Pharmacological hyperprolactinemia: a retrospective analysis of 501 hyperprolactinemia cases in primary care setting

PURPOSE

To describe a series of cases with pharmacological hyperprolactinemia in primary care setting and the prolactin levels, clinical implications of different causes of pharmacological hyperprolactinemia.

METHODS

A retrospective study of all patients with detected hyperprolactinemia in hormonal studies was performed between 2019 and 2020 in 20 Spanish primary care centers. Hyperprolactinemia is defined as a serum prolactin >19.4ng/ml in men and >26.5ng/ml in women. Four pharmacological causes of hyperprolactinemia were established: (i) oral contraceptives (OCPs) and other hormonal treatments; (ii) antipsychotics and antidepressants; (iii) other drugs (calcium antagonists, antiemetics, H2 antihistamines, opioids, and anabolic agents); and (iv) hyperprolactinemia due to several drugs.

RESULTS

From a sample of 501 patients with elevated serum prolactin, 39.4% (n=162) had pharmacological hyperprolactinemia. The most common cause of pharmacological hyperprolactinemia in women was OCPs (n=61) while in men antipsychotics/antidepressants (n=21). In the cases of hyperprolactinemia due to antipsychotics/antidepressants, the prolactin levels were significantly higher in patients taking classical antipsychotics than in those taking second-generation antipsychotics (80.0±43.17 vs. 50.7±28.66 ng/dL, P=0.035). The antidepressant/antipsychotic group showed hyperprolactinemia-related symptoms more frequently than the group of other treatments (58.9% vs. 32%, P=0.001). The concomitant use of several drugs caused hyperprolactinemia-related symptoms more frequently than one drug alone (73% vs. 44%, P=0.031).

CONCLUSION

In this series of cases, drugs represented the 39.4% of the causes of hyperprolactinemia. The most common drugs were OCPs in women and antipsychotics/antidepressants in men. Antidepressants/antipsychotics were drugs that caused the greatest elevation of the prolactin levels and showed hyperprolactinemia-related symptoms more frequently.

Is the 1mg-dexamethasone suppression test a precise marker of glucocorticoid excess and cardiometabolic risk in patients with adrenal incidentalomas?

AIM

To analyze if the 1mg-dexamethasone suppression test (DST) is a reliable marker of glucocorticoid excess and cardiometabolic risk in patients with adrenal incidentalomas (AIs).

METHODS

Cross-sectional study of patients with nonfunctioning adrenal incidentalomas (NFAIs, defined by cortisol post-DST ≤ 1.8 µg/dL) and patients with autonomous cortisol secretion (ACS, defined by cortisol post-DST > 1.8 µg/Dl). The urinary steroid profile (USP) was determined by gas chromatography coupled to mass spectrometry. Both groups were matched by sex, age and body mass index.

RESULTS

Forty-nine patients with AIs (25 with ACS and 24 with NFAI) were included. As a whole, AIs showed a high excretion of β-cortolone, tetrahydro-11-deoxycortisol (THS), α-cortolone, α-cortol, tetrahydrocortisol (THF) and tetrahydrocortisone (THE). A positive yet modest correlation between post-DST cortisol and total excretion of glucocorticoid metabolites (r = 0.401, P = 0.004) was observed, with the stronger being observed with total THS (r = 0.548, P < 0.001) and THF (r = 0.441, P = 0.002). Some of the metabolites that were elevated in patients with AIs, were higher in patients with ACS-related comorbidities than in those without comorbidities. Post-DST cortisol showed a fair diagnostic accuracy for the prediction of ACS-related comorbidities (AUC 0.767 [95% CI 0.634-0.882]). However, post-DST diagnostic accuracy improved when combined with urinary cortisone, α-cortol, THS and serum DHEAS (0.853 [0.712‒0.954]).

CONCLUSION

The DST has a positive, but modest, correlation with urinary glucocorticoid excretion. Similarly, the diagnostic accuracy of the DST for the prediction of ACS-related comorbidities is only fair, but it may be improved if combined with the results of the USP and serum DHEAS.

