Abstract
Objective
Although thyroid cancer has an excellent prognosis, many survivors report persistent quality of life (QoL) impairments. Obesity is highly prevalent among thyroid cancer survivors (TCS) and may exacerbate these impairments, yet data on this association remain limited. This study aimed to evaluate the relationship between body mass index (BMI) and health-related QoL in TCS.
Methods
A cross-sectional study was conducted between January 2021 and July 2022 among 342 TCS. QoL was assessed using the EORTC THY34 module. Clinical, metabolic, and demographic data were collected. Patients were stratified by BMI: normal weight (18.5–24.9 kg/m2), overweight (25–29.9), and obese (≥30). Associations between BMI and QoL domains were analyzed using multivariate linear regression.
Results
Among the 307 respondents to the THY34, 52.9% were obese. Obesity was significantly associated with older age, female sex, and higher prevalence of hypertension, diabetes, dyslipidemia, and metabolic syndrome (P < 0.001). Obese patients reported significantly poorer body image (P = 0.020) and more muscle cramps (P = 0.039) after adjusting for confounders. No significant differences were found in global QoL, emotional well-being, or social support across BMI groups.
Conclusion
While overall health-related QoL did not differ significantly by BMI category, specific physical and body image-related symptoms, particularly body image dissatisfaction and muscle cramps, were more pronounced among obese TCS. These findings underscore the need for comprehensive survivorship care, including metabolic assessment, rehabilitation, and tailored psychosocial support, to address obesity-related challenges.
Key words: thyroid cancer, survivorship, obesity, health-related quality of life, BMI
Highlights
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This study evaluated health-related quality of life (HRQoL) in thyroid cancer survivors using the validated EORTC THY34 module.
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Obesity was associated with poorer body image, reduced physical functioning, and more muscle cramps despite similar global QoL scores across BMI groups.
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Obese survivors experienced a higher symptom burden, underscoring the need for integrated and patient-centered supportive care.
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This study is among the first to examine the link between obesity and QoL in thyroid cancer survivors in a low-resource setting.
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Findings highlight the importance of incorporating weight management and psychosocial support into survivorship care plans.
Clinical Relevance
Obesity is linked to reduced quality of life in thyroid cancer survivors, particularly in areas of physical symptoms and body image. Psychosocial needs are often addressed through counseling, peer support groups, and patient education, but structured and culturally adapted interventions remain limited, especially in low-resource settings. Addressing obesity alongside systematic screening for psychological distress and implementing tailored support and rehabilitation programs could improve survivorship outcomes and overall well-being in this growing population.
Introduction
Over the past few decades, the global incidence of thyroid cancer has risen sharply, largely due to overdiagnosis from improved imaging and screening practices.1,2 Despite this increase, disease-specific mortality has remained low and stable.3 As a result, the population of thyroid cancer survivors (TCS) continues to grow, and by 2030, thyroid cancer is expected to rank among the most common cancers in female survivors.4
Beyond the risk of recurrence and disease-related mortality, TCS face multiple long-term complications, including cardiovascular disease,5 osteoporosis,6 and metabolic syndrome—comprising diabetes, obesity, and hypertension.7 The psychosocial burden of the disease is also considerable. Diagnosis and treatment often lead to distress, anxiety, depression, and reduced well-being, particularly among women, adolescents and young adults, racial or ethnic minorities, and individuals with pre-existing psychological conditions.8 Despite favorable survival outcomes, many survivors report impaired health-related quality of life (HRQoL), sometimes worse than that observed in the general population9,10 and comparable to cancers with poorer prognoses.11 These impairments extend across both physical and psychosocial domains and are further influenced by treatment-related factors and psychological vulnerability.8,12 However, most available data rely on generic quality-of-life instruments rather than thyroid-specific tools, limiting the precision of prior findings.13
Among the various factors affecting survivorship, obesity represents a growing concern. Defined as a chronic, biologically active disease,14 obesity is highly prevalent among cancer survivors, affecting up to two-thirds of TCS.15 Beyond its contribution to cardiometabolic risk, adipose tissue functions as an endocrine organ that releases adipokines and inflammatory mediators, promoting chronic low-grade inflammation that may worsen quality-of-life outcomes.16 Obesity also imposes psychosocial and functional burdens, compounding the physical and emotional challenges faced by survivors. Increasing evidence has linked obesity to thyroid cancer across the disease continuum—it is associated with a higher risk of cancer development,17 more aggressive tumor characteristics and surgical complexity,18,19 and poorer follow-up outcomes, including worse prognosis and diminished HRQoL.12,20,21
Multidisciplinary interventions—combining physical activity, nutritional counseling, and psychological support—have been shown to improve metabolic health and HRQoL, even without substantial weight loss.22,23 However, despite the high prevalence of obesity and its plausible influence on survivorship, the specific relationship between body mass index (BMI) and HRQoL among TCS remains poorly characterized. Therefore, this study aims to examine the association between BMI and HRQoL in TCS using disease-specific instruments.
