Introduction

Melanoma, malignantly transformed from the pigment-producing melanocyte, occurs most commonly in the cutaneous.1,2 Melanoma primarily causes by genetic mutations and environmental factors like UV radiation. Four main histological subtypes of cutaneous melanoma (CM) are categorized: lentigo maligna(LM) melanoma, superficial spreading melanoma (SSM), acral lentiginous melanoma (ALM) or acral melanoma (AM), and nodular melanoma. Other locations such as the eyes, ears, gastrointestinal tract, genitalia, urinary system, and meninges can also be seen. Although CM is most seen in Caucasian population, a rising incidence of AM in Asians are noticed recently.3 AM is the most predominant subtype of melanoma in Asians. According to the statistics of WHO in 2020, Taiwan ranks 2nd upon the incident rate of cutaneous melanoma in East Asia, at about 0.71 per 100,000 people.4 There are more than 200 newly diagnosed cases annually in Taiwan.5

AM is a subtype which occurs over palms, soles, digits and nails. It accounts for 60% of cutaneous melanoma in Asia.6 Unlike other forms of melanoma, AM is not strongly associated with UV exposure. The relationship between trauma, mechanical stress and AM has been a topic of interest, though the connection is not fully understood.7–10 In molecular biology, common gene mutations including KIT, BRAF, NRAS, and NF1 were found in melanoma.11 AM holds lower mutational burdens compared to non-acral melanomas. It is also more aggressive and has a poorer prognosis with the five- and ten-year melanoma-specific survival rates 80.3% and 67.5%, respectively, which were significantly lower than the overall rates for all cutaneous malignant melanoma, which were 91.3% and 87.5% (p<0.001).12 Among acral melanoma cases, the highest five- and ten-year melanoma-specific survival rates were observed in Caucasian persons (82.6% and 69.4%), followed by Black persons (77.2% and 71.5%), while the lowest rates were found in Asian persons (70.2% and 54.1%).13

Obesity results from excessive accumulation of fat which is a common major risk factor for most cardiovascular disease, diabetes and musculoskeletal disorders.14 Based on the statistics from the WHO, obese population has grown 3 times since 1975 in worldwide. In 2019, 39% and 13% of adults were overweight and obese, respectively, around the world. Obesity has also been the 5th leading risk factor got death globally since 2019. In Taiwan, a rising increase of obesity or being overweight in the past 20 years has been recorded with average body mass index (BMI) currently 24.5 (±0.12) in men and 23.8(±0.13) in women.15

The association between obesity and malignancy has been investigated in numerous studies since the early 2000s.16–18 Evidence has shown that increase in adiposity elevates the incidence of and mortality from several common cancers, including endometrial, breast, ovarian, prostate, liver, gallbladder, kidney and colon cancer.15 However, higher BMI has also been correlated with improved outcomes in some cancers, an effect referred to as the “obesity paradox”. A 2015 study found that obesity is associated with increased Breslow thickness, indicating more aggressive melanoma, with some studies linking obesity to a higher melanoma risk in men but not women.19–21 However, other research found better survival rates for overweight individuals with melanoma, while some studies show no correlation between obesity and melanoma.22,23

Based on the above literature, the correlation between melanoma and obesity is still controversial.24 However, little research has been reported about this issue. Given the rising incidence of cutaneous melanoma in Taiwan, we aim to find out the relationship between obesity and prognosis of cutaneous melanoma and its AM subtype in Taiwan.

