Abstract
Background
Despite excellent prognosis, cognitive and emotional disturbances have been reported in survivors of differentiated thyroid cancer (DTC). However, few studies in China have described baseline cognitive and emotional status in patients with newly diagnosed DTC prior to treatment.
Objective
To investigate possible cognitive impairment as well as anxiety and depression levels in patients newly diagnosed with DTC before treatment, and to explore their associated factors, so as to provide baseline data regarding cognitive and emotional disturbances among Chinese patients with DTC.
Methods
This cross-sectional study enrolled patients with DTC treated at a tertiary referral hospital between July and September 2023. Participants completed the Montreal Cognitive Assessment (MoCA), Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS). Chi-square tests were used for intergroup comparisons, while univariate and multivariate logistic regression analyses were performed to explore factors associated with possible cognitive impairment, anxiety, and depression.
Results
A total of 708 preoperative patients with newly diagnosed DTC were enrolled. Among them, 7.2% presented anxiety symptoms, 20.3% presented depression symptoms, and 62.7% exhibited possible cognitive impairment. Among female participants, postmenopausal status was associated with possible cognitive impairment. Multivariate logistic regression showed that age (p = 0.003) and educational levels (p < 0.05) were independent correlates of possible cognitive impairment among women, while age (p < 0.001), work status (p < 0.05) and residence (p = 0.007) were independently correlated with possible cognitive impairment in the overall cohort. Elevated TSH was a correlate of anxiety (p = 0.014). Income status was independently associated with depressive symptoms (p < 0.05).
Conclusion
Psychological and cognitive disturbances are common among preoperative with DTC. Age, postmenopausal status, educational levels, work status, and residence are related to possible cognitive impairment. TSH levels are relevant correlates of anxiety, and income status is correlated with depression. Routine psychological and cognitive screening should be considered for preoperative DTC patients.
Keywords: anxiety, cognitive dysfunction, depression, differentiated thyroid cancer, newly diagnosed patients
Introduction
Thyroid cancer is one of the most common endocrine malignancies and its incidence is steadily increasing yearly (Lin et al., 2021). Despite the excellent prognosis of most thyroid cancers, patients still suffer from disturbances across multiple cognitive domains, including executive function, psychomotor speed, and attention (Jaracz et al., 2012), alongside emotional disorders such as anxiety and depression (Dionisi-Vici et al., 2021). These symptoms significantly affect patients’ quality of life and disease-related prognosis (Larrabee et al., 2023). Previous reports have indicated that the quality of life of differentiated thyroid cancer (DTC) survivors is markedly lower than that of the general population and that of other cancer types with poorer prognoses (van de Wal et al., 2016).
Multiple studies have reported mental disturbances in DTC patients, yet most of these investigations have concentrated on postoperative populations (Gou et al., 2017; Gülsoy Kirnap et al., 2020; Jin et al., 2019; Jung and Visovatti, 2017; Qiao et al., 2022; Su et al., 2023). Compared with healthy controls, DTC patients demonstrate deficits in attention and working memory function (Jung and Visovatti, 2017). Thyroid stimulating hormone (TSH) suppression therapy effectively reduces tumor recurrence and metastasis. Even so, patients receiving this treatment often experience anxiety and depressive symptoms, accompanied by significant changes in short-term memory, attention, and word selection ability across different treatment stages (Gülsoy Kirnap et al., 2020; Jin et al., 2019). Although radioactive iodine (RAI) therapy represents an important treatment for DTC, many patients develop notable anxiety and depression before and after RAI administration. This psychological burden is more evident among female patients with lower education levels and household income (Qiao et al., 2022; Su et al., 2023), reducing their overall quality of life (Gou et al., 2017).
To our knowledge, only one relevant Korean study has assessed pretreatment cognitive function among female DTC patients. In that report, up to 95% of participants experienced cognitive impairment, 13.7% had depressive symptoms, and 58.9% experienced varying degrees of psychological distress (Jung et al., 2022). Nevertheless, that work was limited by its small sample size, exclusive female enrollment, and a lack of adequate predictive indicators. Importantly, to date no investigations have specifically addressed possible cognitive impairment, anxiety, and depression among newly diagnosed patients with DTC in China, pointing to an important unaddressed research gap.
Therefore, the aim of this large-scale study was to determine the prevalence of possible cognitive impairment, as well as anxiety and depressive symptom levels, among Chinese patients with DTC prior to treatment. We further explored the factors associated with these cognitive and emotional abnormalities to provide baseline data on potential cognitive impairment and emotional disorders, and to lay a foundation for investigating their dynamic changes during disease progression.
Materials and methods
Patients and study design
This cross-sectional study included patients who were scheduled for thyroid surgery at The First Hospital of China Medical University between July and September 2023. Patients were asked to fill out a self-report questionnaire before surgery, and two psychologists conducted neuropsychological assessments in a quiet setting.
Patients who provided written informed consent and who were scheduled for treatment within 3 months after pathological DTC confirmation were enrolled in this study. The exclusion criteria included the following: (1) age <18 years; (2) a history of thyroid surgery; (3) postoperative pathological confirmation not of DTC; (4) a history of anxiety, depression, or regular use of psychotropic medications, including antidepressants, antipsychotics, sedative-hypnotics, mood stabilizers, and anxiolytics; (5) impaired listening, speaking, reading, or writing ability; (6) refusal to cooperate; (7) incomplete clinical data. Incomplete clinical data were defined as missing questionnaire-scale information or core demographic data (e.g., age, work status, and income status). Partially missing thyroid function parameters did not result in study exclusion. Baseline demographic and clinicopathological data were collected, including gender, age, body mass index (BMI), comorbid conditions, educational levels, marital status, work status, income status, residence, preoperative fine-needle aspiration (FNA) results, and thyroid function parameters (FT3, FT4, and TSH). Comorbid conditions were defined as pre-existing chronic illnesses prior to thyroid surgery, including hypertension, diabetes mellitus, and coronary heart disease. Among female patients, postmenopausal status was defined as 12 consecutive months of spontaneous amenorrhea without pathological causes. Women who did not meet this criterion were considered premenopausal.
Instruments
In 1971, Zung compiled the Self Rating Anxiety Scale (SAS) to assess anxiety level (Dunstan and Scott, 2020), and in 1965, he compiled the Self Rating Depression Scale (SDS) to assess depressive status (Zung et al., 1965). The Montreal Cognitive Assessment Scale (MoCA) was used to assess seven cognitive function domains: visual space and executive function, naming, attention, language, abstraction, delayed recall, and directional ability (Nasreddine et al., 2005). These instruments have good sensitivity and reliability and are widely used in clinical practice. Detailed scoring rules and cutoff values are shown in Table 1.
Table 1.