Methods
Study Population
This cross-sectional study included adult TCS recruited between January 2021 and July 2022. Eligible participants were adults (aged ≥18 years) with a confirmed diagnosis of thyroid cancer—regardless of histological type—who had completed their primary treatment (surgery and/or radioiodine therapy) at least 6 months before inclusion. For study purposes, the date of surgery was considered the date of diagnosis.
Patients were approached during routine follow-up visits and provided written informed consent prior to participation.
Exclusion criteria included patients diagnosed within the previous 6 months, those lost to follow-up or not actively monitored, pregnant women, individuals who refused consent, and those lacking recent biological assessments.
All procedures adhered to institutional and national ethical guidelines.
Data Collection
Sociodemographic and clinical data—including age, sex, cancer histology, tumor–node–metastasis staging system, treatment details, date of diagnosis, and time since diagnosis—were obtained from medical records.
Metabolic factors were evaluated according to the World Health Organization’s STEPwise approach.19 Measurements included.
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Anthropometry: weight, height (used to calculate BMI), and waist circumference. All measurements were taken in the same clinics using standardized procedures and calibrated equipment.
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Blood pressure: measured using a calibrated digital sphygmomanometer.
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Laboratory values: fasting blood glucose, high-density lipoprotein cholesterol, and triglycerides.
BMI was categorized based on World Health Organization classification cut-offs.
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Normal (18.5–24.9 kg/m2),
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Overweight (25–29.9 kg/m2),
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Obese (≥30 kg/m2).
Measures
Quality of life (QoL) was assessed using the EORTC THY34,21 a thyroid cancer-specific module developed by the European Organization for Research and Treatment of Cancer. THY34 evaluates disease- and treatment-related symptoms, emotional distress, fatigue, and other QoL domains relevant to TCS.
Scores were linearly transformed to a 0–100 scale in accordance with EORTC guidelines. Higher scores on symptom scales indicate greater symptom burden, whereas higher scores on functioning or overall QoL scales indicate better outcomes.
The THY34 is a validated disease-specific tool designed for TCS to assess HRQoL, in contrast to generic instruments such as the QLQ-C30.24 Notably, it has been translated into several languages, including Arabic, enhancing its applicability across diverse populations.21
Statistical Analysis
Statistical analyses were performed using SPSS version 25. Continuous variables were summarized as means ± SDs or medians with IQRs, as appropriate. Categorical variables were expressed as frequencies and percentages.
Comparisons between groups according to metabolic syndrome status were made using:
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Student’s t test or Mann-Whitney U test for continuous variables, and
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Chi-square or Fisher exact test for categorical variables.
Univariate and multivariate linear regression analyses were conducted to explore the association between BMI and THY34 QoL scores among TCS.
Covariates included in the models were age at diagnosis, sex, time since diagnosis, radioactive iodine therapy, thyroid-stimulating hormone (TSH) level, hypertension, diabetes, tumor–node–metastasis classification, and dynamic risk stratification.