Materials and Methods

This was a retrospective cohort study approved by the Institutional Review Board of Taipei Veterans General Hospital. The participants were 201 patients who were diagnosed with cutaneous melanoma between 2000 and 2022 at Taipei Veterans General Hospital, a tertiary medical center in Taiwan. Exclusion criteria were applied to ensure data completeness and follow-up availability. Patients with unknown primary melanoma, mucosal melanoma, or multiple primary melanomas were excluded from the analysis. Additionally, patients who were lost to follow-up were also excluded. Anti-tumor therapy was not considered as a criterion for exclusion, allowing for the inclusion of patients regardless of the type of treatment received. Body mass index (BMI) was used as the measure of obesity and was calculated by dividing the weight of the patient in kilograms by the square of their height in meters (kg/m^2). The included participants were classified into four groups based on their BMI, underweight (BMI:<18.5), normal weight (BMI:18.5–24.9), overweight (BMI:25–29.9) and obesity (BMI: ≥30). The primary objective of this study focused on examining the correlation between obesity and the prognosis of cutaneous melanoma. The secondary objective aimed to compare the findings between the AM and the non-AM group, thereby assessing any potential differences in the observed relationship.

Statistical Analysis

The Analysis of Variance (ANOVA) test was used to assess for differences in continuous variables among the four groups of BMI and Chi-square test for categorical variables. To identify prognostic factors, both univariate and multivariate logistic regression analyses were conducted. These analyses enabled the evaluation of the potential factors that could influence the prognosis of cutaneous melanoma. Furthermore, Kaplan-Meier (KM) survival analysis was performed to analyze the overall survival and disease-free survival outcomes. This analysis helped to determine the impact of different variables on the survival rates of patients. In all statistical analyses, a significance level of P<0.05 was considered, which was employed to estimate any substantial differences or associations between the variables.

Results Basic Characteristics

A total of 201 patients diagnosed with cutaneous melanoma were enrolled in the study. The male to female sex ratio was 1.71. The mean age was 66.9 years. More than half of patients (101 people) were within normal weight (50.24%), 75 people were overweight (37.31%), 15 had obesity (7.46%) and 10 were underweight (4.98%). The mean BMI was 24.56. Melanomas were mainly acral melanoma subtypes (61.69%).

The mean Breslow thickness was 4.17 mm. Patients with higher Breslow thickness (above 2 mm) accounted for 45.27%. There was no difference in distribution of Breslow thickness in different BMI groups. 37.81% of the cases had tumor ulceration. Patients fell into the following cancer stages; stage 0 (7.46%), stage I (14.43%), stage II (34.32%), stage III (18.91%), stage IV (22.39%) respectively. Of all patients, the local recurrence rate was 8.46%, and 47.76% with distant metastasis. The five-year mortality rates were 49.25%. The mean survival was 56 months. The distribution of mean survival according to BMI categories was as follows: 51.9 months for underweight, 50.6 months for normal weight, 61.9 months for overweight, and 65.5 months for obesity. (Table 1)

Table 1 Clinical Characteristic

The univariate analysis of overall survival between different variables and melanoma subtypes respectively was conducted. As shown in Table 2, older age (≥ 65 years old), male sex, advanced Breslow thickness stage (T3 and T4) and tumor ulceration were risk factors of worse overall survival rates in both cutaneous melanoma and AM. Alcohol consumption and tobacco use were not associated with impacting overall survival of melanoma. (Table 2)

Table 2 Univariate Analysis with Respect to Overall Survival of Melanoma in CM and ALM Subtype

In adjusted multivariable analysis of overall survival between different variables and melanoma subtypes, older age (≥ 65 years old) and male were risk factors of worse overall survival rates in both cutaneous melanoma and AM. Interestingly, overweight showed a protective relationship with both cutaneous melanoma (CM) and AM (P value < 0.05). (Table 3)

Table 3 Multivariate Analysis with Respect to Overall Survival of Melanoma in CM and ALM Subtype

We found that when comparing overweight individuals to those with normal BMI or underweight respectively, the hazard ratio decreased. ; This means that the risk of a negative outcome was lower for overweight individuals. The overall survival rates were also higher in the overweight individuals. This trend was observed both for cutaneous and AM outcomes. However, for underweight and obese individuals, while there were trends suggesting worse outcomes, we did not find statistically significant differences. (Table 4)

Table 4 HR for the Association of BMI and Overall Survival

The overall survival rates of included cutaneous melanomas participants in different BMI groups are shown in Figure 1. The mean overall survival for the different BMI groups were: 108.6 months for normal weight, 64.7 months for underweight, 128.2 months for overweight and 82.1 months for obese. Only overweight individuals showed significant difference from normal weight individuals and its hazard ratio was 0.475 (CI: 0.309–0.728).

