Abstract
Background
Cancer survivors have increased risk of endocrine complications, but there is a lack of information on the occurrence of specific endocrinopathies at the population-level.
Methods
We used data from the California Cancer Registry (2006–2018) linked to statewide hospitalisation, emergency department, and ambulatory surgery databases. We estimated the cumulative incidence of and factors associated with endocrinopathies among adolescents and young adults (AYA, 15–39 years) who survived ≥2 years after diagnosis.
Results
Among 59,343 AYAs, 10-year cumulative incidence was highest for diabetes (4.7%), hypothyroidism (4.6%), other thyroid (2.2%) and parathyroid disorders (1.6%). Hypothyroidism was most common in Hodgkin lymphoma, leukaemia, breast, and cervical cancer survivors, while diabetes was highest among survivors of leukaemias, non-Hodgkin lymphoma, colorectal, cervical, and breast cancer. In multivariable models, factors associated with increased hazard of endocrinopathies were treatment, advanced stage, public insurance, residence in low/middle socioeconomic neighbourhoods, older age, and non-Hispanic Black or Hispanic race/ethnicity. Haematopoietic cell transplant was associated with most endocrinopathies, while chemotherapy was associated with a higher hazard of ovarian dysfunction and hypothyroidism.
Conclusions
We observed a high burden of endocrinopathies among AYA cancer survivors, which varied by treatment and social factors. Evidence-based survivorship guidelines are needed for surveillance of these diseases.
Subject terms: Endocrine system and metabolic diseases, Cancer epidemiology, Cancer therapy, Outcomes research
Introduction
With advancements in cancer diagnosis, effective cancer treatments, and improvements in supportive care, remarkable improvements in survival have been observed among adolescents and young adults (AYAs, 15–39 years) diagnosed with cancer over the last five decades. Currently, 5-year cancer survival for AYAs is approximately 85%, and it surpasses 90% for certain malignancies, such as Hodgkin lymphoma (HL), testicular cancer, thyroid cancer, and melanoma of the skin [1–3]. However, this success has been achieved at a cost, which is the development of chronic medical conditions (“late effects”) associated with treatment exposures. Any organ system can be involved, however, endocrinopathies are considered one of the most common late effects among childhood and AYA cancer survivors [4–11]. In the United States (US), studies have shown that up to 50% [12] to 67% [13] of childhood cancer survivors experienced at least one endocrine or metabolic disorder following cancer treatment, an incidence markedly higher than that of their siblings. Importantly, these disorders have been associated with poor health-related quality of life and suboptimal physical activity [13]. The most common factors associated with developing endocrinopathies include external beam radiation to endocrine glands and receipt of chemotherapy, such as alkylating agents [14].
Most information on late effects in the US has been obtained from childhood cancer studies and form the basis of survivorship care recommendations from the Children’s Oncology Group Long-Term Follow-Up Guidelines [15] and the International Guideline Harmonization Group [16–19]. Because malignancies in AYAs may have distinct biological, genetic, and epidemiological features than children [20], the frequency and magnitude of late effects might differ between these groups. Although there have been several studies showing an increased overall incidence of endocrine complications in AYA cancer survivors in the US [6–9, 21], there is a lack of information on distinct endocrinopathies among these patients at the population-level.
Therefore, in the current study, we provide comprehensive and contemporary information on specific endocrinopathies among AYAs with haematologic and other solid malignancies. Our findings may inform the development and evaluation of survivorship care guidelines focussed on preventive and follow-up strategies aimed at reducing morbidity and mortality from these diseases and improving quality of life in an understudied population of AYA cancer survivors.
Methods
Data source and study population
This study used a subset of data from the VOICE (Valuing Opinions and Insight from Cancer Experience) Study [22], a research programme designed to increase our knowledge of the health problems, health care and life experiences of AYA cancer survivors. The VOICE Study uses several data sources, including the California Cancer Registry (CCR) and Utah Cancer Registry linked to healthcare utilisation data, Kaiser Permanente Northern and Southern California, and the North Carolina Cancer Information Population Health Resource. Data for this analysis was provided by the CCR linked to data from the California Department of Health Care Access and Information (HCAI). This linkage employed the deterministic and probabilistic algorithms of the CCR, utilising social security number (SSN), date of birth, gender, and residential zip code. The CCR is one of the country’s largest and most diverse registries by race/ethnicity and socioeconomic status (SES). Because state law requires all cancers diagnosed in California to be reported, the CCR captures over 99% of cancer diagnoses in the state [23]. HCAI data encompasses hospitalisation, emergency department, and ambulatory surgery visits from all non-federal facilities in California. Medical visits in the outpatient setting are not captured by HCAI. We used the International Classification of Diseases, Ninth or Tenth Revision, Clinical Modification (ICD-9-CM/ICD-10-CM) and Current Procedure Terminology (CPT) codes to ascertain selected endocrinopathies during each visit.
We identified AYAs diagnosed with a primary invasive cancer (except breast, where we included both in situ and invasive cancers) in the CCR from 2006 to 2018 who survived at least 2 years after cancer diagnosis. As done previously [6–9], we used data beyond the first two years after cancer diagnosis, so we could focus on late effects after completion of treatment. Various late effects occur between 2 and 5 years after cancer diagnosis [6–9]. Patients without identifiers to link to HCAI (n = 8503) and those with a second cancer within 60 days of diagnosis (synchronous cancers, n = 146) were excluded from the analysis. Most exclusions (n = 8398, 12.4%) were due to invalid or unknown SSN, preventing the linkage between CCR and HCAI. Comparing to patients with a valid SSN, those with invalid/unknown SSN were more likely to be younger (15–19 years), be of Hispanic race/ethnicity, reside in the lowest socioeconomic neighbourhoods, have public or no health insurance, and be diagnosed with cancer in 2012–2018 (Supplemental Table S1).