Psychological questionnaire and scoring principles.
| Test/measure | Neuropsychological domain | Scoring methodology | Scoring principles |
|---|---|---|---|
| MoCA | Visuospatial‑executive function | Total score = 30 points.1 point is awarded for participants with ≤12 years of education. | |
| Naming | |||
| Attention | |||
| Language | <26: Possible cognitive impairment | ||
| Abstraction | ≥26: Normal cognition | ||
| Delayed recall | |||
| Orientation | |||
| SAS | Anxiety symptoms | Contains 20 items (15 positive‑worded, 5 negative‑worded). Raw sum score multiplied by 1.25 yields the standard score. | <50: Normal |
| 50–59: Mild anxiety | |||
| 60–69: Moderate anxiety | |||
| >69: Severe anxiety | |||
| SDS | Depressive symptoms | Contains 20 items (10 positive‑worded, 10 negative‑worded). Raw sum score multiplied by 1.25 yields the standard score. | <53: Normal |
| 53–62: Mild depression | |||
| 63–72: Moderate depression | |||
| >72: Severe depression |
MoCA: Montreal Cognitive Assessment; SAS:Self-Rating Anxiety Scale; SDS:Self-Rating Depression Scale.
Statistical analyses
Categorical variables were expressed as frequency (percentage), whereas continuous variables were presented as median (interquartile range). The chi-square test was used to compare differences across groups for categorical variables. The independent samples t-test or Mann–Whitney test was adopted according to data distribution. Univariate and multivariate logistic regression analyses were performed to explore factors associated with possible cognitive impairment, anxiety, and depression. All statistical analyses were conducted using SPSS version 27.0 (IBM SPSS Inc., Chicago, USA). p < 0.05 was considered statistically significant.
This study was approved by the Institutional Review Board of The First Hospital of China Medical University on June 26, 2023 (Approval No. 2023-338-2). Written informed consent was obtained from all enrolled participants prior to data collection.
Results
Baseline characteristics
Of the 836 participants, 708 preoperative patients with DTC were finally included in the study. In total, 128 patients were excluded, including 82 with a postoperative pathological diagnosis other than DTC, 14 with a history of anxiety or depression, 26 with a history of thyroid surgery, and 6 with incomplete data. The screening process was shown in Figure 1.
Figure 1.
Flow chart of the study participant selection.
All included patients were newly diagnosed with DTC and were scheduled for thyroid surgery according to the 2015 ATA guidelines (Haugen et al., 2016). In total, 708 patients were enrolled in this study. The median age was 43 years (IQR, 36–50 years); most participants were ≤60 years old (682, 96.3%), and only 26 (3.7%) were over 60 years. The cohort was predominantly female (550, 77.7%). Among the 550 female participants, 136 were postmenopausal, whereas 414 were premenopausal. Overall, 7.2% (51/708) of patients presented anxiety symptoms, and 20.3% (144/708) had depressive symptoms. Possible cognitive impairment was observed in 62.7% (444/708) of participants. Thyroid function was available for 607 patients, with median FT3 of 4.5 pmol/L, FT4 of 13.2 pmol/L, and TSH of 1.5 uIU/ml. Baseline demographic and clinical characteristics were shown in Table 2.
Table 2.
DTC patient’s demographic and clinical characteristics at baseline.
| Variables | Participants (n,%/Median, IQR) |
|---|---|
| Age | 43 (36, 50) |
| Age | |
| ≤60 | 682 (96.3%) |
| >60 | 26 (3.7%) |
| Gender | |
| Female | 550 (77.7%) |
| Male | 158 (22.3%) |
| Menopausal status# | |
| Yes | 136 |
| No | 414 |
| BMI | |
| <18 | 23 (3.2%) |
| 18–25 | 364 (51.4%) |
| 25–30 | 246 (34.7%) |
| >30 | 75 (10.6%) |
| Comorbid conditions | |
| No | 560 (79.1%) |
| Yes | 148 (20.9%) |
| Education Levels | |
| Primary school | 35 (4.9%) |
| Middle school | 195 (27.5%) |
| High school | 118 (16.7%) |
| University or above | 360 (50.8%) |
| Marital status | |
| Unmarried | 65 (9.2%) |
| Married | 605 (85.5%) |
| Widowed | 14 (2.0%) |
| Divorced | 24 (3.3%) |
| Work status | |
| No work | 215 (30.3%) |
| In work | 392 (55.4%) |
| Retirement | 101 (14.3%) |
| Income status (RMB) | |
| <2000 | 122 (17.2%) |
| 2000–4,000 | 233 (32.9%) |
| 4,000–6,000 | 168 (23.7%) |
| >6,000 | 185 (26.1%) |
| Residence | |
| Rural | 171 (24.2%) |
| City | 537 (75.8%) |
| Anxiety | |
| No | 657 (92.8%) |
| Yes | 51 (7.2%) |
| Mild | 45 (6.4%) |
| Moderate | 5 (0.7%) |
| Severe | 1 (0.1%) |
| Depression | |
| No | 564 (79.7%) |
| Yes | 144 (20.3%) |
| Mild | 126 (17.8%) |
| Moderate | 18 (2.5%) |
| Severe | 0 |
| Cognitive impairment | |
| No | 264 (37.3%) |
| Yes | 444 (62.7%) |
| Thyroid hormone biomarkers | |
| FT3 (pmol/L)* | 4.5 (4.3-4.9) |
| FT4 (pmol/L)* | 13.2 (12.2-14.3) |
| TSH (uIU/ml)* | 1.5 (1.0-2.1) |
*Analysis performed among 607 patients due to incomplete data collection for the remaining participants. # Analyses regarding menopausal status (post- vs pre-menopausal) were restricted to 550 female participants. Comorbid conditions were defined as pre-existing chronic illnesses prior to thyroid surgery, including hypertension, diabetes mellitus, and coronary heart disease. Median IQR: median and interquartile range. RMB: Renminbi (Chinese Yuan).
Group comparisons of possible cognitive impairment, anxiety and depression
Group comparisons were conducted to examine factors related to possible cognitive impairment, anxiety, and depression, as shown in Table 3. Among female participants, postmenopausal status was significantly associated with possible cognitive impairment (p < 0.001) and anxiety symptoms (p = 0.027). Comorbid conditions, education levels, marital status, income status, and residence differed significantly across groups stratified by possible cognitive impairment status (all p < 0.05). Income status and residence showed significant differences between patients with and without depressive symptoms. No significant differences in thyroid hormone biomarkers were detected across groups.
Table 3.
