-
The Journal of Clinical Endocrinology... Apr 2022Insight into the current landscape of patient-reported outcome (PRO) measures (PROM) and differences between PROs and conventional biochemical outcomes is pivotal for... (Meta-Analysis)
Meta-Analysis
CONTEXT
Insight into the current landscape of patient-reported outcome (PRO) measures (PROM) and differences between PROs and conventional biochemical outcomes is pivotal for future implementation of PROs in research and clinical practice. Therefore, in studies among patients with acromegaly and growth hormone deficiency (GHD), we evaluated (1) used PROMs, (2) their validity, (3) quality of PRO reporting, (4) agreement between PROs and biochemical outcomes, and (5) determinants of discrepancies.
EVIDENCE ACQUISITION
We searched 8 electronic databases for prospective studies describing both PROs and biochemical outcomes in acromegaly and GHD patients. Quality of PRO reporting was assessed using the International Society for Quality of Life Research (ISOQOL) criteria. Logistic regression analysis was used to evaluate determinants.
EVIDENCE SYNTHESIS
Ninety studies were included (acromegaly: n = 53; GHD: n = 37). Besides nonvalidated symptom lists (used in 37% of studies), 36 formal PROMs were used [predominantly Acromegaly Quality of Life Questionnaire in acromegaly (43%) and Quality of Life-Assessment of Growth Hormone Deficiency in Adults in GHD (43%)]. Reporting of PROs was poor, with a median of 37% to 47% of ISOQOL items being reported per study. Eighteen (34%) acromegaly studies and 12 (32%) GHD studies reported discrepancies between PROs and biochemical outcomes, most often improvement in biochemical outcomes without change in PROs.
CONCLUSIONS
Prospective studies among patients with acromegaly and GHD use a multitude of PROMs, often poorly reported. Since a substantial proportion of studies report discrepancies between PROs and biochemical outcomes, PROMs are pivotal in the evaluation of disease activity. Therefore, harmonization of PROs in clinical practice and research by development of core outcome sets is an important unmet need.
Topics: Acromegaly; Adult; Human Growth Hormone; Humans; Patient Reported Outcome Measures; Prospective Studies; Quality of Life
PubMed: 34871425
DOI: 10.1210/clinem/dgab874 -
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 -
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 2021Epithelial-mesenchymal transition (EMT) is a dynamic process by which epithelial cells loss their phenotype and acquire mesenchymal traits, including increased migratory...
Epithelial-mesenchymal transition (EMT) is a dynamic process by which epithelial cells loss their phenotype and acquire mesenchymal traits, including increased migratory and invasive capacities. EMT is involved in physiological processes, such as embryogenesis and wound healing, and in pathological processes such as cancer, playing a pivotal role in tumor progression and metastasis. Pituitary tumors, although typically benign, can be locally invasive. Different studies have shown the association of EMT with increased tumor size and invasion in pituitary tumors, and in particular with a poor response to Somatostatin Receptor Ligands (SRLs) treatment in GH-producing pituitary tumors, the main cause of acromegaly. This review will summarize the current knowledge regarding EMT and SRLs resistance in acromegaly and, based on this relation, will suggest new biomarkers and possible therapies to SRLs resistant tumors.
Topics: Acromegaly; Biomarkers; Cadherins; Cytoskeleton; Drug Resistance; Endocrine Gland Neoplasms; Epithelial-Mesenchymal Transition; Growth Hormone-Secreting Pituitary Adenoma; Humans; Ligands; Phenotype; Pituitary Neoplasms; Receptors, Somatostatin; Somatostatin
PubMed: 33790868
DOI: 10.3389/fendo.2021.646210 -
Endocrine Mar 2023A systematic literature review was conducted to assess the use of home injections (self/partner/healthcare provider [HCP]-administered) of somatostatin analogs (SSAs) as...
PURPOSE
A systematic literature review was conducted to assess the use of home injections (self/partner/healthcare provider [HCP]-administered) of somatostatin analogs (SSAs) as an alternative to healthcare-setting injections in patients with acromegaly and neuroendocrine tumors (NETs).
METHODS
MEDLINE/Embase/the Cochrane Library (2001-September 2021), key congresses (2019-2021), and bibliographies of relevant systematic reviews were searched. Eligible studies reported on efficacy/effectiveness, safety, adherence, patient-reported outcomes (PROs), and economic outcomes in populations receiving home injections of SSAs.
RESULTS
Overall, 12 studies were included, all reporting on SSAs (lanreotide Autogel/Depot or octreotide long-acting release) in acromegaly or NETs. Across four studies, home injection was associated with similar disease control in patients with acromegaly/NETs compared with healthcare-setting administration. High rates of treatment adherence were shown in two studies of patients with acromegaly receiving lanreotide injections at home. Two studies reported non-serious adverse events; incidence of adverse reactions was similar in both the home and healthcare administration settings. Preference for injection setting varied between studies and indications; nonetheless, higher satisfaction/convenience (>75% patients) was reported for home injections. Self- or partner-injection was associated with economic savings compared with administration in the healthcare setting across five studies.
CONCLUSION
Efficacy/effectiveness, adherence, and safety outcomes of SSAs in the home injection setting were similar to those in the healthcare setting, with high reported satisfaction and convenience. Self/partner injection also resulted in cost savings. These findings provide a basis to understand outcomes related to home injection and encourage healthcare providers to discuss optimal treatment choices with their patients.
Topics: Humans; Somatostatin; Acromegaly; Peptides, Cyclic; Octreotide; Injections, Subcutaneous; Neuroendocrine Tumors
PubMed: 36369434
DOI: 10.1007/s12020-022-03227-0 -
Scientific Reports Oct 2019Biochemical remission after transsphenoidal surgery is still unsatisfied in acromegaly patients with macroadenomas, especially with invasive macroadenomas. Concerning... (Comparative Study)
Comparative Study Meta-Analysis
Biochemical remission after transsphenoidal surgery is still unsatisfied in acromegaly patients with macroadenomas, especially with invasive macroadenomas. Concerning the impact of preoperative somatostatin analogues (SSAs) on surgical outcomes, previous studies with limited cases reported conflicting results. To assess current evidence of preoperative medical treatment, we performed a systematic review and meta-analysis of comparative studies. A literature search was conducted in Pubmed, Embase, and the Cochrane Library. Five randomized controlled trials (RCT) and seven non-RCT comparative studies were included. These studies mainly focused on pituitary macroadenomas though a small number of microadenoma cases were included. For safety, preoperative SSAs were not associated with elevated risks of postoperative complications. With respect to efficacy, the short-term cure rate was improved by preoperative SSAs, but the long-term cure rate showed no significant improvement. For invasive macroadenomas, the short-term cure rate was also improved, but the long-term results were not evaluable in clinical practice because adjuvant therapy was generally required. In conclusion, preoperative SSAs are safe in patients with acromegaly, and the favorable impact on surgical results is restricted to the short-term cure rate in macroadenomas and invasive macroadenomas. Further well-designed RCTs to examine long-term results are awaited to update the finding of this meta-analysis.
Topics: Acromegaly; Combined Modality Therapy; Growth Hormone-Secreting Pituitary Adenoma; Humans; Somatostatin; Treatment Outcome
PubMed: 31575930
DOI: 10.1038/s41598-019-50639-6 -
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 -
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 -
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