All tests were 2-sided, and a P value <0.05 was considered statistically significant.
Results
A total of 733 patients were screened for inclusion. After excluding those lost to follow-up, deceased, or lacking complete data, 307 patients who completed the quality-of-life questionnaire were included in the final analysis.
Baseline and Clinical Characteristics
Initially, 342 TCS were enrolled in the study. The median age at diagnosis was 48 years (range: 21–85), and the majority were female (88.9%). Most participants were nonsmokers (90.4%) and literate (78.9%).
Regarding cancer characteristics, 81.9% had no nodal involvement (N0/Nx), and 96.5% had no distant metastasis (M0/Mx). The predominant histological type was papillary thyroid carcinoma (82.2%). Radioiodine therapy was administered in 60.2% of cases.
The prevalence of hypertension, diabetes, and dyslipidemia was 49.4%, 28.1%, and 78.0%, respectively, and 61.7% of participants met the criteria for metabolic syndrome. According to dynamic risk stratification, 74.6% of patients demonstrated an excellent response to treatment.
Of the 342 patients, 307 completed the THY34 HRQoL questionnaire. When stratified by BMI, 66 (19.3%) were of normal weight, 95 (27.8%) were overweight, and 181 (52.9%) were obese.
Obese patients were significantly older at diagnosis compared with those of normal weight (median age: 51 vs 41 years; P = 0.014) and were more frequently female (93.9% vs 75.8%; P < 0.001). The obese group also had a higher prevalence of hypertension (63.5% vs 25.8%), diabetes (37.4% vs 12.1%), dyslipidemia (89.6% vs 61.3%), and metabolic syndrome (78.3% vs 27.3%; P < 0.001 for all).
Conversely, nodal involvement (N1) was more frequent among normal-weight individuals (36.4% vs 13.3%; P < 0.001). No significant differences were found across BMI categories regarding M stage, histological type, radioiodine therapy, or dynamic risk stratification.
Full baseline and clinical characteristics by BMI group are presented in Tables 1 and 2.
Table 1.
Demographic Characteristics According to Weight Status (n = 342)
| Characteristics | Normal weight (n = 66) | Overweight (n = 95) | Obese (n = 181) | Total (n = 342) | P value |
|---|---|---|---|---|---|
| Age at diagnosis, median (range), y | 41 (21–81) | 47 (24–82) | 51 (25–85) | — | 0.014a |
| Sex | NS | ||||
| Female | 50 (75.8%) | 84 (88.4%) | 170 (93.9%) | 304 (88.9%) | NS |
| Male | 16 (24.2%) | 11 (11.6%) | 11 (6.1%) | 38 (11.1%) | 0.000a |
| Smoking status | 0.025a | ||||
| Never | 56 (84.8%) | 86 (90.5%) | 174 (96.1%) | — | NS |
| Former | 7 (10.6%) | 7 (7.4%) | 3 (1.7%) | — | NS |
| Current | 3 (4.5%) | 2 (2.1%) | 4 (2.2%) | — | NS |
| Education level | 0.238 | ||||
| Literate | 55 (85.9%) | 75 (79.8%) | 136 (76.0%) | 266 (78.9%) | NS |
| Illiterate | 9 (14.1%) | 19 (20.2%) | 43 (24.0%) | 71 (21.1%) | NS |
Abbreviation: NS = not significant.
Significant (P < 0.05).
Table 2.
