Risk Factors for Biochemical Recurrence in Prolactinomas After Withdrawal of Dopamine Agonists: A Retrospective Cohort Study

Risk Factors for Biochemical Recurrence in Prolactinomas After Withdrawal of Dopamine Agonists: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Risk Factors for Biochemical Recurrence in Prolactinomas After Withdrawal of Dopamine Agonists: A Retrospective Cohort Study Daniel Cuevas-Ramos, Romina Flores-Cárdenas, Mariana Osorio-Olvera, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4573462/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Context: Dopamine agonists (DA), mainly cabergoline, are the primary therapy for prolactinomas. Risks factors related with biochemical recurrence after DA withdrawal are not completely understood. Objective: To assess hyperprolactinemia recurrence risk factors after dopamine agonist (DA) withdrawal in prolactinomas. Design: Retrospective, comparative, observational cohort study. Survival, and multivariate regression analyses were performed to estimate biochemical remission (prolactin (PRL) 3-25 ng/mL after at least 6 months of DA withdrawal), and recurrence (>25 ng/ml and/or tumor regrowth) at follow-up. Results: 1140 patients with hyperprolactinemia were evaluated. Prolactinoma was confirmed in 182 cases. Micro- (n=95), and macroprolactinoma (n=75) were more frequent in women (99% and 73%, respectively), while giant prolactinomas (n=12) were more common in men (75%). Cabergoline was the most frequently (92-95%) DA used with a median dose of 1.2 (0.25-4.0), 2.2 (1.5-3.5), and 2.8 (1.5-8.0) mg/week (p<0.001), respectively. Higher tumor size at diagnosis was significantly related to biochemical recurrence (p<0.02). However, independently of tumor size at diagnosis, and the DA cumulative dose received, once patient have achieved an 80% volume reduction, tumors were unlikely to decrease further (p=0.02). Among cases under remission at last follow-up, almost half with microprolactinomas (n=51, 54%), and macroprolactinomas (n=35, 46%) persisted with tumor remnants. Multivariate regression analysis confirmed that tumor remnant at last follow-up was not significantly associated with recurrence risk (p=0.81). Duration of therapy was the only variable significantly associated with remission (p<0.01). Conclusion: Probability of biochemical recurrence after withdrawal of DA therapy in micro and macroprolactinomas was not significantly associated with tumor remnant. Duration of DA therapy was the only variable significantly associated with remission. prolactin pituitary adenoma neuroendocrine tumor cabergoline bromocriptine Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Prolactinomas are the most common secretory pituitary tumor, with a prevalence between 32 to 66% in clinical settings [1]. Although these tumors are benign, they produce symptoms due to hyperprolactinemia and local mass effects [2]. Medical therapy with dopamine agonists (DAs) is the first-line treatment, showing success rates of 70-90%, while surgery and radiotherapy are alternatives in selected cases [3]. Tumor size at diagnosis could influence the onset and course of the disease. Classical differences in clinical and biochemical characteristics between micro- and macroadenomas have been described [2]. However, when those tumors are compared with giant prolactinomas (>4 cm), information is scarce. In bigger tumors, some studies have suggested lower rates of biochemical remission, and higher frequency of hypopituitarism [2, 4]. However, other reports have not found an association between tumor size and necessity of long-term medical treatment because of persistent hyperprolactinemia [4]. Since outcome information is limited when comparing medical therapy in micro or macroprolactinomas with giant tumors, here we aimed to assess the risk factors for hyperprolactinemia recurrence after DA treatment withdrawal. Methods The clinical records of all patients with hyperprolactinemia in the Neuroendocrinology Clinic, Department of Endocrinology and Metabolism, at the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, in Mexico City, from January 2000 to October 2023 were reviewed (figure 1). Clinical, biochemical, and radiological features of the tumors were extracted. According to their maximum diameter at diagnosis, tumors were classified as microadenomas (<10 mm), macroadenomas (≥10 mm), and giant adenomas (≥40mm). Tumor volume was calculated by the Ellipsoid formula [0.5 x (width x length x height)][5]. Optic chiasm compression was defined as a grade D in the Hardy classification system, and positive extension and cavernous sinus invasion were defined with the Knosp classification [6]. Treatment included medical therapy with dopamine agonists, surgery, and radiotherapy. The cumulative dosage of the dopaminergic agonist administered was calculated by obtaining the mean dosage given and multiplying it for the time under medical treatment. Withdrawal attempts of DAs required a patient with prolactinoma who had received DAs for at least two years, had normal (3-25 ng/mL) or low (<3 ng/mL) prolactin (PRL) serum concentration and showed a ≥50 % tumor volume shrinkage from baseline [7]. DA’s dose was progressively reduced until stopped when cases remained asymptomatic and without hyperprolactinemia, consistent with disease remission. Remission was defined by persistent normal PRL serum concentration after at least 6 months of DA treatment withdrawal. Recurrence was established if, after remission, the PRL increased above the upper limit of the normal range, and/or tumor regrowth on MRI, requiring DA therapy to be resumed [8]. Tumor remnant was defined as positive MRI for tumor lesion of any volume or size at last follow-up, after accomplished DA therapy withdrawal criteria described above. Post-treatment outcomes included biochemical remission, percentage of tumor volume reduction, and presence of tumor remnant. We included patients treated only with DAs to compare the effect of medical therapy on the biochemical and tumoral outcomes between microprolactinomas, and macroprolactinomas, without the confusion of other treatment strategies like surgery and/or radiotherapy. In the case of giant tumors (n=12), however; other treatment modalities were needed, such as neurosurgery (n=6, 50%) or adjuvant radiotherapy (n=3, 25%), to avoid permanent visual deficits because of tumor growth, and persistent prolactin hypersecretion despite DA therapy. Therefore, in this subgroup we included all patients identified, regardless of their treatment. The Local Ethics Review Committee approved the study protocol and followed the ethical guidelines of the Declaration of Helsinki. Statistical analysis Data was expressed as mean ±SD or median and interquartile range according to variables distribution. Categorical variables were expressed with n, percentage, and compared using chi square test. Dimensional