Value of Early Post-Operative Growth Hormone Testing in Predicting Long-Term Remission and Residual Disease after Transsphenoidal Surgery for Acromegaly

Time to first remission and survival in patients with acromegaly: Evidence from the UK Acromegaly Register Study (UKAR)

OBJECTIVE

This study aimed to understand the effect of time to remission of acromegaly on survival in people living with acromegaly.

DESIGN, PATIENTS AND MEASUREMENT

This cross-sectional study used data from the UK Acromegaly Register. We considered remission of acromegaly growth hormone controlled at ≤2 μg/L following the diagnosis of acromegaly. We used the accelerated failure time model to assess the effect of time to remission on survival in acromegaly.

RESULTS

The study population comprises 3569 individuals with acromegaly, with a median age of diagnosis of 47.3 (36.5-57.8) years, 48% females and a majority white population (61%). The number of individuals with the first remission of acromegaly was 2472, and the median time to first remission was 1.92 (0.70-6.58) years. In this study, time to first remission in acromegaly was found to have a significant effect on survival (p < .001); for every 1-year increase in time to first remission, there was a median 1% reduction in survival in acromegaly. In an analysis adjusted for covariates, the survival rate was 52% higher (p < .001) in those who underwent surgery as compared to those who did not have surgery, 18% higher (p = .01) in those who received treatment with somatostatin analogues (SMA) as compared to those with dopamine agonists and 21% lower (p < .001) in those who received conventional radiotherapy as compared to those who did not receive radiotherapy.

CONCLUSION

In conclusion, this population-based study conducted in patients with acromegaly revealed that faster remission time, surgical intervention and treatment with SMA are linked to improved survival outcomes.

Consensus on criteria for acromegaly diagnosis and remission

PURPOSE

The 14th Acromegaly Consensus Conference was convened to consider biochemical criteria for acromegaly diagnosis and evaluation of therapeutic efficacy.

METHODS

Fifty-six acromegaly experts from 16 countries reviewed and discussed current evidence focused on biochemical assays; criteria for diagnosis and the role of imaging, pathology, and clinical assessments; consequences of diagnostic delay; criteria for remission and recommendations for follow up; and the value of assessment and monitoring in defining disease progression, selecting appropriate treatments, and maximizing patient outcomes.

RESULTS

In a patient with typical acromegaly features, insulin-like growth factor (IGF)-I > 1.3 times the upper limit of normal for age confirms the diagnosis. Random growth hormone (GH) measured after overnight fasting may be useful for informing prognosis, but is not required for diagnosis. For patients with equivocal results, IGF-I measurements using the same validated assay can be repeated, and oral glucose tolerance testing might also be useful. Although biochemical remission is the primary assessment of treatment outcome, biochemical findings should be interpreted within the clinical context of acromegaly. Follow up assessments should consider biochemical evaluation of treatment effectiveness, imaging studies evaluating residual/recurrent adenoma mass, and clinical signs and symptoms of acromegaly, its complications, and comorbidities. Referral to a multidisciplinary pituitary center should be considered for patients with equivocal biochemical, pathology, or imaging findings at diagnosis, and for patients insufficiently responsive to standard treatment approaches.

CONCLUSION

Consensus recommendations highlight new understandings of disordered GH and IGF-I in patients with acromegaly and the importance of expert management for this rare disease.

The State of Machine Learning in Outcomes Prediction of Transsphenoidal Surgery: A Systematic Review

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.

Prognostic Models in Growth-Hormone- and Prolactin-Secreting Pituitary Neuroendocrine Tumors: A Systematic Review

Growth-hormone (GH)- and prolactin (PRL)-secreting PitNETs (pituitary neuroendocrine tumors) are divided into multiple histological subtypes, which determine their clinical and biological variable behavior. Proliferation markers alone have a questionable degree of prediction, so we try to identify validated prognostic models as accurately as possible. (1) Background: The data available so far show that the use of staging and clinical-pathological classification of PitNETs, along with imaging, are useful in predicting the evolution of these tumors. So far, there is no consensus for certain markers that could predict tumor evolution. The application of the WHO (World Health Organisation) classification in practice needs to be further evaluated and validated. (2) Methods: We performed the CRD42023401959 protocol in Prospero with a systematic literature search in PubMed and Web of Science databases and included original full-text articles (randomized control trials and clinical trials) from the last 10 years, published in English, and the search used the following keywords: (i) pituitary adenoma AND (prognosis OR outcome OR prediction), (ii) growth hormone pituitary adenoma AND (prognosis OR outcome OR prediction), (iii) prolactin pituitary adenoma AND (prognosis OR outcome OR prediction); (iv) mammosomatotroph adenoma AND (prognosis OR outcome OR prediction). (3) Results: Two researchers extracted the articles of interest and if any disagreements occurred in the selection process, these were settled by a third reviewer. The articles were then assessed using the ROBIS bias assessment and 75 articles were included. (4) Conclusions: the clinical-pathological classification along with factors such as GH, IGF-1, prolactin levels both preoperatively and postoperatively offer valuable information.

Acromegaly: pathogenesis, diagnosis, and management

Growth hormone-secreting pituitary adenomas that cause acromegaly arise as monoclonal expansions of differentiated somatotroph cells and are usually sporadic. They are almost invariably benign, yet they can be locally invasive and show progressive growth despite treatment. Persistent excess of both growth hormone and its target hormone insulin-like growth factor 1 (IGF-1) results in a wide array of cardiovascular, respiratory, metabolic, musculoskeletal, neurological, and neoplastic comorbidities that might not be reversible with disease control. Normalisation of IGF-1 and growth hormone are the primary therapeutic aims; additional treatment goals include tumour shrinkage, relieving symptoms, managing complications, reducing excess morbidity, and improving quality of life. A multimodal approach with surgery, medical therapy, and (more rarely) radiation therapy is required to achieve these goals. In this Review, we examine the epidemiology, pathogenesis, diagnosis, complications, and treatment of acromegaly, with an emphasis on the importance of tailoring management strategies to each patient to optimise outcomes.