Clinical Characteristics According to Weight Status (n = 342)
| Variable | Normal weight (n = 66) | Overweight (n = 95) | Obese (n = 181) | P value |
|---|---|---|---|---|
| N stage | 0.000a | |||
| N0/Nx | 42 (63.6%) | 76 (80.0%) | 157 (86.7%) | NS |
| N1 | 24 (36.4%) | 19 (20.0%) | 24 (13.3%) | NS |
| M stage | 0.051 | |||
| M0/Mx | 61 (92.4%) | 89 (93.7%) | 178 (98.3%) | NS |
| M1 | 5 (7.6%) | 6 (6.3%) | 3 (1.7%) | — |
| Histological type | 0.661 | |||
| Papillary | 49 (74.2%) | 78 (82.1%) | 152 (84.0%) | NS |
| Medullary | 11 (16.7%) | 9 (9.5%) | 11 (6.1%) | NS |
| Borderline (FT-UMP/NIFTP) | 3 (4.5%) | 3 (3.2%) | 6 (3.3%) | NS |
| Poorly differentiated | 1 (1.5%) | 1 (1.1%) | 2 (1.1%) | NS |
| Anaplastic | 0 (0.0%) | 0 (0.0%) | 1 (0.6%) | NS |
| Follicular (nonvariant) | 2 (3.0%) | 4 (4.2%) | 9 (5.0%) | NS |
| Radioiodine therapy | 0.273 | |||
| Not performed | 32 (48.5%) | 46 (48.4%) | 72 (39.8%) | NS |
| Performed | 34 (51.5%) | 49 (51.6%) | 109 (60.2%) | NS |
| Hypertension (HTN) | <0.001a | |||
| Yes | 17 (25.8%) | 35 (36.8%) | 115 (63.5%) | NS |
| No | 49 (74.2%) | 60 (63.2%) | 66 (36.5%) | NS |
| Diabetes | <0.001a | |||
| Diabetic | 8 (12.1%) | 19 (20.0%) | 67 (37.4%) | NS |
| Nondiabetic | 58 (87.9%) | 76 (80.0%) | 112 (62.6%) | NS |
| Dyslipidemia | <0.001a | |||
| Yes | 38 (61.3%) | 71 (77.2%) | 155 (89.6%) | NS |
| No | 24 (38.7%) | 21 (22.8%) | 18 (10.4%) | NS |
| Metabolic syndrome | <0.001a | |||
| Yes | 18 (27.3%) | 51 (53.7%) | 141 (78.3%) | NS |
| No | 48 (72.7%) | 44 (46.3%) | 39 (21.7%) | NS |
| Dynamic risk stratification | 0.055 | |||
| Excellent response | 44 (66.7%) | 68 (71.6%) | 143 (79.0%) | NS |
| Indeterminate response | 11 (16.7%) | 11 (11.6%) | 22 (12.2%) | NS |
| Incomplete biochemical response | 0 (0.0%) | 4 (4.2%) | 1 (0.6%) | NS |
| Incomplete structural response | 11 (16.7%) | 12 (12.6%) | 15 (8.3%) | NS |
Abbreviations: FT-UMP = follicular tumor of uncertain malignant potential; NIFTP = noninvasive follicular thyroid neoplasm with papillary-like nuclear features; NS = not significant.
Significant (P < 0.05).
BMI and Quality-of-Life Outcomes
Quality-of-life outcomes among TCS were analyzed according to BMI categories and are summarized in Table 3.
Table 3.
