Subsequent Primary Malignancies in Patients with Initial Diagnosis of Pituitary Adenoma (Pit-NET): a Surveillance, Epidemiology, and End Results (SEER) Data Analysis

Subsequent Primary Malignancies in Patients with Initial Diagnosis of Pituitary Adenoma (Pit-NET): a Surveillance, Epidemiology, and End Results (SEER) Data Analysis | 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 Subsequent Primary Malignancies in Patients with Initial Diagnosis of Pituitary Adenoma (Pit-NET): a Surveillance, Epidemiology, and End Results (SEER) Data Analysis Maxwell W. Pickles, Thomas Z. Rohan, Sydney M. Macon, Preston Carey, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7810484/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Feb, 2026 Read the published version in Pituitary → Version 1 posted 9 You are reading this latest preprint version Abstract Background : Pituitary Adenoma (Pit-NET) is a frequently encountered intracranial mass that is typically characterized by slow growth and benign behavior. There remains limited knowledge regarding the risk of developing a “subsequent primary malignancy” (SPM) in a patient with a pituitary adenoma. This study assessed the risk of developing a SPM after a Pit-NET diagnosis. Methods : The Surveillance, Epidemiology, and End Results (SEER-17) data registry, which consisted of 9,208,295 patients, was utilized to generate a cohort of 60,677 patients diagnosed with Pit-NET to identify patients at risk for a SPM. The SEER patient data was collected from the years 2000 to 2020. Statistical analysis was performed through SEER’s stat package and Standardized Incidence Ratios (SIRs) for various malignancies after the diagnosis of primary Pit-NET were obtained. We also collected basic demographic, surgical, and postoperative data. Results : Of the 60,677 patients, 4,067 (6.7%) received a diagnosis of a SPM, which correlates to a higher risk than the general population (SIR, 1.1, 99% CI, 1.06-1.15). Patients with a Pit-NET had an increased risk of the following cancers: lymphatic and hematopoietic (SIR, 1.25; 99% CI, 1.09-1.41), kidney and renal pelvis (SIR, 1.45; 99% CI, 1.2-1.74), cutaneous melanoma (SIR, 1.36; 99% CI, 1.15-1.16), and thyroid cancer (SIR, 2.76; 99% CI, 2.32-3.26). Additionally, females were more predisposed to the following cancers: Digestive system (SIR, 1.19; 99% CI, 1.11-1.25), and non-Hodgkin's Lymphoma (SIR, 1.41; 99% CI, 1.04-1.88). Conclusion : Utilizing the SEER database, we have discovered an increased risk of SPM in patients with pituitary adenoma. Supplementary research may be done to determine any shared genetic abnormalities between the development of Pit-NET and these SPMs. Additionally, further research of the endocrinological effects of Pit-NET and potential associations to SPMs should be studied. Pituitary Adenoma Subsequent Primary Malignancy SEER Standardized Incidence Ratio (SIR) Epidemiology Endocrine neoplasms Figures Figure 1 Figure 2 Figure 3 Introduction Pituitary Adenoma (Pit-NET) represent 15% of all primary cranial neoplasms [1]. Clinically relevant Pit-NETs occur with a mean prevalence of 89.1 per 100,000 (range, 75.7-115.6 per 100,000) [2]. From the most recent report of the Central Brain Tumor Registry of the US, from the years 2012-2016, Pit-NETs comprise a sizeable portion of newly diagnosed tumors annually with an incidence of 4.07 cases per 100,000 per year [3]. A separate SEER study that studied 47,180 Pit-NET patients from 2004-2016, found an overall standardized incidence rate (SIR) of 4.8 cases per 100,000 person years, and the annual incidence rate continually trended upwards [4]. Pit-NETs have a statistically significant higher incidence in blacks compared with whites and make up the highest proportion of central nervous system tumors occurring in children, adolescents and young adults (15-39 years) (2). Prolactinomas make up 53% of Pit-NETs and are frequently associated with clinical symptoms such as hypogonadism, infertility, and galactorrhea [5]. Transsphenoidal surgery is indicated as the first-line therapy for most cases of functioning Pit-NETs, with the exception of prolactinomas in which medical therapy including dopamine agonists are the first line [6]. Radiation therapy is a third-line therapy option following unsuccessful transsphenoidal surgery, unresectable tumor recurrence, and failure of medical treatment [6]. Given the increased incidence rates due to widespread use of magnetic resonance imaging and the generally favorable prognosis of pituitary adenoma, researchers have begun shifting their attention towards long-term outcomes such as development of subsequent primary malignancies (SPM) following an initial diagnosis of Pit-NET [1,4]. Previous studies, including those by Yamanaka at el. [7] and Minniti at el. [8], have investigated the risk of secondary intracranial tumors following radiotherapy for Pit-NETs. These studies reported elevated risk of neuroepithelial tumors, meningioma, meningeal sarcoma, and astrocytoma. However, the scope of those studies was limited to intracranial malignancies and relied on smaller samples sizes. Our study seeks to address these limitations by expanding the focus to include the risk of malignancies throughout the body, utilizing a larger sample size. There remains a significant gap in understanding the risk of subsequent intracranial and systemic malignancies in pituitary adenoma. To address this, our objective was to evaluate the risk of SPM in Pit-NET patients utilizing the Surveillance, Epidemiology, and End Results program available through the National Cancer Institute. By leveraging a robust cohort of over 60,000 patients, we aim to provide comprehensive insights into the long-term malignancy risks associated with pituitary adenoma. Methods Patients and design: This Pit-NET cohort was generated from the SEER-17 cancer registries that included San Franciso-Oakland SMSA, Connecticut, Hawaii, Iowa, New Mexico, Seattle (Puget Sound), Utah, Atlanta (Metropolitan), San Jose-Monterey, Los Angeles, Alaska Native, Rural Georgia, California excluding SF/SJM/LA, Kentucky, Louisiana, New Jersey, and Greater Georgia. This registry excluded Alaska and covers roughly 27% of the U.S. population. Cancer diagnoses occurred any time between January 2000 and December 2020. The primary Pit-NET cohort was selected via the World Health Organization’s International Classification of Diseases for Oncology, third edition (ICD-O-3) code. The subtypes of Pit-NET included: adenoma (NOS; 8140/0), atypical adenoma (8140/1), adenocarcinoma in suit, (8140/2), and adenocarcinoma (8140/3). First record matching selection criteria was selected. All outcome variables provided in SEER were selected using ICD-O-3/WHO 2008 (for SIRs) site codes. The timing of the first primary diagnosis of Pit-NET was used as the initial date from which outcome latencies were calculated. Patients diagnosed with an SPM within 2 months of their primary Pit-NET diagnosis were excluded, due to the high likelihood of them being related malignancies and to decrease the chance a metastatic disease was misclassified. Prior studies investigating SPMs have excluded patients with a SPM less than 6 months after index malignancy, in order to avoid including primary cancers that may have been present, but not clinically evident at the time of initial diagnosis [9]. We opted for a two-month threshold, as we believed it would similarly reduce the risk of misclassification while retaining more patients in the study. Patients were also excluded if the report was obtained solely from a death certificate or autopsy report with no confirmation of diagnosis. The study of this SEER generated cohort was exempt from institutional review board approval. Statistical analysis: Relative risk was calculated by using the Standardized Incidence Ratio (SIR), defined as the ratio between observed cases (O) and expected cases (E) of malignancies (SIR = O/E). An SIR of 1.0 would indicate no difference in incidence rates between patients and the general population. Statistical significance was established based on 99% confidence intervals (CI). Person-years at risk (PYR) were calculated for each participant starting two months after their initial Pit-NET diagnosis, and ending upon death, the date last known alive, or December 31, 2020. The excess absolute risk (EAR) per 10,000 person-years was calculated as: [(O-E) / PYR)] x 10,000. EAR measures the actual number of excess events, normalized to the number of person-years observed. In contrast, relative risks like SIR measure the fold difference (e.g., 3-fold increase). SIR serves to test etiological hypotheses, while EAR tends to be more representative when assessing cancer burden impact in a given population. To calculate the number of expected malignancies, a reference rate file of each cancer per 100,000 was calculated using SEER*Stat software package 8.4.0.1 (National Cancer Institute, Bethesda, MD) and applied to the number of patients in our cohort and the SEER-17 cohort registry. Results Our analysis identified 62,627 unique cases of primary Pit-NET diagnosed between January 2000 and December 2020 (Figure 1). A total of 1,950 patients were excluded based on our inclusion criteria, resulting in a final cohort of 60,677 (Figure 2). Among these cases, 4,074 patients subsequently developed a SPM (Figure 1). Of these patients, 2,283 (56%) were male, and 1,791 (44%) were female (Table 1). Most patients (84.3%) were aged between 40 and 79 years, while a smaller proportion were younger than 40 (8.9%) or older than 80 years (6.7%) (Table 1). Additionally, the patient population was predominantly White (74.2%), followed by Black patients (17.8%) (Table 1). We observed a 10% increase in risk in developing a SPM at all sites in both male and female patients (SIR, 1.1, 99% CI, 1.06-1.15, EAR, 9.21/10,000 person-years) when compared to the general population (Fig. 1, Table 2). Male and female patients diagnosed with Pit-NET showed increased risk of all the cancers included in Table 2, but the risk was disproportionately higher for the following malignancies: small intestine (SIR, 2.02, 99% CI, 1.30-2.98), kidney and renal pelvis (SIR, 1.45, 99% CI, 1.20-1.74), and thyroid (SIR, 2.76, 99% CI, 2.32-3.26) (Table 2). Upon gender-based stratification of the data, male patients did not exhibit a universally increased risk at all sites (SIR, 1.05, 99% CI, 0.99-1.10, EAR, 5.81/10,000 person-years), however they did demonstrate a statistically significant predisposition to SPMs of lymphatic and hematopoietic (SIR, 1.2, 99% CI, 1.01-1.41), kidney and renal pelvis (SIR, 1.41, 99% CI, 1.11-1.72), cutaneous melanoma (SIR, 1.33, 99% CI, 1.07-1.62), and thyroid (SIR, 3.53, 99% CI, 