parameters were analyzed using independent t student or Mann-Whitney U test as needed. One-way ANOVA or Kruskal-Wallis tests were used to compare quantitative variables between three of more groups. Log-rank test and Kaplan-Meier curves were used to estimate the probability of biochemical remission, and recurrence at last follow-up. A multivariate logistic regression analyses adjusted for potential confounders were performed to identified independent and significant risk factors related with remission and recurrence at last follow-up. Statistical significance was assumed if p <0.05. We used IBM SPSS Statistics 25 software. Results Baseline characteristics A total of 182 patients were included in the analysis (figure 1). The clinical and biochemical characteristics of the patients are shown in Table 1. The median age at diagnosis was not statistically different between microprolactinoma [31 years (25-38)], macroprolactinoma [31 (22-41)], and giant prolactinoma [34 (19-38)], respectively (p=0.99). Micro- and macroprolactinoma were more frequent in women, with 99% and 73% respectively, while giant prolactinomas were more common in men (75%) (Table 1). Patients with larger tumors were associated with higher baseline prolactin concentration, greater frequency of optic chiasm compression and cavernous sinus invasion (p<0.05). However, galactorrhea showed a significant relationship with smaller tumor size being more frequent in microprolactinomas, and macroprolactinomas, than in giant tumors because of the gender distribution of these tumors (Table 1, p<0.05). Treatment The following information is presented for microprolactinoma, macroprolactinoma, and giant prolactinoma. The median follow-up after withdrawal was 11.7 (5.7-15.5), 7.0 (5.0-13.0), and 2.5 (0-6.8) years ( p <0.05), respectively. Cabergoline was the most frequently used DA [90 (95%); 71 (95%); and 11 (92%)] with a median dose of 1.2 (0.25-4.0), 2.2 (1.5-3.5), and 2.8 (1.5-8.0) mg/week (p<0.001), respectively. Other DA used (bromocriptine, quinagolide, and lisuride) are summarized in supplementary table 1. Patients with greater tumor diameter received higher doses of cabergoline and bromocriptine (supplementary table 1). Duration of treatment was 4.2 (2.1-8.1); 4.5 (2.4-7.7), and 6.1 (2.6-9.2) years, respectively (p=0.09). Overweight and obesity was highly prevalent on three groups (table 1). Biochemical outcomes The biochemical and radiological data of the patients are shown in table 1. Biochemical remission was achieved in 77 (81%), 50 (67%), and 3 (27%) cases of micro-, macro-, and giant -prolactinomas, respectively (log-rank test, p<0.001, figure 2). Microprolactinomas showed the lowest rate of hypopituitarism (n=13, 13.6%), followed by macroprolactinomas (n=22, 29%), and giant prolactinomas (n=12, 100%). The gonadotroph axis was the most commonly affected (n=40, 23%), followed by central hypothyroidism (n=22, 12%), and central hypocortisolism (n=19, 10%). A lineal association was found between tumor-size (micro-, macro-, and giant-prolactinomas, respectively) and proportion of central hypothyroidism (n=6, 6.3%; n=6, 8.2%; n=10, 83%), central hypocortisolism (n=3, 4.1%; n=8, 12.5%; n=8, 73%), and GH deficiency (n=1, 1.7%; n=3, 5.5%; n=3, 43%) (all p<0.001). The only cases with arginine-vasopressin deficiency (central diabetes insipidus) at diagnosis, were giant prolactinomas (n=2, 1.1%). Radiologic outcomes Probability for negative MRI throughout follow-up was significatively higher for microprolactinomas (24%) and macroprolactinomas (19%) after compared to giant prolactinomas (0%) (Figure 3, p=0.02). However, we noticed that frequency of visible tumor at last follow-up was high in the three groups. Therefore, we also compared the percentage of tumor volume reduction in each group (figure 4). The median (interquartile range) of tumor volume reduction was also not significantly different between microprolactinoma [61% (17-96)], macroprolactinoma [92% (66-97)], and giant prolactinoma [84% (20-94), p=0.12, figure 4]. After excluding outliers (n=2), the median volume reduction in all tumors were 81% (48-96, figure 4A). The median volume of tumor remnants were significantly different at last follow-up, been 14 mm 3 (2-46) for microprolactinomas, 96 mm 3 (14-270) for macroprolactinomas, and 2189 mm 3 (1483-19518) for giant prolactinomas (p<0.001, figure 4B). Remission rates by tumor size Macroprolactinomas showed significantly higher probability of biochemical recurrence at last follow-up (figure 5A, p=0.02). Around half of cases that were under remission showed persistent tumor remnants, seen in 54% (n=51) of micro- (figure 5B), and 46% (n=35) of macroprolactinomas (figure 5C, all p<0.01). All cases with persistent hyperprolactinemia showed a remnant microprolactinoma (figure 5B). Also, two cases with macroprolactinomas (3%) without tumor remnant at last MRI could not reached remission (Figure 5C). Factors independently associated with remission or recurrence We performed a logistic regression analysis adjusted for potential confounders such as duration of treatment, DAs cumulative dose, and tumor size at diagnosis, to identify risk factors independently and significantly associated with remission or recurrence. Duration of therapy with DAs was the only variable significantly associated with remission (p<0.01). Also, results confirmed that the tumor size at diagnosis was significantly related to biochemical recurrence, but tumor remnant at last follow-up was not (p=0.81). Discussion We report a higher likelihood to achieve biochemical remission in patients with microprolactinomas compared to both macroadenomas and giant prolactinomas. In addition, independently of tumor size at diagnosis, and the DA cumulative dose received, once patient have achieved a median of ~80% volume reduction, tumors were unlikely to decrease further. Consequently, among cases under remission at last follow-up, almost half with microprolactinomas and macroprolactinomas persisted with tumor remnants (figure 5). Multivariate regression analysis confirmed that tumor remnant at last follow-up, therefore, was not significantly associated with recurrence risk (p=0.81). In fact, duration of therapy, was the only variable independently and significantly associated with remission at last follow-up (p<0.01). The association of tumor remnants and remission rates has yielded varied results [9-11]. In our cohort, microprolactinomas showed higher probability of remission. Nevertheless, it was not dependent on tumor disappearance. Such patients showed the higher probability of remission (p<0.05) despite 54% of them having remnant tumors at last MRI. Similarly, 81% of macroprolactinomas had tumor remnant, and 46% were cases under remission (figure 5). Probably, DAs therapy progressively causes structural changes in lactotroph tumor cells related with fibrosis, which may