Figure 1 Estimated overall survival of patients with cutaneous melanoma based on BMI category.

We re-categorized participants into 2 groups by non-excess body weight (BMI<25) and excess body weight (BMI≥25). As shown, individuals with non-excess body weight and excess body weight had mean overall survival of 107 and 114.8 respectively and a hazard ratio 0.563 (CI: 0.377–0.842), which indicated a better prognosis of cutaneous melanomas in individuals with excess body weight compared to individuals without non-excess body weight. (Figure 2)

Figure 2 Estimated overall survival of patients with cutaneous melanoma based on whether BMI ≥25 (overweight and obesity).

We further divided these 201 patients into two groups, AM and non-AM, and conducted survival analysis based on whether they exceeded a BMI of 25 or not. Our findings revealed that there were no significant differences in overall survival. (Figure 3)

Figure 3 Estimated overall survival of patients according to ALM and non-ALM group based on BMI≥25 (A) and BMI<25 (B).

Abbreviation: ALM = acral lentiginous melanoma.

Discussion

The rising incidence of life-threatening acral melanoma in Asia demands investigation into its cause in order to prevent the disease.10,25 The association between obesity and malignancy of many different organs has been reported previously, including for endometrial, breast, ovarian, prostate, liver, gallbladder, kidney and colon cancer.26 Currently, the correlation between melanoma and obesity is inconclusive. Some studies have indeed pointed out that obese patients might have better survival rates after receiving melanoma treatment, a phenomenon known as the “obesity paradox.” This refers to the situation where obesity appears to be associated with better outcomes in certain cancers or diseases, even though obesity is generally considered a negative health factor.21,27 This study aims to understand the association between obesity and melanoma while highlighting its primary outcome (The overall survival).

A large-scale study on more than 90,000 adults conducted in the United States in 2003 found that higher BMI levels did not increase the mortality rate from melanoma in males or females.28 Among 340 Italian melanoma patients with an average Breslow thickness of 0.4 mm, the prognosis was found to be similar between normal weight patients and those who are overweight or obese.29 Hardie CM et al reported a recent analysis of the Leeds Melanoma Cohort, with a median follow-up of 6.7 years, found that BMI was not linked to overall survival or melanoma-specific survival.30 Additionally, a study of the Leeds Melanoma Cohort, comprising 2,182 melanoma patients, from the United Kingdom in 2015 revealed that overweight individuals exhibited better prognoses than normal weight individuals after adjustment for age and sex, and after further adjustment for site and Breslow thickness.31 Contrarily, a multicenter study in Korea suggested that a BMI greater than 23 may be associated with disease metastasis and shorter overall survival (OR=2.10 [CI 1.2–3.6], P value=0.033).32 Besides overall survival, obesity appeared to be a clinical independent risk factor of thicker cutaneous melanoma, which increased severity of cutaneous melanomas.19 A possible explanation put forth was the “Obesity Paradox”. Wang Z et al33 shows that obesity accelerates immune aging, encourages tumor growth, and causes T cell dysfunction via the PD-1 pathway, partially influenced by leptin. Surprisingly, despite these negative effects, obesity improves the effectiveness of PD-1/PD-L1 blockade, suggesting that it could serve as a potential biomarker for specific cancer immunotherapies.34 The authors also highlighted a paradoxical relationship where obesity worsens immune dysfunction and tumor progression but enhances anti-tumor responses and survival through checkpoint blockade.29,35

In our study, overweight was observed to be an independent protective factor for both cutaneous and AM and have better outcomes in overall survival rates. The mean overall survival of overweight individuals was 128.2 months (108.6, 64.7 and 82.1 months in normal, underweight and obesity individuals) and had 0.475 in hazard ratio (CI: 0.309–0.728). Interestingly, we found no significant differences between obesity and Breslow thickness, a well-established prognostic factor of melanoma, which was contrary to previous study from Korea.32