Quality of Life Domain Scores According to Weight Status in Thyroid Cancer Survivors (THY34 Questionnaire)
| Scales | Normal (n = 60) | Overweight (n = 88) | Obese (n = 159) | Univariate, P | Multivariate, P |
|---|---|---|---|---|---|
| Fatigue score (mean ± SD) | 40.2 ± 27.4 | 40.4 ± 25.3 | 41.1 ± 26.6 | 0.932 | NS |
| Discomfort in head and neck | 19.6 ± 21.9 | 17.3 ± 17.8 | 18.6 ± 19.5 | 0.939 | NS |
| Voice concerns | 19.1 ± 23.2 | 17.8 ± 20.5 | 17.3 ± 19.9 | 0.965 | NS |
| Hair problems | 24.4 ± 26.7 | 24.6 ± 24.9 | 28.3 ± 28.5 | 0.588 | NS |
| Swallowing difficulties | 14.2 ± 19.8 | 11.2 ± 15.7 | 17.0 ± 21.2 | 0.171 | NS |
| Dry mouth | 23.9 ± 26.8 | 29.2 ± 29.4 | 33.5 ± 29.4 | 0.078 | 0.133 |
| Altered temperature tolerance | 32.2 ± 33.0 | 39.4 ± 32.6 | 38.8 ± 31.8 | 0.295 | NS |
| Body image | 20.0 ± 28.9 | 24.6 ± 31.8 | 32.9 ± 34.4 | 0.020 | 0.020a |
| Restlessness | 36.1 ± 26.6 | 42.6 ± 23.8 | 41.9 ± 26.5 | 0.302 | NS |
| Shoulder functioning | 16.7 ± 29.8 | 13.3 ± 21.8 | 21.4 ± 26.6 | 0.028 | 0.693 |
| Fear | 18.5 ± 19.6 | 23.4 ± 22.2 | 21.7 ± 20.8 | 0.434 | NS |
| Joint pain | 30.0 ± 31.7 | 39.0 ± 29.1 | 42.6 ± 32.9 | 0.029 | 0.530 |
| Tingling/numbness | 17.5 ± 18.0 | 18.2 ± 20.3 | 22.1 ± 19.7 | 0.092 | 0.266 |
| Cramps | 16.1 ± 26.4 | 23.9 ± 26.7 | 28.5 ± 30.7 | 0.013 | 0.039a |
| Worry about important others | 23.1 ± 24.7 | 23.6 ± 20.1 | 23.7 ± 22.4 | 0.778 | NS |
| Impact on job or education | 23.9 ± 34.2 | 20.5 ± 30.5 | 23.7 ± 29.4 | 0.523 | NS |
| Social support | 84.4 ± 18.4 | 81.2 ± 22.7 | 81.3 ± 21.9 | 0.731 | NS |
Abbreviation: NS = not significant.
Significant (P < 0.05).
Overall, there were no significant differences across BMI groups in fatigue, head and neck discomfort, voice concerns, hair problems, swallowing difficulties, or dry mouth scores. However, dry mouth symptoms tended to increase with BMI, though this trend did not reach statistical significance in multivariate analysis (P = 0.133).
Body image scores were significantly poorer among obese participants compared with those of normal weight (P = 0.020), and this association remained significant after adjusting for baseline and clinical variables (P = 0.020).
Shoulder functioning was significantly worse among obese patients in univariate analysis (P = 0.028), but this association did not persist in multivariate regression (P = 0.693).
Joint pain and cramps were also more frequently reported by obese individuals. While joint pain differences were significant in univariate analysis (P = 0.029), the association lost significance after adjustment (P = 0.530). In contrast, cramps remained significantly associated with higher BMI after adjustment (P = 0.039).
No significant differences were found between BMI groups in emotional distress (fear), restlessness, tingling or numbness, worry about others, impact on job or education, or perceived social support.
These findings suggest that, although overall HRQoL did not differ markedly across BMI groups, certain physical symptoms, particularly body image issues and cramps, were more prominent among obese TCS.
Discussion
In this cross-sectional study of 307 TCS assessed with the disease-specific THY34 questionnaire, we investigated the association between BMI and HRQoL. Overall HRQoL did not differ significantly across BMI categories; however, obese patients reported poorer outcomes in specific domains, particularly body image and muscle cramps. In contrast, fatigue, joint pain, and oropharyngeal symptoms showed no significant variation between BMI groups, and emotional well-being appeared largely unaffected by BMI. These results suggest that obesity selectively impairs certain physical and psychosocial aspects of HRQoL rather than global well-being among TCS.
Our findings aligned with previous studies showing that HRQoL in TCS can be shaped by both metabolic and psychosocial factors. In Tunisia, Missaoui et al 24 identified age, menopausal status, surgical complications, and TSH suppression as predictors of reduced HRQoL, though BMI was not evaluated. By directly examining BMI, our study helps fill this knowledge gap in North African populations.