We included 11 common malignancies in AYAs: acute lymphoblastic leukaemia (ALL), acute myeloid leukaemia (AML), non-Hodgkin lymphoma (NHL), HL, melanoma, sarcoma, colorectal cancer (CRC, excludes anus), cervical, thyroid, testicular, and breast cancer. Topography (anatomic site) and morphology (tumour histology and behaviour) were based on the International Classification of Diseases for Oncology, Third edition (ICD-O-3) [24], and malignancies were categorised according to Barr et al. [25].
Study outcomes
The study outcomes included 9 categories of endocrinopathies as follows: hypothyroidism, other thyroid disorders (non-toxic goitre, thyrotoxicosis, thyroiditis and other), diabetes mellitus, pancreatic, parathyroid, pituitary, and adrenal disorders, ovarian and testicular dysfunction; and 14 subcategories, coded according to ICD-9/10 and CPT codes, and underlying cause of death (ICD-10) (Supplemental Table S2). We identified all patients visits in HCAI databases with a diagnosis of endocrinopathies as principal diagnosis or recorded in any position during a medical encounter for other diagnoses ≥2 years after cancer diagnosis [26, 27]. Because surgery is the primary treatment for thyroid cancer and results in hypothyroidism soon after total gland resection [28], we excluded thyroid cancer from the analyses of hypothyroidism and other thyroid disorders. In our thyroid cancer cohort, 98.4% patients underwent surgical resection: total (84%) or partial (15%) thyroidectomy, with or without radioiodine therapy. Likewise, as the most common type of acquired parathyroid disorder is postsurgical hypoparathyroidism, especially after thyroid surgery [29], thyroid cancer patients were excluded in the analysis of parathyroid conditions (which include hypoparathyroidism, hyperparathyroidism, and other parathyroid disorders).
Endocrinopathies were ascertained from 2 years after cancer diagnosis until patient death, last known vital status or end of study (12/31/2020), whichever occurred first. For patients who had >1 visit for a specific endocrine condition, only the first encounter was reported, consistent with previous studies [26, 27]. Patients who had a pre-existing endocrinopathy in the 5 years prior to cancer diagnosis were excluded from having this endocrinopathy outcome in our analyses.
Sociodemographic and clinical variables
Sociodemographic variables collected at cancer diagnosis included in this study encompass age, year of diagnosis, sex, race/ethnicity (non-Hispanic (NH) White, NH Black/African American (AA), Hispanic, NH Asian/Pacific Islander (PI), other/unknown), health insurance (private, no insurance, Medicaid, Medicare), and neighbourhood SES (nSES, categorised as low, middle or high). In the multivariable models, patients with no insurance or Medicaid insurance were combined because, in California, patients who receive a cancer diagnosis become eligible for Medicaid. nSES is an aggregated measure of seven indicators of education, poverty, and unemployment rates at the census block-group level [30] and has been used extensively in prior studies. [6–9, 21] Cancer stage at diagnosis was based on the American Joint Committee on Cancer. Initial treatment includes chemotherapy, radiation, primary surgery, and haematopoietic cell transplant (HCT), categorised as ‘yes’ or ‘none/unknown’.
Statistical analysis
Descriptive analysis was conducted to show the distribution of patient characteristics by sex. Cumulative incidence (CMI) at 2–5 years (hereafter referred to as 5-year CMI) and 2–10 years (hereafter referred to as 10-year CMI) post-cancer diagnosis and associated 95% confidence intervals (CIs) of developing endocrinopathies were estimated using nonparametric models, accounting for death as a competing risk [31]. We used multivariable Cox proportional hazards regression to investigate the association of each endocrinopathy with sociodemographic and clinical factors (all described above). HCT was analysed as a time-dependent variable. The proportional hazard assumption was tested by using the Schoenfeld residuals test, and covariates violating the proportional hazard assumption were included as stratification variables in the models. Melanoma was selected as the reference category for cancer sites because it is a common malignancy with high survival, affects both sexes, and is not an endocrine gland tumour. All analyses were conducted using SAS version 9.4 software.
Results
We identified a total of 59,343 AYAs who survived ≥2 years after cancer diagnosis. The median follow-up time was 7.4 years after cancer diagnosis (range 2–15 years). Table 1 shows patients’ characteristics by sex. The most common cancer sites in males were testicular (35.6%), lymphomas (20.7%), melanoma (11.6%) and thyroid (9.9%); whereas in females they were invasive breast (29.9%), thyroid (26.5%), melanoma (10.2%), and lymphomas (10.0%). Compared to females, males were more often diagnosed with advanced stage (III/IV) (20.3% vs. 15.5%) and more likely to received chemotherapy (44.9% vs. 40.2%) or HCT (5.3% vs. 2.1%); whereas female AYAs were more likely to undergo surgery (84.9% vs. 77.2%) or radiation (36.6% vs. 21.1%).
Table 1.
