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Endocrine Jun 2024Patients with acromegaly oftentimes exhibit a reduced physical and psychological health-related quality of life (HRQoL). Maladaptive coping styles are associated with...
PURPOSE
Patients with acromegaly oftentimes exhibit a reduced physical and psychological health-related quality of life (HRQoL). Maladaptive coping styles are associated with poor HRQoL in a number of diseases and patients with pituitary adenomas in general exhibit less effective coping styles than healthy controls. This study aimed to assess coping strategies in acromegaly patients in order to explore leverage points for the improvement of HRQoL.
METHODS
In this cross-sectional study, we administered self-report surveys for coping strategies and HRQoL (Short Form SF-36, Freiburg questionnaire on coping with illness, FKV-LIS) in patients with acromegaly. These were set into relation with a variety of health variables.
RESULTS
About half of the 106 patients (44.3% female) with a mean age of 56.4 ± 1.3 years showed impaired physical and psychological HRQoL on average 11.2 years after the initial diagnosis. Body mass index, age at survey date and concomitant radiotherapy explained 27.8% of the variance of physical HRQoL, while depressive coping added an additional 9.2%. Depressive coping style and trivialization and wishful thinking were pivotal predictors of an impaired psychological HRQoL with a total explained variance of 51.6%, whereas patient health variables did not affect psychological HRQoL.
CONCLUSION
Our results show that maladaptive coping styles have a substantial negative impact on psychological HRQoL in patients with acromegaly, whereas physical HRQoL is influenced to a lesser extent. Specialized training programs aimed at improving coping strategies could reduce long-term disease burden and increase HRQoL in the affected patients.
Topics: Humans; Acromegaly; Quality of Life; Female; Middle Aged; Male; Adaptation, Psychological; Cross-Sectional Studies; Adult; Aged; Depression; Surveys and Questionnaires; Health Status; Coping Skills
PubMed: 38613640
DOI: 10.1007/s12020-024-03813-4 -
Frontiers in Endocrinology 2024Serum levels of growth hormone (GH) and insulin-like growth factor (IGF)-I are crucial in the diagnosis and management of GH-related diseases. However, these levels are...
Serum levels of growth hormone (GH) and insulin-like growth factor (IGF)-I are crucial in the diagnosis and management of GH-related diseases. However, these levels are affected by nutritional and metabolic status. To elucidate the correlations between GH and IGF-I in various conditions, a retrospective analysis was performed for adult patients in which GH levels were examined by general practitioners during the period from January 2019 to December 2021. Of 642 patients, 33 patients were diagnosed with acromegaly, 21 were diagnosed with GH deficiency (GHD), and 588 were diagnosed with non-GH-related diseases (NGRD). In contrast to the positive correlations found between the levels of GH and IGF-I in patients with acromegaly (=0.50; <0.001) and patients with GHD (=0.39; =0.08), a negative correlation was found in the NGRD group (=-0.23; <0.001). In that group, the results of multivariable analysis showed that GH levels were predominantly influenced by gender and body mass index (BMI), whereas IGF-I levels were modulated by albumin in addition to age and GH. Of note, in the NGRD group, there was an enhanced negative correlation between GH and IGF-I under conditions of BMI < 22 and albumin < 4.0 g/dL (=-0.45; <0.001), and the negative correlation between GH and IGF-I was reinforced by excluding patients with other pituitary diseases and patients taking oral steroids (=-0.51; <0.001 and =-0.59; <0.001, respectively). Collectively, the results indicate that attention should be given to the presence of a negative correlation between serum levels of GH and IGF-I, especially in lean and low-nutritious conditions.
Topics: Adult; Humans; Growth Hormone; Acromegaly; Insulin-Like Peptides; Insulin-Like Growth Factor I; Retrospective Studies; Human Growth Hormone; Dwarfism, Pituitary; General Practice; Albumins
PubMed: 38596224
DOI: 10.3389/fendo.2024.1381083 -
Frontiers in Endocrinology 2024Pasireotide, a somatostatin receptor ligand, is approved for treating acromegaly and Cushing's disease (CD). Hyperglycemia during treatment can occur because of the... (Randomized Controlled Trial)
Randomized Controlled Trial
Predictive factors and the management of hyperglycemia in patients with acromegaly and Cushing's disease receiving pasireotide treatment: analyses from the SOM230B2219 study.
INTRODUCTION
Pasireotide, a somatostatin receptor ligand, is approved for treating acromegaly and Cushing's disease (CD). Hyperglycemia during treatment can occur because of the drug's mechanism of action, although treatment discontinuation is rarely required. The prospective, randomized, Phase IV SOM230B2219 (NCT02060383) trial was designed to assess optimal management of pasireotide-associated hyperglycemia. Here, we investigated predictive factors for requiring antihyperglycemic medication during pasireotide treatment.