cause lower expression of dopamine D2 receptor, and less PRL secretion. After years of good responsiveness, the tumor stops decreasing in size with a persistent remnant, but without any further PRL secretion. Therefore, patients with prolactinoma may persist with positive MRI findings. This is important to avoid overtreatment, and, suggests that DAs withdrawal should not be based on the absence of tumor at MRI [9-13]. We suggest that after at least two years (ideally 3 years) of therapy and, normalization or also ideally suppression of PRL serum concentration throughout follow-up, it might be considered enough criteria to gradually initiate DAs dose reduction to evaluate remission, and withdrawal of medical therapy. Although these assumptions may also be expected for giant prolactinomas, in our cohort, these tumors received multiple interventions and, therefore, associations with DAs outcomes alone, were not possible. However, we decided to include giant tumors to compare other interesting results. First, the median age at diagnosis was similar independently of tumor size (p=0.99, Table 1). This may be explained because symptoms related to hyperprolactinemia, rather than those related to mass effect, are the main reason why patients reach for medical attention. Secondly, we confirmed excellent response to DAs in patients with giant prolactinoma, with an important reduction of tumor volume, been very helpful to correct optic chiasm compression in all but 1 case (figure 4). Nevertheless, giant tumors showed a lower probability of disease control at follow-up (27%). Such result may be due to lower maximum doses of DAs in our cohort than those suggested in previous studies (19-24). Third, higher tumor volume was related to a higher frequency of anterior pituitary hormone deficiencies. Giant prolactinomas additionally showed posterior pituitary lobe involvement and arginine-vasopressin deficiency (central diabetes insipidus). Fourth, weight increment is common in cases with hyperprolactinemia. However, overweight and obesity was similarly prevalent in all three groups, independently of tumor size and prolactin levels. Therefore, it can be considered a frequent clinical finding in prolactinomas independently of tumor size at diagnosis. Finally, giant prolactinomas were observed more frequently in males (75%) which was consistent with previous studies [14-16]. Limitations of our cohort study include its observational nature, and the relatively small number of patients with giant prolactinoma. However, the number of cases reach enough statistical power to compare study outcomes. In conclusion, microprolactinomas have a higher probability of biochemical remission with medical therapy. Duration of DA therapy was the only variable significantly associated with persistent biochemical remission at last follow-up. Probability of biochemical recurrence after withdrawal of DA therapy in micro and macroprolactinomas was not associated with tumor remnant. Declarations Conflicts of interest: Authors have nothing to disclose. Funding statement: This study did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector. References Vroonen L, Daly AF, Beckers A.: Epidemiology and Management Challenges in Prolactinomas. Neuroendocrinology. (2019). https://doi.org/10.1159/000497746 Chanson P, Maiter D.: The epidemiology, diagnosis and treatment of Prolactinomas: The old and the new. Best. Pract. Res. Clin. Endocrinol. Metab. (2019) https://doi.org/101290.10.1016/j.beem.2019.101290 Melmed S, Casanueva FF, Hoffman AR, Kleinberg DL, Montori VM, Schlechte JA, et al.: Diagnosis and treatment of hyperprolactinemia: an Endocrine Society clinical practice guideline. J. Clin. Endocrinol. Metab. (2011) https://doi.org/10.1210/jc.2010-1692 Shrivastava RK, Arginteanu MS, King WA, Post KD.: Giant prolactinomas: clinical management and long-term follow up. J. Neurosurg. (2002) https://doi.org/10.3171/jns.2002.97.2.0299 Lundin P, Pedersen F.: Volume of pituitary macroadenomas: assessment by MRI. J. Comput. Assist. Tomogr. (1992) https://doi.org/10.1097/00004728-199207000-00004 Di Ieva A, Rotondo F, Syro LV, Cusimano MD, Kovacs K.: Aggressive pituitary adenomas--diagnosis and emerging treatments. Nat. Rev. Endocrinol. (2014) https://doi.org/10(7):423-35.10.1038/nrendo.2014.64 Dogansen SC, Selcukbiricik OS, Tanrikulu S, Yarman S.: Withdrawal of dopamine agonist therapy in prolactinomas: In which patients and when? Pituitary. (2016) https://doi.org/10.1007/s11102-016-0708-3 Teixeira M, Souteiro P, Carvalho D.: Prolactinoma management: predictors of remission and recurrence after dopamine agonists withdrawal. Pituitary. (2017) https://doi.org/10.1007/s11102-017-0806-x Kharlip J, Salvatori R, Yenokyan G, Wand GS.: Recurrence of hyperprolactinemia after withdrawal of long-term cabergoline therapy. J. Clin. Endocrinol. Metab. (2009) https://doi.org/10.1210/jc.2008-2103 Biswas M, Smith J, Jadon D, McEwan P, Rees DA, Evans LM, et al.: Long-term remission following withdrawal of dopamine agonist therapy in subjects with microprolactinomas. Clin. Endocrinol. (2005) https://doi.org/10.1111/j.1365-2265.2005.02293.x Huda MS, Athauda NB, Teh MM, Carroll PV, Powrie JK.: Factors determining the remission of microprolactinomas after dopamine agonist withdrawal. Clin. Endocrinol. (2010) https://doi.org/10.1111/j.1365-2265.2009.03657.x Passos VQ, Souza JJ, Musolino NR, Bronstein MD.: Long-term follow-up of prolactinomas: normoprolactinemia after bromocriptine withdrawal. J. Clin. Endocrinol. Metab. (2002) https://doi.org/10.1210/jcem.87.8.8722 Colao A, Di Sarno A, Guerra E, Pivonello R, Cappabianca P, Caranci F, et al.: Predictors of remission of hyperprolactinaemia after long-term withdrawal of cabergoline therapy. Clin. Endocrinol. (2007) https://doi.org/10.1111/j.1365-2265.2007.02905.x Maiter D, Delgrange E.: Therapy of endocrine disease: the challenges in managing giant prolactinomas. Eur. J. Endocrinol. (2014) https://doi.org/10.1530/eje-14-0013 Espinosa E, Sosa E, Mendoza V, Ramírez C, Melgar V, Mercado M.: Giant prolactinomas: are they really different from ordinary macroprolactinomas? Endocrine. (2016) https://doi.org/10.1007/s12020-015-0791-7 Hamidi O, Van Gompel J, Gruber L, Kittah NE, Donegan D, Philbrick KA, et al.: MANAGEMENT AND OUTCOMES OF GIANT PROLACTINOMA: A SERIES OF 71 PATIENTS. Endocrine. Pract. (2019) https://doi.org/10.4158/ep-2018-0392 Tables Table 1 . Baseline clinical, biochemical, and radiological characteristics of patients with prolactinomas treated with DA only (n=182) Characteristic Microprolactinomas (n=95) Macroprolactinomas (n=75) Giant prolactinomas (n=12) p-value Clinical Female n (%) 94 (99) 55 (73) 3 (25) . 000 Age (years) 31 (25-38) 31 (22-41) 34 (19-38) .994 BMI (kg/m 2 ) 26.1 (21.5-30.3) 26.8 (23.6-31) 28.2(26.5-31) .098 Headache 69 (86.3%) 53 (84.1%) 8 (100%) .473 Menstrual disorders 71 (79.8%) 49 (90.7%) 3 (100%) .431 Erectile dysfunction 1 (100%) 10 (66.7%) 5 (100%) .269 Galactorrhea 76 (84.4%) 46 (74.2%) 3 (25%) . 