2.58-4.70) (Table 2). In comparison to female patients, men were more predisposed to SPM of the thyroid (SIR, 3.53, 99% CI, 2.58-4.70 vs SIR, 2.5, 99% CI, 2.02-3.06) (Table 2). Conversely, females exhibited an increased risk of SPM across all sites (SIR, 1.18, 99% CI, 1.11-1.25, EAR, 11.71/10,000 person-years), with elevated risk, relative to males, to SPMs of the small intestine (SIR, 2.93, 99% CI, 1.62-4.86), pancreas (SIR, 1.48, 99% CI, 1.05-2.02), and non-Hodgkin’s lymphoma (SIR, 1.41, 99% CI,1.05-1.88) (Table 2). Temporal stratification of SIR scores revealed a significant increase in risk of SPMs at all sites in patients in the 2 months-1-year (SIR, 1.51) and 1-5-year time frame (SIR, 1.11) (Table 3). No elevated risk for SPMs at all sites was noted in subsequent intervals spanning 5-10-year, 10-15-year, and 15-year + (Table 3). The 2 month-1-year timeframe demonstrated increased risk of neoplasms of the pancreas (SIR, 2.49), kidney and renal pelvis (SIR, 1.86), cutaneous melanoma (SIR, 1.85), non-Hodgkin’s lymphoma (SIR, 2.04), and thyroid (SIR, 7.27) (Table 3). Elevated risk of Lymphatic and hematopoietic (SIR, 1.29) and small intestine (SIR, 2.22) SPMs was exclusive to the 1-5-year timeframe (Table 3). Thyroid cancer exhibited the most prolonged elevation in risk among the cohort, with SIR scores of 7.27, 2.62, and 2.15, indicating an increased risk up to 10-years following initial diagnosis (Table 3). Further age-stratified analysis indicated that patients <40-years (SIR, 1.65) and 40-50-years (SIR, 1,23) of age at the time of diagnosis were subject to a higher risk of SPMs across all sites, a risk that waned with advancing age. No increased risk was observed in those in the 50-60-year, 60-70-year, and 70+ age group (Table 3). Individuals in the 70+ cohort were susceptible to the greatest number of SPMs including lymphatic and hematopoietic (SIR, 1.27), kidney and renal pelvis (SIR, 1.47), cutaneous melanoma (SIR, 1.39), and thyroid (SIR, 2.86) (Table 3). The 40-50-year age group demonstrated the second-highest incidence of SPMs, particularly in the small intestine (SIR, 3.44), kidney and renal pelvis (SIR, 2.11), and thyroid (SIR, 2.42) (Table 3). Across all age groups, an elevated risk for thyroid cancer was present (Table 3). The <40-year age group displayed disproportionally heightened risk of pancreatic cancer (SIR, 9.72) (Table 3). Upon stratification by tumor size, across all cancer sites, statistically significant increased risks were observed for Pit-NETs sized 1-10 mm (SIR 1.13, 99% CI 1.02-1.25) and 11-20 mm (SIR 1.10, 99% CI 1.01-1.20). Among specific malignancies increased risks were found for pancreatic cancer in patients with 1-10 mm adenomas (SIR 1.87, 99% CI 1.08-2.98), kidney and renal pelvis cancer in 1-10 mm adenomas (SIR 1.97, 99% CI 1.26-2.92), and cutaneous melanoma in 11-20 mm adenoma (SIR 1.55, 99% CI 1.09-2.14). For thyroid cancer, statistically significant associations were noted across all tumor sizes, with the highest SIR observed in adenomas measuring 31-40 mm (SIR 4.00, 99% CI 1.94-7.23). Statistically significant associations were not observed for small intestine cancer, non-Hodgkin’s lymphoma, or lymphatic and hematopoietic malignancies. Discussion This study investigated the risk of developing subsequent malignancies following an initial diagnosis of Pit-NET utilizing the SEER database. This study incorporated 60,677 patients with pituitary adenoma, of which 4,074 developed a subsequent malignancy. Additionally, we evaluated the influence of age at initial diagnosis and time from initial diagnosis. Studies investigating SPMs in Pit-NET have focused more on the effects of radiation treatment and developing secondary intracranial malignancy [7,8,10] with patient populations in the hundreds, whereas our study is among the first to evaluate the development of systemic malignancies with a larger patient population of over 60,000 patients. The analysis revealed a 10% increased risk for developing all types of subsequent cancers after initial Pit-NET diagnosis, when compared to the general population. Notably, both genders exhibited an increased risk for various cancers, with particularly higher risks observed for small intestine, kidney and renal pelvis, and thyroid malignancies. Gender-specific stratification indicated that females exhibited an overall increased risk across all sites, with a higher risk for SPMs of the small intestine, pancreas, and non-Hodgkin’s lymphoma. Temporal stratification of SIR scores indicated a significant increased risk of SPM at all sites in the first year after initial diagnosis compared to the general population. Age-stratified analysis further demonstrated that those younger than 40 and between ages 40-50 patients, were at higher risk for SPMs. When stratified by tumor size, Pit-NETs measuring 1-20 mm were associated with an elevated risk of SPM at all sites. Our findings conveyed that among males, females, different age groups, and differing adenoma sizes, thyroid cancer demonstrated the most elevated risk. The observed elevated risk of SPMs among females with Pit-NETs may be attributed to several potential factors. First, hormonal influences could play a significant role. Estrogen is known to be involved in the carcinogenesis of certain cancers, such as breast and thyroid malignancies [11]. Pit-NETs may disrupt hormonal cycles, amplifying estrogen’s effects and potentially increasing susceptibility to SPM development [12]. Another explanation might be increased healthcare utilization among women. Females are more likely to engage in routine health screenings and medical evaluations compared to males, which could result in earlier and more frequent detection of SPMs [13]. Lastly, there may be sex-specific genetic or epigenetic predispositions. Differences in genetic profiles or epigenetic regulation between men and women might contribute to heightened susceptibility to both Pit-NETs and subsequent malignancies [14]. Further research is necessary to elucidate the mechanisms underlying this finding and to validate these theories. Our temporal findings indicated that patients within the first five years of their initial diagnosis, along with younger patients, faced an increased risk of developing a SPM. Notably, patients diagnosed within one year exhibited an SIR of 7.27 specifically for thyroid cancer. This striking finding, coupled with the overall increased risk of SPMs within five years of diagnosis, may be attributable to treatment-related effects. While the latency period for radiation-induced malignancies can vary, early effects of radiation therapy might explain the elevated SIR scores observed during this timeframe [7,8]. For younger patients, an early diagnosis of Pit-NETmay lead to prolonged exposure to endocrine dysregulation. This sustained imbalance could contribute to an increased cumulative risk for malignancies over time, potentially explaining the higher susceptibility in this group. Stratification by tumor size revealed that Pit-NETs measuring 1-20 mm were associated with significantly increased risk of SPMs at all sites, whereas larger adenomas (>21 mm) did not demonstrate this finding. The highest SIR values were observed for thyroid cancer across all tumor sizes, with the greatest risk in patients with adenomas measuring 31-40 mm. Increased risk in smaller adenomas may partially be explained by their greater likelihood of being functional tumors due to early manifestation of hormonal symptoms leading to prompt medical attention. Microadenomas (<10 mm) are more often functional, with prolactin-, growth hormone (GH), and adrenocorticotropic hormone (ACTH)-secreting subtypes being the most frequent [15]. Excess hormone production of GH and ACTH has been shown to increase cancer risk through mechanisms such as enhanced cellular proliferation, inhibition of apoptosis, and system inflammation [16]. Specifically, there has been reported a positive association between circulating IGF-1 levels and primary cancers, such as breast, colorectal, and prostate cancer [16]. These findings suggest that endocrine dysregulation in functional Pit-NETs may contribute to the observed increased risk of SPMs. The SIR and EAR scores demonstrated variability, reflecting their representation of different aspects of cancer risk. The EAR was highest in females when analyzing risk of SPM at all sites, which aligned with the elevated SIR score observed in females compared to males (EAR, 11.71 vs 5.81). Interestingly, EAR scores indicated a higher risk for certain malignancies in males compared to females, including lymphatic and hematopoietic cancers (EAR, 2.41 vs 1.62), kidney and renal pelvis cancers (EAR, 2.22 vs 0.97), and cutaneous melanoma (EAR, 2.28 vs 1.13). In contrast, SIR scores for these malignancies were more elevated in females, suggesting that while females may have a proportionally higher relative risk, males experience a greater absolute increase in number of cases per population. The observed differences in SIR and EAR scores could reflect a complex interplay between biological, behavioral, and environmental factors. This difference highlights the importance of considering both metrics when assessing cancer risk. Previous studies, such as those by Yamanaka et al. [7], Minniti et al. [8], and Brada et al. [17], have documented an increased risk of secondary intracranial tumors, including neuroepithelial tumors, meningiomas, and astrocytoma’s, following radiotherapy for Pit-NETs. Conversely, conflicting findings have been reported by Pollock et al. [18] and Dumot et al. [19], who found no elevated risk of secondary intracranial tumors in similar patient populations. This discrepancy highlights the ongoing controversy regarding whether radiation therapy definitively elevates the risk of SPMs. Our study, however, incorporates patients with and without radiation treatment and focuses on the broader risk of subsequent systemic malignancies rather than solely intracranial tumors. While it may not necessarily resolve the question of radiation-associated risks, our findings demonstrate that, regardless of radiation therapy, patients with Pit-NETs are more susceptible to developing SPMs compared to the general population. When discussing subsequent malignancies, it is essential to consider the role of cancer susceptibility syndromes that may predispose individuals to Pit-NETs and other cancers [20]. For example, Multiple Endocrine Neoplasia type 1 (MEN1) is a hereditary syndrome associated with a higher risk of developing Pit-NETs, as well as other tumors such as pancreatic neuroendocrine tumors, and thymic and bronchial carcinoids [21,22]. Our study’s finding of elevated risks for pancreatic