Sociodemographic and clinical characteristics of survivors of adolescent and young adult cancer, by sex, California, 2006–2018.
| Characteristics | All | Male | Female | P value |
|---|---|---|---|---|
| N (%) | N (%) | N (%) | ||
| All | 59,343 (100.0) | 21,249 (100.0) | 38,094 (100.0) | |
| Age at cancer diagnosis, years | ||||
| 15–19 | 3769 (6.4) | 2036 (9.6) | 1733 (4.5) | <0.0001 |
| 20–29 | 17,979 (30.3) | 8372 (39.4) | 9607 (25.2) | |
| 30–39 | 37,595 (63.4) | 10,841 (51.0) | 26,754 (70.2) | |
| Median (IQR) | 32 (27–36) | 30 (24–35) | 33 (28–37) | |
| Year of cancer diagnosis | ||||
| 2006–2011 | 28,609 (48.2) | 10,194 (48.0) | 18,415 (48.3) | 0.3911 |
| 2012–2018 | 30,734 (51.8) | 11,055 (52.0) | 19,679 (51.7) | |
| Race/ethnicity | ||||
| Non-Hispanic White | 28,465 (48.0) | 10,821 (50.9) | 17,644 (46.3) | <0.0001 |
| Non-Hispanic Black | 2849 (4.8) | 815 (3.8) | 2034 (5.3) | |
| Hispanic | 18,745 (31.6) | 7063 (33.2) | 11,682 (30.7) | |
| Asian/Pacific Islander | 7618 (12.8) | 1923 (9.0) | 5695 (14.9) | |
| American Indian/Alaska Native | 415 (0.7) | 152 (0.7) | 263 (0.7) | |
| Unknown | 1251 (2.1) | 475 (2.2) | 776 (2.0) | |
| Neighbourhood socioeconomic status (nSES) | ||||
| Highest | 25,911 (43.7) | 8878 (41.8) | 17,033 (44.7) | <0.0001 |
| Middle | 12,376 (20.9) | 4484 (21.1) | 7892 (20.7) | |
| Lowest | 19,666 (33.1) | 7391 (34.8) | 12,275 (32.2) | |
| Unknown | 1390 (2.3) | 496 (2.3) | 894 (2.3) | |
| Health insurance at diagnosis | ||||
| Private | 44,802 (75.5) | 15,421 (72.6) | 29,381 (77.1) | <0.0001 |
| Public or no insurance | 12,351 (20.8) | 5004 (23.5) | 7347 (19.3) | |
| Public-Medicaid | 10,101 (17.0) | 3900 (18.4) | 6201 (16.3) | |
| Public-Medicare | 1012 (1.7) | 392 (1.8) | 620 (1.6) | |
| No insurance | 1238 (2.1) | 712 (3.4) | 526 (1.4) | |
| Unknown | 2190 (3.7) | 824 (3.9) | 1366 (3.6) | |
| Cancer site | ||||
| Acute lymphoblastic leukaemia | 1139 (1.9) | 709 (3.3) | 430 (1.1) | <0.0001 |
| Acute myeloid leukaemia | 1068 (1.8) | 515 (2.4) | 553 (1.5) | |
| Non-Hodgkin lymphoma | 3930 (6.6) | 2225 (10.5) | 1705 (4.5) | |
| Hodgkin lymphoma | 4284 (7.2) | 2177 (10.2) | 2107 (5.5) | |
| Melanoma | 6356 (10.7) | 2457 (11.6) | 3899 (10.2) | |
| Thyroid | 12,208 (20.6) | 2100 (9.9) | 10,108 (26.5) | |
| Sarcoma | 3285 (5.5) | 1684 (7.9) | 1601 (4.2) | |
| Colorectal | 3555 (6.0) | 1794 (8.4) | 1761 (4.6) | |
| In situ breast | 1351 (2.3) | 5 (0.0) | 1346 (3.5) | |
| Breast | 11,405 (19.2) | 19 (0.1) | 11,386 (29.9) | |
| Cervical | 3198 (5.4) | ‒ | 3198 (8.4) | |
| Testicular | 7564 (12.7) | 7564 (35.6) | ‒ | |
| Haematopoietic cell transplant | ||||
| Yes | 1949 (3.3) | 1135 (5.3) | 814 (2.1) | <0.0001 |
| No/unknown | 57,394 (96.7) | 20,114 (94.7) | 37,280 (97.9) | |
| Surgery primary site | ||||
| Yes | 48,772 (82.2) | 16,414 (77.2) | 32,358 (84.9) | <0.0001 |
| No/unknown | 10,571 (17.8) | 4835 (22.8) | 5736 (15.1) | |
| Radiotherapy | ||||
| Yes | 18,428 (31.1) | 4482 (21.1) | 13,946 (36.6) | <0.0001 |
| No/unknown | 40,915 (68.9) | 16,767 (78.9) | 24,148 (63.4) | |
| Chemotherapy | ||||
| Yes | 24,872 (41.9) | 9541 (44.9) | 15,331 (40.2) | <0.0001 |
| No/unknown | 34,471 (58.1) | 11,708 (55.1) | 22,763 (59.8) | |
| Stage at diagnosis | ||||
| In situ | 1351 (2.3) | 5 (0.0) | 1346 (3.5) | <0.0001 |
| Stage I | 30,636 (51.6) | 10,675 (50.2) | 19,961 (52.4) | |
| Stage II | 11,160 (18.8) | 3332 (15.7) | 7828 (20.5) | |
| Stage III | 6814 (11.5) | 2783 (13.1) | 4031 (10.6) | |
| Stage IV | 3392 (5.7) | 1536 (7.2) | 1856 (4.9) | |
| Unknown | 3783 (6.4) | 1694 (8.0) | 2089 (5.5) | |
| Not applicable | 2207 (3.7) | 1224 (5.8) | 983 (2.6) | |
IQR interquartile range.
P value was calculated using chi-square (χ2) test.
Over the study follow-up period, 5342 patients (9.0%) had a diagnosis code for at least one endocrinopathy ≥2 years after diagnosis. Most endocrinopathies were diagnosed from in-patient hospitalisations (48%), followed by emergency department visits (32%), and ambulatory surgery visits (20%). Among the visits that included the endocrinopathy diagnosis, the top three ‘principal diagnosis’ in HCAI were cancer (13.7%), ‘symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified’ (11.5%), and endocrinopathies (8.9%); whereas the top three ‘first other diagnosis’ were endocrinopathies (24.3%), cancer (13.2%) and ‘symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified’ (8.7%). AYAs with endocrinopathies had a higher number of visits 2 or more years after diagnosis than their counterparts without endocrinopathies (data not shown).