SIGNIFICANCE STATEMENT

This is the first study aimed to evaluate if 1mg-dexamethasone suppression test (DST) is a reliable marker of glucocorticoid excess and cardiometabolic risk in patients with adrenal incidentalomas (AIs) and if urinary steroid profile was measured by GS-MS could improve such a prediction. We found a positive yet modest correlation between post-DST cortisol and total excretion of glucocorticoid metabolites, with the stronger being observed with total tetrahydro-11-deoxycortisol (THS) and tetrahydrocortisol. Post-DST cortisol showed a fair diagnostic accuracy for the prediction of ACS-related comorbidities (AUC 0.767). However, post-DST diagnostic accuracy improved when combined with urinary cortisone, α-cortol, THS and serum DHEAS (0.853).

Prevalence and incidence of type 2 diabetes mellitus in patients with adrenal incidentalomas: a study of 709 cases

AIM

To evaluate the prevalence and incidence of type 2 diabetes in patients with nonfunctioning adrenal incidentalomas (NFAI) or adrenal incidentalomas (AI) with autonomous cortisol secretion (ACS).

METHODS

In this single-center retrospective study, all patients with adrenal incidentalomas ≥1 cm and ACS or NFAI studied between 2013 and 2020 were included. ACS was defined by a post-dexamethasone suppression test (DST) serum cortisol concentration ≥1.8 μg/dl, in the absence of signs of hypercortisolism, and NFAI was defined as a DST < 1.8 μg/dl without biochemical evidence of hypersecretion of other hormones.

RESULTS

Inclusion criteria were met by 231 patients with ACS and 478 with NFAI. At diagnosis, type 2 diabetes was present in 24.3% of patients. No differences were found in the prevalence of type 2 diabetes (27.7 vs. 22.6%, P = 0.137) between patients with ACS and NFAI. However, fasting plasma glucose values and glycated hemoglobin levels were significantly higher in patients with ACS than with NFAI (112 ± 35.6 vs. 105 ± 29 mg/dl, P = 0.004; and 6.5 ± 1.4 vs. 6.1 ± 0.9%, P = 0.005, respectively). Furthermore, patients with type 2 diabetes had higher urinary free cortisol (P = 0.039) and late-night salivary cortisol levels (P = 0.010) than those without type 2 diabetes. After a median follow-up of 28 months, no differences were found in the incidence of type 2 diabetes between the groups (HR 1.17, 95% 0.52-2.64).

CONCLUSION

Type 2 diabetes was present in one fourth of our cohort. We found no differences in its prevalence or incidence between the groups. However, glycemic control might be worse among diabetic patients with ACS. Higher concentrations of urinary and salivary cortisol were found in patients with than without type 2 diabetes.

Predictive model for autonomous cortisol secretion development in non-functioning adrenal incidentalomas

PURPOSE

We aimed to develop a predictive model able to stratify patients with non-functioning adrenal incidentalomas (AIs), according to their risk for developing autonomous cortisol secretion (ACS) during follow-up.

METHODS

This was a retrospective study of patients with non-functioning AIs consecutively evaluated at a single institution between 2013 and 2019 in whom hormonal follow-up information was available for at least 1 year. Clinical, biochemical, and radiological features were used to build a multivariate Cox regression model using the estimation of all possible equations.

RESULTS

We included 331 patients with non-functioning AIs. ACS (post-dexamethasone suppression test (DST) serum cortisol > 1.8 µg/dL) developed in 73 patients during a median follow-up time of 35.7 months [range 12.8-165.4]. The best predictive model for ACS development during follow-up combined age, post-DST serum cortisol, and bilaterality at presentation and showed good diagnostic accuracy (AUC-ROC 0.70 [95% CI 0.65-0.75]). The lowest risk for ACS development was found among patients < 50 years old with cortisol post-DST values < 0.45 µg/dL and with unilateral tumors (risk 2.42%). Baseline post-DST serum cortisol levels at diagnosis were the most important factor for the development of ACS during follow-up (hazard ratio 3.56 for each µg/dL, p < 0.001). The rate of ACS development was associated with post-DST cortisol levels, being 19.2, 32.3, and 68.1 cases/10,000 person-years for patients with baseline post-DST cortisol < 0.9 µg/dL, 0.9-1.3 µg/dL, and > 1.3 µg/dL, respectively.

