Impact of pre-treatment with somatostatin analogs on surgical management of acromegalic patients referred to a single center

Revisiting the Role of Insulin-like Growth Factor-1 Measurement After Surgical Treatment of Acromegaly

CONTEXT

In the management of growth hormone (GH)-secreting pituitary adenomas, the oral glucose tolerance test (OGTT) has been the gold standard not only for diagnoses but also for the determination of biochemical remission. Insulin-like growth factor-1 (IGF-1) is an essential biomarker, although it should be adjusted for both age and sex.

OBJECTIVE

We evaluated whether IGF-1 levels could serve as a reliable alternative to an OGTT for disease monitoring after the surgical treatment of acromegaly. We retrospectively reviewed the medical records of 320 patients who underwent surgical resection of their GH-secreting pituitary tumors at the Severance hospital. Receiver operator characteristic (ROC) analyses were performed to validate the accuracy of IGF-1 levels for the assessment of remission. In addition, regression analyses were performed to identify factors associated with discrepancy between OGTT and IGF-1 levels.

RESULTS

Except for 1 week after surgery, ROC analyses showed an area under the curve of greater than 0.8 for IGF-1 at all time points. Of 320 patients, 270 achieved endocrine remission after surgery alone. Among these patients, IGF-1 levels were normalized in 250 patients. The mean duration from surgery to IGF-1 normalization was 4.7 months. Regression analyses demonstrated that risk of failed IGF-1 normalization was increased by 3.1-fold when the tumor invaded the cavernous sinus and increased by 9.0-fold in patients with incomplete tumor removal.

CONCLUSION

IGF-1 level is a reliable alternative to OGTT and plays a valuable role in monitoring acromegaly status.

Clinical and Radiological Predictors of Biochemical Response to First-Line Treatment With Somatostatin Receptor Ligands in Acromegaly: A Real-Life Perspective

BACKGROUND

First-generation somatostatin receptor ligands (fg-SRLs) represent the first-line medical treatment for acromegaly, recommended in patients with persistent disease after neurosurgery, or when surgical approach is not feasible. Despite the lack of strong recommendations from guidelines and consensus statements, data from national Registries report an increasing use of medical therapy as first-line treatment in acromegaly.

OBJECTIVE

We retrospectively evaluated the potential role of a large number of clinical and radiological parameters in predicting the biochemical response to 6-month treatment with fg-SRLs, in a cohort of naïve acromegaly patients referred to a single tertiary center for pituitary diseases.

METHODS

Univariable and multivariable logistic regression and linear regression analyses were performed. Biochemical response was defined based on IGF-1 levels, represented as both categorical (tight control, control, >50% reduction) and continuous (linear % reduction) variables.

RESULTS

Fifty-one patients (33 females, median age 57 years) were included in the study. At univariable logistic regression analysis, we found that younger age (≤ 40 years; OR 0.04, p=0.045) and higher BMI (OR 0.866, p=0.034) were associated with a lower chance of achieving >50% IGF-1 reduction. On the contrary, higher IGF-1 xULN values at diagnosis (OR 2.304, p=0.007) and a T2-hypointense tumor (OR 18, p=0.017) were associated with a significantly higher likelihood of achieving >50% IGF-1 reduction after SRL therapy. Of note, dichotomized age, IGF1 xULN at diagnosis, and T2-hypointense signal of the tumor were retained as significant predictors by our multivariable logistic regression model. Furthermore, investigating the presence of predictors to the linear % IGF-1 reduction, we found a negative association with younger age (≤ 40 years; β -0.533, p<0.0001), while a positive association was observed with both IGF-1 xULN levels at diagnosis (β 0.330, p=0.018) and the presence of a T2-hypointense pituitary tumor (β 0.466, p=0.019). All these variables were still significant predictors at multivariable analysis.

CONCLUSIONS

Dichotomized age, IGF-1 levels at diagnosis, and tumor T2-weighted signal are reliable predictors of both >50% IGF-1 reduction and linear % IGF-1 reduction after 6 month fg-SRL treatment in naïve acromegaly patients. These parameters should be considered in the light of an individualized treatment for acromegaly patients.