009 MEN1 syndrome 5 (5.3%) 3 (4%) 1 (8.3%) .796 Biochemical Prolactin (ng/mL) 98 (74-130) 244 (112-765) 680(117- 2000) .000 Hormonal co-secretion 0 (0.0%) 1 (1.3%) 3 (25%) .000 Hypogonadism in women 9 (9.5%) 10 (18.2%) 2 (66%) .028 Hypogonadism in men 1 (100%) 10 (50%) 7 (77.7%) .135 Central hypothyroidism 4 (4.2%) 7 (9.3%) 4 (33.3%) .001 Central hypocortisolism 2 (2.1%) 4 (5.3%) 4 (33.3%) .001 GH deficiency 0 (0.0%) 5 (6.6%) 2 (16.6%) .135 Central diabetes insipidus 0 0 1 (8.3%) - Radiological Maximal diameter (mm) 6 (5-7.9) 14 (11-19.6) 47 (43-57) .000 Chiasm compression 3 (3.1%) 18 (24%) 8 (66.6%) .000 Cavernous sinus invasion 7 (7.4%) 32 (42.6%) 5 (41.2%) .000 Tumor size (mm 3 ) 81 (33-144) 1063 (350-2732) 31500 (27249-45109) .000 Data expressed as n(%) or median (interquartile range). BMI, body mass index. MEN, Multiple Endocrine Neoplasia. GH, growth hormone. Additional Declarations No competing interests reported. Supplementary Files Suppltable1Medicaltreatmentadministeredtopatientswithprolactinomas.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4573462","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":319477696,"identity":"1755c5ee-ed0b-49cd-b7b4-4b162b055310","order_by":0,"name":"Daniel 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studied.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4573462/v1/64d64c07ee869409628935bd.png"},{"id":59965833,"identity":"5f58c593-abb5-485c-a6aa-b2f324c5f961","added_by":"auto","created_at":"2024-07-10 02:01:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":28758,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier survival analysis comparing probability of remission between microprolactinomas (black solid line), macroprolactinomas (gray solid line), and giant prolactinomas (dashed line).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4573462/v1/fb09cbc3d1c61722e1ce6832.png"},{"id":59965828,"identity":"ebf5e532-f11f-4f42-96eb-ca0f4300c9d6","added_by":"auto","created_at":"2024-07-10 02:01:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":23189,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier survival analysis comparing the probability of negative MRI at last follow-up between microprolactinomas (black solid line), macroprolactinomas (gray solid line), and giant prolactinomas (dashed line).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4573462/v1/b6aad5039abc6633fdfbd1bd.png"},{"id":59965831,"identity":"aa80ed19-7170-417e-9b55-979f5edf4240","added_by":"auto","created_at":"2024-07-10 02:01:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":289929,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA. \u003c/strong\u003eMedian (interquartile range) of percentage of tumor volume reduction after treatment with dopamine agonists grouped by tumor size at diagnosis. \u003cstrong\u003eB. \u003c/strong\u003eRemnant volume (mm\u003csup\u003e3\u003c/sup\u003e) at last follow-up grouped by tumor size at diagnosis (volume scale adjusted for each tumor size). Kurskal-Wallis test p\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4573462/v1/42ea07c4d22a546a32ea63df.png"},{"id":59965832,"identity":"60ae658a-e3ee-41cc-8276-465d9e43c6a1","added_by":"auto","created_at":"2024-07-10 02:01:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":80993,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA. \u003c/strong\u003eCumulative hazard to biochemical recurrence in microprolactinomas (black line), and macroprolactinomas (gray line). \u003cstrong\u003eB. \u003c/strong\u003eMicroprolactinomas and, \u003cstrong\u003eC. \u003c/strong\u003eMacroprolactinomas, with persistent hyperprolactinemia (“active”) or under remission, grouped by tumor remnant at last follow-up.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4573462/v1/8b291b92c60ceff08887ac16.png"},{"id":59967098,"identity":"d6107862-2e97-4232-9cbb-93bd58bdc946","added_by":"auto","created_at":"2024-07-10 02:17:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":992009,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4573462/v1/623093d3-dd79-4d8c-a2b2-8661d3ed059a.pdf"},{"id":59965830,"identity":"93a981a9-c527-4e1a-b69a-1eb0efe9d3f8","added_by":"auto","created_at":"2024-07-10 02:01:16","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14214,"visible":true,"origin":"","legend":"","description":"","filename":"Suppltable1Medicaltreatmentadministeredtopatientswithprolactinomas.docx","url":"https://assets-eu.researchsquare.com/files/rs-4573462/v1/4696c8bf641c4d84f6ccb1c5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk Factors for Biochemical Recurrence in Prolactinomas After Withdrawal of Dopamine Agonists: A Retrospective Cohort Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProlactinomas are the most common secretory pituitary tumor, with a prevalence between 32 to 66% in clinical settings\u0026nbsp;[1]. Although these tumors are benign, they produce symptoms due to hyperprolactinemia and local mass effects\u0026nbsp;[2]. Medical therapy with dopamine agonists (DAs) is the first-line treatment, showing success rates of 70-90%, while surgery and radiotherapy are alternatives in selected cases\u0026nbsp;[3].\u003c/p\u003e\n\u003cp\u003eTumor size at diagnosis could influence the onset and course of the disease. Classical differences in clinical and biochemical characteristics between micro- and macroadenomas have been described [2]. However, when those tumors are compared with giant prolactinomas (\u0026gt;4 cm), information is scarce. In bigger tumors, some studies have suggested lower rates of biochemical remission, and higher frequency of hypopituitarism [2, 4]. However, other reports have not found an association between tumor size and necessity of long-term medical treatment because of persistent hyperprolactinemia [4]. Since outcome information is limited when comparing medical therapy in micro or macroprolactinomas with giant tumors, here we aimed to assess the risk factors for hyperprolactinemia recurrence after DA treatment withdrawal. \u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe clinical records of all patients with hyperprolactinemia in the Neuroendocrinology Clinic, Department of Endocrinology and Metabolism, at the Instituto Nacional de Ciencias M\u0026eacute;dicas y Nutrici\u0026oacute;n Salvador Zubir\u0026aacute;n, in Mexico City, from January 2000 to October 2023 were reviewed (figure 1). \u0026nbsp; Clinical, biochemical, and radiological features of the tumors were extracted.\u0026nbsp;According to their maximum diameter at diagnosis, tumors were classified as\u0026nbsp;microadenomas (\u0026lt;10 mm), macroadenomas (\u0026ge;10 mm), and giant adenomas\u0026nbsp;(\u0026ge;40mm).\u0026nbsp;Tumor volume was calculated by the Ellipsoid formula [0.5 x (width x length x height)][5].