and thyroid cancers may be reflective of such underlying genetic predispositions. It is unclear as to whether this association is genetically caused or might be due to treatment of Pit-NET with radiation, but this connection warrants further exploration to better understand potential genetic factors contributing to the increased risk of SPMs in these patients. It is also important to consider the role of endocrine dysregulation in the development of SPMs, as hormonal imbalances associated with Pit-NETs may contribute to a pro-tumorigenic environment. Pit-NETs can have diverse endocrinological effects, leading to excess production of hormones such as prolactin, growth hormone, cortisol, and thyroid-stimulating hormone [23]. The hormonal imbalances caused by these adenomas can have far-reaching consequences. For example, the growth hormone elevation associated with acromegaly has association with an increased risk of colorectal cancer, while hyperprolactinemia has been linked to an elevated risk of breast cancer [10]. These hormonal effects could potentially contribute to the development of SPMs. Limitations to this study include that the SEER database does not allow for adjustment of various confounders such as psychosocial variables and environmental risk factors. Modifiable risk factors such as alcohol use, smoking, and radiation, or non-modifiable risk factors such as obesity or diabetes mellitus all can have a significant impact on overall risk and incidence of cancer [24,25]. The database also does not allow us to extend generalizability worldwide as it only captures data from the United States. Additionally, while we identified several significant associations, the underlying mechanisms driving these increased risks remain unclear. Future studies should focus on prospective cohort designs to validate these findings and explore the biological pathways involved. Investigating the genetic and molecular underpinnings of Pit-NETs and their relationship with subsequent cancers could provide valuable insights for developing targeted prevention and treatment strategies. Findings such as these may inform follow-up guidelines in patients with pituitary adenoma. For example, patients with Pit-NET who were initially diagnosed younger than the age of 50 might require screening for high-risk SPMs such as thyroid cancer [26]. This might include physical examination and laboratory testing to further evaluate risk. Additionally, our findings underscore the need for tailored prevention and screening strategies that account for sex-specific risks. These findings are important to consider because targeted screening and preventive measures to reduce the rate of SPMs could significantly improve morbidity and mortality of these patients. Conclusion In conclusion, our study emphasizes the elevated risk of SPMs in patients with Pit-NETs, with significant increases observed in cancers of the small intestine, kidney and renal pelvis, and thyroid. Female patients, those within 5 years of diagnosis, individuals younger than 40 at diagnosis, and patients with adenomas smaller than 20 mm demonstrated the highest risk of SPM development. These findings highlight the importance of long-term surveillance and a multidisciplinary approach to managing these patients. By understanding the genetic, endocrinological, and treatment-related factors contributing to this increased risk, we can better tailor surveillance and intervention strategies to improve patient outcomes. Declarations The authors declare that they have no competing interests. Author contributions: The project’s research question was created by Maxwell W. Pickles and Thomas Z. Rohan. Data collection was performed by Thomas Z. Rohan. Data interpretation and writing of the manuscript were performed by Maxwell W. Pickles, Sydney M. Macon, and Preston Carey. Project oversight was provided by Roger Murayi, David P. Bray, and James J. Evans. All authors read and approved the final manuscript. Disclosure of Potential Conflicts of Interest: The authors declare they have no competing interest. Research Involving Human Participants and/or Animals: This study was conducted using de-identified, publicly available data from the Surveillance, Epidemiology, and End Results (SEER) database. Therefore, ethical approval and informed consent were not required in accordance with institutional and national research committee standards. Informed consent: This article does not contain any studies with human participants performed by any of the authors. 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Demographics of 4,074 Pituitary Adenoma Patients with SPM Characteristic Gender Total, N (% total) Male, N (%) Female, N (%) Number of Pituitary Adenoma Patients with Subsequent Primary Malignancy 4,074 2,283 (56.0%) 1,791 (43.9%) Age Group at Diagnosis <40 361 (8.9) 91(4.0) 270 (15.1) 40-49 470(11.5) 170 (7.4) 300 (16.7) 50-59 839 (20.6) 881(38.5) 358 (20.0) 60-69 1,203(29.5) 791(34.6) 412 (23.0) 70-79 927 (22.7) 583 (25.5) 344 (19.2) 80+ 274 (6.7) 167 (7.32) 107 (6.0) Race White 3,020 (74.2) 1,758 (77.0) 1,262 (70.3) Black 732 (17.8) 378 (16.5) 354 (19.7) American Indian/Alaska Native 30 (0.7) 17 (0.7) 13 (0.7) Asian or Pacific Islander 283 (6.9) 125 (5.5) 158 (8.8) Unknown 9 (0.2) 5 (0.2) 4 (0.2) Table 2. Risk of Select Cancers Following Pituitary Adenoma Diagnosis, Stratified by Gender Site of Primary Tumor Male and Female Male Female SIR (99% CI) EAR SIR (99% CI) EAR SIR (99% CI) EAR All sites 1.1 (1.06 – 1.15) 9.21 1.05 (0.99 – 1.10) 5.81 1.18 (1.11 – 1.25) 11.71 All L&H 1.25 (1.09 – 1.41) 1.96 1.2 (1.01 – 1.41) 2.41 1.31 (1.06 – 1.60) 1.62 Small intestine 2.02 (1.30 – 2.98) 0.51 1.40 (0.68 – 2.54) 0.29 2.93 (1.62 – 4.86) 0.68 Pancreas 1.34 (1.08 – 1.65) 0.95 1.25 (0.93 – 1.65) 0.99 1.48 (1.05 – 2.02) 0.92 Kidney and renal pelvis 1.45 (1.20 – 1.74) 1.5 1.41 (1.11 – 1.76) 2.22 1.55 (1.09 – 2.12) 0.97 Cutaneous melanoma 1.36 (1.15 – 1.16) 1.62 1.33 (1.07 – 1.62) 2.28 1.43 (1.07 – 1.88) 1.13 NHL 1.28 (1.06 – 1.54) 1.06 1.21 (0.93 – 1.53) 1.12 1.41 (1.04 – 1.88) 1.01 Thyroid 2.76 (2.32 – 3.26) 3.75 3.53 (2.58 – 4.70) 3.23 2.5 (2.02 – 3.06) 4.14 Bolded values represent statistical significance , as defined as p < .01. Abbreviations: SIR, standardized incidence ratio; NHL, Non-Hodgkin’s Lymphoma; L&H, lymphatic and hematopoietic Table 3. Risk of Select Cancers Following Pituitary Adenoma Diagnosis a , Stratified by Latency SPM Site Time from initial Pituitary Adenoma diagnosis 2mo-1y 1y-5y 5y-10y 10y-15y 15y+ Total Obs SIR Obs SIR Obs SIR Obs SIR Obs SIR Obs Exp SIR (99% CI) All sites 610 1.51 1760 1.11 1204 1.0 456 0.98 37 1.06 4067 3696 1.1 (1.06 – 1.15) All L&H 51 1.44 181 1.29 134 1.24 39 0.93 3 0.96 408 329 1.24 (1.09 – 1.41) Small intestine 5 2.34 19 2.22 12 1.78 5 1.88 0 0 41 20 2.02 (1.3 – 2.98) Pancreas 29 2.49 57 1.22 41 1.11 20 1.34 3 2.67 150 112 1.34 (1.08 – 1.65) Kidney and renal pelvis 27 1.86 88 1.53 53 1.2 23 1.34 4 3.15 195 134 1.45 (1.2 – 1.74) Cutaneous melanoma 35 1.85 115 1.51 72 1.2 21 0.88 3 1.67 246 181 1.36 (1.15 – 1.6) NHL 33 2.04 76 1.19 68 1.39 15 0.79 0 0 192 149 1.28 (1.06 – 1.54) Thyroid 69 7.27 98 2.62 60 2.15 9 0.87 1 1.37 237 86 2.76 (2.32 – 3.26) SPM Site Age at Pituitary Adenoma diagnosis <40y 40-50 50-60 60-70 70+ Total Obs SIR Obs SIR Obs SIR Obs SIR Obs SIR Obs Exp SIR (99% CI) All sites 361 1.65 469 1.23 837 1.07 1202 1.05 1198 1.03 4067 3696 1.1 (1.06 – 1.15) All L&H 32 1.57 41 1.38 79 1.29 104 1.05 152 1.27 408 329 1.24 (1.09 – 1.41) Small intestine 4 3.8 8 3.44 8 1.81 9 6.34 12 1.94 41 20 2.02 (1.3 – 2.98) Pancreas 22 9.72 16 2.07 32 1.51 40 1.11 40 0.9 150 112 1.34 (1.08 – 1.65) Kidney and renal pelvis 8 1.12 33 2.11 57 1.8 43 1.0 54 1.47 195 134 1.45 (1.2 – 1.74) Cutaneous melanoma 20 1.17 20 0.99 42 1.19 84 1.66 80 1.39 246 181 1.36 (1.15 – 1.6) NHL 14 1.68 18 1.28 30 1.05 62 1.39 68 1.27 192 149 1.28 (1.06 – 1.54) Thyroid 78 2.83 44 2.42 51 2.94 40 2.79 24 2.86 237 86 2.76 (2.32 – 3.26) Abbreviations: Obs., observed cases of melanoma in cancer survivors; SIR, standardized incidence ratio; Exp., expected number of cases; NHL, Non-Hodgkin’s Lymphoma; L&H, lymphatic and hematopoietic Bolded values represent statistical significance, as defined as p < .01. a Only 6 cancers with an increased risk after Pituitary Adenoma are included here. Table 4. Risk of Select Cancers Following Pituitary Adenoma Diagnosis Stratified by Size of Tumor SPM Site Size of Pituitary Adenoma (SIR, 99% CI) 1-10 mm 11-20 mm 21-30 mm 31-40 mm All sites 1.13 (1.02-1.25) 1.10 (1.01-1.20) 1.05 (0.96-1.15) 0.93 (0.78-1.10) All L&H 1.31 (0.92-1.79) 1.20 (0.90-1.57) 1.24 (0.92-1.65) 1.23 (0.71-1.97) Small intestine 1.94 (0.50-5.06) 1.78 (0.52-4.37) 1.78 (0.52-4.37) 1.42 (0.07-6.57) Pancreas 1.87 (1.08-2.98) 1.20 (0.72-1.88) 0.79 (0.39-1.41) 0.89 (0.26-2.19) Kidney and renal pelvis 1.97 (1.26-2.92) 1.49 (0.97-2.18) 1.33 (0.82-2.03) 1.14 (0.45-2.37) Cutaneous melanoma 0.94 (0.55-1.49) 1.55 (1.09-2.14) 1.18 (0.75-1.75) 1.43 (0.69-2.59) NHL 1.25 (0.72-1.99) 1.40 (0.93-2.01) 1.09 (0.66-1.69) 1.07 (0.42-2.22) Thyroid 2.56 (1.80-1.80) 2.80 (1.83-4.08) 2.36 (1.34-3.84) 4.00 (1.94-7.23) Bolded values represent statistical significance , as defined as p < .01. Abbreviations: SIR, standardized incidence ratio; NHL, Non-Hodgkin’s Lymphoma; L&H, lymphatic and hematopoietic Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 09 Feb, 2026 Read the published version in Pituitary → Version 1 posted Editorial decision: Revision requested 27 Oct, 2025 Reviews received at journal 26 Oct, 2025 Reviews received at journal 23 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers invited by journal 11 Oct, 2025 Editor assigned by journal 09 Oct, 2025 Submission checks completed at journal 09 Oct, 2025 First submitted to journal 08 Oct, 2025 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. 