Results of the MoCA, SAS and SDS assessments.
| Variables | MoCA | SAS | SDS | ||||||
|---|---|---|---|---|---|---|---|---|---|
| No cognitive impairment (n, %) | Cognitive impairment (n, %) | p-value | No anxiety (n, %) | Anxiety (n, %) | p-value | No depression (n, %) | Depression (n, %) | p-value | |
| Total | 264 (37.3%) | 444 (62.7%) | 657 (92.8%) | 51 (7.2%) | 564 (79.7%) | 144 (20.3%) | |||
| Gender | 0.604 | 0.630 | 0.345 | ||||||
| Female | 215 (39.1%) | 335 (60.9%) | 509 (92.5%) | 41 (7.5%) | 434 (78.9%) | 116 (21.1%) | |||
| Male | 49 (31.0%) | 109 (69.0%) | 148 (93.7%) | 10 (6.3%) | 130 (82.3%) | 28 (17.7%) | |||
| Menopausal status# | 18 (13.2%) | <0.001 | 0.027 | 0.683 | |||||
| No | 197 (47.6%) | 217 (52.4%) | 389 (94.0%) | 25 (6.0%) | 325 (78.5%) | 89 (21.5%) | |||
| Yes | 18 (13.2%) | 118 (86.8%) | 120 (88.2%) | 16 (11.8%) | 109 (80.1%) | 27 (19.9%) | |||
| BMI | 0.508 | 0.382 | 0.186 | ||||||
| <18 | 10 (43.5%) | 13 (56.5%) | 23 (100%) | 0 | 18 (78.3%) | 5 (21.7%) | |||
| 18–25 | 143 (39.3%) | 221 (60.7%) | 335 (92.0%) | 29 (8.0%) | 280 (76.9%) | 84 (23.1%) | |||
| 25–30 | 83 (33.7%) | 163 (66.3%) | 231 (93.9%) | 15 (6.1%) | 207 (84.1%) | 39 (15.9%) | |||
| >30 | 28 (37.3%) | 47 (62.7%) | 68 (90.7%) | 7 (9.3%) | 59 (78.7%) | 16 (21.3%) | |||
| Comorbid conditions | 0.004 | 0.403 | 0.476 | ||||||
| No | 224 (40.0%) | 336 (60.0%) | 522 (93.2%) | 38 (6.8%) | 443 (79.1%) | 117 (20.9%) | |||
| Yes | 40 (27.0%) | 108 (73.0%) | 135 (91.2%) | 13 (8.8%) | 121 (81.8%) | 27 (18.2%) | |||
| Education Levels | 0.001 | 0.964 | 0.066 | ||||||
| Primary school | 2 (5.7%) | 33 (94.3%) | 33 (94.3%) | 2 (5.7%) | 27 (77.1%) | 8 (22.9%) | |||
| Middle school | 44 (22.6%) | 151 (77.4%) | 182 (93.3%) | 13 (6.7%) | 148 (75.9%) | 47 (24.1%) | |||
| High school | 41 (34.7%) | 77 (65.3%) | 109 (92.4%) | 9 (7.6%) | 88 (74.6%) | 30 (25.4%) | |||
| University or above | 177 (49.2%) | 183 (50.8%) | 333 (92.5%) | 27 (7.5%) | 301 (83.6%) | 59 (16.4%) | |||
| Marital status | 0.001 | 0.771 | 0.192 | ||||||
| Unmarried | 39 (60.0%) | 26 (40.0%) | 62 (95.4%) | 3 (4.6%) | 53 (81.5%) | 12 (18.5%) | |||
| Married | 212 (35.0%) | 393 (65.0%) | 559 (92.4%) | 46 (7.6%) | 483 (79.8%) | 122 (20.2%) | |||
| Widowed | 3 (21.4%) | 11 (78.6%) | 13 (92.9%) | 1 (7.1%) | 8 (57.1%) | 6 (42.9%) | |||
| Divorced | 10 (41.7%) | 14 (58.3%) | 23 (95.8%) | 1 (4.2%) | 20 (83.3%) | 4 (16.7%) | |||
| Work status | 0.054 | 0.393 | 0.971 | ||||||
| No work | 66 (30.7%) | 149 (69.3%) | 198 (92.1%) | 17 (7.9%) | 172 (80.0%) | 43 (20.0%) | |||
| In work | 156 (39.8%) | 236 (60.2%) | 362 (92.3%) | 30 (7.7%) | 311 (79.3%) | 81 (20.7%) | |||
| Retirement | 42 (41.6%) | 59 (58.4%) | 97 (96.0%) | 4 (4.0%) | 81 (80.2%) | 20 (19.8%) | |||
| Income status (RMB) | <0.001 | 0.904 | 0.035 | ||||||
| <2000 | 23 (18.9%) | 99 (81.1%) | 115 (94.3%) | 7 (5.7%) | 89 (73.0%) | 33 (27.0%) | |||
| 2000–4,000 | 78 (33.5%) | 155 (66.5%) | 215 (92.3%) | 18 (7.7%) | 179 (76.8%) | 54 (23.2%) | |||
| 4,000–6,000 | 70 (41.7%) | 98 (58.3%) | 155 (92.3%) | 13 (7.7%) | 139 (82.7%) | 29 (17.3%) | |||
| >6,000 | 93 (50.3%) | 92 (49.7%) | 172 (93.0%) | 13 (7.0%) | 157 (84.9%) | 28 (15.1%) | |||
| Residence | <0.001 | 0.914 | 0.026 | ||||||
| Rural | 36 (21.1%) | 135 (78.9%) | 159 (93.0%) | 12 (7.0%) | 126 (73.7%) | 45 (26.3%) | |||
| City | 228 (42.5%) | 309 (57.5%) | 498 (92.7%) | 39 (7.3%) | 438 (81.6%) | 99 (18.4%) | |||
| FNA | 0.681 | 0.134 | 0.603 | ||||||
| No | 101 (38.3%) | 163 (61.7%) | 240 (90.9%) | 24 (9.1%) | 213 (80.7%) | 51 (19.3%) | |||
| Yes | 163 (36.7%) | 281 (63.3%) | 417 (93.9%) | 27 (6.1%) | 351 (79.1%) | 93 (20.9%) | |||
| FT3* | 4.6 (4.3-5.0) | 4.6 (4.3–5.0) | 0.732 | 4.6 (4.3–4.9) | 4.5 (4.2–4.9) | 0.630 | 4.6 (4.3–4.9) | 4.5 (4.2–4.9) | 0.438 |
| FT4* | 13.2 (12.2-14.3) | 13.2 (12.2–14.3) | 0.757 | 13.2 (12.2–14.3) | 13.0 (12.2–14.2) | 0.993 | 13.2 (12.2–14.3) | 13.22 (12.3–14.3) | 0.631 |
| TSH* | 1.5 (1.0–2.3) | 1.5 (1.0–2.3) | 0.406 | 1.4 (1.0–2.1) | 1.4 (1.0–2.4) | 0.595 | 1.4 (1.0–2.1) | 1.5 (1.0–2.2) | 0.382 |
#Analyses for perimenopause-related outcomes (MoCA, SAS, SDS) were restricted to 550 female participants, as perimenopause status applies only to women. *Thyroid hormone data were available in 607 participants. Median IQR: median and interquartile range. RMB: Renminbi (Chinese Yuan). Comorbid conditions were defined as pre-existing chronic illnesses prior to thyroid surgery, including hypertension, diabetes mellitus, and coronary heart disease.