Possible explanations for our findings include that research have found that obese melanoma patients may have higher survival rates after receiving certain immunotherapies, such as PD-1 inhibitors.27,36 Several mechanisms could potentially elucidate this phenomenon. Firstly, obesity has been associated with alterations in immune system functionality, which may modify the patient’s response to immunotherapy.34 Secondly, individuals with higher adiposity may possess greater energy reserves, potentially ameliorating the adverse effects of treatment-related anorexia or cachexia.37 Additionally, adipose tissue secretes various adipokines and cytokines, which could play a role in modulating inflammatory responses and, by extension, influence the efficacy of immunotherapeutic agents.38 Moreover, the pharmacokinetics of drugs can vary with body composition; the increased adipose tissue in obese patients might affect the distribution and metabolism of administered immunotherapies, thereby impacting therapeutic outcomes.38 Finally, it is also plausible that the chronic low-grade inflammation observed in obesity could interact synergistically with the mechanisms of action of PD-1 inhibitors, enhancing their anti-tumor activity.34 Further studies are warranted to explore these hypotheses and fully understand the relationship between obesity and melanoma patient outcomes in the context of immunotherapy. However, these findings do not mean that obesity is a protective factor. Obesity is still associated with numerous health issues, including other types of cancer and metabolic diseases. The impact of obesity on melanoma treatment requires further research to understand its underlying biological mechanisms.

Biological and genetic mechanisms play significant roles in understanding the impact of obesity on various diseases. Adipose tissue, in particular, has been identified as a key player in altering both systemic and microenvironmental factors through the endocrine or paracrine pathways.39 Several studies have shown, to better understand the development of melanoma in relation to obesity, it is crucial to investigate the role of the activated PI3K/Akt and the MAPK pathway, which can be activated by mutations in BRAF.39,40 Additionally, specific genetic factors have been found to be associated with the severity of certain diseases. Research has shown a strong correlation between the frequency of the IGF-1(CA)19 repeat and the severity of melanoma, as measured by the Breslow index.41,42 Furthermore, the presence of the C allele in the rs17782313 single nucleotide polymorphism (SNP) within the melanocortin-4 receptor has been linked to increased body mass index and poorer overall survival.33 These findings highlight the intricate relationship between biological and genetic factors and their impact on disease outcomes, providing valuable insights into potential avenues for further research and therapeutic interventions. By analyzing the biological and genetic aspects, we can examine the repeatability of IGF-1 and the SNPs of obesity-related genes. Such analyses can offer us valuable insights into the transformation of obesity’s impact on diseases, enabling us to develop tools for treatment and prevention.

Obesity is influenced by numerous complex factors, many of which were not fully accounted for in this retrospective nature and association study. Additionally, the limited number of cases and the incomplete availability of data from a single center may not accurately represent the entire Asian population. Further, BMI, a widely-used tool since it was first introduced in the 19th century, did not differentiate between muscle and fat tissue or provide information about the distribution of fat tissue, whether it is central, peripheral, or around target organs.43 Its accuracy is also limited for older adults and postmenopausal women.44 However, currently, BMI can still serve as a marker that partially reflects biological genetic mechanisms, as well as lifestyle and external environmental factors. Other feasible measurement methods for assessing fat distribution include hip circumference, waist circumference, waist-to-height ratio, and waist-to-hip ratio. These alternative measures provide additional insights into the distribution of fat tissue and can be utilized alongside BMI to obtain a more comprehensive understanding of an individual’s body composition. In order to enhance the evaluation of obesity, it is advisable to explore more suitable assessment methods such as bioelectrical impedance analysis (BIA), air displacement plethysmography (ADP), and dual-energy x-ray absorptiometry (DXA). Furthermore, it is important to investigate the molecular analysis of the relationship between obesity and melanoma. Such analysis can provide valuable insights into the intricate interplay between obesity and melanoma, potentially uncovering novel therapeutic targets and strategies for managing and preventing both conditions.

