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Frontiers in Endocrinology 2024Acromegaly is a rare endocrine disorder caused by hypersecretion of growth hormone (GH) from a pituitary adenoma. Elevated GH levels stimulate excess production of...
UNLABELLED
Acromegaly is a rare endocrine disorder caused by hypersecretion of growth hormone (GH) from a pituitary adenoma. Elevated GH levels stimulate excess production of insulin-like growth factor 1 (IGF-1) which leads to the insidious onset of clinical manifestations. The most common primary central nervous system (CNS) tumors, meningiomas originate from the arachnoid layer of the meninges and are typically benign and slow-growing. Meningiomas are over twice as common in women as in men, with age-adjusted incidence (per 100,000 individuals) of 10.66 and 4.75, respectively. Several reports describe co-occurrence of meningiomas and acromegaly. We aimed to determine whether patients with acromegaly are at elevated risk for meningioma. Investigation of the literature showed that co-occurrence of a pituitary adenoma and a meningioma is a rare phenomenon, and the majority of cases involve GH-secreting adenomas. To the best of our knowledge, a systematic review examining the association between meningiomas and elevated GH levels (due to GH-secreting adenomas in acromegaly or exposure to exogenous GH) has never been conducted. The nature of the observed coexistence between acromegaly and meningioma -whether it reflects causation or mere co-association -is unclear, as is the pathophysiologic etiology.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/, identifier CRD42022376998.
Topics: Humans; Meningioma; Acromegaly; Meningeal Neoplasms; Human Growth Hormone; Risk Factors; Adenoma
PubMed: 38919490
DOI: 10.3389/fendo.2024.1407615 -
Pituitary Jun 2024Prolactinomas are common tumours that significantly reduce quality-of-life (QOL) due to sellar mass effect, secondary hypogonadism, and the peripheral effects of...
BACKGROUND
Prolactinomas are common tumours that significantly reduce quality-of-life (QOL) due to sellar mass effect, secondary hypogonadism, and the peripheral effects of prolactin. Understanding the factors that influence QOL would provide insights into therapeutic targets to optimise patient outcomes and improve wellbeing in prolactinoma.
METHODS
A systematic review was performed in accordance with the PRISMA statement. Studies that reported patient QoL using validated metrics were included. Bias and methodological rigour were assessed using the MINORS criteria.
RESULTS
A total of 18 studies were identified studies were available for review, comprising 877 patients. Most were small cross-sectional studies at high risk of bias. Prolactinoma exhibit worse QOL than healthy controls, particularly mental and psychosocial wellbeing. QOL is also worse than patients with non-functional adenomas, but better than those with Cushing's disease and acromegaly. QOL correlates with prolactin levels, and approaches population baseline with prolonged biochemical control. Dopamine agonists and surgery both improve overall QOL, however improvements are more rapid with surgery.
CONCLUSION
Poor quality of life in prolactinoma is multifactorial, related to biochemical control, side effects of therapy, and sellar mass effect. Targeting persistent symptoms, reducing healthcare costs, and reducing side-effects of therapy are avenues to improving QOL in patients with prolactinoma.
Topics: Prolactinoma; Humans; Quality of Life; Pituitary Neoplasms; Dopamine Agonists
PubMed: 38656635
DOI: 10.1007/s11102-024-01392-1 -
Frontiers in Endocrinology 2024Double pituitary adenomas (DPA) are a rare clinical condition, and our knowledge of them is limited. Missing the second lesion leading to incomplete biochemical...
OBJECTIVE
Double pituitary adenomas (DPA) are a rare clinical condition, and our knowledge of them is limited. Missing the second lesion leading to incomplete biochemical remission after surgery is an important challenge in DPA management. This study aims to analyze independent prognostic factors in DPA patients and summarize clinical experiences to prevent surgical failure.
METHODS
Two cases of DPA patients with Cushing's disease diagnosed and surgically treated at Peking Union Medical College Hospital are reported. A literature review was performed on the online database Pubmed, and 57 DPA patients from 22 retrieved articles were included. Demographic characteristics, endocrine manifestations, diagnostic methods, tumor size, and immunohistochemical features of 59 patients were analyzed. Binary logistic regression models were used to identify independent prognostic factors affecting postoperative biochemical remission.