METHODS
Participants with acromegaly or CD initiated long-acting pasireotide 40 mg/28 days intramuscularly (acromegaly) or pasireotide 600 μg subcutaneously twice daily during pre-randomization (≤16 weeks). Those who did not need antihyperglycemic medication, were managed with metformin, or received insulin from baseline entered an observational arm ending at 16 weeks. Those who required additional/alternative antihyperglycemic medication to metformin were randomized to incretin-based therapy or insulin for an additional 16 weeks. Logistic-regression analyses evaluated quantitative and qualitative factors for requiring antihyperglycemic medication during pre-randomization.
RESULTS
Of 190 participants with acromegaly and 59 with CD, 88 and 15, respectively, did not need antihyperglycemic medication; most were aged <40 years (acromegaly 62.5%, CD 86.7%), with baseline glycated hemoglobin (HbA) <6.5% (<48 mmol/mol; acromegaly 98.9%, CD 100%) and fasting plasma glucose (FPG) <100 mg/dL (<5.6 mmol/L; acromegaly 76.1%, CD 100%). By logistic regression, increasing baseline HbA (odds ratio [OR] 3.6; =0.0162) and FPG (OR 1.0; =0.0472) and history of diabetes/pre-diabetes (OR 3.0; =0.0221) predicted receipt of antihyperglycemic medication in acromegaly participants; increasing baseline HbA (OR 12.6; =0.0276) was also predictive in CD participants. Investigator-reported hyperglycemia-related adverse events were recorded in 47.9% and 54.2% of acromegaly and CD participants, respectively, mainly those with diabetes/pre-diabetes.
CONCLUSION
Increasing age, HbA, and FPG and pre-diabetes/diabetes were associated with increased likelihood of requiring antihyperglycemic medication during pasireotide treatment. These risk factors may be used to identify those who need more vigilant monitoring to optimize outcomes during pasireotide treatment.
Topics: Humans; Acromegaly; Blood Glucose; Diabetes Mellitus; Hyperglycemia; Hypoglycemic Agents; Insulin; Metformin; Pituitary ACTH Hypersecretion; Prediabetic State; Prospective Studies; Somatostatin
PubMed: 38577574
DOI: 10.3389/fendo.2024.1250822 -
Best Practice & Research. Clinical... Mar 2024Although predictors of response to first-generation somatostatin receptor ligands (fg-SRLs), and to a lesser extent to pasireotide, have been studied in acromegaly for... (Review)
Review
Although predictors of response to first-generation somatostatin receptor ligands (fg-SRLs), and to a lesser extent to pasireotide, have been studied in acromegaly for many years, their use is still not recommended in clinical guidelines. Is there insufficient evidence to use them? Numerous biomarkers including various clinical, functional, radiological and molecular markers have been identified. The first ones are applicable pre-surgery, while the molecular predictors are utilized for patients not cured after surgery. In this regard, factors predicting a good response to fg-SRLs are specifically: low basal GH, a low GH nadir in the acute octreotide test, T2 MRI hypointensity, a densely granulated pattern, high immunohistochemistry staining for somatostatin receptor 2 (SSTR2), and E-cadherin. However, there is still a lack of consensus regarding which of these biomarkers is more useful or how to integrate them into clinical practice. With classical statistical methods, it is complex to define reliable and generalizable cut-off values for a single biomarker. The potential solution to the limitations of traditional methods involves combining systems biology with artificial intelligence, which is currently providing answers to such long-standing questions that may eventually be finally included into the clinical guidelines and make personalized medicine a reality. The aim of this review is to describe the current knowledge of the main fg-SRLs and pasireotide response predictors, discuss their current usefulness, and point to future directions in the research of this field.
PubMed: 38575404
DOI: 10.1016/j.beem.2024.101893 -
Oman Medical Journal Jan 2024To estimate the incidence of pituitary adenomas (PA) in adult Omani patients and describe its epidemiological, clinical, and radiological characteristics.
OBJECTIVES
To estimate the incidence of pituitary adenomas (PA) in adult Omani patients and describe its epidemiological, clinical, and radiological characteristics.
METHODS
In this longitudinal, descriptive study, we reviewed the records of all PA patients from January 2015 to January 2020 who presented at the endocrinology facilities at Sultan Qaboos University Hospital, Muscat.
