
NA
Study of the Association Between Presbycusis With the Incidence of Frailty
NCT04360109
UNKNOWN
Age-related Conditions in the Context of Multimorbidity and Frailty: Relative Weight of Frailty in Determining the Course and Outcomes of Different Chronic Diseases and Viceversa
NCT06324149
RECRUITING
Multifactorial Intervention on Frailty in Vulnerable Older Adults
NCT02554994
COMPLETED
NA
Integration of Clinical, Biological and Psycho-social Variables for a Gender-sensitive Frailty Prediction
NCT07109596
RECRUITING
Apolipoprotein E (ApoE) and Metabolism
NCT03109561
COMPLETED
Feasibility of an Extended Test Battery and Influencing Factors for Detecting Frailty
NCT04190329
COMPLETED
Cognitive Frailty and Oxygen-ozone Therapy
NCT06071611
COMPLETED
NA
Smart Home Technologies for Assessing and Monitoring Frailty in Older Adults
NCT05961319
COMPLETED
eHealth for Screening Health Risks in Home-Based Older Adults: A Prospective Study
NCT06019390
UNKNOWN
NA
PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer's Disease With Machine Learning
NCT05569083
UNKNOWN
Metabolic Dysregulation as Biomarker of Frailty: Role of the Mitochondrial Dysfunction
NCT06433427
NOT_YET_RECRUITING
Characterising Frailty Using Magnetic Resonance Imaging
NCT04612686
UNKNOWN
Prevalence of Sarcopenia and Its Geriatric Features
NCT02664376
COMPLETED
Determinant of the Risk of the Becoming Frail in the Non-dependent Elederly
NCT04012840
RECRUITING
Evaluation of the Hospital Pathway for Frail Elderly Patients Hospitalised for Pathologies Leading to Medical Decompensation
NCT06873256
COMPLETED