Univariate and multivariate logistic regression analyses for possible cognitive impairment
Univariate and multivariate logistic regression analyses were performed to explore factors associated with possible cognitive impairment. Variables with p < 0.05 in the univariate logistic regression analyses and clinically relevant covariates were entered into multivariate logistic regression models. Two separate multivariate models were constructed. The first multivariate logistic regression model, which incorporated menopausal status, was fitted exclusively among female participants (n = 550; Table 4). The second model excluded menopausal status and was fitted in the overall study population (n = 708; Supplementary Table 1).
Table 4.
Multivariate logistic regression analyses of factors associated with possible cognitive impairment among female participants (n = 550).
| Characteristics | Univariate analysis | Multivariate analysis | ||||
|---|---|---|---|---|---|---|
| β | OR 95%CI | p-value | β | OR 95%CI | p-value | |
| Gender | ||||||
| Female | Reference | |||||
| Male | −0.356` | 0.700 (0.480–1.022) | 0.065 | |||
| Menopausal status# | ||||||
| Yes | Reference | Reference | ||||
| No | −1.784 | 0.168 (0.099–0.286) | <0.001 | −0.940 | 0.390 (0.198–0.771) | 0.007 |
| Age | 0.078 | 1.081 (1.062–1.101) | <0.001 | 0.043 | 1.044 (1.015–1.073) | 0.003 |
| BMI | ||||||
| <18 | Reference | |||||
| 18–25 | −0.256 | 0.774 (0.300–1.998) | 0.597 | |||
| 25–30 | −0.083 | 0.921 (0.551–1.538) | 0.752 | |||
| >30 | 0.157 | 1.170 (0.684–2.002) | 0.567 | |||
| Comorbid conditions | ||||||
| No | Reference | Reference | ||||
| Yes | 0.993 | 0.556 (0.372–0.829) | 0.004 | −0.002 | 0.998 (0.573–1.738) | 0.993 |
| Education levels | ||||||
| Primary school | Reference | Reference | ||||
| Middle school | 2.770 | 15.959 (3.773–67.504) | <0.001 | 1.686 | 5.398 (1.150–25.342) | 0.033 |
| High school | 1.200 | 3.319 (2.238–4.923) | <0.001 | 0.290 | 1.336 (0.786–2.271) | 0.285 |
| University or above | 0.597 | 1.816 (1.180–2.797) | 0.007 | 0.117 | 1.124 (0.648–1.950) | 0.677 |
| Marital status | ||||||
| Unmarried | Reference | |||||
| Married | −0.742 | 0.476 (0.184–1.233) | 0.126 | |||
| Widowed | 0.281 | 1.324 (0.578–3.032) | 0.507 | |||
| Divorced | 0.963 | 2.619 (0.577–11.888) | 0.212 | |||
| Work status | ||||||
| No work | Reference | Reference | ||||
| In work | 0.474 | 1.607 (0.984–2.625) | 0.058 | 0.524 | 1.689 (0.896–3.186) | 0.105 |
| Retirement | 0.074 | 1.077 (0.691–1.679) | 0.744 | 0.111 | 1.117 (0.623–2.005) | 0.710 |
| Income status (RMB) | ||||||
| <2000 | Reference | Reference | ||||
| 2000–4,000 | 1.470 | 4.351 (2.542–7.448) | <0.001 | 0.554 | 1.741 (0.859–3.529) | 0.124 |
| 4,000–6,000 | 0.698 | 2.009 (1.351–2.986) | <0.001 | 0.199 | 1.221 (0.733–2.032) | 0.443 |
| >6,000 | 0.347 | 1.415 (0.929–2.156) | 0.106 | 0.183 | 1.201 (0.705–2.046) | 0.500 |
| Residence | ||||||
| Rural | Reference | Reference | ||||
| City | 1.018 | 2.767 (1.845–4.151) | <0.001 | 0.493 | 1.638 (0.951–2.821) | 0.075 |
| FNA | ||||||
| No | Reference | |||||
| Yes | −0.066 | 0.936 (0.684–1.282) | 0.681 | |||
| FT3* | −0.051 | 0.950 (0.722–1.251) | 0.717 | |||
| FT4* | −0.015 | 0.986 (0.894–1.086) | 0.769 | |||
| TSH* | −0.018 | 0.982 (0.846–1.140) | 0.811 | |||
Menopausal status, age, comorbid conditions, educational levels, work status, income status, and place of residence were included in the multivariate regression analysis. # Analyses regarding menopausal status (post- vs pre-menopausal) were restricted to 550 female participants. *Thyroid hormone data were available in 607 participants. Comorbid conditions were defined as pre-existing chronic illnesses prior to thyroid surgery, including hypertension, diabetes mellitus, and coronary heart disease. RMB: Renminbi (Chinese Yuan).
When menopausal status was incorporated into the multivariate regression analysis, postmenopausal status (p = 0.007), age (p = 0.003), and educational level (p < 0.05) were independently associated with possible cognitive impairment (Table 4). When menopausal status was not incorporated into the multivariate regression analysis, age (p < 0.001), work status (p = 0.049), and residence (p = 0.007) were related to possible cognitive impairment (Supplementary Table 1).
Univariate and multivariate logistic regression analyses for anxiety and depression
We used logistic regression analyses to explore factors correlated with anxiety and depressive symptoms. In univariate analyses, both menopausal status (p = 0.030) and TSH levels (p = 0.014) were significantly correlated with anxiety (Table 5). For depressive symptoms, multivariate regression analysis demonstrated that income status (p < 0.05) was independently associated with these symptoms (Table 6).
Table 5.