Future studies that consider a more comprehensive range of factors and involve diverse populations are required to provide a more robust understanding of the relationship between obesity and cutaneous melanomas.

Conclusion

In our study, we observed that melanoma patients with excess body weight had better survival outcomes compared to those with normal or underweight status. Additionally, no significant differences were found between AM and non-AM subtypes in relation to body weight impacting overall survival. Further investigation is needed to better understand the relationship between obesity and melanoma, including taking into account various factors such as genetic predisposition, tumor biology, and treatment responses. Such research endeavors will contribute to a more comprehensive understanding of the impact of obesity on melanoma prognosis and guide future therapeutic strategies.

Abbreviations

CM, Cutaneous melanoma; AM, Acral melanoma; ALM, Acral lentiginous melanoma; LM, lentigo maligna; melanoma; SSM, superficial spreading melanoma; BMI, Body mass index; ANOVA, Analysis of Variance; KM, Kaplan-Meier; survival analysis; OR, Odds ratio; CI, Confidence interval; HR, Hazard ratio; SNPs, Single nucleotide polymorphisms; BIA, Bioelectrical impedance analysis; ADP, Air displacement plethysmography; DXA, Dual-energy x-ray absorptiometry; SD, standard deviation.

Data Sharing Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics Approval and Consent to Participate

The Ethics Committee of Taipei Veterans General Hospital approved the present study (approval no. IRB‑2021‑05-002AC; IRB‑2024-07-001BC). This study only collected clinical medical records of patients without gathering any personal identifying information, and all data were anonymized. Approval for a waiver of informed consent was obtained from the ethics committee, as the waiver did not negatively impact the rights or welfare of the research subjects. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This study was supported by a grant (No. V113B-006) from Taipei Veterans General Hospital, Taiwan; a grant (MOST 113-2314-B-075-020) from the Ministry of Science and Technology, Taiwan; a grant (MLCF_V113_A11307) from Melissa Lee Cancer Foundation, Taiwan.

Disclosure

The authors report no conflicts of interest in this work.

References

1. Strashilov S, Yordanov A. Aetiology and pathogenesis of cutaneous melanoma: current concepts and advances. Int J Mol Sci. 2021;22(12):6395. doi:10.3390/ijms22126395

2. Chiu YJ, Yang JS, Tsai FJ, et al. Curcumin suppresses cell proliferation and triggers apoptosis in vemurafenib‐resistant melanoma cells by downregulating the EGFR signaling pathway. Environ Toxicol. 2022;37(4):868–879. doi:10.1002/tox.23450

3. Chen K-C, Chu P-Y, Li C-Y, Wang T-H, Chiu Y-J. Diagnostic value of 18F-fluoro-2-deoxyglucose positron emission tomography/computed tomography imaging in acral melanoma–predominant Asian patients. J Chin Med Assoc. 2023;86(11):975–980. doi:10.1097/JCMA.0000000000001002

4. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA. 2021;71(3):209–249. doi:10.3322/caac.21660

5. Chu P-Y, Chen Y-F, Li C-Y, Wang T-H, Chiu Y-J, Ma H. Influencing factors associated with lymph node status in patients with cutaneous melanoma: an Asian population study. J Chin Med Assoc. 2023;86(1):72–79. doi:10.1097/JCMA.0000000000000809

6. Chang J. Cutaneous melanoma: Taiwan experience and literature review. Chang Gung Med J. 2010;33(6):602–612.

7. Zhang N, Wang L, Zhu G, et al. The association between trauma and melanoma in the Chinese population: a retrospective study. J Eur Acad Dermatol Venereol. 2014;28(5):597–603. doi:10.1111/jdv.12141

8. Richard MA, Grob JJ, Avril MF, et al. Delays in diagnosis and melanoma prognosis (I): the role of patients. Int J Cancer. 2000;89(3):271–279. doi:10.1002/1097-0215(20000520)89:3<271::AID-IJC10>3.0.CO;2-7

9. Huang R, Zhao M, Zhang G, et al. Trauma plays an important role in acral melanoma: a retrospective study of 303 patients. Cancer Med. 2024;13(7):e7137. doi:10.1002/cam4.7137