Overall, the 10-year CMI was highest for diabetes mellitus (4.7%), hypothyroidism (4.6%), other thyroid (2.2%) and parathyroid disorders (1.6%) (Table 2, Supplemental Figs. S1A–C and S2A). Incidence varied by cancer site, with patients with ALL and AML experiencing the highest disease burden for diabetes, hypothyroidism, parathyroid, adrenal and pituitary gland disorders, as well as ovarian and testicular dysfunction. Sex differences were observed, particularly for thyroid disorders, which were consistently higher among females than males (Supplemental Table S3).
Table 2.
Five-year and 10-year cumulative incidence of endocrine diseases among survivors of adolescent and young adult cancer, by cancer site, California, 2006–2018.
| Hypothyroidism | Other diseases of thyroid gland | Diseases of parathyroid gland | Diabetes mellitus | Pancreatic disorders (other than diabetes) | Diseases of pituitary gland | Diseases of adrenal gland | Ovarian dysfunction | Testicular dysfunction | ||
|---|---|---|---|---|---|---|---|---|---|---|
| Cumulative incidence (%) and 95% confidence interval | ||||||||||
| All cancers | 5-year | 2.04 (1.91, 2.18) | 0.94 (0.85, 1.04) | 0.84 (0.76, 0.93) | 2.24 (2.12, 2.37) | 0.26 (0.22, 0.31) | 0.40 (0.35, 0.46) | 0.41 (0.36, 0.47) | 0.23 (0.19, 0.29) | 0.34 (0.26, 0.43) |
| 10-year | 4.64 (4.40, 4.88) | 2.18 (2.02, 2.35) | 1.59 (1.46, 1.73) | 4.67 (4.46, 4.89) | 0.56 (0.49, 0.64) | 0.72 (0.64, 0.80) | 0.75 (0.67, 0.84) | 0.42 (0.35, 0.51) | 0.73 (0.60, 0.89) | |
| Cancer site | ||||||||||
| Acute lymphoblastic leukaemia | 5-year | 3.70 (2.65, 5.02) | 1.17 (0.64, 1.99) | 3.45 (2.45, 4.72) | 11.2 (9.36, 13.2) | 1.23 (0.67, 2.09) | 3.01 (2.09, 4.20) | 4.05 (2.96, 5.38) | 3.40 (1.90, 5.59) | 1.22 (0.54, 2.41) |
| 10-year | 5.76 (4.21, 7.63) | 1.64 (0.94, 2.67) | 5.77 (4.24, 7.62) | 15.1 (12.8, 17.7) | 2.04 (1.21, 3.22) | 3.54 (2.46, 4.91) | 5.51 (4.12, 7.18) | 5.27 (3.10, 8.25) | 2.12 (1.12, 3.68) | |
| Acute myeloid leukaemia | 5-year | 1.80 (1.09, 2.81) | 0.40 (0.14, 0.99) | 1.54 (0.90, 2.48) | 6.91 (5.42, 8.63) | 0.31 (0.09, 0.87) | 1.25 (0.68, 2.12) | 1.78 (1.08, 2.78) | 1.91 (0.94, 3.47) | 1.92 (0.95, 3.50) |
| 10-year | 4.10 (2.81, 5.75) | 0.86 (0.38, 1.74) | 3.00 (1.94, 4.41) | 9.35 (7.47, 11.5) | 1.00 (0.43, 2.05) | 1.98 (1.15, 3.19) | 2.54 (1.62, 3.79) | 2.47 (1.30, 4.27) | 2.48 (1.31, 4.27) | |
| Non-Hodgkin lymphoma | 5-year | 1.59 (1.21, 2.04) | 0.69 (0.45, 1.01) | 0.72 (0.48, 1.05) | 2.64 (2.14, 3.21) | 0.35 (0.19, 0.60) | 0.32 (0.18, 0.55) | 0.81 (0.55, 1.15) | 0.33 (0.13, 0.75) | 0.25 (0.10, 0.57) |
| 10-year | 4.25 (3.48, 5.12) | 1.85 (1.37, 2.46) | 1.56 (1.13, 2.10) | 5.56 (4.70, 6.52) | 0.75 (0.46, 1.17) | 0.65 (0.39, 1.01) | 1.14 (0.81, 1.56) | 0.73 (0.33, 1.44) | 0.51 (0.24, 1.01) | |
| Hodgkin lymphoma | 5-year | 2.64 (2.16, 3.19) | 0.67 (0.45, 0.97) | 0.34 (0.19, 0.57) | 1.98 (1.58, 2.46) | 0.38 (0.22, 0.61) | 0.18 (0.08, 0.37) | 0.39 (0.23, 0.63) | 0.27 (0.11, 0.62) | 0.15 (0.04, 0.43) |
| 10-year | 7.90 (6.91, 8.97) | 2.01 (1.52, 2.61) | 0.98 (0.66, 1.42) | 4.26 (3.56, 5.04) | 0.68 (0.44, 1.02) | 0.50 (0.30, 0.81) | 0.79 (0.52, 1.17) | 0.75 (0.39, 1.33) | 0.44 (0.20, 0.90) | |
| Melanoma | 5-year | 1.75 (1.44, 2.12) | 0.69 (0.50, 0.93) | 0.52 (0.36, 0.73) | 0.85 (0.64, 1.11) | 0.14 (0.07, 0.28) | 0.26 (0.15, 0.42) | 0.30 (0.18, 0.47) | 0.06 (0.01, 0.20) | 0.12 (0.04, 0.35) |