Univariate logistic regression analyses of factors associated with anxiety in the overall cohort (n = 708)
| Characteristics | Univariate analysis | ||
|---|---|---|---|
| β | OR 95%CI | p-value | |
| Gender | |||
| Female | Reference | ||
| Male | 0.176 | 1.192 (0.583–2.437) | 0.630 |
| Menopausal status# | |||
| Yes | Reference | ||
| No | −0.730 | 0.482 (0.249–0.933) | 0.030 |
| Age | 0.017 | 1.017 (0.989–1.046) | 0.240 |
| BMI | |||
| <18 | Reference | ||
| 18–25 | −18.929 | NE | 0.998 |
| 25–30 | −0.173 | 0.841 (0.354–1.998) | 0.695 |
| >30 | −0.461 | 0.631 (0.247–1.610) | 0.335 |
| Comorbid conditions | |||
| No | Reference | ||
| Yes | −0.28 | 0.756 (0.392–1.459) | 0.404 |
| Education levels | |||
| Primary school | Reference | ||
| Middle school | −0.291 | 0.747 (0.170–3.284) | 0.700 |
| High school | −0.127 | 0.881 (0.444–1.749) | 0.717 |
| University or above | 0.018 | 1.018 (0.465–2.232) | 0.964 |
| Marital status | |||
| Unmarried | Reference | ||
| Married | 0.107 | 1.113 (0.110–11.248) | 0.928 |
| Widowed | 0.638 | 1.893 (0.250–14.333) | 0.537 |
| Divorced | 0.571 | 1.769 (0.102–30.709) | 0.695 |
| Work status | |||
| No work | Reference | ||
| In work | 0.733 | 2.082 (0.682–6.355) | 0.198 |
| Retirement | 0.698 | 2.010 (0.691–5.842) | 0.200 |
| Income status (RMB) | |||
| <2,000 | Reference | ||
| 2,000–4,000 | −0.216 | 0.805 (0.312–2.080) | 0.655 |
| 4,000–6,000 | 0.102 | 1.108 (0.528–2.324) | 0.787 |
| >6,000 | 0.104 | 1.110 (0.499–2.467) | 0.798 |
| Residence | |||
| Rural | Reference | ||
| City | −0.037 | 0.964 (0.493–1.886) | 0.914 |
| FNA | |||
| No | Reference | ||
| Yes | 0.435 | 1.544 (0.871–2.737) | 0.137 |
| FT3* | −0.145 | 0.865 (0.508–1.473) | 0.594 |
| FT4* | 0.029 | 1.029 (0.864–1.226) | 0.746 |
| TSH* | 0.267 | 1.306 (1.054–1.618) | 0.014 |
# Analyses regarding menopausal status (post- vs. pre-menopausal) were restricted to 550 female participants. *Thyroid hormone data were available in 607 participants. Comorbid conditions were defined as pre-existing chronic illnesses prior to thyroid surgery, including hypertension, diabetes mellitus, and coronary heart disease. NE: not estimable, NE indicates that the OR and 95% CI for BMI 18–25 could not be reliably estimated because of sparse cell counts and unstable parameter estimation. RMB: Renminbi (Chinese Yuan).
Table 6.
Multivariate logistic regression analyses of factors associated with depressive symptoms in the overall cohort (n = 708).
| Characteristics | Univariate analysis | Multivariate analysis | ||||
|---|---|---|---|---|---|---|
| β | OR 95%CI | p-value | β | OR 95%CI | p-value | |
| Gender | ||||||
| Female | Reference | |||||
| Male | 0.216 | 1.2421 (0.786–1.960) | 0.354 | |||
| Menopausal status# | ||||||
| Yes | Reference | |||||
| No | 0.100 | 1.106 (0.683–1.791) | 0.683 | |||
| Age | 0.006 | 1.006 (0.988–1.025) | 0.500 | |||
| BMI | ||||||
| <18 | Reference | |||||
| 18–25 | 0.024 | 1.024 (0.329–3.185) | 0.967 | |||
| 25–30 | 0.101 | 1.106 (0.605–2.024) | 0.743 | |||
| >30 | −0.364 | 0.695 (0.363–1.331) | 0.272 | |||
| Comorbid conditions | ||||||
| No | Reference | |||||
| Yes | 0.169 | 1.184 (0.744–1.883) | 0.477 | |||
| Education levels | ||||||
| Primary school | Reference | Reference | ||||
| Middle school | 0.413 | 1.512 (0.655–3.490) | 0.333 | −0.030 | 0.970 (0.386–2.443) | 0.949 |
| High school | 0.483 | 1.620 (1.053–2.492) | 0.028 | 0.185 | 1.204 (0.728–1.991) | 0.471 |
| University or above | 0.553 | 1.739 (1.055–2.866) | 0.030 | 0.433 | 1.542 (0.920–2.582) | 0.100 |
| Marital status | ||||||
| Unmarried | Reference | |||||
| Married | 0.124 | 1.132 (0.327–3.924) | 0.845 | |||
| Widowed | 0.233 | 1.263 (0.424–3.763) | 0.675 | |||
| Divorced | 1.322 | 3.750 (0.830–16.935) | 0.086 | |||
| Work status | ||||||
| No work | Reference | |||||
| In work | 0.012 | 1.012 (0.560–1.831) | 0.967 | |||
| Retirement | 0.053 | 1.055 (0.610–1.823) | 0.848 | |||
| Income status (RMB) | ||||||
| <2000 | Reference | Reference | ||||
| 2000–4,000 | 0.732 | 2.079 (1.180–3.664) | 0.011 | 0.732 | 2.079 (1.180–3.664) | 0.011 |
| 4,000–6,000 | 0.526 | 1.692 (1.022–2.801) | 0.041 | 0.526 | 1.692 (1.022–2.801) | 0.041 |
| >6,000 | 0.157 | 1.170 (0.663–2.063) | 0.588 | 0.157 | 1.170 (0.663–2.063) | 0.588 |
| Residence | ||||||
| City | Reference | |||||
| Rural | 0.457 | 1.580 (1.055–2.367) | 0.027 | |||
| FNA | ||||||
| No | Reference | |||||
| Yes | −0.101 | 0.904 (0.617–1.324) | 0.603 | |||
| FT3* | −0.213 | 0.808 (0.569–1.148) | 0.234 | |||
| FT4* | 0.012 | 1.012 (0.901-1.137) | 0.838 | |||
| TSH* | 0.059 | 1.060 (0.892-1.261) | 0.507 | |||
We incorporated education levels, income status, residence into the multivariate regression model. Comorbid conditions were defined as pre-existing chronic illnesses prior to thyroid surgery, including hypertension, diabetes mellitus, and coronary heart disease. *Thyroid hormone data were available in 607 participants. # Analyses regarding menopausal status (post- vs pre-menopausal) were restricted to 550 female participants. RMB: Renminbi (Chinese Yuan).
Discussion
To our knowledge, this is the first large-scale study to explore baseline possible cognitive impairment and emotional disturbances in China. This study is of great significance, since it not only adds to existing research on cancer-related cognitive impairment, but also enhances clinicians’ awareness of the mental health of patients newly diagnosed with DTC before treatment. In this study, the rates of possible cognitive impairment, anxiety, and depression were 62.7, 7.2, and 20.3%, respectively, which were significantly higher than those in the general population (Lu et al., 2021; Huang et al., 2019). A cancer diagnosis may trigger anxiety, fear, and other negative emotions, which could in turn interfere with cognitive performance and impair quality of life (Pitt et al., 2021). Therefore, it is valuable to comprehensively identify the factors related to possible cognitive impairment and emotional disorders among DTC patients.