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2","display":"","copyAsset":false,"role":"figure","size":257117,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of Excluded Patients in Pituitary Adenoma cohort\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7810484/v1/23941a0fbbf3a74b91bac3b8.jpeg"},{"id":94396808,"identity":"54ab1841-adb1-4d81-acb6-6892d49e1b80","added_by":"auto","created_at":"2025-10-27 13:56:16","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":245090,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of Select Cancers in Males and Females Following Pituitary Adenoma Diagnosis with Increased Percentage of Risk Relative to General Population\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7810484/v1/0b3baf9327eb62c298baf4a9.jpeg"},{"id":102785120,"identity":"87134a75-5fa1-449d-8214-0a666b615772","added_by":"auto","created_at":"2026-02-16 15:59:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2148706,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7810484/v1/f4fbf08c-dc71-46af-9083-e9ad7436fb1b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Subsequent Primary Malignancies in Patients with Initial Diagnosis of Pituitary Adenoma (Pit-NET): a Surveillance, Epidemiology, and End Results (SEER) Data Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePituitary Adenoma (Pit-NET) represent 15% of all primary cranial neoplasms [1]. Clinically relevant Pit-NETs occur with a mean prevalence of 89.1 per 100,000 (range, 75.7-115.6 per 100,000) [2]. From the most recent report of the Central Brain Tumor Registry of the US, from the years 2012-2016, Pit-NETs comprise a sizeable portion of newly diagnosed tumors annually with an incidence of 4.07 cases per 100,000 per year [3]. A separate SEER study that studied 47,180 Pit-NET patients from 2004-2016, found an overall standardized incidence rate (SIR) of 4.8 cases per 100,000 person years, and the annual incidence rate continually trended upwards [4].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePit-NETs have a statistically significant higher incidence in blacks compared with whites and make up the highest proportion of central nervous system tumors occurring in children, adolescents and young adults (15-39 years) (2). Prolactinomas make up 53% of Pit-NETs and are frequently associated with clinical symptoms such as hypogonadism, infertility, and galactorrhea [5]. Transsphenoidal surgery is indicated as the first-line therapy for most cases of functioning Pit-NETs, with the exception of prolactinomas in which medical therapy including dopamine agonists are the first line [6]. \u0026nbsp;Radiation therapy is a third-line therapy option following unsuccessful transsphenoidal surgery, unresectable tumor recurrence, and failure of medical treatment [6].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven the increased incidence rates due to widespread use of magnetic resonance imaging and the generally favorable prognosis of pituitary adenoma, researchers have begun shifting their attention towards long-term outcomes such as development of subsequent primary malignancies (SPM) following an initial diagnosis of Pit-NET [1,4]. Previous studies, including those by Yamanaka at el. [7] and Minniti at el. [8], have investigated the risk of secondary intracranial tumors following radiotherapy for Pit-NETs. These studies reported elevated risk of neuroepithelial tumors, meningioma, meningeal sarcoma, and astrocytoma. However, the scope of those studies was limited to intracranial malignancies and relied on smaller samples sizes.\u003c/p\u003e\n\u003cp\u003eOur study seeks to address these limitations by expanding the focus to include the risk of malignancies throughout the body, utilizing a larger sample size. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere remains a significant gap in understanding the risk of subsequent intracranial and systemic malignancies in pituitary adenoma. To address this, our objective was to evaluate the risk of SPM in Pit-NET patients utilizing the Surveillance, Epidemiology, and End Results program available through the National Cancer Institute. By leveraging a robust cohort of over 60,000 patients, we aim to provide comprehensive insights into the long-term malignancy risks associated with pituitary adenoma.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003ePatients and design:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis Pit-NET cohort was generated from the SEER-17 cancer registries that included San Franciso-Oakland SMSA, Connecticut, Hawaii, Iowa, New Mexico, Seattle (Puget Sound), Utah, Atlanta (Metropolitan), San Jose-Monterey, Los Angeles, Alaska Native, Rural Georgia, California excluding SF/SJM/LA, Kentucky, Louisiana, New Jersey, and Greater Georgia. This registry excluded Alaska and covers roughly 27% of the U.S. population. Cancer diagnoses occurred any time between January 2000 and December 2020. The primary Pit-NET cohort was selected via the World Health Organization\u0026rsquo;s International Classification of Diseases for Oncology, third edition (ICD-O-3) code. The subtypes of Pit-NET included: adenoma (NOS; 8140/0), atypical adenoma (8140/1), adenocarcinoma in suit, (8140/2), and adenocarcinoma (8140/3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFirst record matching selection criteria was selected. All outcome variables provided in SEER were selected using ICD-O-3/WHO 2008 (for SIRs) site codes. The timing of the first primary diagnosis of Pit-NET was used as the initial date from which outcome latencies were calculated. Patients diagnosed with an SPM within 2 months of their primary Pit-NET diagnosis were excluded, due to the high likelihood of them being related malignancies and to decrease the chance a metastatic disease was misclassified. Prior studies investigating SPMs have excluded patients with a SPM less than 6 months after index malignancy, in order to avoid including primary cancers that may have been present, but not clinically evident at the time of initial diagnosis [9]. We opted for a two-month threshold, as we believed it would similarly reduce the risk of misclassification while retaining more patients in the study. Patients were also excluded if the report was obtained solely from a death certificate or autopsy report with no confirmation of diagnosis. The study of this SEER generated cohort was exempt from institutional review board approval. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStatistical analysis:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRelative risk was calculated by using the Standardized Incidence Ratio (SIR), defined as the ratio between observed cases (O) and expected cases (E) of malignancies (SIR = O/E). An SIR of 1.0 would indicate no difference in incidence rates between patients and the general population. Statistical significance was established based on 99% confidence intervals (CI). Person-years at risk (PYR) were calculated for each participant starting two months after their initial Pit-NET diagnosis, and ending upon death, the date last known alive, or December 31, 2020. The excess absolute risk (EAR) per 10,000 person-years was calculated as: [(O-E) / PYR)] x 10,000. EAR measures the actual number of excess events, normalized to the number of person-years observed. In contrast, relative risks like SIR measure the fold difference (e.g., 3-fold increase). SIR serves to test etiological hypotheses, while EAR tends to be more representative when assessing cancer burden impact in a given population. To calculate the number of expected malignancies, a reference rate file of each cancer per 100,000 was calculated using SEER*Stat software package 8.4.0.1 (National Cancer Institute, Bethesda, MD) and applied to the number of patients in our cohort and the SEER-17 cohort registry.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOur analysis identified 62,627 unique cases of primary Pit-NET diagnosed between January 2000 and December 2020 (Figure 1). A total of 1,950 patients were excluded based on our inclusion criteria, resulting in a final cohort of 60,677 (Figure 2). \u0026nbsp;Among these cases, 4,074 patients subsequently developed a SPM (Figure 1). Of these patients, 2,283 (56%) were male, and 1,791 (44%) were female (Table 1). Most patients (84.3%) were aged between 40 and 79 years, while a smaller proportion were younger than 40 (8.9%) or older than 80 years (6.7%) (Table 1). Additionally, the patient population was predominantly White (74.2%), followed by Black patients (17.8%) (Table 1).\u003c/p\u003e\n\u003cp\u003eWe observed a 10% increase in risk in developing a SPM at all sites in both male and female patients (SIR, 1.1, 99% CI, 1.06-1.15, EAR, 9.21/10,000 person-years) when compared to the general population (Fig. 1, Table 2). Male and female patients diagnosed with Pit-NET showed increased risk of all the cancers included in Table 2, but the risk was disproportionately higher for the following malignancies: small intestine (SIR, 2.02, 99% CI, 1.30-2.98), kidney and renal pelvis (SIR, 1.45, 99% CI, 1.20-1.74), and thyroid (SIR, 2.76, 99% CI, 2.32-3.26) (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUpon gender-based stratification of the data, male patients did not exhibit a universally increased risk at all sites (SIR, 1.05, 99% CI, 0.99-1.10, EAR, 5.81/10,000 person-years), however they did demonstrate a statistically significant predisposition to SPMs of lymphatic and hematopoietic (SIR, 1.2, 99% CI, 1.01-1.41), kidney and renal pelvis (SIR, 1.41, 99% CI, 1.11-1.72), cutaneous melanoma (SIR, 1.33, 99% CI, 1.07-1.62), and thyroid (SIR, 3.53, 99% CI, 2.58-4.70) (Table 2). In comparison to female patients, men were more predisposed to SPM of the thyroid (SIR, 3.53, 99% CI, 2.58-4.70 vs SIR, 2.5, 99% CI, 2.02-3.06) (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConversely, females exhibited an increased risk of SPM across all sites (SIR, 1.18, 99% CI, 1.11-1.25, EAR, 11.71/10,000 person-years), with elevated risk, relative to males, to SPMs of the small intestine (SIR, 2.93, 99% CI, 1.62-4.86), pancreas (SIR, 1.48, 99% CI, 1.05-2.02), and non-Hodgkin\u0026rsquo;s lymphoma (SIR, 1.41, 99% CI,1.05-1.88) (Table 2). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTemporal stratification of SIR scores revealed a significant increase in risk of SPMs at all sites in patients in the 2 months-1-year (SIR, 1.51) and 1-5-year time frame (SIR, 1.11) (Table 3). No elevated risk for SPMs at all sites was noted in subsequent intervals spanning 5-10-year, 10-15-year, and 15-year + (Table 3). The 2 month-1-year timeframe demonstrated increased risk of neoplasms of the pancreas (SIR, 2.49), kidney and renal pelvis (SIR, 1.86), cutaneous melanoma (SIR, 1.85), non-Hodgkin\u0026rsquo;s lymphoma (SIR, 2.04), and thyroid (SIR, 7.27) (Table 3). Elevated risk of Lymphatic and hematopoietic (SIR, 1.29) and small intestine (SIR, 2.22) SPMs was exclusive to the 1-5-year timeframe (Table 3). Thyroid cancer exhibited the most prolonged elevation in risk among the cohort, with SIR scores of 7.27, 2.62, and 2.15, indicating an increased risk up to 10-years following initial diagnosis (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurther age-stratified analysis indicated that patients \u0026lt;40-years (SIR, 1.65) and 40-50-years (SIR, 1,23) of age at the time of diagnosis were subject to a higher risk of SPMs across all sites, a risk that waned with advancing age. No increased risk was observed in those in the 50-60-year, 60-70-year, and 70+ age group (Table 3). Individuals in the 70+ cohort were susceptible to the greatest number of SPMs including lymphatic and hematopoietic (SIR, 1.27), kidney and renal pelvis (SIR, 1.47), cutaneous melanoma (SIR, 1.39), and thyroid (SIR, 2.86) (Table 3). \u0026nbsp;The 40-50-year age group demonstrated the second-highest incidence of SPMs, particularly in the small intestine (SIR, 3.44), kidney and renal pelvis (SIR, 2.11), and thyroid (SIR, 2.42) (Table 3). Across all age groups, an elevated risk for thyroid cancer was present (Table 3). The \u0026lt;40-year age group displayed disproportionally heightened risk of pancreatic cancer (SIR, 9.72) (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUpon stratification by tumor size, across all cancer sites, statistically significant increased risks were observed for Pit-NETs sized 1-10 mm (SIR 1.13, 99% CI 1.02-1.25) and 11-20 mm (SIR 1.10, 99% CI 1.01-1.20). Among specific malignancies increased risks were found for pancreatic cancer in patients with 1-10 mm adenomas (SIR 1.87, 99% CI 1.08-2.98), kidney and renal pelvis cancer in 1-10 mm adenomas (SIR 1.97, 99% CI 1.26-2.92), and cutaneous melanoma in 11-20 mm adenoma (SIR 1.55, 99% CI 1.09-2.14). For thyroid cancer, statistically significant associations were noted across all tumor sizes, with the highest SIR observed in adenomas measuring 31-40 mm (SIR 4.00, 99% CI 1.94-7.23). Statistically significant associations were not observed for small intestine cancer, non-Hodgkin\u0026rsquo;s lymphoma, or lymphatic and hematopoietic malignancies.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the risk of developing subsequent malignancies following an initial diagnosis of Pit-NET utilizing the SEER database. This study incorporated 60,677 patients with pituitary adenoma, of which 4,074 developed a subsequent malignancy. Additionally, we evaluated the influence of age at initial diagnosis and time from initial diagnosis. Studies investigating SPMs in Pit-NET have focused more on the effects of radiation treatment and developing secondary intracranial malignancy [7,8,10] with patient populations in the hundreds, whereas our study is among the first to evaluate the development of systemic malignancies with a larger patient population of over 60,000 patients.\u003c/p\u003e\n\u003cp\u003eThe analysis revealed a 10% increased risk for developing all types of subsequent cancers after initial Pit-NET diagnosis, when compared to the general population. Notably, both genders exhibited an increased risk for various cancers, with particularly higher risks observed for small intestine, kidney and renal pelvis, and thyroid malignancies. Gender-specific stratification indicated that females exhibited an overall increased risk across all sites, with a higher risk for SPMs of the small intestine, pancreas, and non-Hodgkin\u0026rsquo;s lymphoma. Temporal stratification of SIR scores indicated a significant increased risk of SPM at all sites in the first year after initial diagnosis compared to the general population. Age-stratified analysis further demonstrated that those younger than 40 and between ages 40-50 patients, were at higher risk for SPMs. When stratified by tumor size, Pit-NETs measuring 1-20 mm were associated with an elevated risk of SPM at all sites. Our findings conveyed that among males, females, different age groups, and differing adenoma sizes, thyroid cancer demonstrated the most elevated risk.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe observed elevated risk of SPMs among females with Pit-NETs may be attributed to several potential factors. First, hormonal influences could play a significant role. Estrogen is known to be involved in the carcinogenesis of certain cancers, such as breast and thyroid malignancies [11]. Pit-NETs may disrupt hormonal cycles, amplifying estrogen\u0026rsquo;s effects and potentially increasing susceptibility to SPM development [12]. Another explanation might be increased healthcare utilization among women. Females are more likely to engage in routine health screenings and medical evaluations compared to males, which could result in earlier and more frequent detection of SPMs [13]. Lastly, there may be sex-specific genetic or epigenetic predispositions. Differences in genetic profiles or epigenetic regulation between men and women might contribute to heightened susceptibility to both Pit-NETs and subsequent malignancies [14]. Further research is necessary to elucidate the mechanisms underlying this finding and to validate these theories.\u003c/p\u003e\n\u003cp\u003eOur temporal findings indicated that patients within the first five years of their initial diagnosis, along with younger patients, faced an increased risk of developing a SPM. Notably, patients diagnosed within one year exhibited an SIR of 7.27 specifically for thyroid cancer. This striking finding, coupled with the overall increased risk of SPMs within five years of diagnosis, may be attributable to treatment-related effects. While the latency period for radiation-induced malignancies can vary, early effects of radiation therapy might explain the elevated SIR scores observed during this timeframe [7,8]. For younger patients, an early diagnosis of Pit-NETmay lead to prolonged exposure to endocrine dysregulation. This sustained imbalance could contribute to an increased cumulative risk for malignancies over time, potentially explaining the higher susceptibility in this group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStratification by tumor size revealed that Pit-NETs measuring 1-20 mm were associated with significantly increased risk of SPMs at all sites, whereas larger adenomas (\u0026gt;21 mm) did not demonstrate this finding. The highest SIR values were observed for thyroid cancer across all tumor sizes, with the greatest risk in patients with adenomas measuring 31-40 mm. Increased risk in smaller adenomas may partially be explained by their greater likelihood of being functional tumors due to early manifestation of hormonal symptoms leading to prompt medical attention. Microadenomas (\u0026lt;10 mm) are more often functional, with prolactin-, growth hormone (GH), and adrenocorticotropic hormone (ACTH)-secreting subtypes being the most frequent [15]. Excess hormone production of GH and ACTH has been shown to increase cancer risk through mechanisms such as enhanced cellular proliferation, inhibition of apoptosis, and system inflammation [16]. Specifically, there has been reported a positive association between circulating IGF-1 levels and primary cancers, such as breast, colorectal, and prostate cancer [16]. These findings suggest that endocrine dysregulation in functional Pit-NETs may contribute to the observed increased risk of SPMs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe SIR and EAR scores demonstrated variability, reflecting their representation of different aspects of cancer risk. The EAR was highest in females when analyzing risk of SPM at all sites, which aligned with the elevated SIR score observed in females compared to males (EAR, 11.71 vs 5.81). Interestingly, EAR scores indicated a higher risk for certain malignancies in males compared to females, including lymphatic and hematopoietic cancers (EAR, 2.41 vs 1.62), kidney and renal pelvis cancers (EAR, 2.22 vs 0.97), and cutaneous melanoma (EAR, 2.28 vs 1.13). In contrast, SIR scores for these malignancies were more elevated in females, suggesting that while females may have a proportionally higher relative risk, males experience a greater absolute increase in number of cases per population. The observed differences in SIR and EAR scores could reflect a complex interplay between biological, behavioral, and environmental factors. This difference highlights the importance of considering both metrics when assessing cancer risk.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrevious studies, such as those by Yamanaka et al. [7], Minniti et al. [8], and Brada et al. [17], have documented an increased risk of secondary intracranial tumors, including neuroepithelial tumors, meningiomas, and astrocytoma\u0026rsquo;s, following radiotherapy for Pit-NETs. Conversely, conflicting findings have been reported by Pollock et al. [18] and Dumot et al. [19], who found no elevated risk of secondary intracranial tumors in similar patient populations. This discrepancy highlights the ongoing controversy regarding whether radiation therapy definitively elevates the risk of SPMs. Our study, however, incorporates patients with and without radiation treatment and focuses on the broader risk of subsequent systemic malignancies rather than solely intracranial tumors. While it may not necessarily resolve the question of radiation-associated risks, our findings demonstrate that, regardless of radiation therapy, patients with Pit-NETs are more susceptible to developing SPMs compared to the general population.\u003c/p\u003e\n\u003cp\u003eWhen discussing subsequent malignancies, it is essential to consider the role of cancer susceptibility syndromes that may predispose individuals to Pit-NETs and other cancers [20]. For example, Multiple Endocrine Neoplasia type 1 (MEN1) is a hereditary syndrome associated with a higher risk of developing Pit-NETs, as well as other tumors such as pancreatic neuroendocrine tumors, and thymic and bronchial carcinoids [21,22]. Our study\u0026rsquo;s finding of elevated risks for pancreatic and thyroid cancers may be reflective of such underlying genetic predispositions. It is unclear as to whether this association is genetically caused or might be due to treatment of Pit-NET with radiation, but this connection warrants further exploration to better understand potential genetic factors contributing to the increased risk of SPMs in these patients.\u003c/p\u003e\n\u003cp\u003eIt is also important to consider the role of endocrine dysregulation in the development of SPMs, as hormonal imbalances associated with Pit-NETs may contribute to a pro-tumorigenic environment. Pit-NETs can have diverse endocrinological effects, leading to excess production of hormones such as prolactin, growth hormone, cortisol, and thyroid-stimulating hormone [23]. The hormonal imbalances caused by these adenomas can have far-reaching consequences. For example, the growth hormone elevation associated with acromegaly has association with an increased risk of colorectal cancer, while hyperprolactinemia has been linked to an elevated risk of breast cancer [10]. These hormonal effects could potentially contribute to the development of SPMs.