Similarly, Giusti et al 25 in Italy and Dong et al 26 in China demonstrated that higher BMI was associated with poorer thyroid cancer-specific HRQoL, particularly in domains related to body image, musculoskeletal discomfort, and thyroid-related symptoms. Long-term follow-up data from Australia also showed that elevated BMI predicted lower HRQoL and impaired social functioning.27 Collectively, these findings reinforce the notion that BMI represents a modifiable determinant of HRQoL in TCS, alongside well-established clinical factors such as disease stage, recurrence, and TSH suppression.
The impact of obesity on HRQoL among TCS likely reflects both biological and psychosocial pathways. Interestingly, emotional well-being was not significantly affected by BMI in our cohort, in contrast to observations in other cancer populations.28 This difference may reflect better coping mechanisms or cultural resilience among regularly monitored TCS. Furthermore, although cancer is fundamentally a genetic disease, its impact on QoL varies depending on tumor aggressiveness, treatment modality, and disease severity. Not all cancer treatments directly affect brain or cognitive function, and therefore cancer-related cognitive impairment remains a matter of debate.29,30 Finally, nutritional status and BMI should be viewed as interrelated rather than independent factors influencing both physical and psychosocial outcomes in survivorship.
This study has several strengths, including a relatively large sample size, the use of a validated thyroid cancer-specific HRQoL instrument (THY34), and a comprehensive assessment of metabolic comorbidities. However, some limitations should be acknowledged. The cross-sectional design precludes causal inference and does not allow for evaluation of HRQoL changes over time. Selection bias may be present, as patients lost to follow-up or deceased were excluded. In addition, lifestyle changes during the COVID-19 pandemic could have affected both BMI and HRQoL. Finally, BMI does not distinguish between fat and lean mass, and the THY34 tool may not fully capture obesity-specific symptoms.
Conclusion
In summary, while overall HRQoL did not differ significantly across BMI categories, obese TCS reported poorer outcomes in body image and musculoskeletal domains. These findings underscore the need to integrate obesity management and psychosocial support into survivorship care. Multidisciplinary interventions—combining exercise, nutritional counseling, and psychological rehabilitation—may improve both metabolic health and HRQoL. Future longitudinal studies are warranted to confirm these associations and to evaluate the benefits of targeted lifestyle interventions.
Author Contributions
N.K. conceived the study, contributed to its design, supervised data collection, performed statistical analyses, and drafted the manuscript. A.L. contributed to study design, data collection, and manuscript revision for important intellectual content. N.N. assisted in data interpretation, contributed to the discussion section, and performed detailed manuscript revisions. All authors have read and approved the final manuscript.
Data Availability
All relevant data have been presented in the manuscript.
Code Availability
Not applicable.
Declaration of Generative AI and AI-Assisted Technologies in the Writing Process
During the preparation of this work the author(s) used ChatGPT (OpenAI) in order to improve the language and readability of this manuscript. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.
Acknowledgment
We would like to express our sincere gratitude to all the residents and the team at the Endocrinology Department of Constantine University Hospital, as well as the Internal Medicine Department of Bejaia University Hospital, for their invaluable support. Special thanks to Dr Kouachi from the Department of Epidemiology at Constantine University Hospital for his contributions.