Factors affecting cognitive function in DTC
Cumulative evidence has demonstrated that DTC patients experience impairment in multiple cognitive domains, such as memory, attention, executive function, and processing speed, during treatment (Wefel et al., 2015). Consistent with previous findings (Larrabee et al., 2023), our study identified a high prevalence (62.7%) of possible cognitive impairment among preoperative DTC patients. In addition, the MoCA scale is highly sensitive in screening for mild cognitive impairment and allows effective detection of preoperative possible cognitive impairment, further underscoring its clinical value. The development of possible cognitive impairment is multifactorial. It is closely linked to hippocampal atrophy, morphological deformation, and altered functional connectivity (Peukert et al., 2020). In addition, changes in cytokine and oxidative stress levels in the tumor microenvironment also play a role (Ren et al., 2017). Genetic predisposition and protein deposition further exacerbate cognitive deficits. For example, APOEε4 and amyloid substance deposition impair patients’ attention, learning ability, and cognitive processing speed (Reinvang et al., 2013). Moreover, fluctuations in thyroid hormone levels can alter hippocampal hormonal responsiveness, which in turn induces a series of psychological and cognitive alterations in DTC patients (Jurado-Flores et al., 2022; Eslami-Amirabadi and Sajjadi, 2021; Bavarsad et al., 2019).
In multivariate analysis, perimenopausal status, age, educational level, work status, and residence were independently associated with possible cognitive impairment. Multiple studies have explored the biological mechanisms underlying these associations. Estrogen contributes to neuroprotective effects and supports neuronal development, connectivity, and plasticity. During the perimenopausal transition, declining ovarian function leads to reduced estrogen levels, which may impair cognitive performance in women (Metcalf et al., 2023). Aging is accompanied by increased neuronal death and reduced synaptic connections. Furthermore, the incidence of cardiovascular and cerebrovascular diseases such as diabetes and hypertension rises with advancing age, accompanied by alterations in cerebral blood flow, which further contribute to cognitive deficits. The hippocampus serves as the core structure for learning, memory, and cognitive functions, and it is highly vulnerable to hypoxic ischemic injury (Johnson, 2023).
Education levels reflect knowledge reserves and helps strengthen brain network connectivity, preserves cognitive function, maintaining normal cognitive function, and resisting brain aging (Du et al., 2023). A higher educational level is also associated with enhanced information processing, problem solving, and decision-making abilities (Jefferson et al., 2011). Patients with higher educational levels tend to have better understanding and awareness regarding the diagnosis, treatment, and prognosis of DTC. In contrast, individuals with lower educational levels are more likely to develop adverse cognitive perceptions.
Individuals living in rural areas often have relatively lower income, lower education levels, and insufficient access to health related information, which may contribute to increased psychological distress (Du et al., 2023). Therefore, adequate attention and informational support should be offered to patients with these risk factors before treatment to avoid further cognitive deterioration.
Factors affecting anxiety and depression in DTC
A cancer diagnosis and concerns regarding subsequent treatment may increase anxiety, depression, and fear among patients with DTC (Pitt et al., 2021). In a study conducted in 2022, the prevalence of anxiety in patients with thyroid cancer was as high as 37.6%, particularly in women with elevated BMI, recurrent laryngeal nerve injury, or hypoparathyroidism (Noto et al., 2022). This proportion is substantially higher than the anxiety prevalence observed in our cohort (7.2%). This discrepancy may be partially explained by our exclusion of 14 participants with prior anxiety or depression. In addition, differences in recruitment settings, assessment instruments, timing of evaluation, and patient demographic characteristics may also account for divergent findings. Our study enrolled preoperative patients, whereas the study by Noto et al. included postoperative individuals. Postoperative patients tend to pay more attention to treatment related complications, such as recurrent laryngeal nerve injury, hypoparathyroidism, and scar-related problems (Campagnoli et al., 2023).
Postoperative RAI treatment, TSH suppressive therapy, and potential thyroid dysfunction (including hyperthyroidism (Tagay et al., 2005), hypothyroidism (Tagay et al., 2006)) during treatment can also increase the patient’s anxiety levels. Economic burden and anticipation of final pathological results also contribute to psychological distress (Mongelli et al., 2020; Yang and Xu, 2022). In our study, the prevalence of anxiety was lower but still significantly higher than that in general populations (Huang et al., 2019). In univariable analysis, postmenopausal status was associated with greater odds of anxiety among women. This trend merits consideration, as it may be partly explained by hormonal fluctuations and menopausal related symptoms in postmenopausal females (Campagnoli et al., 2023). In the Chinese context, women entering retirement commonly experience shifts in lifestyle and living circumstances. Therefore, more attention should be paid to patients in perimenopausal period.
In this study, up to 20.3% of the patients reported depressive symptoms, with income level identified as an independent correlate. This prevalence was higher than that reported in a previous study (Noto et al., 2022). Several factors may account for this discrepancy. Preoperative patients often face financial pressure, which may represent an important contributor to depressive symptoms (Srivastava et al., 2021). Furthermore, long-term subsequent cancer treatment may also affect the future economic status of the family, and this concern is more prominent among patients with lower income levels (Bresner et al., 2015).
In addition, the income level is closely related to knowledge reserves (Herrera-Escobar et al., 2019). Individuals with higher income level are more likely to achieve higher educational levels, which allows them to acquire more comprehensive knowledge about their disease. This may alleviate concerns regarding surgical risks, postoperative recovery, and potential complications (e.g., surgical scars).
Limitations
This study has several limitations. As a cross-sectional investigation, it cannot establish causality. We could not distinguish whether possible cognitive impairment existed prior to cancer diagnosis or resulted from diagnosis related stress; accordingly, variables identified in regression analyses represent correlates rather than causal risk factors.
Recruitment from a single tertiary hospital may limit generalizability, as enrolled patients tended to have more complex thyroid conditions and higher comorbidity burdens compared with individuals in community. Voluntary participation might introduce selection bias, given potential psychological differences between responders and non-responders. Information bias cannot be fully excluded because psychological and cognitive outcomes relied on self-reported questionnaires.
Several key variables were unavailable before surgery, including detailed DTC pathological subtype information (e.g., follicular variant and tall-cell variant of papillary thyroid carcinoma), planned surgical approach, and intended RAI therapy. Residual confounding may exist due to unmeasured factors such as social support, the interval between diagnosis and assessment, family history of thyroid disease, and reasons for clinical consultation. Furthermore, formal adjustment for multiple comparisons was not conducted for these exploratory analyses, which may increase the risk of Type I error. Future prospective studies incorporating these unmeasured variables will help better characterize psychological outcomes among DTC patients.