\u0026nbsp;Optic chiasm compression was defined as a grade D in the Hardy classification system, and positive extension and cavernous sinus invasion were defined with the Knosp classification\u0026nbsp;[6]. Treatment included medical therapy with dopamine agonists, surgery, and radiotherapy. The cumulative dosage of the dopaminergic agonist administered was calculated by obtaining the mean dosage given and multiplying it for the time under medical treatment. Withdrawal attempts of DAs required a patient with prolactinoma who had received DAs for at least two years, had normal (3-25 ng/mL) or low (\u0026lt;3 ng/mL) prolactin (PRL) serum concentration and showed a \u0026ge;50 % tumor volume shrinkage from baseline\u0026nbsp;[7]. DA\u0026rsquo;s dose was progressively reduced until stopped when cases remained asymptomatic and without hyperprolactinemia, consistent with disease remission.\u0026nbsp;Remission was defined by persistent normal PRL serum concentration after at least 6 months of DA treatment withdrawal.\u0026nbsp;Recurrence was established if, after remission, the PRL increased above the upper limit of the normal range, and/or tumor regrowth on MRI, requiring DA therapy to be\u0026nbsp;resumed\u0026nbsp;[8].\u0026nbsp;Tumor remnant was defined as positive MRI for tumor lesion of any volume or size at last follow-up, after accomplished DA therapy withdrawal criteria described above.\u003c/p\u003e\n\u003cp\u003ePost-treatment outcomes included biochemical remission, percentage of tumor volume reduction, and presence of tumor remnant. We included patients treated only with DAs to compare the effect of medical therapy on the biochemical and tumoral outcomes between microprolactinomas, and macroprolactinomas, without the confusion of other treatment strategies like surgery and/or radiotherapy. In the case of giant tumors (n=12), however; other treatment modalities were needed, such as neurosurgery (n=6, 50%) or adjuvant radiotherapy (n=3, 25%), to avoid permanent visual deficits because of tumor growth, and persistent prolactin hypersecretion despite DA therapy. Therefore, in this subgroup we included all patients identified, regardless of their treatment. The Local Ethics Review Committee approved the study protocol and followed the ethical guidelines of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData was expressed as mean\u0026nbsp;\u0026plusmn;SD or median and interquartile range according to variables distribution. Categorical variables were expressed with n, percentage, and compared using chi square test. Dimensional parameters were analyzed using independent t student or Mann-Whitney U test as needed. One-way ANOVA or Kruskal-Wallis tests were used to compare quantitative variables between three of more groups. Log-rank test and Kaplan-Meier curves were used to estimate the probability of biochemical remission, and recurrence at last follow-up.\u0026nbsp;A multivariate logistic regression analyses adjusted for potential confounders\u0026nbsp;were performed to identified independent and significant risk factors related with remission and recurrence at last follow-up. Statistical significance was assumed if \u003cem\u003ep\u003c/em\u003e \u0026lt;0.05. We used IBM SPSS Statistics 25 software.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eBaseline characteristics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA total of 182 patients were included in the analysis (figure 1). The clinical and biochemical characteristics of the patients are shown in Table 1. \u0026nbsp;The median age at diagnosis was not statistically different between microprolactinoma [31 years (25-38)], macroprolactinoma [31 (22-41)], and giant prolactinoma [34 (19-38)], respectively (p=0.99). Micro- and macroprolactinoma were more frequent in women, with 99% and 73% respectively, while giant prolactinomas were more common in men (75%) (Table 1). Patients with larger tumors were associated with higher baseline prolactin concentration, greater frequency of optic chiasm compression and cavernous sinus invasion (p\u0026lt;0.05). However, galactorrhea showed a significant relationship with smaller tumor size being more frequent in microprolactinomas, and macroprolactinomas, than in giant tumors because of the gender distribution of these tumors (Table 1,\u0026nbsp;p\u0026lt;0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTreatment\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following information is presented for microprolactinoma, macroprolactinoma, and giant prolactinoma. The median follow-up after withdrawal was 11.7 (5.7-15.5), 7.0 (5.0-13.0), and 2.5 (0-6.8) years (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05), respectively. Cabergoline was the most frequently used DA [90 (95%); 71 (95%); and 11 (92%)] with a median dose of 1.2 (0.25-4.0), 2.2 (1.5-3.5), and 2.8 (1.5-8.0) mg/week (p\u0026lt;0.001), respectively. \u0026nbsp;Other DA used (bromocriptine, quinagolide, and lisuride) are summarized in supplementary table 1. Patients with greater tumor diameter received higher doses of cabergoline and bromocriptine (supplementary table 1). Duration of treatment was 4.2 (2.1-8.1); 4.5 (2.4-7.7), and 6.1 (2.6-9.2) years, respectively (p=0.09). Overweight and obesity was highly prevalent on three groups (table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBiochemical outcomes\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe biochemical and radiological data of the patients are shown in table 1. Biochemical remission was achieved in 77 (81%), 50 (67%), and 3 (27%) cases of micro-, macro-, and giant -prolactinomas, respectively (log-rank test, p\u0026lt;0.001, figure 2). Microprolactinomas showed the lowest rate of hypopituitarism (n=13, 13.6%), followed by macroprolactinomas (n=22, 29%), and giant prolactinomas (n=12, 100%). The gonadotroph axis was the most commonly affected (n=40, 23%), followed by central hypothyroidism (n=22, 12%), and central hypocortisolism (n=19, 10%). A lineal association was found between tumor-size (micro-, macro-, and giant-prolactinomas, respectively) and proportion of central hypothyroidism (n=6, 6.3%; n=6, 8.2%; n=10, 83%), central hypocortisolism (n=3, 4.1%; n=8, 12.5%; n=8, 73%), and GH deficiency (n=1, 1.7%; n=3, 5.5%; n=3, 43%) (all p\u0026lt;0.001). The only cases with arginine-vasopressin deficiency (central diabetes insipidus) at diagnosis, were giant prolactinomas (n=2, 1.1%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRadiologic outcomes\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eProbability for negative MRI throughout follow-up was significatively higher for microprolactinomas (24%) and macroprolactinomas (19%) after compared to giant prolactinomas (0%) (Figure 3, p=0.02). However, we noticed that frequency of visible tumor at last follow-up was high in the three groups. Therefore, we also compared the percentage of tumor volume reduction