Octreotide-Resistant Acromegaly: Challenges and Solutions

Acromegaly is a rare and severe disease caused by an increased and autonomous secretion of growth hormone (GH), thus resulting in high circulating levels of insulin-like growth factor 1 (IGF-1). Comorbidities and mortality rate are closely related to the disease duration. However, in most cases achieving biochemical control means reducing or even normalizing mortality and restoring normal life expectancy. Current treatment for acromegaly includes neurosurgery, radiotherapy and medical therapy. Transsphenoidal surgery often represents the recommended first-line treatment. First-generation somatostatin receptor ligands (SRLs) are the drug of choice in patients with persistent disease after surgery and are suggested as first-line treatment for those ineligible for surgery. However, only about half of patients treated with octreotide (or lanreotide) achieve biochemical control. Other available drugs approved for clinical use are the second-generation SRL pasireotide, the dopamine agonist cabergoline, and the GH-receptor antagonist pegvisomant. In the present paper, we revised the current literature about the management of acromegaly, aiming to highlight the most relevant and recent therapeutic strategies proposed for patients resistant to first-line medical therapy. Furthermore, we discussed the potential molecular mechanisms involved in the variable response to first-generation SRLs. Due to the availability of different medical therapies, the choice for the most appropriate drug can be currently based also on the peculiar clinical characteristics of each patient.

Development and assessment of machine learning algorithms for predicting remission after transsphenoidal surgery among patients with acromegaly

PURPOSE

Preoperative prediction of transsphenoidal surgical (TSS) response is important for determining individual treatment strategies for acromegaly. There is currently no accurate predictive model for TSS response for acromegaly. The current study sought to develop and validate machine learning (ML)-based models for preoperative prediction of TSS response for acromegaly.

METHODS

Six hundred sixty-eight patients with acromegaly were enrolled and divided into training (n = 534) and text datasets (n = 134) in this retrospective, data mining and ML study. The forward search algorithm was used to select features, and six ML algorithms were applied to construct TSS response prediction models. The performance of these ML models was validated using receiver operating characteristics analysis. Model calibration, discrimination ability, and clinical usefulness were also assessed.

RESULTS

Three hundred forty-nine (52.2%) patients achieved postoperative remission criteria and exhibited good TSS response. A univariate analysis was conducted and eight features, including age, hypertension, ophthalmic disorders, GH, IGF-1, nadir GH, maximal tumor diameter, and Knosp grade, were significantly associated with the TSS response in patients with acromegaly. After feature selection, the gradient boosting decision tree (GBDT), which was constructed with the eight significant features showed the best favorable discriminatory ability both the training (AUC = 0.8555) and validation (AUC = 0.8178) cohorts. The GBDT model showed good discrimination ability and calibration, with the highest levels of accuracy and specificity, and provided better estimates of TTS responses of patients with acromegaly compared with using only the Knosp grade. Decision curve analysis confirmed that the model was clinically useful.

CONCLUSIONS

ML-based models could aid neurosurgeons in the preoperative prediction of TTS response for patients with acromegaly, and could contribute to determining individual treatment strategies.

Current perspectives on the impact of clinical disease and biochemical control on comorbidities and quality of life in acromegaly

Acromegaly is a rare chronic, systemic disorder caused by excessive growth hormone (GH) secretion from a somatotroph pituitary adenoma. GH hypersecretion leads to overproduction of insulin-like growth factor-1 (IGF-1), which contributes to the somatic overgrowth, physical disfigurement, onset of multiple systemic comorbidities, reduced quality of life (QoL) and premature mortality of uncontrolled patients. Somatostatin receptor ligands, dopamine agonists and a GH receptor antagonist are currently available for medical therapy of acromegaly. The main aim of treatment is biochemical normalisation, defined as age-normalised serum IGF-1 values and random GH levels <1.0 μg/L. However, there is an increasing evidence suggesting that achieving biochemical control does not always decrease the burden of disease-related comorbidities and/or improve patients' QoL. This lack of correlation between biochemical and clinical control can be due to both disease duration (late diagnosis) or to the peculiarity of a given comorbidity. Herein we conducted ad hoc literature searches in order to find the most recent and relevant reports on biochemical and clinical disease control during medical treatment of acromegaly. Particularly, we analyse and describe the relationship between biochemical, as well as clinical disease control in patients with acromegaly receiving medical therapy, with a focus on comorbidities and QoL. In conclusion, we found that current literature data seem to indicate that clinical disease control (besides biochemical control), encompassing clinical signs and symptoms, comorbidities and QoL, emerge as a primary focus of acromegaly patient management.