Conclusion
Clinicians should pay attention to the psychological and cognitive status of patients newly diagnosed with DTC before treatment. Our findings suggest that postmenopausal status, age and educational levels are independent correlates of possible cognitive impairment in women, whereas age, work status, and residence are independent correlates in the overall cohort. TSH levels are associated with anxiety, and income status is an independent correlate of depressive symptoms. Given the cross-sectional design, causal inferences cannot be drawn from the present study. Future prospective studies are needed to validate these associations and clarify relevant mechanisms.
Funding Statement
The author(s) declared that financial support was received for this work and/or its publication. Doctoral Start-up Fund of the Affiliated Hospital of Inner Mongolia University for the Nationalities, No. MDFY2020001.
Footnotes
Edited by: Minghua Wu, Central South University, China
Reviewed by: Ahmed H. Assar, The George Washington University School of Medicine and Health Sciences, United States
Mercado-Lara Maria Fernanda, Fundación Colombiana de Cancerología Clínica Vida, Colombia
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The study received ethical approval from the Institutional Review Board (IRB) of The First Hospital of China Medical University (IRB No. 2023-338-2), and informed consent was obtained from all participants. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
TJ: Data curation, Investigation, Writing – original draft, Writing – review & editing, Funding acquisition. HS: Data curation, Investigation, Methodology, Writing – original draft, Writing – review & editing. YZ: Formal analysis, Methodology, Writing – original draft, Writing – review & editing. PL: Writing – original draft. MW: Funding acquisition, Methodology, Writing – original draft.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that Generative AI was not used in the creation of this manuscript.
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Supplementary material
The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2026.1908212/full#supplementary-material
References
- Bavarsad K., Hosseini M., Hadjzadeh M. A., Sahebkar A. (2019). The effects of thyroid hormones on memory impairment and Alzheimer's disease. J. Cell. Physiol. 234, 14633–14640. doi: 10.1002/jcp.28198, [DOI] [PubMed] [Google Scholar]
- Bresner L., Banach R., Rodin G., Thabane L., Ezzat S., Sawka A. M. (2015). Cancer-related worry in Canadian thyroid cancer survivors. J. Clin. Endocrinol. Metab. 100, 977–985. doi: 10.1210/jc.2014-3169, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Campagnoli M., Dell'Era V., Rosa M. S., Negri F., Malgrati E., Garzaro M., et al. (2023). Patient's scar satisfaction after conventional thyroidectomy for differentiated thyroid Cancer. J Pers Med 13:1066. doi: 10.3390/jpm13071066, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Dionisi-Vici M., Fantoni M., Botto R., Nervo A., Felicetti F., Rossetto R., et al. (2021). Distress, anxiety, depression and unmet needs in thyroid cancer survivors: a longitudinal study. Endocrine 74, 603–610. doi: 10.1007/s12020-021-02786-y, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Du C., Miyazaki Y., Dong X., Li M. (2023). Education, social engagement, and cognitive function: a cross-lagged panel analysis. J. Gerontol. B Psychol. Sci. Soc. Sci. 78, 1756–1764. doi: 10.1093/geronb/gbad088, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Dunstan D. A., Scott N. (2020). Norms for Zung's self-rating anxiety scale. BMC Psychiatry 20:90. doi: 10.1186/s12888-019-2427-6, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Eslami-Amirabadi M., Sajjadi S. A. (2021). The relation between thyroid dysregulation and impaired cognition/behaviour: an integrative review. J. Neuroendocrinol. 33:e12948. doi: 10.1111/jne.12948, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gou J., Cheng W., Lei J., Pan Q., You W., Cai M., et al. (2017). Health-related quality-of-life assessment in surgical patients with papillary thyroid carcinoma: a single-center analysis from mainland China. Medicine (Baltimore) 96:e8070. doi: 10.1097/md.0000000000008070, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gülsoy Kirnap N., Turhan Iyidir Ö., Bozkuş Y., Işildak S. M., Anil C., Firat S. N., et al. (2020). The effect of iatrogenic subclinical hyperthyroidism on anxiety, depression and quality of life in differentiated thyroid carcinoma. Turk J Med Sci 50, 870–876. doi: 10.3906/sag-1902-176, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Haugen B. R., Alexander E. K., Bible K. C., Doherty G. M., Mandel S. J., Nikiforov Y. E., et al. (2016). 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid Cancer: the American Thyroid Association guidelines task force on thyroid nodules and differentiated thyroid Cancer. Thyroid 26, 1–133. doi: 10.1089/thy.2015.0020, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Herrera-Escobar J. P., Seshadri A. J., Rivero R., Toppo A., al Rafai S. S., Scott J. W., et al. (2019). Lower education and income predict worse long-term outcomes after injury. J. Trauma Acute Care Surg. 87, 104–110. doi: 10.1097/ta.0000000000002329, [DOI] [PubMed] [Google Scholar]
- Huang Y., Wang Y., Wang H., Liu Z., Yu X., Yan J., et al. (2019). Prevalence of mental disorders in China: a cross-sectional epidemiological study. Lancet Psychiatry 6, 211–224. doi: 10.1016/s2215-0366(18)30511-x, [DOI] [PubMed] [Google Scholar]
- Jaracz J., Kucharska A., Rajewska-Rager A., Lacka K. (2012). Cognitive functions and mood during chronic thyrotropin-suppressive therapy with L-thyroxine in patients with differentiated thyroid carcinoma. J. Endocrinol. Investig. 35, 760–765. doi: 10.3275/8013, [DOI] [PubMed] [Google Scholar]
- Jefferson A. L., Gibbons L. E., Rentz D. M., Carvalho J. O., Manly J., Bennett D. A., et al. (2011). A life course model of cognitive activities, socioeconomic status, education, reading ability, and cognition. J. Am. Geriatr. Soc. 59, 1403–1411. doi: 10.1111/j.1532-5415.2011.03499.x, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Jin S., Yang Y. T., Bao W., Bai Y., Ai J. W., Liu Y., et al. (2019). Naming difficulties after thyroid stimulating hormone suppression therapy in patients with differentiated thyroid carcinoma: a prospective cohort study. Endocrine 65, 327–337. doi: 10.1007/s12020-019-01943-8, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Johnson A. C. (2023). Hippocampal vascular supply and its role in vascular cognitive impairment. Stroke 54, 673–685. doi: 10.1161/strokeaha.122.038263, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Jung M. S., Visovatti M. (2017). Post-treatment cognitive dysfunction in women treated with thyroidectomy for papillary thyroid carcinoma. Support Care Cancer 25, 915–923. doi: 10.1007/s00520-016-3481-y, [DOI] [PubMed] [Google Scholar]