RESULTS
Among 59 DPA patients, the mean ± SD age was 43.64 ± 14.42 years, with 61.02% being female (n = 36). The most common endocrine manifestations were Cushing's syndrome (23/59, 38.98%) and acromegaly (20/59, 33.90%). The most prevalent immunohistochemical types were ACTH-immunopositive (31/118, 26.27%) and GH-immunopositive (31/118, 26.27%) tumors. Microadenomas (<1cm) were the most frequent in terms of tumor size (62/92, 67.39%). The detection rate for double lesions on 3.0T MRI was 50.00% (14/28), which significantly higher than 1.5T MRI (P = 0.034). Univariate analysis revealed that female, Cushing's syndrome and only single lesion detected by surgical exploration were associated with significantly worse prognosis (P<0.05). Multivariate analysis identified double lesion detected by surgical exploration (OR = 0.08, P = 0.003) and contiguous type tumor (OR = 0.06, P = 0.017) as independent protective factors for DPA patients.
CONCLUSIONS
The double lesion detected by surgical exploration is independently associated with a better prognosis for DPA patients. Comprehensive intraoperative exploration are crucial measures to avoid missing causative lesions.
Topics: Adult; Female; Humans; Male; Middle Aged; Acromegaly; Adenoma; Cushing Syndrome; Pituitary ACTH Hypersecretion; Pituitary Neoplasms
PubMed: 38628582
DOI: 10.3389/fendo.2024.1373869 -
BMC Endocrine Disorders Jan 2024Management of recurrent acromegaly is challenging for both neurosurgeons and endocrinologists. Several treatment options including repeat surgery, medical therapy, and...
BACKGROUND AND OBJECTIVE
Management of recurrent acromegaly is challenging for both neurosurgeons and endocrinologists. Several treatment options including repeat surgery, medical therapy, and radiation are offered for such patients. The efficacy of these modalities for the treatment of recurrence has not been studied previously in the literature. In this study, we aim to systematically review the existing cases of recurrence and come to a conclusion regarding the appropriate treatment in such cases.
METHOD
A systematic review was performed through PubMed, Scopus, Web of Science, and Cochrane database to identify studies reporting the treatment outcome of recurrent acromegaly patients. Using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, the included studies were reviewed for primary and secondary treatment, complications, and outcomes of the secondary treatment.
RESULTS
The systematic review retrieved 23 records with 95 cases of recurrent acromegaly. The mean time of recurrence was 4.16 years after the initial treatment. The most common primary treatment was surgery followed by radiotherapy. The remission rate was significantly higher in medical and radiotherapy compared to surgical treatment.
CONCLUSION
In cases of recurrent acromegaly, the patient may benefit more from radiotherapy and medical therapy compared to surgery. As the quality of evidence is low on this matter feature studies specifically designed for recurrent patients are needed.