| 10-year | 3.97 (3.42, 4.59) | 1.75 (1.39, 2.18) | 0.85 (0.62, 1.14) | 1.93 (1.56, 2.37) | 0.23 (0.13, 0.40) | 0.66 (0.45, 0.94) | 0.77 (0.54, 1.07) | 0.09 (0.03, 0.25) | 0.27 (0.10, 0.64) | |
| Thyroid | 5-year | – | – | – | 1.80 (1.57, 2.07) | 0.11 (0.06, 0.19) | 0.05 (0.02, 0.11) | 0.16 (0.10, 0.25) | 0.06 (0.02, 0.13) | 0.45 (0.21, 0.86) |
| 10-year | – | – | – | 4.29 (3.84, 4.77) | 0.25 (0.16, 0.38) | 0.22 (0.13, 0.35) | 0.33 (0.23, 0.48) | 0.07 (0.03, 0.16) | 0.85 (0.47, 1.44) | |
| Sarcoma | 5-year | 2.21 (1.73, 2.79) | 0.60 (0.37, 0.95) | 1.23 (0.88, 1.69) | 2.12 (1.65, 2.69) | 0.47 (0.27, 0.77) | 1.05 (0.73, 1.47) | 0.50 (0.30, 0.81) | 0.47 (0.21, 0.93) | 0.49 (0.22, 0.98) |
| 10-year | 4.87 (4.02, 5.82) | 1.60 (1.14, 2.19) | 2.24 (1.68, 2.93) | 4.37 (3.58, 5.27) | 0.82 (0.52, 1.24) | 1.64 (1.20, 2.20) | 1.18 (0.79, 1.71) | 0.87 (0.42, 1.63) | 0.81(0.41, 1.48) | |
| Colorectal | 5-year | 1.89 (1.45, 2.43) | 1.17 (0.83, 1.62) | 1.35 (0.99, 1.81) | 3.55 (2.94, 4.25) | 0.65 (0.41, 0.99) | 0.71 (0.46, 1.05) | 0.59 (0.36, 0.92) | 0.28 (0.09, 0.69) | 0.18 (0.05, 0.50) |
| 10-year | 3.80 (3.05, 4.67) | 2.12 (1.57, 2.80) | 2.11 (1.59, 2.74) | 6.39 (5.41, 7.49) | 1.07 (0.72, 1.54) | 1.05 (0.70, 1.51) | 1.01 (0.65, 1.50) | 0.55 (0.22, 1.21) | 0.18 (0.05, 0.50) | |
| Breast | 5-year | 2.92 (2.61, 3.27) | 1.59 (1.36, 1.85) | 1.03 (0.85, 1.24) | 2.62 (2.32, 2.95) | 0.26 (0.17, 0.38) | 0.56 (0.43, 0.73) | 0.32 (0.22, 0.45) | 0.22 (0.14, 0.33) | – |
| 10-year | 6.17 (5.63, 6.73) | 3.51 (3.10, 3.96) | 2.06 (1.76, 2.40) | 5.30 (4.80, 5.82) | 0.76 (0.58, 0.99) | 1.13 (0.90, 1.39) | 0.66 (0.50, 0.86) | 0.41 (0.28, 0.58) | – | |
| In situ breast | 5-year | 1.77 (1.14, 2.63) | 0.91 (0.49, 1.59) | 0.17 (0.04, 0.58) | 1.19 (0.69, 1.95) | – | 0.18 (0.04, 0.62) | 0.09 (0.01, 0.50) | – | – |
| 10-year | 4.54 (3.27, 6.12) | 3.27 (2.23, 4.61) | 0.88 (0.41, 1.70) | 4.07 (2.89, 5.55) | 0.11 (0.01, 0.61) | 0.31 (0.09, 0.90) | 0.33 (0.09, 0.93) | – | – | |
| Cervical | 5-year | 2.57 (2.04, 3.20) | 1.76 (1.33, 2.30) | 1.17 (0.82, 1.62) | 2.56 (2.03, 3.20) | 0.41 (0.23, 0.70) | 0.35 (0.18, 0.63) | 0.32 (0.16, 0.59) | 0.24 (0.11, 0.49) | NA |
| 10-year | 5.19 (4.31, 6.18) | 3.46 (2.75, 4.30) | 1.91 (1.40, 2.54) | 5.86 (4.91, 6.93) | 0.59 (0.34, 0.97) | 0.39 (0.21, 0.69) | 0.53 (0.28, 0.93) | 0.54 (0.30, 0.91) | NA | |
| Testicular | 5-year | 0.45 (0.31, 0.63) | 0.21 (0.13, 0.35) | 0.30 (0.19, 0.46) | 1.04 (0.82, 1.31) | 0.09 (0.04, 0.20) | 0.15 (0.08, 0.27) | 0.12 (0.06, 0.24) | NA | 0.27 (0.17, 0.42) |
| 10-year | 1.10 (0.83, 1.43) | 0.60 (0.41, 0.86) | 0.61 (0.42, 0.87) | 3.38 (2.87, 3.95) | 0.35 (0.21, 0.57) | 0.19 (0.10, 0.33) | 0.24 (0.13, 0.41) | NA | 0.88 (0.63, 1.20) | |
Dash (–) indicates no outcome events.
NA not applicable.
Thyroid and parathyroid disorders
Hypothyroidism
The highest CMI of hypothyroidism at 10-years was observed in HL (7.9%), invasive breast (6.2%), ALL (5.8%), and cervical (5.2%) cancer survivors. In the multivariable model, female sex, older age at cancer diagnosis (30–39 vs. <30), later years of diagnosis, low/middle nSES, public insurance, chemotherapy, and particularly HCT and radiation were associated with increased hazard of hypothyroidism. Patients with HL (vs. melanoma) and NH Whites (vs. other race/ethnicities) had the highest hazard of this condition (Fig. 1a).