CONCLUSION

After ruling out malignancy, follow-up visits for patients < 50 years old with unilateral non-functioning AIs and post-DST serum cortisol < 0.45 µg/dL are considered unnecessary given the low risk of developing ACS during follow-up.

Characterisation of the urinary steroid profile of patients with nonfunctioning adrenal incidentalomas: A matched controlled cross-sectional study

AIM

To identify alterations in steroid metabolism in patients with nonfunctioning adrenal incidentalomas (NFAIs) through the analysis of their urinary steroid profile (USP).

METHODS

Cross-sectional study with one study group (NFAIs, cortisol post dexamethasone suppression test [DST] ≤ 1.8 µg/dl [49.7 nmol/L]) and 2 control groups: patients with autonomous cortisol secretion (ACS group, cortisol post-DST > 1.8 µg/dl (49.7 nmol/L) and patients without adrenal tumours (healthy-adrenal group). Twenty-four-hour urine collections for USP measurement (total and free fraction of 51 24 h-urine specimens) were obtained from 73 participants (24 with NFAIs, 24 without AIs, and 25 with ACS). USP was determined by gas chromatography coupled to mass spectrometry. Patients of the three groups were matched according to sex, age (±5 years-old) and body mass index (±5 kg/m² ).

RESULTS

Compared to healthy-adrenal controls, patients with NFAIs had a lower excretion of androgen metabolites (230.5 ± 190.12 vs. 388.7 ± 328.58 µg/24 h, p = .046) and a higher excretion of urinary free cortisol (UFC) (54.3 ± 66.07 vs. 25.4 ± 11.16 µg/24 h, p = .038). UFC was above the reference range in 20.8% of patients in the NFAI, compared to 0% in the healthy-adrenal group (p = .018). Patients with ACS had a higher prevalence of hypertension, dyslipidemia, and diabetes than patients with NFAIs or the control group. A lower excretion of androgen metabolites (218.4 ± 204.24 vs. 231 ± 190 µg/24 h, p = .041) and a nonsignificant higher excretion of glucocorticoid metabolites (2129.6 ± 1195.96 vs. 1550.8 ± 810.03 µg/24 h, p = .180) was found in patients with ACS compared to patients with NFAIs.

CONCLUSION

NFAIs seem to secrete a subtle, yet clinically relevant, excess of glucocorticoids. Future studies are needed to confirm our findings; and to identify metabolic alterations associated with an increased cardiometabolic risk.

Evaluation of Body Composition in Patients With and Without Adrenal Tumors and Without Overt Hypersecretory Syndromes

OBJECTIVE

To compare body composition between patients with autonomous cortisol secretion (ACS), those with nonfunctioning adrenal incidentalomas (NFAIs), and control subjects without adrenal tumors.

METHODS

A cross-sectional study was performed, incluidng the following 3 groups: patients with ACS (cortisol post-dexamethasone suppression test [DST] >1.8 μg/dL), NFAIs (cortisol post-DST ≤ 1.8 μg/dL), and patients without adrenal tumors (control group). Patients of the 3 groups were matched according to age (±5 years), sex, and body mass index (±5 kg/m²). Body composition was evaluated by bioelectrical impedance and abdominal computed tomography (CT) and urinary steroid profile by gas chromatography mass spectrometry.

RESULTS

This study enrolled 25 patients with ACS, 24 with NFAIs, and 24 control subjects. Based on CT images, a weak positive correlation between the serum cortisol level post-DST and subcutaneous fat area (r = 0.3, P =.048) was found. As assessed by bioelectrical impedance, lean mass and bone mass were positively correlated with the excretion of total androgens (r = 0.56, P <.001; and r = 0.58, P <.001, respectively); visceral mass was positively correlated with the excretion of glucocorticoid metabolites and total glucocorticoids (r = 0.28, P =.031; and r = 0.42, P =.001, respectively). Based on CT imaging evaluation, a positive correlation was observed between lean mass and androgen metabolites (r = 0.30, P =.036) and between visceral fat area, total fat area, and visceral/total fat area ratio and the excretion of glucocorticoid metabolites (r = 0.34, P =.014; r = 0.29, P =.042; and r = 0.31, P =.170, respectively).