\u003c/p\u003e\n\u003cp\u003eLimitations to this study include that the SEER database does not allow for adjustment of various confounders such as psychosocial variables and environmental risk factors. Modifiable risk factors such as alcohol use, smoking, and radiation, or non-modifiable risk factors such as obesity or diabetes mellitus all can have a significant impact on overall risk and incidence of cancer [24,25]. The database also does not allow us to extend generalizability worldwide as it only captures data from the United States. Additionally, while we identified several significant associations, the underlying mechanisms driving these increased risks remain unclear. Future studies should focus on prospective cohort designs to validate these findings and explore the biological pathways involved. Investigating the genetic and molecular underpinnings of Pit-NETs and their relationship with subsequent cancers could provide valuable insights for developing targeted prevention and treatment strategies.\u003c/p\u003e\n\u003cp\u003eFindings such as these may inform follow-up guidelines in patients with pituitary adenoma. For example, patients with Pit-NET who were initially diagnosed younger than the age of 50 might require screening for high-risk SPMs such as thyroid cancer [26]. This might include physical examination and laboratory testing to further evaluate risk. Additionally, our findings underscore the need for tailored prevention and screening strategies that account for sex-specific risks. These findings are important to consider because targeted screening and preventive measures to reduce the rate of SPMs could significantly improve morbidity and mortality of these patients.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, our study emphasizes the elevated risk of SPMs in patients with Pit-NETs, with significant increases observed in cancers of the small intestine, kidney and renal pelvis, and thyroid. Female patients, those within 5 years of diagnosis, individuals younger than 40 at diagnosis, and patients with adenomas smaller than 20 mm demonstrated the highest risk of SPM development. These findings highlight the importance of long-term surveillance and a multidisciplinary approach to managing these patients. By understanding the genetic, endocrinological, and treatment-related factors contributing to this increased risk, we can better tailor surveillance and intervention strategies to improve patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor contributions:\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe project\u0026rsquo;s research question was created by Maxwell W. Pickles and Thomas Z. Rohan. Data collection was performed by Thomas Z. Rohan. Data interpretation and writing of the manuscript were performed by Maxwell W. Pickles, Sydney M. Macon, and Preston Carey. Project oversight was provided by Roger Murayi, David P. Bray, and James J. Evans. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eDisclosure of Potential Conflicts of Interest:\u003c/p\u003e\n\u003cp\u003eThe authors declare they have no competing interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResearch Involving Human Participants and/or Animals:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was conducted using de-identified, publicly available data from the Surveillance, Epidemiology, and End Results (SEER) database. Therefore, ethical approval and informed consent were not required in accordance with institutional and national research committee standards.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInformed consent:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis article does not contain any studies with human participants performed by any of the authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData availability:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the Surveillance, Epidemiology, and End Results (SEER) program\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGheorghiu ML, Negreanu F, Fleseriu M. Updates in the Medical Treatment of Pit-NETs. \u003cem\u003eHorm Metab Res.\u003c/em\u003e 2020;52(1):8-24. doi:10.1055/a-1029-2878.\u003c/li\u003e\n\u003cli\u003eDaly AF, Beckers A. The Epidemiology of Pit-NETs. \u003cem\u003eEndocrinol Metab Clin North Am.\u003c/em\u003e 2020;49(3):347-355. doi:10.1016/j.ecl.2020.05.001.\u003c/li\u003e\n\u003cli\u003eOstrom QT, Cioffi G, Gittleman H, Patil N, Waite K, Kruchko C, et al. CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2012\u0026ndash;2016. \u003cem\u003eNeuro-Oncol.\u003c/em\u003e 2019;21(Suppl 5):v1-v100. doi:10.1093/neuonc/noz150.\u003c/li\u003e\n\u003cli\u003eAl-Dorzi HM, Alruwaita AA, Marae BO, Alraddadi BS, Tamim HM, Ferayan A, et al. Incidence, risk factors and outcomes of seizures occurring after craniotomy for primary brain tumor resection. \u003cem\u003eNeurosciences (Riyadh).\u003c/em\u003e 2017;22(2):107-113. doi:10.17712/nsj.2017.2.20160641.\u003c/li\u003e\n\u003cli\u003eTritos NA, Miller KK. Diagnosis and Management of Pit-NETs: A Review. \u003cem\u003eJAMA.\u003c/em\u003e 2023;329(16):1386-1398. doi:10.1001/jama.2023.2407.\u003c/li\u003e\n\u003cli\u003eVarlamov EV, McCartney S, Fleseriu M. Functioning Pit-NETs \u0026ndash; Current Treatment Options and Emerging Medical Therapies. \u003cem\u003eEur Endocrinol.\u003c/em\u003e 2019;15(1):30-40. doi:10.17925/EE.2019.15.1.30.\u003c/li\u003e\n\u003cli\u003eYamanaka R, Abe E, Sato T, Hayano A, Takashima Y. Secondary Intracranial Tumors Following Radiotherapy for Pit-NETs: A Systematic Review. \u003cem\u003eCancers (Basel).\u003c/em\u003e 2017;9(8):103. doi:10.3390/cancers9080103.\u003c/li\u003e\n\u003cli\u003eMinniti G, Traish D, Ashley S, Gonsalves A, Brada M. Risk of second brain tumor after conservative surgery and radiotherapy for pituitary adenoma: update after an additional 10 years. \u003cem\u003eJ Clin Endocrinol Metab.\u003c/em\u003e 2005;90(2):800-804. doi:10.1210/jc.2004-1164.\u003c/li\u003e\n\u003cli\u003eBen Lassan M, Laitman Y, Keinan-Boker L, Silverman B, Friedman E. Secondary cancer after meningioma diagnosis: an Israeli national study. Cancer Causes Control. 2022;33(10):1277-1284. doi:10.1007/s10552-022-01609-3.\u003c/li\u003e\n\u003cli\u003eHamblin R, Vardon A, Akpalu J, Tampourlou M, Spiliotis I, Sbardella E, et al. Risk of second brain tumour after radiotherapy for Pit-NETor craniopharyngioma: a retrospective, multicentre, cohort study of 3679 patients with long-term imaging surveillance. \u003cem\u003eLancet Diabetes Endocrinol.\u003c/em\u003e 2022;10(8):581-588. doi:10.1016/S2213-8587(22)00157-2.\u003c/li\u003e\n\u003cli\u003eGheorghiu ML, Negreanu F, Fleseriu M. Estrogen and its Role in the Pathogenesis of Pituitary Tumors. \u003cem\u003eEndocr Relat Cancer.\u003c/em\u003e 2014;21(5):T273-T283. doi:10.1530/ERC-14-0053.\u003c/li\u003e\n\u003cli\u003ePekic S, Stojanovic M, Popovic V. Pituitary tumors and the risk of other malignancies: is the relationship coincidental or causal? \u003cem\u003eEndocr Oncol.\u003c/em\u003e 2022;2(1):R1-R13. doi:10.1530/EO-21-0033.\u003c/li\u003e\n\u003cli\u003eBertakis KD, Azari R. Gender Differences in the Utilization of Health Care Services. \u003cem\u003eJ Fam Pract.\u003c/em\u003e 2000;49(2):147-152. Available from: https://pubmed.ncbi.nlm.nih.gov/10718692/.\u003c/li\u003e\n\u003cli\u003eToader C, Dobrin N, Tataru C-I, et al. From Genes to Therapy: Pit-NETs in the Era of Precision Medicine. \u003cem\u003eBiomedicines.\u003c/em\u003e 2024;12(1):23. doi:10.3390/biomedicines12010023.\u003c/li\u003e\n\u003cli\u003eTritos NA, Miller KK. Diagnosis and Management of Pit-NETs: A Review. \u003cem\u003eJAMA.\u003c/em\u003e 2023;329(16):1386\u0026ndash;1398. doi:10.1001/jama.2023.5444\u003c/li\u003e\n\u003cli\u003eShanmugalingam T, Bosco C, Ridley AJ, Van Hemelrijck M. Is there a role for IGF-1 in the development of second primary cancers? Cancer Med. 2016 Nov;5(11):3353-3367. doi: 10.1002/cam4.871.\u003c/li\u003e\n\u003cli\u003eBrada M, Ford D, Ashley S, et al. Risk of second brain tumor after radiotherapy for pituitary adenoma. \u003cem\u003eJ Clin Endocrinol Metab.\u003c/em\u003e 1993;77(5):1283-1286. doi:10.1210/jcem.77.5.8077333. Available from: https://pubmed.ncbi.nlm.nih.gov/8334743/.\u003c/li\u003e\n\u003cli\u003eDumot C, Mantziaris G, Dayawansa S, et al. Risk of new tumor, carotid stenosis, and stroke after stereotactic radiosurgery for pituitary tumor: A multicenter study of 2254 patients with imaging follow-up. \u003cem\u003eNeuro-Oncol.\u003c/em\u003e 2024;26(12):2328-2338. doi:10.1093/neuonc/noae133.\u003c/li\u003e\n\u003cli\u003ePollock BE, Link MJ, Stafford SL, Garces YI, Foote RL. The Risk of Radiation-Induced Tumors or Malignant Transformation After Single-Fraction Intracranial Radiosurgery. \u003cem\u003eInt J Radiat Oncol Biol Phys.\u003c/em\u003e 2017;97(5):919-923. doi:10.1016/j.ijrobp.2016.12.021.\u003c/li\u003e\n\u003cli\u003eMcGee RB, Nichols KE. Introduction to cancer genetic susceptibility syndromes. \u003cem\u003eHematol Am Soc Hematol Educ Program.\u003c/em\u003e 2016;2016(1):293-301. doi:10.1182/asheducation-2016.1.293.\u003c/li\u003e\n\u003cli\u003eSingh G, Mulji NJ, Jialal I. Multiple Endocrine Neoplasia Type 1. In: \u003cem\u003eStatPearls\u003c/em\u003e [Internet]. Treasure Island (FL): StatPearls Publishing; 2024. Available from: http://www.ncbi.nlm.nih.gov/books/NBK536980/.\u003c/li\u003e\n\u003cli\u003eVerg\u0026egrave;s B, Boureille F, Goudet P, et al. Pituitary disease in MEN type 1 (MEN1): data from the France-Belgium MEN1 multicenter study. \u003cem\u003eJ Clin Endocrinol Metab.\u003c/em\u003e 2002;87(2):457-465. doi:10.1210/jcem.87.2.8180.\u003c/li\u003e\n\u003cli\u003eRuss S, Anastasopoulou C, Shafiq I. Pituitary Adenoma. In: \u003cem\u003eStatPearls\u003c/em\u003e [Internet]. Treasure Island (FL): StatPearls Publishing; 2024. Available from: http://www.ncbi.nlm.nih.gov/books/NBK554451/.\u003c/li\u003e\n\u003cli\u003eJun S, Park H, Kim UJ, et al. The Combined Effects of Alcohol Consumption and Smoking on Cancer Risk by Exposure Level: A Systematic Review and Meta-Analysis. \u003cem\u003eJ Korean Med Sci.\u003c/em\u003e 2024;39(22):e185. doi:10.3346/jkms.2024.39.e185.\u003c/li\u003e\n\u003cli\u003eGarg SK, Maurer H, Reed K, Selagamsetty R. Diabetes and cancer: two diseases with obesity as a common risk factor. \u003cem\u003eDiabetes Obes Metab.\u003c/em\u003e 2014;16(2):97-110. doi:10.1111/dom.12124.\u003c/li\u003e\n\u003cli\u003eBeck-Peccoz P, Persani L, Lania A. Thyrotropin-Secreting Pit-NETs. In: \u003cem\u003eEndotext\u003c/em\u003e [Internet]. MDText.com, Inc.; 2022. Available from: https://www.ncbi.nlm.nih.gov/books/NBK278978/.