References
- 1.Li M., Dal Maso L., Vaccarella S. Global trends in thyroid cancer incidence and the impact of overdiagnosis. Lancet Diabetes Endocrinol. 2020;8(6):468–470. doi: 10.1016/S2213-8587(20)30115-7. [DOI] [PubMed] [Google Scholar]
- 2.Vaccarella S., Franceschi S., Bray F., Wild C.P., Plummer M., Dal Maso L. Worldwide thyroid-cancer epidemic? The increasing impact of overdiagnosis. N Engl J Med. 2016;375(7):614–617. doi: 10.1056/NEJMp1604412. [DOI] [PubMed] [Google Scholar]
- 3.Davies L., Hoang J.K. Thyroid cancer in the USA: current trends and outstanding questions. Lancet Diabetes Endocrinol. 2021;9(1):11–12. doi: 10.1016/S2213-8587(20)30372-7. [DOI] [PubMed] [Google Scholar]
- 4.Miller K.D., Nogueira L., Mariotto A.B., et al. Cancer treatment and survivorship statistics, 2019. CA Cancer J Clin. 2019;69(5):363–385. doi: 10.3322/caac.21565. [DOI] [PubMed] [Google Scholar]
- 5.Park J., Blackburn B.E., Ganz P.A., et al. Risk factors for cardiovascular disease among thyroid cancer survivors: findings from the Utah cancer survivors study. J Clin Endocrinol Metab. 2018;103(7):2468–2477. doi: 10.1210/jc.2017-02629. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Blackburn B.E., Ganz P.A., Rowe K., et al. Aging-related disease risks among young thyroid cancer survivors. Cancer Epidemiol Biomarkers Prev. 2017;26(12):1695–1704. doi: 10.1158/1055-9965.EPI-17-0623. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Kaouache N., Lakehal A. Cardiometabolic risk factors among thyroid cancer survivors. Discover Med. 2024;1(1):140. [Google Scholar]
- 8.Haymart P., Levin N.J., Haymart M.R. The psychosocial impact of thyroid cancer. Curr Opin Endocrinol Diabetes Obes. 2023;30(5):252–258. doi: 10.1097/MED.0000000000000815. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Husson O., Haak H.R., Buffart L.M., et al. Health-related quality of life and disease specific symptoms in long-term thyroid cancer survivors: a study from the population-based PROFILES registry. Acta Oncol. 2013;52(2):249–258. doi: 10.3109/0284186X.2012.741326. [DOI] [PubMed] [Google Scholar]
- 10.Singer S., Lincke T., Gamper E., et al. Quality of life in patients with thyroid cancer compared with the general population. Thyroid. 2012;22(2):117–124. doi: 10.1089/thy.2011.0139. [DOI] [PubMed] [Google Scholar]
- 11.Applewhite M.K., James B.C., Kaplan S.P., et al. Quality of life in thyroid cancer is similar to that of other cancers with worse survival. World J Surg. 2016;40(3):551–561. doi: 10.1007/s00268-015-3300-5. [DOI] [PubMed] [Google Scholar]
- 12.Walshaw E.G., Smith M., Kim D., Wadsley J., Kanatas A., Rogers S.N. Systematic review of health-related quality of life following thyroid cancer. Tumori. 2022;108(4):291–314. doi: 10.1177/03008916211025098. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Lee J., Lee Y.J., Lim D.J., Lee J.M., Chang S.A., Kim M.H. Quality of life of survivors of thyroid cancer is not inferior to that in subjects without cancer: long-term after over 5 years. Endocrinol Metab (Seoul) 2022;37(4):664–673. doi: 10.3803/EnM.2022.1499. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Bray G.A., Kim K.K., Wilding J.P.H. Obesity: a chronic relapsing progressive disease process. A position statement of the World obesity Federation. Obes Rev. 2017;18(7):715–723. doi: 10.1111/obr.12551. [DOI] [PubMed] [Google Scholar]
- 15.Huynh C.N., Pearce J.V., Kang L., Celi F.S. Weight gain after thyroidectomy: a systematic review and meta-analysis. J Clin Endocrinol Metab. 2021;106(1):282–291. doi: 10.1210/clinem/dgaa754. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Lippi L., de Sire A., Folli A., et al. Obesity and cancer rehabilitation for functional recovery and quality of life in breast cancer survivors: a comprehensive review. Cancers. 2024;16(3):521. doi: 10.3390/cancers16030521. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Kouidrat Y., Louhou R., Mondot C., Daami I., Amad A., Diouf M. Quality of life in patients with obesity: the role of multidisciplinary rehabilitation medicine. Obesities. 2024;4(2):160–168. [Google Scholar]