in each group (figure 4). The median (interquartile range) \u0026nbsp;of tumor volume reduction was also not significantly different between microprolactinoma [61% (17-96)], macroprolactinoma [92% (66-97)], and giant prolactinoma [84% (20-94), p=0.12, figure 4]. After excluding outliers (n=2), the median volume reduction in all tumors were 81% (48-96, figure 4A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe median volume of tumor remnants were significantly different at last follow-up, been 14 mm\u003csup\u003e3\u003c/sup\u003e (2-46) for microprolactinomas, 96 mm\u003csup\u003e3\u003c/sup\u003e (14-270) for macroprolactinomas, and 2189 mm\u003csup\u003e3\u0026nbsp;\u003c/sup\u003e(1483-19518) for giant prolactinomas (p\u0026lt;0.001, figure 4B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRemission rates by tumor size\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMacroprolactinomas showed significantly higher probability of biochemical recurrence at last follow-up (figure 5A, p=0.02). Around half of cases that were under remission showed persistent tumor remnants, seen in 54% (n=51) of micro- (figure 5B), and 46% (n=35) of macroprolactinomas (figure 5C, all p\u0026lt;0.01). All cases with persistent hyperprolactinemia showed a remnant microprolactinoma (figure 5B). Also, two cases with macroprolactinomas (3%) without tumor remnant at last MRI could not reached remission (Figure 5C).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFactors independently associated with remission or recurrence\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe performed a logistic regression analysis adjusted for potential confounders such as duration of treatment, DAs cumulative dose, and tumor size at diagnosis, to identify risk factors independently and significantly associated with remission or recurrence. Duration of therapy with DAs was the only variable significantly associated with remission (p\u0026lt;0.01). Also, results confirmed that the tumor size at diagnosis was significantly related to biochemical recurrence, but tumor remnant at last follow-up was not (p=0.81). \u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe report a higher likelihood to achieve biochemical remission in patients with microprolactinomas compared to both macroadenomas and giant prolactinomas. In addition,\u0026nbsp;independently of tumor size at diagnosis, and the DA cumulative dose received,\u0026nbsp;once patient have achieved a median of\u0026nbsp;~80% volume reduction, tumors were unlikely to decrease further. Consequently,\u0026nbsp;among cases under remission at last follow-up, almost half with\u0026nbsp;microprolactinomas and macroprolactinomas\u0026nbsp;persisted with tumor remnants (figure 5). Multivariate regression analysis confirmed\u0026nbsp;that tumor remnant at last follow-up, therefore, was not significantly associated with recurrence risk (p=0.81). In fact,\u0026nbsp;duration of therapy, was the only variable independently and significantly associated with remission at last follow-up (p\u0026lt;0.01).\u003c/p\u003e\n\u003cp\u003eThe association of tumor remnants and remission rates has yielded varied results\u0026nbsp;[9-11]. \u0026nbsp;In our cohort, microprolactinomas showed higher probability of remission. Nevertheless, it was not dependent on tumor disappearance. Such patients showed the higher probability of remission\u0026nbsp;(p\u0026lt;0.05) despite 54% of them having remnant tumors at last MRI. Similarly, 81% of macroprolactinomas had tumor remnant, and 46% were cases under remission (figure 5). Probably, DAs therapy progressively causes structural changes in lactotroph tumor cells related with fibrosis, which may cause lower expression of dopamine D2 receptor, and less PRL secretion. After years of good responsiveness, the tumor stops decreasing in size with a persistent remnant, but without any further PRL secretion. Therefore, patients with prolactinoma may persist with positive MRI findings. This is important to avoid overtreatment, and, suggests that DAs withdrawal should not be based on the absence of tumor at MRI\u0026nbsp;[9-13]. We suggest that after at least two years (ideally 3 years) of therapy and, normalization or also ideally suppression of PRL serum concentration throughout follow-up, it might be considered enough criteria to gradually initiate DAs dose reduction to evaluate remission, and withdrawal of medical therapy. Although these assumptions may also be expected for giant prolactinomas, in our cohort, these tumors received multiple interventions and, therefore, associations with DAs outcomes alone, were not possible. However, we decided to include giant tumors to compare other interesting results. First, the median age at diagnosis was similar independently of tumor size (p=0.99, Table 1). This may be explained because symptoms related to hyperprolactinemia, rather than those related to mass effect, are the main reason why patients reach for medical attention. Secondly, we confirmed excellent response to DAs in patients with giant prolactinoma, with an important reduction of tumor volume, been very helpful to correct optic chiasm compression in all but 1 case (figure 4). Nevertheless, giant tumors showed a lower probability of disease control at follow-up (27%). Such result may be due to lower maximum doses of DAs in our cohort than those suggested in previous studies (19-24). Third, higher tumor volume was related to a higher frequency of anterior pituitary hormone deficiencies. Giant prolactinomas additionally showed posterior pituitary lobe involvement and arginine-vasopressin deficiency (central diabetes insipidus). Fourth, weight increment is common in cases with hyperprolactinemia. However, overweight and obesity was similarly prevalent in all three groups, independently of tumor size and prolactin levels. Therefore, it can be considered a frequent clinical finding in prolactinomas independently of tumor size at diagnosis. Finally, giant prolactinomas were observed more frequently in males (75%) which was consistent with previous studies\u0026nbsp;[14-16].\u003c/p\u003e\n\u003cp\u003eLimitations of our cohort study include its observational nature, and the relatively small number of patients with giant prolactinoma. However, the number of cases reach enough statistical power to compare study outcomes. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn conclusion, microprolactinomas have a higher probability of biochemical remission with medical therapy. Duration of DA therapy was the only variable significantly associated with persistent biochemical remission at last follow-up. Probability of biochemical recurrence after withdrawal of DA therapy in micro and macroprolactinomas was not associated with tumor remnant.