RESULTS
The participants comprised of 112 Omani patients with PA. The incidence of PA among all adult patients at Sultan Qaboos University Hospital (inpatient and outpatient) over five years (2015-2020) was 0.23%. The cohort had a mean age of 41.0±15.0 years. Of the 112 patients included in this study, 79 (70.5%) were women. Nearly half (51; 45.5%) of adenomas were prolactinomas while 46 (41.1%) were non-functioning adenomas, and seven (6.3%) were growth hormone-secreting adenomas while six (5.4%) were adrenocorticotropic hormone secreting adenomas. Headache was present in 67 (59.8%) patients, followed by visual field defects (40; 35.7%), galactorrhea (26; 23.2%), and fatigue (19; 17.0%). The majority of women (45/79; 57.0%) presented with menstrual cycle abnormalities. Radiological appearances were nearly equally distributed between micro- and macroadenomas. Most cases (58/112; 52.0%) of PA were treated medically by cabergoline, octreotide, and replacement therapies such as hydrocortisone and thyroxin, 38 (33.9%) were treated surgically (mainly by trans-sphenoidal pituitary resection), and the remaining 10 (8.9%) cases were subjected to radiotherapy. Medical treatment combined with surgery was employed for 15 (13.4%) patients.
CONCLUSIONS
In our investigation, PA was primarily prevalent among Omani female patients, and the most common subtype of pituitary tumors was prolactinomas. The most common presentation symptom was headaches; most female patients had menstrual irregularities. Medical treatment was the primary approach for the applicable types of PAs, while surgery and radiotherapy were found to be secondary and tertiary treatment options, respectively.
PubMed: 38567166
DOI: 10.5001/omj.2024.44 -
Case Reports in Endocrinology 2024We present a case of acromegaly associated with Arnold-Chiari 1 malformation and a literature review regarding this association, mainly focusing on the importance of a...
We present a case of acromegaly associated with Arnold-Chiari 1 malformation and a literature review regarding this association, mainly focusing on the importance of a clear distinction between Chiari malformation and herniation of cerebellar tonsils (CTH). Indeed, in many clinical cases, this distinction has not been properly made and a better description of the radiological findings could be important for the clinical management of these patients. In fact, Arnold-Chiari 1 malformation, as a congenital disease, is not caused by acquired growth hormone (GH) excess, but the latter could worsen pre-existing CTH or even induce it . Therefore, awareness of this condition in the clinical management of acromegaly appears crucial.
PubMed: 38550571
DOI: 10.1155/2024/4733399 -
Quantitative Imaging in Medicine and... Mar 2024Facial anthropometry based on 3-dimensional (3D) imaging technology, or 3D photogrammetry, has gained increasing popularity among surgeons. It outperforms direct...
BACKGROUND
Facial anthropometry based on 3-dimensional (3D) imaging technology, or 3D photogrammetry, has gained increasing popularity among surgeons. It outperforms direct measurement and 2-dimensional (2D) photogrammetry because of many advantages. However, a main limitation of 3D photogrammetry is the time-consuming process of manual landmark localization. To address this problem, this study developed a U-NET-based deep learning algorithm to enable automated and accurate anatomical landmark detection on 3D facial models.
METHODS
The main structure of the algorithm stacked 2 U-NETs. In each U-NET block, we used 3×3 convolution kernel and rectified linear unit (ReLU) as activation function. A total of 200 3D images of healthy cases, acromegaly patients, and localized scleroderma patients were captured by Vectra H1 handheld 3D camera and input for algorithm training. The algorithm was tested to detect 20 landmarks on 3D images. Percentage of correct key points (PCK) and normalized mean error (NME) were used to evaluate facial landmark detection accuracy.
RESULTS
Among healthy cases, the average NME was 1.4 mm. The PCK reached 90% when the threshold was set to the clinically acceptable limit of 2 mm. The average NME was 2.8 and 2.2 mm among acromegaly patients and localized scleroderma patients, respectively.
CONCLUSIONS
This study developed a deep learning algorithm for automated facial landmark detection on 3D images. The algorithm was innovatively validated in 3 different groups of participants. It achieved accurate landmark detection and improved the efficiency of 3D image analysis.