Topics: Humans; Acromegaly; Treatment Outcome; Reoperation
PubMed: 38279102
DOI: 10.1186/s12902-023-01533-w -
PloS One 2023The incidence of cancer in acromegaly patients may be higher than that in the general population, although this has not been fully elucidated yet. This study analyzed... (Meta-Analysis)
Meta-Analysis
The incidence of cancer in acromegaly patients may be higher than that in the general population, although this has not been fully elucidated yet. This study analyzed the risk of various important types of cancer in acromegaly patients. The study was registered in INPLASY (registration number: INPLASY202340037). The PubMed, Web of Science, and EMBASE databases were searched for studies based on strict inclusion and exclusion criteria, from the time of database inception up to June 30, 2022. All observational studies of acromegaly patients with cancer were included, without language restrictions. We used the Newcastle-Ottawa scale (NOS) checklist to assess the quality of evidence. A meta-analysis revealed the relationship between acromegaly and cancer using the standardized incidence rates (SIRs) and 95% confidence intervals (CIs) retrieved from the included studies. Nineteen studies were included and analyzed. The overall incidence of cancer (SIR = 1.45, 95%CI = 1.20-1.75), as well as that of thyroid (SIR = 6.96, 95%CI = 2.51-19.33), colorectal and anal (SIR = 1.95, 95%CI = 1.32-2.87), brain and central nervous system (SIR = 6.14, 95%CI = 2.73-13.84), gastric (SIR = 3.09, 95%CI = 1.47-6.50), urinary (SIR = 2.66, 95%CI = 1.88-3.76), hematological (SIR = 1.89, 95%CI = 1.17-3.06), pancreatic and small intestine (SIR = 2.59, 95%CI = 1.58-4.24), and connective tissue (SIR = 3.15, 95%CI = 1.18-8.36) cancers, was higher among patients with acromegaly than among the general population. No association between acromegaly and hepatobiliary, respiratory, reproductive, skin, breast, or prostate cancer was observed. This study demonstrated that acromegaly patients have a modestly increased chance of cancer as compared to the general population. Risk factors for cancer need to be further explored to monitor patients with acromegaly at a high risk for cancer more carefully.
Topics: Male; Humans; Acromegaly; Neoplasms; Risk Factors; Incidence; Prostatic Neoplasms; Skin
PubMed: 38032888
DOI: 10.1371/journal.pone.0285335 -
Journal of Neurological Surgery. Part... Dec 2023The purpose of this analysis is to assess the use of machine learning (ML) algorithms in the prediction of postoperative outcomes, including complications, recurrence,...
The purpose of this analysis is to assess the use of machine learning (ML) algorithms in the prediction of postoperative outcomes, including complications, recurrence, and death in transsphenoidal surgery. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically reviewed all papers that used at least one ML algorithm to predict outcomes after transsphenoidal surgery. We searched Scopus, PubMed, and Web of Science databases for studies published prior to May 12, 2021. We identified 13 studies enrolling 5,048 patients. We extracted the general characteristics of each study; the sensitivity, specificity, area under the curve (AUC) of the ML models developed as well as the features identified as important by the ML models. We identified 12 studies with 5,048 patients that included ML algorithms for adenomas, three with 1807 patients specifically for acromegaly, and five with 2105 patients specifically for Cushing's disease. Nearly all were single-institution studies. The studies used a heterogeneous mix of ML algorithms and features to build predictive models. All papers reported an AUC greater than 0.7, which indicates clinical utility. ML algorithms have the potential to predict postoperative outcomes of transsphenoidal surgery and can improve patient care. Ensemble algorithms and neural networks were often top performers when compared with other ML algorithms. Biochemical and preoperative features were most likely to be selected as important by ML models. Inexplicability remains a challenge, but algorithms such as local interpretable model-agnostic explanation or Shapley value can increase explainability of ML algorithms. Our analysis shows that ML algorithms have the potential to greatly assist surgeons in clinical decision making.
PubMed: 37854535
DOI: 10.1055/a-1941-3618 -
BMC Medical Research Methodology May 2023There is a pressing need to improve the accuracy of rare disease clinical study endpoints. Neutral theory, first described here, can be used to assess the accuracy of...
BACKGROUND
There is a pressing need to improve the accuracy of rare disease clinical study endpoints. Neutral theory, first described here, can be used to assess the accuracy of endpoints and improve their selection in rare disease clinical studies, reducing the risk of patient misclassification.
METHODS
Neutral theory was used to assess the accuracy of rare disease clinical study endpoints and the resulting probability of false positive and false negative classifications at different disease prevalence rates. Search strings were extracted from the Orphanet Register of Rare Diseases using a proprietary algorithm to conduct a systematic review of studies published until January 2021. Overall, 11 rare diseases with one disease-specific disease severity scale (133 studies) and 12 rare diseases with more than one disease-specific disease severity scale (483 studies) were included. All indicators from clinical studies were extracted, and Neutral theory was used to calculate their match to disease-specific disease severity scales, which were used as surrogates for the disease phenotype. For those with more than one disease-severity scale, endpoints were compared with the first disease-specific disease severity scale and a composite of all later scales. A Neutrality score of > 1.50 was considered acceptable.