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of interest:\u0026nbsp;\u003c/strong\u003eAuthors have nothing to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement: \u0026nbsp;\u003c/strong\u003eThis study did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVroonen L, Daly AF, Beckers A.: Epidemiology and Management Challenges in Prolactinomas. Neuroendocrinology. (2019). https://doi.org/10.1159/000497746\u003c/li\u003e\n\u003cli\u003eChanson P, Maiter D.: The epidemiology, diagnosis and treatment of Prolactinomas: The old and the new. Best. Pract. Res. Clin. Endocrinol. Metab. (2019) https://doi.org/101290.10.1016/j.beem.2019.101290\u003c/li\u003e\n\u003cli\u003eMelmed S, Casanueva FF, Hoffman AR, Kleinberg DL, Montori VM, Schlechte JA, et al.: Diagnosis and treatment of hyperprolactinemia: an Endocrine Society clinical practice guideline. J. Clin. Endocrinol. Metab. (2011) https://doi.org/10.1210/jc.2010-1692\u003c/li\u003e\n\u003cli\u003eShrivastava RK, Arginteanu MS, King WA, Post KD.: Giant prolactinomas: clinical management and long-term follow up. J. Neurosurg. (2002) https://doi.org/10.3171/jns.2002.97.2.0299\u003c/li\u003e\n\u003cli\u003eLundin P, Pedersen F.: Volume of pituitary macroadenomas: assessment by MRI. J. Comput. Assist. Tomogr. (1992) https://doi.org/10.1097/00004728-199207000-00004\u003c/li\u003e\n\u003cli\u003eDi Ieva A, Rotondo F, Syro LV, Cusimano MD, Kovacs K.: Aggressive pituitary adenomas--diagnosis and emerging treatments. Nat. Rev. Endocrinol. (2014) https://doi.org/10(7):423-35.10.1038/nrendo.2014.64\u003c/li\u003e\n\u003cli\u003eDogansen SC, Selcukbiricik OS, Tanrikulu S, Yarman S.: Withdrawal of dopamine agonist therapy in prolactinomas: In which patients and when? Pituitary. (2016) https://doi.org/10.1007/s11102-016-0708-3\u003c/li\u003e\n\u003cli\u003eTeixeira M, Souteiro P, Carvalho D.: Prolactinoma management: predictors of remission and recurrence after dopamine agonists withdrawal. Pituitary. (2017) https://doi.org/10.1007/s11102-017-0806-x\u003c/li\u003e\n\u003cli\u003eKharlip J, Salvatori R, Yenokyan G, Wand GS.: Recurrence of hyperprolactinemia after withdrawal of long-term cabergoline therapy. J. Clin. Endocrinol. Metab. (2009) https://doi.org/10.1210/jc.2008-2103\u003c/li\u003e\n\u003cli\u003eBiswas M, Smith J, Jadon D, McEwan P, Rees DA, Evans LM, et al.: Long-term remission following withdrawal of dopamine agonist therapy in subjects with microprolactinomas. Clin. Endocrinol. (2005) https://doi.org/10.1111/j.1365-2265.2005.02293.x\u003c/li\u003e\n\u003cli\u003eHuda MS, Athauda NB, Teh MM, Carroll PV, Powrie JK.: Factors determining the remission of microprolactinomas after dopamine agonist withdrawal. Clin. Endocrinol. (2010) https://doi.org/10.1111/j.1365-2265.2009.03657.x\u003c/li\u003e\n\u003cli\u003ePassos VQ, Souza JJ, Musolino NR, Bronstein MD.: Long-term follow-up of prolactinomas: normoprolactinemia after bromocriptine withdrawal. J. Clin. Endocrinol. Metab. (2002) https://doi.org/10.1210/jcem.87.8.8722\u003c/li\u003e\n\u003cli\u003eColao A, Di Sarno A, Guerra E, Pivonello R, Cappabianca P, Caranci F, et al.: Predictors of remission of hyperprolactinaemia after long-term withdrawal of cabergoline therapy. Clin. Endocrinol. (2007) https://doi.org/10.1111/j.1365-2265.2007.02905.x\u003c/li\u003e\n\u003cli\u003eMaiter D, Delgrange E.: Therapy of endocrine disease: the challenges in managing giant prolactinomas. Eur. J. Endocrinol. (2014) https://doi.org/10.1530/eje-14-0013\u003c/li\u003e\n\u003cli\u003eEspinosa E, Sosa E, Mendoza V, Ram\u0026iacute;rez C, Melgar V, Mercado M.: Giant prolactinomas: are they really different from ordinary macroprolactinomas? Endocrine. (2016) https://doi.org/10.1007/s12020-015-0791-7\u003c/li\u003e\n\u003cli\u003eHamidi O, Van Gompel J, Gruber L, Kittah NE, Donegan D, Philbrick KA, et al.: MANAGEMENT AND OUTCOMES OF GIANT PROLACTINOMA: A SERIES OF 71 PATIENTS. Endocrine. Pract. (2019) https://doi.org/10.4158/ep-2018-0392\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Baseline clinical, biochemical, and radiological characteristics of patients with prolactinomas treated with DA only (n=182)\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"101%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003eMicroprolactinomas (n=95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\" valign=\"top\"\u003e\n \u003cp\u003eMacroprolactinomas (n=75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\"\u003e\n \u003cp\u003eGiant prolactinomas (n=12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.625%\" rowspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003eClinical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.708333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eFemale n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.875%\" valign=\"top\"\u003e\n \u003cp\u003e94 (99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.875%\" valign=\"top\"\u003e\n \u003cp\u003e55 (73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" valign=\"top\"\u003e\n \u003cp\u003e3 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.291666666666667%\" valign=\"top\"\u003e\n \u003cp\u003e.\u003cstrong\u003e000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e31 (25-38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e31 (22-41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e34 (19-38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e26.1 (21.5-30.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e26.8 (23.6-31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e28.2(26.5-31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eHeadache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e69 (86.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e53 (84.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e8 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eMenstrual disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e71 (79.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e49 (90.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e3 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eErectile dysfunction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e1 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e10 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e5 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e.269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eGalactorrhea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e76 (84.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e46 (74.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e3 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e.