Fig. 1. Multivariable models showing the associations of sociodemographic and clinical factors with late endocrine diseases.
a Hypothyroidism, b other thyroid diseases, c parathyroid disorders. HR hazard ratio, CI confidence interval, NH non-Hispanic, AA African American, Mid middle, nSES neighbourhood socioeconomic status, HCT haematopoietic cell transplant, ALL acute lymphoblastic leukaemia, AML acute myeloid leukaemia, NHL non-Hodgkin lymphoma, HL Hodgkin lymphoma. Asterisk (*) indicates time-dependent variable.
Other thyroid disorders
The highest 10-year CMI of non-toxic goitre, thyrotoxicosis, thyroiditis, and other thyroid disease diagnoses was observed in patients with breast (invasive, 3.5% and in situ, 3.3%), cervical cancer (3.5%), CRC (2.1%) and HL (2.0%). In a multivariable model (Fig. 1b), factors associated with higher hazard of other thyroid diseases were female sex, older age at cancer diagnosis (30–39), public insurance, radiation, and later years of diagnosis.
Parathyroid disorders
Among AYAs who developed hypoparathyroidism, hyperparathyroidism, or other parathyroid disorders during follow-up, the highest 10-year CMI was found in those with ALL (5.8%), AML (3.0%), sarcoma, CRC, and invasive breast cancer (~2.1% each). After adjustment for covariates, higher hazard of this condition was observed among NH Blacks/AAs and Hispanics (vs. NH Whites), AYAs diagnosed in the later calendar period, with late-stage disease, with public insurance, recipients of HCT, and AYA survivors of ALL (vs. melanoma) (Fig. 1c).
Diabetes and pancreatic disorders
The greatest 10-year CMI of diabetes was observed among AYAs with ALL (15.1%), AML (9.4%), CRC (6.4%), cervical (5.9%), NHL (5.6%), and invasive breast cancer (5.3%). In the multivariable analysis (Fig. 2a), patients of NH Black/AA, Hispanic, and Asian/PI race/ethnicity (vs. NH Whites), older age at cancer diagnosis, those living in low/middle nSES, and those with public insurance were more likely to develop diabetes. When we examined treatment exposures, those who underwent a HCT had an increased hazard of diabetes compared to those who did not undergo this treatment. Compared to melanoma, all cancers, except in situ breast and testicular cancer, were associated with higher hazard of diabetes.
Fig. 2. Multivariable models showing the associations of sociodemographic and clinical factors with late endocrine diseases.
a Diabetes, b pancreatic disorders, c pituitary disorders. HR hazard ratio, CI confidence interval, NH non-Hispanic, AA African American, Mid Middle, nSES neighbourhood socioeconomic status, HCT haematopoietic cell transplant, ALL acute lymphoblastic leukaemia, AML acute myeloid leukaemia, NHL non-Hodgkin lymphoma, HL Hodgkin lymphoma. Asterisk (*) indicates time-dependent variable); dash (–) indicates no outcome events.
Higher CMI of pancreatic disorders (e.g. pancreatic insufficiency) at 10 years was observed among AYAs with ALL (2.0%), followed by those with AML and CRC (~1.1% each). In a multivariable model (Fig. 2b), greater hazard of this condition was observed among AYAs of NH Black/AA race/ethnicity (vs. NH Whites), those who lived in low/middle nSES, had public insurance, and were diagnosed with ALL, CRC, and sarcoma (vs. melanoma).
Pituitary and adrenal disorders
AYAs with ALL (3.5%), AML (2.0%) and sarcoma (1.6%) had the greatest 10-year CMI of pituitary disorders. In a multivariable model (Fig. 2c), patients with late-stage disease, public insurance, recipients of HCT, and ALL (vs. melanoma) were more likely to develop these conditions.
Greater 10-year CMI of adrenal disorders was found in AYAs diagnosed with ALL (5.5%) and AML (2.5%). In the multivariable analysis (Fig. 3a), hazard of adrenal disorders was increased among Hispanics, later period of diagnosis, patients diagnosed with late-stage disease, with public insurance, and among those who underwent a HCT.
Fig. 3. Multivariable models showing the associations of sociodemographic and clinical factors with late endocrine diseases.
a Adrenal disorders, b ovarian dysfunction, c testicular dysfunction. HR hazard ratio, CI confidence interval, NH non-Hispanic, AA African American, Mid middle, nSES neighbourhood socioeconomic status, HCT haematopoietic cell transplant, ALL acute lymphoblastic leukaemia, AML acute myeloid leukaemia, NHL non-Hodgkin lymphoma, HL Hodgkin lymphoma, NA not applicable. Asterisk (*) indicates time-dependent variable; dash (–) indicates no outcome events.
Gonadal dysfunction
Ovarian
Ten-year CMI of ovarian dysfunction was higher among survivors of ALL and AML (5.3% and 2.5%, respectively). In multivariable models (Fig. 3b), higher hazard of ovarian disorders was observed among AYAs diagnosed in the later period of diagnosis, those who received chemotherapy and HCT, and among survivors of sarcoma and cervical cancer (vs. melanoma).
Testicular
Like ovarian dysfunction, 10-year CMI of testicular dysfunction was higher among patients with AML and ALL (2.5% and 2.1%, respectively). Greater hazard of testicular dysfunction was found in those who underwent a HCT and had thyroid cancer (vs. melanoma) (Fig. 3c).