CONCLUSION

The urinary steroid profile observed in adrenal tumors, comprising a low excretion of androgen metabolites and high excretion of glucocorticoid metabolites, is associated with a lower lean mass and bone mass and higher level of visceral mass in patients with adrenal tumors.

Causes of hyperprolactinaemia in the primary care setting: How to optimise hyperprolactinaemia management

BACKGROUND AND PURPOSE

To analyse the causes of hyperprolactinaemia in patients with symptoms compatible with hyperprolactinaemia evaluated in a primary care setting.

PATIENTS AND METHODS

A retrospective study of all patients tested for serum prolactin levels between 2019 and 2020 in 20 primary care centres at the Hospital Ramón y Cajal in Madrid. Hyperprolactinaemia is defined as a serum prolactin>19.4ng/ml in men and >26.5ng/ml in women. Aetiology is grouped into physiological (pregnancy, lactation, inadequate venipuncture, macroprolactinaemia), pharmacological, pathological (hypothalamic and/or pituitary diseases, chronic renal failure, primary hypothyroidism), and idiopathic.

RESULTS

In 1630 patients tested for serum prolactin, 30.7% (n=501) had hyperprolactinaemia. Of these 501 patients, 89.6% were females. 149 patients were referred to the Endocrinology Department and 164 to the Gynaecology Department. Aetiological diagnosis of hyperprolactinaemia was achieved in 411 out of 501 cases. The most frequent cause of hyperprolactinaemia was pharmacological, in 39.1%. The second more frequent cause was idiopathic (29%) and less common were inadequate venipuncture extraction (13.4%), tumour (8.5%) and macroprolactinaemia (3.9%). Patients with tumoural hyperprolactinaemia presented higher serum prolactin levels (87.0±80.19 vs 49.7±39.62ng/ml, P=0.010). In addition, symptoms, such as galactorrhoea (33.3% vs 16.5%, P=0.018), and headache (25.7% vs 13.3%, P=0.045), were more frequent than in patients of the other aetiological groups.

CONCLUSION

Hyperprolactinaemia is common among patients evaluated in a primary care setting with symptoms of hyperprolactinaemia, but more than 50% of cases are due to pharmacological treatments or improper sample extraction. It is necessary to establish referral protocols to specialised medicine to optimise healthcare resources and avoid unnecessary studies.

[Cardiometabolic risk in patients with primary aldosteronism and autonomous cortisol secretion. Case-control study]

OBJECTIVE

To analyse the differences in the cardio-metabolic profile of patients with primary aldosteronism (PA) and autonomous cortisol secretion (ACS) matched by age and sex.

METHODS

Case-control study; cases of PA without associated ACS and as controls patients with ACS (dexamethasone suppression test ≥ 1.8 μg/dL in the absence of specific hypercortisolism clinical data), matched by age and sex. Comorbidities of hypertension, diabetes, obesity, dyslipidaemia, chronic kidney failure, and cardiovascular and cerebrovascular events were analysed, as well as their degree of control.

RESULTS

57 patients with PA and 57 with ACS were included. On diagnosis, in addition to a higher prevalence of hypertension in the PA patients (100 vs. 52.7%, p < .0001) and higher systolic blood pressure levels (143.2 (2.5) vs. 135.3 (2.6) mmHg, p = .032) than in the ACS patients, no other differences were detected in the prevalence of other cardio-metabolic comorbidities. Nevertheless, the patients with ACS had higher HbA1c levels (p = .028) than the PA patients. After a median follow-up of 2.25 years, the patients with PA presented a greater deterioration in kidney function (Average decrease in glomerular filtration rate (MDRD-4) -17.4 (3.0) vs. -2.3 (4.4) mL/min/1.73 m^2, p = .005) and lipid profile (Δtriglycerides of 34.5 (15.8) vs. -6.7 (11.3) mg/dL, p = .038) than the ACS patients.

CONCLUSIONS

Despite the higher prevalence of hypertension in the patients with PA than in the patients with ACS matched by age and sex, no differences were detected in the prevalence of other cardio-metabolic comorbidities. However, the PA patients showed a greater deterioration in kidney function and lipid profile throughout the follow-up than the ACS patients.