\u003cstrong\u003e009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eMEN1 syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e5 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e3 (4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e1 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e.796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.625%\" rowspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003eBiochemical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.708333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eProlactin (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.875%\" valign=\"top\"\u003e\n \u003cp\u003e98 (74-130)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.875%\" valign=\"top\"\u003e\n \u003cp\u003e244 (112-765)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" valign=\"top\"\u003e\n \u003cp\u003e680(117- 2000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.291666666666667%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eHormonal co-secretion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e3 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eHypogonadism in women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e9 (9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e10 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e2 (66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.028\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eHypogonadism in men\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e1 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e10 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e7 (77.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eCentral hypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e4 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e7 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e4 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eCentral hypocortisolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e2 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e4 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eGH deficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e5 (6.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e2 (16.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eCentral diabetes insipidus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e1 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.625%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eRadiological\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.708333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eMaximal diameter (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.875%\" valign=\"top\"\u003e\n \u003cp\u003e6 (5-7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.875%\" valign=\"top\"\u003e\n \u003cp\u003e14 (11-19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" valign=\"top\"\u003e\n \u003cp\u003e47 (43-57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.291666666666667%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eChiasm compression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e3 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e18 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e8 (66.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eCavernous sinus invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e7 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e32 (42.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e5 (41.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.987654320987655%\" valign=\"top\"\u003e\n \u003cp\u003eTumor size (mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e81 (33-144)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e1063 (350-2732)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e31500 (27249-45109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.641975308641975%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eData expressed as n(%) or median (interquartile range). BMI, body mass index. MEN, Multiple Endocrine Neoplasia. GH, growth hormone.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"prolactin, pituitary adenoma, neuroendocrine tumor, cabergoline, bromocriptine","lastPublishedDoi":"10.21203/rs.3.rs-4573462/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4573462/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eContext: \u003c/strong\u003eDopamine agonists (DA), mainly cabergoline, are the primary therapy for prolactinomas. Risks factors related with biochemical recurrence after DA withdrawal are not completely understood.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eTo assess hyperprolactinemia recurrence risk factors after dopamine agonist (DA) withdrawal in prolactinomas.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign: \u003c/strong\u003eRetrospective, comparative, observational cohort study. Survival, and multivariate regression analyses were performed to estimate biochemical remission (prolactin (PRL) 3-25 ng/mL after at least 6 months of DA withdrawal), and recurrence (\u0026gt;25 ng/ml and/or tumor regrowth) at follow-up.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003e1140 patients with hyperprolactinemia were evaluated. Prolactinoma was confirmed in 182 cases. Micro- (n=95), and macroprolactinoma (n=75) were more frequent in women (99% and 73%, respectively), while giant prolactinomas (n=12) were more common in men (75%). Cabergoline was the most frequently (92-95%) DA used with a median dose of 1.2 (0.25-4.0), 2.2 (1.5-3.5), and 2.8 (1.5-8.0) mg/week (p\u0026lt;0.001), respectively. Higher tumor size at diagnosis was significantly related to biochemical recurrence (p\u0026lt;0.02). However, independently of tumor size at diagnosis, and the DA cumulative dose received, once patient have achieved an 80% volume reduction, tumors were unlikely to decrease further (p=0.02). Among cases under remission at last follow-up, almost half with microprolactinomas (n=51, 54%), and macroprolactinomas (n=35, 46%) persisted with tumor remnants. Multivariate regression analysis confirmed that tumor remnant at last follow-up was not significantly associated with recurrence risk (p=0.81). Duration of therapy was the only variable significantly associated with remission (p\u0026lt;0.01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eProbability of biochemical recurrence after withdrawal of DA therapy in micro and macroprolactinomas was not significantly associated with tumor remnant. Duration of DA therapy was the only variable significantly associated with remission.\u003c/p\u003e","manuscriptTitle":"Risk Factors for Biochemical Recurrence in Prolactinomas After Withdrawal of Dopamine Agonists: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-10 02:01:12","doi":"10.21203/rs.3.rs-4573462/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"05ca03a7-ec61-4aae-b0f2-05c437279397","owner":[],"postedDate":"July 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-10T02:01:14+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-10 02:01:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4573462","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4573462","identity":"rs-4573462","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}