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cem\u003eTable 1\u003c/em\u003e. Demographics of 4,074 Pituitary Adenoma Patients with SPM\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"666\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 63.2163%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal, N (% total)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale, N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale, N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Pituitary Adenoma\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePatients with Subsequent Primary Malignancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4,074\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,283 (56.0%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,791 (43.9%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 666px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Group at Diagnosis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003e\u0026lt;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e361 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e91(4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e270 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003e40-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e470(11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e170 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e300 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003e50-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e839 (20.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e881(38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e358 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003e60-69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e1,203(29.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e791(34.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e412 (23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003e70-79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e927 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e583 (25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e344 (19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003e80+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e274 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e167 (7.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e107 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 666px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e3,020 (74.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1,758 (77.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1,262 (70.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e732 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e378 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e354 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003eAmerican Indian/Alaska Native\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e30 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e17 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e13 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e283 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e125 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e158 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.5989%;\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.8115%;\"\u003e\n \u003cp\u003e9 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e5 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e4 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 2.\u0026nbsp;\u003c/em\u003eRisk of Select Cancers Following Pituitary Adenoma Diagnosis, Stratified by Gender\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"660\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite of Primary Tumor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale and Female\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSIR (99% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEAR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSIR (99% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEAR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSIR (99% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEAR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003eAll sites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.1 (1.06 \u0026ndash; 1.15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e9.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1.05 (0.99 \u0026ndash; 1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e5.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.18 (1.11 \u0026ndash; 1.25)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e11.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003eAll L\u0026amp;H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.25 (1.09 \u0026ndash; 1.41)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.2 (1.01 \u0026ndash; 1.41)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.31 (1.06 \u0026ndash; 1.60)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003eSmall intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.02 (1.30 \u0026ndash; 2.98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1.40 (0.68 \u0026ndash; 2.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.93 (1.62 \u0026ndash; 4.86)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.34 (1.08 \u0026ndash; 1.65)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1.25 (0.93 \u0026ndash; 1.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.48 (1.05 \u0026ndash; 2.02)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003eKidney and renal pelvis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.45 (1.20 \u0026ndash; 1.74)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.41 (1.11 \u0026ndash; 1.76)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.55 (1.09 \u0026ndash; 2.12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003eCutaneous melanoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.36 (1.15 \u0026ndash; 1.16)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.33 (1.07 \u0026ndash; 1.62)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.43 (1.07 \u0026ndash; 1.88)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003eNHL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.28 (1.06 \u0026ndash; 1.54)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1.21 (0.93 \u0026ndash; 1.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.41 (1.04 \u0026ndash; 1.88)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003eThyroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.76 (2.32 \u0026ndash; 3.26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.53 (2.58 \u0026ndash; 4.70)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.5 (2.02 \u0026ndash; 3.06)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e4.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 660px;\"\u003e\n \u003cp\u003e\u003cem\u003eBolded values represent statistical significance\u003c/em\u003e\u003cem\u003e, as defined as p \u0026lt; .01.\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eAbbreviations: SIR, standardized incidence ratio; NHL, Non-Hodgkin\u0026rsquo;s Lymphoma; L\u0026amp;H, lymphatic and hematopoietic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 3.\u0026nbsp;\u003c/em\u003eRisk of Select Cancers Following Pituitary Adenoma\u0026nbsp;Diagnosis\u003csup\u003ea\u003c/sup\u003e, Stratified by Latency\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"768\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSPM Site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"13\" style=\"width: 683px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime from initial Pituitary Adenoma diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2mo-1y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1y-5y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5y-10y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10y-15y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15y+\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eSIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eSIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003eSIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eSIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eSIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003eExp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003eSIR (99% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eAll sites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.51\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e1760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e4067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e3696\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.1 (1.06 \u0026ndash; 1.15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eAll L\u0026amp;H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.29\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.24 (1.09 \u0026ndash; 1.41)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eSmall intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.02 (1.3 \u0026ndash; 2.98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.49\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.34 (1.08 \u0026ndash; 1.65)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eKidney and renal pelvis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.53\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.45 (1.2 \u0026ndash; 1.74)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eCutaneous melanoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.85\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.51\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.36 (1.15 \u0026ndash; 1.6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eNHL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.28 (1.06 \u0026ndash; 1.54)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eThyroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.62\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.76 (2.32 \u0026ndash; 3.26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSPM Site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"13\" style=\"width: 683px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at Pituitary Adenoma diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;40y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e40-50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e50-60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e60-70\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e70+\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eSIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eSIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003eSIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eSIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eSIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003eExp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003eSIR (99% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eAll sites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e1202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e4067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e3696\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.1 (1.06 \u0026ndash; 1.15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eAll L\u0026amp;H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.24 (1.09 \u0026ndash; 1.41)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eSmall intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e6.