- 18.Oppert J.M., Ciangura C., Bellicha A. Health-enhancing physical activity in obesity management: the need to (seriously) go beyond weight loss. Int J Obes (Lond) 2025;49(2):211–213. doi: 10.1038/s41366-024-01632-1. [DOI] [PubMed] [Google Scholar]
- 19.World Health Organization. Noncommunicable, D. and C. Mental health . Genève; 2006. STEPS: l'approche STEPwise de l'OMS pour la Surveill des facteurs de risque des maladies chroniques: manuel de Surveill STEPS de l'OMS. Approche STEPwise de l'OMS pour la surveillance des facteurs de risque des maladies chroniques. Manuel de Surveillance STEPS de l'OMS Organisation mondiale de la Santé. [Google Scholar]
- 20.Hisan U.K., Myung S.K., Nguyen G.V. Associations between obesity and risk of thyroid cancer: a meta-analysis of cohort studies. Nutr Cancer. 2025;77(2):288–298. doi: 10.1080/01635581.2024.2419488. [DOI] [PubMed] [Google Scholar]
- 21.Singer S., Jordan S., Locati L.D., et al. The EORTC module for quality of life in patients with thyroid cancer: phase III. Endocr Relat Cancer. 2017;24(4):197–207. doi: 10.1530/ERC-16-0530. [DOI] [PubMed] [Google Scholar]
- 22.Economides A., Giannakou K., Mamais I., Economides P.A., Papageorgis P. Association between aggressive clinicopathologic features of papillary thyroid carcinoma and body mass index: a systematic review and meta-analysis. Front Endocrinol (Lausanne) 2021;12 doi: 10.3389/fendo.2021.692879. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Rossi L., Becucci C., Iachini M., et al. The impact of obesity on thyroidectomy outcomes: a case-matched study. Updates Surg. 2024;76(1):219–225. doi: 10.1007/s13304-023-01687-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Missaoui A.M., Hamza F., Maaloul M., et al. Health-related quality of life in long-term differentiated thyroid cancer survivors: a cross-sectional Tunisian-based study. Front Endocrinol (Lausanne) 2022;13 doi: 10.3389/fendo.2022.999331. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Giusti M., Gay S., Conte L., et al. Evaluation of quality of life in patients with differentiated thyroid cancer by means of the thyroid-specific patient-reported outcome questionnaire: a 5-Year longitudinal study. Eur Thyroid J. 2020;9(5):247–255. doi: 10.1159/000501201. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Dong Z., Zhan X., Liu W., et al. Factors influencing the quality of life in survivors of differentiated thyroid cancer based on patient-reported outcomes: a single-center cross-sectional study. Front Endocrinol (Lausanne) 2025;16 doi: 10.3389/fendo.2025.1565633. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Blefari N.D.A., Rowe C.W., Wiadji E., et al. Long-term health-related quality of life outcomes following thyroid surgery for malignant or benign disease: deficits persist in cancer survivors beyond five years. World J Surg. 2022;46(10):2423–2432. doi: 10.1007/s00268-022-06643-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Gomez D., Jimenez-Fonseca P., Fernández A.M., et al. Impact of obesity on quality of life, psychological distress, and coping on patients with Colon cancer. The Oncologist. 2021;26(5):e874–e882. doi: 10.1002/onco.13687. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Lange M., Joly F., Vardy J., et al. Cancer-related cognitive impairment: an update on state of the art, detection, and management strategies in cancer survivors. Ann Oncol. 2019;30(12):1925–1940. doi: 10.1093/annonc/mdz410. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Zhang Y., Kesler S.R., Dietrich J., Chao H.H. Cancer-related cognitive impairment: a practical guide for oncologists. JCO Oncol Pract. 2025;21(10):1377–1381. doi: 10.1200/OP-24-00953. [DOI] [PMC free article] [PubMed] [Google Scholar]
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Data Availability Statement
All relevant data have been presented in the manuscript.