RESULTS
Around half the clinical studies for half the rare diseases with one disease-specific disease severity score (palmoplantar psoriasis, achalasia, systemic lupus erythematosus, systemic sclerosis and Fournier's gangrene) met the threshold for an acceptable match to the disease phenotype, one rare disease (Guillain-Barré syndrome) had one study with an acceptable match, and four diseases (Behcet's syndrome, Creutzfeldt-Jakob disease, atypical hemolytic uremic syndrome and Prader-Willi syndrome) had no studies. Clinical study endpoints in almost half the rare diseases with more than one disease-specific DSS (acromegaly, amyotrophic lateral sclerosis, cystic fibrosis, Fabry disease and juvenile rheumatoid arthritis) were a better match to the composite, while endpoints in the remaining rare diseases (Charcot Marie Tooth disease, Gaucher disease Type I, Huntington's disease, Sjogren's syndrome and Tourette syndrome) were a worse match. Misclassifications varied with increasing disease prevalence.
CONCLUSIONS
Neutral theory confirmed that disease-severity measurement needs improvement in rare disease clinical studies, especially for some diseases, and suggested that the potential for accuracy increases as the body of knowledge on a disease increases. Using Neutral theory to benchmark disease-severity measurement in rare disease clinical studies may reduce the risk of misclassification, ensuring that recruitment and treatment effect assessment optimise medicine adoption and benefit patients.
Topics: Humans; Rare Diseases; Endpoint Determination; Clinical Studies as Topic
PubMed: 37210484
DOI: 10.1186/s12874-023-01947-z -
Pituitary Aug 2023Diagnostic delay is high in acromegaly and leads to increased morbidity and mortality. The aim of this study is to systematically assess the most prevalent clinical... (Review)
Review
OBJECTIVE
Diagnostic delay is high in acromegaly and leads to increased morbidity and mortality. The aim of this study is to systematically assess the most prevalent clinical signs, symptoms and comorbidities of acromegaly at time of diagnosis.
DESIGN
A literature search (in PubMed, Embase and Web of Science) was performed on November 18, 2021, in collaboration with a medical information specialist.
METHODS
Prevalence data on (presenting) clinical signs, symptoms and comorbidities at time of diagnosis were extracted and synthesized as weighted mean prevalence. The risk of bias was assessed for each included study using the Joanna Briggs Institute Critical Appraisal Checklist for Studies Reporting Prevalence Data.
RESULTS
Risk of bias and heterogeneity was high in the 124 included articles. Clinical signs and symptoms with the highest weighted mean prevalence were: acral enlargement (90%), facial features (65%), oral changes (62%), headache (59%), fatigue/tiredness (53%; including daytime sleepiness: 48%), hyperhidrosis (47%), snoring (46%), skin changes (including oily skin: 37% and thicker skin: 35%), weight gain (36%) and arthralgia (34%). Concerning comorbidities, acromegaly patients more frequently had hypertension, left ventricle hypertrophy, dia/systolic dysfunction, cardiac arrhythmias, (pre)diabetes, dyslipidemia and intestinal polyps- and malignancy than age- and sex matched controls. Noteworthy, cardiovascular comorbidity was lower in more recent studies. Features that most often led to diagnosis of acromegaly were typical physical changes (acral enlargement, facial changes and prognatism), local tumor effects (headache and visual defect), diabetes, thyroid cancer and menstrual disorders.
CONCLUSION
Acromegaly manifests itself with typical physical changes but also leads to a wide variety of common comorbidities, emphasizing that recognition of a combination of these features is key to establishing the diagnosis.