PubMed: 38545057
DOI: 10.21037/qims-22-1108 -
Best Practice & Research. Clinical... May 2024It is usually considered that only 5% of all pituitary neuroendocrine tumours are due to inheritable causes. Since this estimate was reported, however, multiple genetic... (Review)
Review
It is usually considered that only 5% of all pituitary neuroendocrine tumours are due to inheritable causes. Since this estimate was reported, however, multiple genetic defects driving syndromic and nonsyndromic somatotrophinomas have been unveiled. This heterogeneous genetic background results in overlapping phenotypes of GH excess. Genetic tests should be part of the approach to patients with acromegaly and gigantism because they can refine the clinical diagnoses, opening the possibility to tailor the clinical conduct to each patient. Even more, genetic testing and clinical screening of at-risk individuals have a positive impact on disease outcomes, by allowing for the timely detection and treatment of somatotrophinomas at early stages. Future research should focus on determining the actual frequency of novel genetic drivers of somatotrophinomas in the general population, developing up-to-date disease-specific multi-gene panels for clinical use, and finding strategies to improve access to modern genetic testing worldwide.
Topics: Humans; Acromegaly; Gigantism; Genetic Testing; Pituitary Neoplasms; Growth Hormone-Secreting Pituitary Adenoma
PubMed: 38521632
DOI: 10.1016/j.beem.2024.101892 -
Frontiers in Surgery 2024We aimed to investigate empty sella syndrome in somatotrophic pituitary adenoma for possible etiology, complications, and treatment options.
PURPOSE
We aimed to investigate empty sella syndrome in somatotrophic pituitary adenoma for possible etiology, complications, and treatment options.
METHOD
Among over 2,000 skull base masses that have been managed in our center since 2013, we searched for growth hormone-producing adenomas. Clinical, surgical, and imaging data were retrospectively collected from hospital records to check for sella that lacked pituitary tissue on routine imaging.
RESULT
In 220 somatotrophic adenomas, 23 patients had an empty sella with surgical and follow-up data. The mean age of the sample was 46 years with the same male-to-female ratio. Five cases had partial empty sella and the rest were complete empty sellas. The most common simultaneous hormonal disturbance was high prolactin levels. Six had adenoma invasion into the clivus or sphenoid sinus and 10 had cavernous sinus intrusion. Peri-operative low-flow and high-flow cerebrospinal fluid (CSF) leaks were encountered in one and two patients, respectively, which were successfully sealed by abdominal fat. The majority of cases required growth hormone replacement therapy while it was controlled without any replacement therapy in nine patients. No pituitary hormonal disturbance occurred after transsphenoidal surgery except for hypothyroidism in one patient.
CONCLUSION
An empty sella filled with fluid can be detected frequently in pituitary adenomas, especially in the setting of acromegaly. The pituitary gland may be pushed to the roof of the sella and might be visible as a narrow rim on imaging or may be detected in unusual places out of the sella. The pathophysiology behind such finding originates from soft and hard tissue changes and CSF pressure alternations during abundant growth hormone production.
PubMed: 38500594
DOI: 10.3389/fsurg.2024.1350032 -
Scientific Reports Mar 2024Acromegaly is a rare disease characterized by a diagnostic delay ranging from 5 to 10 years from the symptoms' onset. The aim of this study was to develop and internally...
Machine learning-based algorithms applied to drug prescriptions and other healthcare services in the Sicilian claims database to identify acromegaly as a model for the earlier diagnosis of rare diseases.
Acromegaly is a rare disease characterized by a diagnostic delay ranging from 5 to 10 years from the symptoms' onset. The aim of this study was to develop and internally validate machine-learning algorithms to identify a combination of variables for the early diagnosis of acromegaly. This retrospective population-based study was conducted between 2011 and 2018 using data from the claims databases of Sicily Region, in Southern Italy. To identify combinations of potential predictors of acromegaly diagnosis, conditional and unconditional penalized multivariable logistic regression models and three machine learning algorithms (i.e., the Recursive Partitioning and Regression Tree, the Random Forest and the Support Vector Machine) were used, and their performance was evaluated. The random forest (RF) algorithm achieved the highest Area under the ROC Curve value of 0.83 (95% CI 0.79-0.87). The sensitivity in the test set, computed at the optimal threshold of predicted probabilities, ranged from 28% for the unconditional logistic regression model to 69% for the RF. Overall, the only diagnosis predictor selected by all five models and algorithms was the number of immunosuppressants-related pharmacy claims. The other predictors selected by at least two models were eventually combined in an unconditional logistic regression to develop a meta-score that achieved an acceptable discrimination accuracy (AUC = 0.71, 95% CI 0.66-0.75). Findings of this study showed that data-driven machine learning algorithms may play a role in supporting the early diagnosis of rare diseases such as acromegaly.
Topics: Humans; Rare Diseases; Retrospective Studies; Acromegaly; Delayed Diagnosis; Algorithms; Machine Learning; Drug Prescriptions; Early Diagnosis; Sicily
PubMed: 38485706
DOI: 10.1038/s41598-024-56240-w