Discussion
To our knowledge, this is the first population-based study in the US to comprehensively assess the burden of specific endocrinopathies in survivors of AYA cancer. We estimated incidence based on diagnosis codes from hospitalisations, emergency department, and ambulatory surgery visits, which may have resulted in underestimation of true incidence of some disorders. Even so, with a median follow-up of 7.4 years, our findings demonstrated a high burden of endocrinopathies in AYA cancer survivors, which varied by treatment exposures and cancer type. Incidence was highest for diabetes, hypothyroidism and other thyroid disorders, and parathyroid disorders. We also provided important information on sociodemographic subgroups of AYAs at increased risk for these conditions, including those with public insurance, those residing in lower nSES and AYAs of Hispanic or NH Black/AA race/ethnicity. To date, most survivorship care recommendations for AYAs are based on childhood cancer studies. Our in-depth analysis of the risk of endocrinopathies in AYA cancer survivors may help clinicians to better understand which population is at higher risk of developing endocrinopathies, particularly as follow-up time from cancer treatment increases.
We found that HCT was one of the strongest determinants of endocrinopathies, with an increased hazard of all conditions except pancreatic and other thyroid disorders. Endocrinopathies after HCT have been commonly described in childhood cancer survivors and have been attributed to conditioning regimens with high-dose total body irradiation, chemotherapy, and/or prolonged immunosuppressive therapy [32–36]. A European study showed a high prevalence of thyroid, gonadal, and adrenal abnormalities among survivors of haematologic diseases who underwent an allogenic HCT at ages 13–45 years. These patients were not treated with total body irradiation, suggesting that chemotherapy, immunosuppressive therapies, and immune dysregulation (e.g. graft versus host disease), contributed to the development of these conditions [36]. In a recent European study, Felicetti et al. examined the development of endocrinopathies among adults (median age 53 years) who received allogenic HCT from 2010 to 2017. The authors found that 25% of patients developed a hypothyroidism during a median follow-up of 3.7 years, with a higher incidence observed in females [37]. Our results confirm an elevated risk of endocrinopathies among HCT recipients.
We observed that exposure to radiation was associated with increased hazard of hypothyroidism and other thyroid disorders, particularly in females who had higher CMI of these conditions than males. Additionally, females were more likely to receive radiation. Radiation is an established risk factor for endocrinopathies, and can cause harm to the endocrine glands via direct cellular injury [38] or indirect effects through DNA damage [11, 39]. The incidence of hypothyroidism was higher in patients with HL, supporting evidence of prior studies [40–43]. For example, Sklar et al. showed that among survivors of HL diagnosed in children and adolescents, increasing radiation dose was an independent predictor for hypothyroidism [42]. This raises an important question of how often AYA cancer survivors (and also other age groups) should be screened for hypothyroidism and with what modality tests (e.g. laboratory tests such as thyroid-stimulating hormone (TSH)).
Diabetes was one of the more common late effects observed in AYAs in our study. Leukaemia survivors, especially those with ALL, had a higher risk of developing diabetes. Other cancer types, except for in situ breast and testicular cancers, also had an increased risk of this condition. We found a borderline association between radiation and diabetes, possibly secondary to total body or abdominal radiation, as observed in childhood cancer studies [44]. Diabetes has been associated with increased mortality among childhood cancer survivors [45]. A recent study in North America showed that survivors of childhood cancer without diabetes had a lower risk of health-related and cardiovascular death compared to the US general population, independent of lifestyle and cardiovascular risk factors [45]. This highlights the importance of preventive measures, early diagnosis and treatment of diabetes.
Although we did not have specific information about the chemotherapy drugs used, we found that chemotherapy was an independent determinant of ovarian dysfunction, supporting results and recommendations of previous studies [16]. Alkylating agents (e.g. cyclophosphamide, ifosfamide, busulfan) frequently used as frontline treatment for malignancies such as lymphomas and leukaemias, can disrupt the normal function of endocrine glands, especially gonadal glands. This may result in infertility, sexual impairment, and premature menopause, leading to severe psychological distress in AYAs [46–48]. To date, several surveillance recommendations have been developed to address gonadal toxicity in cancer survivors. These guidelines emphasise the importance of physician awareness of the risk of these conditions, the need of counselling AYA cancer survivors, and ongoing research aimed at informing future guideline updates [16, 18].
Late-stage diagnosis was associated with increased risk of parathyroid, pituitary, and adrenal disorders in survivors. Several factors may have contributed to this association, including the need for more intensive therapies in patients with advanced disease and the potential metastases of cancer to endocrine glands [49]. For example, due to their rich blood supply, the adrenal glands are a common site of distant metastases, particularly in breast, melanoma, thyroid, and gastrointestinal cancer patients, and especially in those younger than 50 years [50, 51]. Cancer survivors can develop asymptomatic adrenal insufficiency many years after cancer treatment [52], which can progress to Addison crisis, a life-threatening condition. Thus, patients diagnosed at a late-stage should be screened for adrenal insufficiency and need careful long-term follow-up [53].
In addition, our study revealed an increased risk of thyroid, parathyroid and adrenal disorders, and ovarian dysfunction in AYAs diagnosed with cancer more recently. As treatment evolves, new therapies may raise the risk of endocrinopathies. For example, immune checkpoint inhibitors (e.g. ipilimumab, nivolumab, pembrolizumab) now used in patients with a variety of cancers may cause thyroid disorders, diabetes, hypophysitis, and adrenal insufficiency [54]. Further research is necessary to explore the long-term effects of these novel cancer treatments among cancer survivors.