- Jung M. S., Visovatti M., Kim M., Cha K., Dlamini N., Cui X. (2022). Cognitive impairment in women newly diagnosed with thyroid cancer before treatment. Support Care Cancer 30, 8959–8967. doi: 10.1007/s00520-022-07299-6, [DOI] [PubMed] [Google Scholar]
- Jurado-Flores M., Warda F., Mooradian A. (2022). Pathophysiology and clinical features of neuropsychiatric manifestations of thyroid disease. J Endocr Soc 6:bvab194. doi: 10.1210/jendso/bvab194, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Larrabee K., Meeks N., Williams A. M., Springer K., Siddiqui F., Chang S. S., et al. (2023). Cognitive function and postoperative outcomes in patients with head and neck Cancer. Laryngoscope 133, 2999–3005. doi: 10.1002/lary.30677, [DOI] [PubMed] [Google Scholar]
- Lin L., Li Z., Yan L., Liu Y., Yang H., Li H. (2021). Global, regional, and national cancer incidence and death for 29 cancer groups in 2019 and trends analysis of the global cancer burden, 1990-2019. J. Hematol. Oncol. 14:197. doi: 10.1186/s13045-021-01213-z, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lu J., Xu X., Huang Y., Li T., Ma C., Xu G., et al. (2021). Prevalence of depressive disorders and treatment in China: a cross-sectional epidemiological study. Lancet Psychiatry 8, 981–990. doi: 10.1016/s2215-0366(21)00251-0, [DOI] [PubMed] [Google Scholar]
- Metcalf C. A., Duffy K. A., Page C. E., Novick A. M. (2023). Cognitive problems in perimenopause: a review of recent evidence. Curr. Psychiatry Rep. 25, 501–511. doi: 10.1007/s11920-023-01447-3, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mongelli M. N., Giri S., Peipert B. J., Helenowski I. B., Yount S. E., Sturgeon C. (2020). Financial burden and quality of life among thyroid cancer survivors. Surgery 167, 631–637. doi: 10.1016/j.surg.2019.11.014, [DOI] [PubMed] [Google Scholar]
- Nasreddine Z. S., Phillips N. A., Bédirian V., Charbonneau S., Whitehead V., Collin I., et al. (2005). The Montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment. J. Am. Geriatr. Soc. 53, 695–699. doi: 10.1111/j.1532-5415.2005.53221.x, [DOI] [PubMed] [Google Scholar]
- Noto B., Asmus I., Schäfers M., Görlich D., Riemann B. (2022). Predictors of anxiety and depression in differentiated thyroid Cancer survivors: results of a cross-sectional study. Thyroid 32, 1077–1085. doi: 10.1089/thy.2022.0067, [DOI] [PubMed] [Google Scholar]
- Peukert X., Steindorf K., Schagen S. B., Runz A., Meyer P., Zimmer P. (2020). Hippocampus-related cognitive and affective impairments in patients with breast Cancer-a systematic review. Front. Oncologia 10. doi: 10.3389/fonc.2020.00147, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Pitt S. C., Saucke M. C., Wendt E. M., Schneider D. F., Orne J., Macdonald C. L., et al. (2021). Patients' reaction to diagnosis with thyroid Cancer or an indeterminate thyroid nodule. Thyroid 31, 580–588. doi: 10.1089/thy.2020.0233, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Qiao T., Gao D., Tong J., Shen Y., Ma J., Lv Z., et al. (2022). Anxiety and depression status prior to radioactive iodine therapy among differentiated thyroid cancer patients during the COVID-19 pandemic. Support Care Cancer 30, 10169–10177. doi: 10.1007/s00520-022-07422-7, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Reinvang I., Espeseth T., Westlye L. T. (2013). APOE-related biomarker profiles in non-pathological aging and early phases of Alzheimer's disease. Neurosci. Biobehav. Rev. 37, 1322–1335. doi: 10.1016/j.neubiorev.2013.05.006, [DOI] [PubMed] [Google Scholar]
- Ren X., St Clair D. K., Butterfield D. A. (2017). Dysregulation of cytokine mediated chemotherapy induced cognitive impairment. Pharmacol. Res. 117:267. doi: 10.1016/j.phrs.2017.01.001, [DOI] [PubMed] [Google Scholar]
- Srivastava S., Debnath P., Shri N., Muhammad T. (2021). The association of widowhood and living alone with depression among older adults in India. Sci. Rep. 11:21641. doi: 10.1038/s41598-021-01238-x, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Su Y. R., Yu X. P., Huang L. Q., Xie L., Zha J. S. (2023). Factors influencing postoperative anxiety and depression following Iodine-131 treatment in patients with differentiated thyroid cancer: a cross-sectional study. World J Psychiatry 13, 486–494. doi: 10.5498/wjp.v13.i7.486, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Tagay S., Herpertz S., Langkafel M., Erim Y., Bockisch A., Senf W., et al. (2006). Health-related quality of life, depression and anxiety in thyroid cancer patients. Qual. Life Res. 15, 695–703. doi: 10.1007/s11136-005-3689-7, [DOI] [PubMed] [Google Scholar]
- Tagay S., Herpertz S., Langkafel M., Erim Y., Freudenberg L., Schöpper N., et al. (2005). Health-related quality of life, anxiety and depression in thyroid cancer patients under short-term hypothyroidism and TSH-suppressive levothyroxine treatment. Eur. J. Endocrinol. 153, 755–763. doi: 10.1530/eje.1.02047, [DOI] [PubMed] [Google Scholar]
- van de Wal M., van de Poll-Franse L., Prins J., Gielissen M. (2016). Does fear of cancer recurrence differ between cancer types? A study from the population-based PROFILES registry. Psychooncology 25, 772–778. doi: 10.1002/pon.4002, [DOI] [PubMed] [Google Scholar]
- Wefel J. S., Kesler S. R., Noll K. R., Schagen S. B. (2015). Clinical characteristics, pathophysiology, and management of noncentral nervous system cancer-related cognitive impairment in adults. CA Cancer J. Clin. 65, 123–138. doi: 10.3322/caac.21258, [DOI] [PMC free article] [PubMed] [Google Scholar]
- Yang S., Xu X. (2022). Anxiety and quality of life among papillary thyroid cancer patients awaiting final pathology results after surgery. Endocrine 76, 377–384. doi: 10.1007/s12020-022-02996-y, [DOI] [PubMed] [Google Scholar]
- Zung W. W., Richards C. B., Short M. J. (1965). Self-rating depression scale in an outpatient clinic. Further validation of the SDS. Arch. Gen. Psychiatry 13, 508–515. doi: 10.1001/archpsyc.1965.01730060026004, [DOI] [PubMed] [Google Scholar]
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Data Availability Statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.