Topics: Humans; Acromegaly; Prevalence; Delayed Diagnosis; Comorbidity; Headache; Hypertension; Diabetes Mellitus
PubMed: 37210433
DOI: 10.1007/s11102-023-01322-7 -
Brain Sciences Mar 2023The complex nature and heterogeneity involving pituitary surgery results have increased interest in machine learning (ML) applications for prediction of outcomes over... (Review)
Review
BACKGROUND
The complex nature and heterogeneity involving pituitary surgery results have increased interest in machine learning (ML) applications for prediction of outcomes over the last decade. This study aims to systematically review the characteristics of ML models involving pituitary surgery outcome prediction and assess their reporting quality.
METHODS
We searched the PubMed, Scopus, and Web of Knowledge databases for publications on the use of ML to predict pituitary surgery outcomes. We used the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) to assess report quality. Our search strategy was based on the terms "artificial intelligence", "machine learning", and "pituitary".
RESULTS
20 studies were included in this review. The principal models reported in each article were post-surgical endocrine outcomes ( = 10), tumor management ( = 3), and intra- and postoperative complications ( = 7). Overall, the included studies adhered to a median of 65% (IQR = 60-72%) of TRIPOD criteria, ranging from 43% to 83%. The median reported AUC was 0.84 (IQR = 0.80-0.91). The most popular algorithms were support vector machine ( = 5) and random forest ( = 5). Only two studies reported external validation and adherence to any reporting guideline. Calibration methods were not reported in 15 studies. No model achieved the phase of actual clinical applicability.
CONCLUSION
Applications of ML in the prediction of pituitary outcomes are still nascent, as evidenced by the lack of any model validated for clinical practice. Although studies have demonstrated promising results, greater transparency in model development and reporting is needed to enable their use in clinical practice. Further adherence to reporting guidelines can help increase AI's real-world utility and improve clinical practice.
PubMed: 36979305
DOI: 10.3390/brainsci13030495 -
Journal of Clinical Medicine Dec 2022Acromegaly is characterized by a very particular alteration of bone microarchitecture, leading to increased vertebral fragility. However, due to inconsistent and... (Review)
Review
INTRODUCTION
Acromegaly is characterized by a very particular alteration of bone microarchitecture, leading to increased vertebral fragility. However, due to inconsistent and insufficient evidence, no guidelines are available for the evaluation of this osteopathy.
METHODS
We performed a literature review of studies published between 1968 and January 2022 on the PubMed and SCOPUS databases using the terms "acromegaly" and "vertebral fractures". Twenty-four studies were found eligible for inclusion, published between June 2005 and November 2021. Included studies evaluated acromegaly patients, who were assessed for the presence of vertebral fractures. We excluded case reports, reviews, meta-analyses, letters to the editor, articles not written in English, and research performed on the same set of patients without significant differences in study design. Risk of bias was avoided by following the ROBIS risk of bias recommendations. We executed rigorous data collection, and the results are depicted as a narrative overview, but also, as statistical synthesis. Limitations of the evidence presented in the study include study heterogeneity, small sample sizes, and a small number of prospective studies with short follow-up.
FINDINGS
Data regarding vertebral fractures (VFs) in acromegaly and their influencing factors are variable. Twenty-four studies were included, nine out of which had a prospective design. The smallest group of acromegaly patients had 18 subjects and the largest included 248 patients. Prevalence ranges between 6.5% and 87.1%, although most studies agree that it is significantly higher than in controls. VFs also have a higher incidence (between 5.6% and 42%) and are more frequently multiple (between 46.15% and 71%). Evidence shows that disease activity and active disease duration are influencing factors for the prevalence and incidence of VFs. Nonetheless, hypogonadism does not seem to influence the frequency of VFs. While reports are conflicting regarding the use of bone mineral density in acromegaly, evidence seems to be slightly in favor of it not being associated with VFs. However, trabecular bone score is significantly lower in fractured patients, although no prospective studies are available.
INTERPRETATION
Vertebral fractures evaluation should be performed with regularity in all acromegalic patients, especially in the presence of active disease. Disease activity is an important determinant of vertebral fracture incidence and prevalence, although hypogonadism is less so. To clarify the predictive value of both BMD and TBS for vertebral fractures, additional, larger, prospective studies are necessary.
PubMed: 36614962
DOI: 10.3390/jcm12010164