The incidence of endocrinopathies varied by cancer type. We found that patients with leukaemias, particularly ALL, had a high burden of these diseases, including diabetes, hypothyroidism, parathyroid and adrenal disorders, and ovarian dysfunction. Factors that may have contributed to this elevated risk include high-intensity chemotherapy regimens and total body irradiation [27–30], genetic disorders [55], and rarely, leukaemia cells infiltration to endocrine glands [56, 57]. Additionally, prior intense treatment with corticosteroid is related to adverse adrenal outcomes in patients with leukaemias [58]. Similar to our findings, a nationwide, population-based study in Denmark observed that leukaemia survivors had an elevated risk for any endocrinopathy [26]. Additionally, this study reported that HL survivors had the highest excess risk for hypothyroidism [26]. Further, we found that AYA survivors of sarcoma and cervical cancer had an elevated risk of ovarian dysfunction, likely due to surgery, radiation or and/or chemotherapy, all which can damage the ovary and decrease its function [59, 60]. Likewise, pancreatic disorders were associated with sarcoma and CRC, possibly due to radiation fields that affected the pancreas.
Our findings also revealed a high burden of endocrine diseases among AYAs with public insurance, those residing in low SES neighbourhoods, and AYAs of Hispanic and NH Black/AA race/ethnicity (except for NH Whites, who had a higher risk of hypothyroidism than their counterpart), even after accounting for treatment exposures. These findings are consistent with our previous studies that described late effects among AYAs with haematologic malignancies and thyroid cancer [6–9, 21], highlighting the potential contribution of social determinants of heath to late effects [61]. Food insecurity leads to poor access to food with high nutritional value and contributes to an increased risk of obesity and diabetes [62–64], but risk factors for the elevated risks of other endocrine disorders remains unclear. It will be important to focus future research on interventions that could reduce barriers to care and improve health for these patients.
The strengths of our study include a very large statewide cancer registry data linked to hospitalisation databases in a highly racial/ethnic and socioeconomic diverse population of AYA cancer survivors in the US. Limitations include the use of administrative claims data, such that conditions that clinicians were not aware of or did not bill for were not captured. This may play a role in changes over time, for example, if clinicians became more aware of ovarian toxicity in more recent years, that could have resulted in more coding and contributed to an apparent increase in the condition over time. Additionally, although we used all information available from hospitalisations, ambulatory surgeries, and emergency departments databases, we could not capture diagnoses only coded during routine clinical ambulatory visits. While our findings likely underestimate the incidence of some endocrinopathies, we likely capture more higher grade/severe diseases. In a European study that investigated endocrinopathies after childhood cancer, the authors compared results using only hospital visits to those with hospital and outpatient information. They found only slightly elevated risk estimates when outpatient visits were included [27]. It is also plausible that AYA cancer survivors with more severe endocrinopathies or more interactions with the healthcare system were more likely be diagnosed with endocrinopathies in our study. Further, we did not have detailed information on chemotherapy/immunotherapy drugs, radiation fields/doses, and other endocrinopathies, such as dyslipidemia and obesity. Finally, health insurance status and nSES were collected at cancer diagnosis, thus potential changes or moves over time were not captured in our analysis. However, a recent study linking residential history to cancer registry data found that the proportion of cancer patients in California who moved out of the state between 2015 and 2019 was less than 4.0% [65].
In conclusion, our study identified substantial endocrinopathies in AYA cancer survivors and provided evidence of associations of these diseases with treatment exposures, particularly HCT. We also demonstrated a higher burden of endocrinopathies among underserved AYAs and AYAs of Hispanic and NH Black/AA race/ethnicity. Primary and secondary prevention (e.g. lifestyle modifications), early detection, and timely treatment of endocrinopathies can decrease morbidity, mortality, and enhance quality of life of cancer survivors [13, 45]. Thus, it is crucial to provide these patients with comprehensive and coordinated survivorship care that meets their unique physical and psychosocial needs. While some surveillance guidelines for endocrine diseases exist (e.g. for gonadal toxicity and thyroid cancer) [15–18, 66, 67], others are under development, including those for metabolic syndrome and thyroid dysfunction [68]. Our study may inform the refinement of existing guidelines and the development and evaluation of new recommendations for AYA cancer survivors. Importantly, implementation of these guidelines requires awareness and collaboration among endocrinologists, oncologists, and primary care physicians to ensure equitable survivorship care for this population.
Supplementary information
Author contributions
Conception and design: Renata Abrahão, Theresa Keegan, Ann Brunson. Administrative support: Theresa Keegan, Ted Wun. Collection and assembly of data: Theresa Keegan, Renata Abrahão. Ann Brunson, Ted Wun, Judy Li, Qian Li. Data analysis and interpretation: Renata Abrahão, Theresa Keegan, Ann Brunson. Manuscript writing: all authors. Final approval of manuscript: all authors.
Funding
Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number P01CA233432. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The collection of cancer incidence data used in this study was supported by the California Department of Public Health pursuant to California Health and Safety Code Section 103885; Centers for Disease Control and Prevention’s (CDC) National Program of Cancer Registries, under cooperative agreement 5NU58DP006344; the NCI’s Surveillance, Epidemiology and End Results (SEER) Program under contract HHSN261201800032I awarded to the University of California, San Francisco, contract HHSN261201800015I awarded to the University of Southern California, and contract HHSN261201800009I awarded to the Public Health Institute. The ideas and opinions expressed herein are those of the authors and do not necessarily reflect the opinions of the State of California, Department of Public Health, the NCI, and the CDC or their Contractors and Subcontractors.
Data availability
The data that support the findings of this study are available from the California Cancer Registry and the California Department of Health Care Access and Innovation. Access to these data sources is granted through an application process by the management or data custodians.
Competing interests
The authors declare no competing interests.
Ethical approval and consent to participate statement
This study was approved by the California Committee for the Protection of Human Subjects and Kaiser Permanente Institutional Review Board. We obtained waiver of informed consent as our study does not involve direct data collection from or contact with study participants.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
The online version contains supplementary material available at 10.1038/s41416-024-02594-x.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available from the California Cancer Registry and the California Department of Health Care Access and Innovation. Access to these data sources is granted through an application process by the management or data custodians.