Pituitary magnetic resonance imaging predictive role in the therapeutic response of growth hormone-secreting pituitary adenomas

Background

Growth hormone (GH)-secreting pituitary adenomas, responsible for the development of acromegaly, are the second most frequent type of secreting pituitary adenomas and are characterized by very variable T2-weighted signal intensity on pituitary magnetic resonance imaging (MRI). Previous data have demonstrated a correlation between T2-weighted tumor signal intensity and response to therapy with conventional somatostatin analogs (SSA) in patients with acromegaly. The aim of the current retrospective study was to investigate the correlation between the T2-weighted tumor signal on pituitary MRI and both biochemical and radiological response to first-line SSA therapy.

Methods

Twenty-two naive patients with acromegaly were eligible for the study (14 females and 8 males, mean age ± SD: 58.8±15.74). A biochemical evaluation (GH and IGF-I levels) and an MRI assessment (volume and signal intensity analysis of adenoma) were conducted in each patient at diagnosis and after 12 months of SSA therapy.

Results

On diagnostic pituitary MRI, 16 (72.7%) adenomas were T2- hypointense and 6 (27.2%) T2-hyperintense. After 12 months of SSA therapy, IGF-I levels decreased by more than 50% from baseline in 62.5% of patients with T2-hypointense and 33.3% of patients with T2- hyperintense tumor signal, respectively (P=0.03). Moreover, GH levels decreased by more than 80% from baseline in 81.3% and 33.3% of patients with T2-hypointense and T2-hyperintense tumor signal (P=0.02). A significant tumor volume reduction (≥20%) was observed in 75% of the T2-hypointense and 33.3% of the T2-hyperintense adenomas (P=0.001).

Conclusions

In naive patients with acromegaly, first-line SSA therapy is associated with a better biochemical response and greater tumor shrinkage in T2-hypointense compared to T2-hyperintense adenomas. Therefore, T2-weighted sequences of pituitary MRI can help to classify GH-secreting pituitary adenomas into a T2-hypointense and T2-hyperintense type and, therefore, to identify patients who can better respond to first-line SSA therapy.

Predicting response to somatostatin analogues in acromegaly: machine learning-based high-dimensional quantitative texture analysis on T2-weighted MRI

OBJECTIVE

To investigate the value of machine learning (ML)-based high-dimensional quantitative texture analysis (qTA) on T2-weighted magnetic resonance imaging (MRI) in predicting response to somatostatin analogues (SA) in acromegaly patients with growth hormone (GH)-secreting pituitary macroadenoma, and to compare the qTA with quantitative and qualitative T2-weighted relative signal intensity (rSI) and immunohistochemical evaluation.

METHODS

Forty-seven patients (24 responsive; 23 resistant patients to SA) were eligible for this retrospective study. Coronal T2-weighted images were used for qTA and rSI evaluation. The immunohistochemical evaluation was based on the granulation pattern of the adenomas. Dimension reduction was carried out by reproducibility analysis and wrapper-based algorithm. ML classifiers were k-nearest neighbours (k-NN) and C4.5 algorithm. The reference standard was the biochemical response status. Predictive performance of qTA was compared with those of the quantitative and qualitative rSI and immunohistochemical evaluation.