10. Chiu YJ, Li CY, Wang TH, Ma H, Chou TY. Comparative transcriptomic analysis reveals differences in gene expression and regulatory pathways between nonacral and acral melanoma in Asian individuals. J Dermatol. 2024;51(5):659–670. doi:10.1111/1346-8138.17187

11. Sheen YS, Tan KT, Tse KP, et al. Genetic alterations in primary melanoma in Taiwan. Br J Dermatol. 2020;182(5):1205–1213. doi:10.1111/bjd.18425

12. Chiu YJ, Weng HY, Lin YY, et al. Genomic profiling with whole‐exome sequencing revealed distinct mutations and novel pathways in Asian melanoma. J Dermatol. 2022;49(12):1299–1309. doi:10.1111/1346-8138.16579

13. Bradford PT, Goldstein AM, McMaster ML, Tucker MA. Acral lentiginous melanoma: incidence and survival patterns in the United States, 1986-2005. Arch Dermatol. 2009;145(4):427–434. doi:10.1001/archdermatol.2008.609

14. World Health Organization. Obesity and overweight fact sheet; 2006.

15. Wu S-Y, Lee S-C, Yeh N-H, et al. Dietary characteristics of elders with frailty and with mild cognitive impairment: cross-sectional findings and implications from the nutrition and health survey in Taiwan 2014–2017. Nutrients. 2022;14(24):5216. doi:10.3390/nu14245216

16. Greenlee H, Unger JM, LeBlanc M, Ramsey S, Hershman DL. Association between body mass index and cancer survival in a pooled analysis of 22 clinical trials. Cancer Epidemiol Biomarkers Prev. 2017;26(1):21–29. doi:10.1158/1055-9965.EPI-15-1336

17. Kroenke CH, Neugebauer R, Meyerhardt J, et al. Analysis of body mass index and mortality in patients with colorectal cancer using causal diagrams. JAMA Oncol. 2016;2(9):1137–1145. doi:10.1001/jamaoncol.2016.0732

18. Albiges L, Hakimi AA, Xie W, et al. Body mass index and metastatic renal cell carcinoma: clinical and biological correlations. J Clin Oncol. 2016;34(30):3655–3663. doi:10.1200/JCO.2016.66.7311

19. Skowron F, Bérard F, Balme B, Maucort‐Boulch D. Role of obesity on the thickness of primary cutaneous melanoma. J Eur Acad Dermatol Venereol. 2015;29(2):262–269. doi:10.1111/jdv.12515

20. Sergentanis TN, Antoniadis AG, Gogas HJ, et al. Obesity and risk of malignant melanoma: a meta-analysis of cohort and case–control studies. Eur J Cancer. 2013;49(3):642–657. doi:10.1016/j.ejca.2012.08.028

21. Dobbins M, Decorby K, Choi BC. The association between obesity and cancer risk: a meta‐analysis of observational studies from 1985 to 2011. Int Scholarly Res Notices. 2013;2013(1):680536.

22. Samanic C, Chow W-H, Gridley G, Jarvholm B, Fraumeni JF. Relation of body mass index to cancer risk in 362,552 Swedish men. Cancer Causes Control. 2006;17:901–909. doi:10.1007/s10552-006-0023-9

23. Præstegaard C, Kjær SK, Christensen J, Tjønneland A, Halkjær J, Jensen A. Obesity and risks for malignant melanoma and non-melanoma skin cancer: results from a large Danish prospective cohort study. J Investig Dermatol. 2014;135(3):901–904. doi:10.1038/jid.2014.438

24. Smith LK, Arabi S, Lelliott EJ, McArthur GA, Sheppard KE. Obesity and the impact on cutaneous melanoma: friend or foe? Cancers. 2020;12(6):1583. doi:10.3390/cancers12061583

25. Chen KC, Wang TH, Li CY, Chiu YJ. The diameter of cutaneous melanoma serves as a prognostic indicator for survival among acral‐melanoma predominant East Asian patients. World J Surg. 2024;48(7):1692–1699. doi:10.1002/wjs.12192