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.02 (1.3 \u0026ndash; 2.98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.72\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.34 (1.08 \u0026ndash; 1.65)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eKidney and renal pelvis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.47\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.45 (1.2 \u0026ndash; 1.74)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eCutaneous melanoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.66\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.36 (1.15 \u0026ndash; 1.6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eNHL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.28 (1.06 \u0026ndash; 1.54)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eThyroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.83\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.42\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.94\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.79\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.76 (2.32 \u0026ndash; 3.26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" valign=\"top\" style=\"width: 768px;\"\u003e\n \u003cp\u003e\u003cem\u003eAbbreviations: Obs., observed cases of melanoma in cancer survivors; SIR, standardized incidence ratio; Exp., expected number of cases; NHL, Non-Hodgkin\u0026rsquo;s Lymphoma; L\u0026amp;H, lymphatic and hematopoietic\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eBolded values represent statistical significance, as defined as p \u0026lt; .01.\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eOnly 6 cancers with an increased risk after\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e\u003cem\u003ePituitary Adenoma are\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cem\u003eincluded here.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 4. Risk of Select Cancers Following\u0026nbsp;\u003c/em\u003e\u003cem\u003ePituitary Adenoma\u0026nbsp;\u003c/em\u003e\u003cem\u003eDiagnosis Stratified by Size of Tumor\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSPM Site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 499px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSize of Pituitary Adenoma (SIR, 99% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1-10 mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11-20 mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21-30 mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e31-40 mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eAll sites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.13 (1.02-1.25)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.10 (1.01-1.20)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.05 (0.96-1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.93 (0.78-1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eAll L\u0026amp;H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.31 (0.92-1.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.20 (0.90-1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.24 (0.92-1.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.23 (0.71-1.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eSmall intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.94 (0.50-5.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.78 (0.52-4.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.78 (0.52-4.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.42 (0.07-6.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.87 (1.08-2.98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.20 (0.72-1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.79 (0.39-1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.89 (0.26-2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eKidney and renal pelvis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.97 (1.26-2.92)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.49 (0.97-2.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.33 (0.82-2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.14 (0.45-2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eCutaneous melanoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.94 (0.55-1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.55 (1.09-2.14)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.18 (0.75-1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.43 (0.69-2.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eNHL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.25 (0.72-1.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.40 (0.93-2.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.09 (0.66-1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.07 (0.42-2.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eThyroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.56 (1.80-1.80)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.80 (1.83-4.08)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.36 (1.34-3.84)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.00 (1.94-7.23)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cem\u003eBolded values represent statistical significance\u003c/em\u003e\u003cem\u003e, as defined as p \u0026lt; .01.\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eAbbreviations: SIR, standardized incidence ratio; NHL, Non-Hodgkin\u0026rsquo;s Lymphoma; L\u0026amp;H, lymphatic and hematopoietic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"pituitary","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pitu","sideBox":"Learn more about [Pituitary]()","snPcode":"11102","submissionUrl":"https://submission.nature.com/new-submission/11102/3","title":"Pituitary","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Pituitary Adenoma, Subsequent Primary Malignancy, SEER, Standardized Incidence Ratio (SIR), Epidemiology, Endocrine neoplasms ","lastPublishedDoi":"10.21203/rs.3.rs-7810484/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7810484/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Pituitary Adenoma (Pit-NET) is a frequently encountered intracranial mass that is typically characterized by slow growth and benign behavior. There remains limited knowledge regarding the risk of developing a “subsequent primary malignancy” (SPM) in a patient with a pituitary adenoma. This study assessed the risk of developing a SPM after a Pit-NET diagnosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: The Surveillance, Epidemiology, and End Results (SEER-17) data registry, which consisted of 9,208,295 patients, was utilized to generate a cohort of 60,677 patients diagnosed with Pit-NET to identify patients at risk for a SPM. The SEER patient data was collected from the years 2000 to 2020. Statistical analysis was performed through SEER’s stat package and Standardized Incidence Ratios (SIRs) for various malignancies after the diagnosis of primary Pit-NET were obtained. We also collected basic demographic, surgical, and postoperative data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Of the 60,677 patients, 4,067 (6.7%) received a diagnosis of a SPM, which correlates to a higher risk than the general population (SIR, 1.1, 99% CI, 1.06-1.15). Patients with a Pit-NET had an increased risk of the following cancers: lymphatic and hematopoietic (SIR, 1.25; 99% CI, 1.09-1.41), kidney and renal pelvis (SIR, 1.45; 99% CI, 1.2-1.74), cutaneous melanoma (SIR, 1.36; 99% CI, 1.15-1.16), and thyroid cancer (SIR, 2.76; 99% CI, 2.32-3.26). Additionally, females were more predisposed to the following cancers: Digestive system (SIR, 1.19; 99% CI, 1.11-1.25), and non-Hodgkin's Lymphoma (SIR, 1.41; 99% CI, 1.04-1.88).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Utilizing the SEER database, we have discovered an increased risk of SPM in patients with pituitary adenoma. Supplementary research may be done to determine any shared genetic abnormalities between the development of Pit-NET and these SPMs. Additionally, further research of the endocrinological effects of Pit-NET and potential associations to SPMs should be studied.\u003c/p\u003e","manuscriptTitle":"Subsequent Primary Malignancies in Patients with Initial Diagnosis of Pituitary Adenoma (Pit-NET): a Surveillance, Epidemiology, and End Results (SEER) Data Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-26 00:51:34","doi":"10.21203/rs.3.rs-7810484/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-27T13:15:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-26T23:32:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-23T22:43:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"870615166079311721485716554874270563","date":"2025-10-13T17:15:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"52463924318522012993595462868777262134","date":"2025-10-13T15:06:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-11T17:02:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-09T07:35:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-09T07:34:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"Pituitary","date":"2025-10-08T18:05:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"pituitary","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pitu","sideBox":"Learn more about [Pituitary]()","snPcode":"11102","submissionUrl":"https://submission.nature.com/new-submission/11102/3","title":"Pituitary","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5bf28003-1b70-430f-bf3d-c3273e935699","owner":[],"postedDate":"October 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-16T15:59:45+00:00","versionOfRecord":{"articleIdentity":"rs-7810484","link":"https://doi.org/10.1007/s11102-026-01641-5","journal":{"identity":"pituitary","isVorOnly":false,"title":"Pituitary"},"publishedOn":"2026-02-09 15:56:55","publishedOnDateReadable":"February 9th, 2026"},"versionCreatedAt":"2025-10-26 00:51:34","video":"","vorDoi":"10.1007/s11102-026-01641-5","vorDoiUrl":"https://doi.org/10.1007/s11102-026-01641-5","workflowStages":[]},"version":"v1","identity":"rs-7810484","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7810484","identity":"rs-7810484","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}