RESULTS

Five hundred thirty-five out of 828 texture features had excellent reproducibility. For the qTA, k-NN correctly classified 85.1% of the macroadenomas regarding response to SAs with an area under the receiver operating characteristic curve (AUC-ROC) of 0.847. The accuracy and AUC-ROC ranges of the other methods were 57.4-70.2% and 0.575-0.704, respectively. Differences in predictive performance between qTA-based classification and the other methods were significant (p < 0.05).

CONCLUSIONS

The ML-based qTA of T2-weighted MRI is a potential non-invasive tool in predicting response to SAs in patients with acromegaly and GH-secreting pituitary macroadenoma. The method performed better than the qualitative and quantitative rSI and immunohistochemical evaluation.

KEY POINTS

• Machine learning-based texture analysis of T2-weighted MRI can correctly classify response to somatostatin analogues in more than four fifths of the patients. • Machine learning-based texture analysis performs better than qualitative and quantitative evaluation of relative T2 signal intensity and immunohistochemical evaluation. • About one third of the texture features may not be excellently reproducible, indicating that a reliability analysis is necessary before model development.

Pros and cons in endocrine practice: pre-surgical treatment with somatostatin analogues in acromegaly

The aim of this commentary is to balance the pros and cons for pre-surgical SSA treatment in a modern perspective ending up with a pragmatic recommendation for treatment based on the current evidence and expertise of the authors. Even though prospective and randomized studies in this particular area are hampered by obvious limitations, the interpretation of the four published trials has in general been in favor of pre-treatment with SSA, showing a better outcome following surgery. However, major drawbacks of these studies, such as non-optimal diagnostic criteria for cure, potential selection bias, and timing of the postoperative evaluation in SSA pre-treated patients, limit their overall interpretation. Three matched-controlled studies showed remarkably similar results with no apparent beneficial effect of SSA pre-treatment on surgical outcome. Both prospective, randomized studies and retrospective studies did not find any significant difference in the rate of endocrine and non-endocrine complications related to surgery, despite the beneficial clinical effects of SSA treatment in most acromegalic patients. The newly diagnosed patient with acromegaly should be carefully evaluated in the trans-disciplinary neuroendocrine team and treatment individualized accordingly. The issue of SSA pre-treatment to improve surgical outcome is yet to be settled and further methodologically sound studies are probably necessary to clarify this point.

Quantitative analyses of T2-weighted MRI as a potential marker for response to somatostatin analogs in newly diagnosed acromegaly

In growth hormone (GH)-producing adenomas, T2-weighted MRI signal intensity is a marker for granulation pattern and response to somatostatin analogs (SSA). Prediction of treatment response is necessary for individualized treatment, and T2 intensity assessment might improve preoperative classification of somatotropinomas. The objectives of this study are (I) to explore the feasibility of quantitative T2-weighted MRI histogram analyses in newly diagnosed somatotroph adenomas and their relation to clinical and histological parameters and (II) to compare the quantitative method to conventional, visual assessment of T2 intensity. The study was a retrospective cohort study of 58 newly diagnosed patients. In 34 of these, response to primary SSA treatment after median 6 months was evaluated. Parameters from the T2 histogram analyses (T2 intensity ratio and T2 homogeneity ratio) were correlated to visually assessed T2 intensity (hypo-, iso-, hyperintense), baseline characteristics, response to SSA treatment, and histological granulation pattern (anti-Cam5.2). T2 intensity ratio was lowest in the hypointense tumors and highest in the hyperintense tumors (0.66 ± 0.10 vs. 1.07 ± 0.11; p < 0.001). T2 intensity at baseline correlated with reduction in GH (r = -0.67; p < 0.001) and IGF-1 (r = -0.36; p = 0.037) after primary SSA treatment (n = 34). The T2 homogeneity ratio correlated with adenoma size reduction (r = -0.45; p = 0.008). Sparsely granulated adenomas had a higher T2 intensity than densely or intermediately granulated adenomas. T2 histogram analyses are an applicable tool to assess T2 intensity in somatotroph adenomas. Quantitatively assessed T2 intensity ratio in GH-producing adenomas correlates with conventional assessment of T2 intensity, baseline characteristics, response to SSA treatment, and histological granulation pattern.