26. Bandera EV, Fay SH, Giovannucci E, et al. The use and interpretation of anthropometric measures in cancer epidemiology: a perspective from the world cancer research fund international continuous update project. Int J Cancer. 2016;139(11):2391–2397. doi:10.1002/ijc.30248

27. McQuade JL, Daniel CR, Hess KR, et al. Association of body-mass index and outcomes in patients with metastatic melanoma treated with targeted therapy, immunotherapy, or chemotherapy: a retrospective, multicohort analysis. Lancet Oncol. 2018;19(3):310–322. doi:10.1016/S1470-2045(18)30078-0

28. Calle EE, Rodriguez C, Walker-Thurmond K, Thun MJ. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of US adults. N Engl J Med. 2003;348(17):1625–1638. doi:10.1056/NEJMoa021423

29. Moliterni E, Paolino G, Veronese N, et al. Prognostic correlation between vitamin D serological levels, body mass index and clinical-pathological features in melanoma patients. GIORNALE ITALIANO DI DERMATOLOGIA E VENEREOLOGIA. 2018;153(5):732–733. doi:10.23736/S0392-0488.17.05652-8

30. Hardie C, Elliott F, Chan M, Rogers Z, Bishop D, Newton-Bishop J. Environmental exposures such as smoking and low vitamin D are predictive of poor outcome in cutaneous melanoma rather than other deprivation measures. J Invest Dermatol. 2020;140(2):327–337.e322. doi:10.1016/j.jid.2019.05.033

31. Newton‐Bishop JA, Davies JR, Latheef F, et al. 25‐Hydroxyvitamin D2/D3 levels and factors associated with systemic inflammation and melanoma survival in the Leeds Melanoma Cohort. Int J Cancer. 2015;136(12):2890–2899. doi:10.1002/ijc.29334

32. Kim JE, Chung BY, Sim CY, et al. Clinicopathologic features and prognostic factors of primary cutaneous melanoma: a multicenter study in Korea. J Korean Med Sci. 2019;34(16). doi:10.3346/jkms.2019.34.e126

33. Wang Z, Aguilar EG, Luna JI, et al. Paradoxical effects of obesity on T cell function during tumor progression and PD-1 checkpoint blockade. Nature Med. 2019;25(1):141–151. doi:10.1038/s41591-018-0221-5

34. Pasquarelli-do-Nascimento G, Machado SA, de Carvalho JMA, Magalhães KG. Obesity and adipose tissue impact on T-cell response and cancer immune checkpoint blockade therapy. Immunother Adv. 2022;2(1):ltac015. doi:10.1093/immadv/ltac015

35. Caraban BM, Aschie M, Deacu M, et al. A narrative review of current knowledge on cutaneous melanoma. Clin Pract. 2024;14(1):214–241. doi:10.3390/clinpract14010018

36. Roccuzzo G, Moirano G, Fava P, Maule M, Ribero S, Quaglino P Obesity and immune-checkpoint inhibitors in advanced melanoma: a meta-analysis of survival outcomes from clinical studies. Paper presented at: Seminars in Cancer Biology; 2023.

37. Vaughan VC, Martin P, Lewandowski PA. Cancer cachexia: impact, mechanisms and emerging treatments. J Cachexia Sarcopenia Muscle. 2013;4:95–109. doi:10.1007/s13539-012-0087-1

38. Clemente-Suárez VJ, Redondo-Flórez L, Beltrán-Velasco AI, et al. The role of adipokines in health and disease. Biomedicines. 2023;11(5):1290.

39. Chen J, Chi M, Chen C, Zhang XD. Obesity and melanoma: exploring molecular links. J Cell Biochem. 2013;114(9):1955–1961. doi:10.1002/jcb.24549

40. Sharma SD, Katiyar SK. Leptin deficiency-induced obesity exacerbates ultraviolet B radiation-induced cyclooxygenase-2 expression and cell survival signals in ultraviolet B-irradiated mouse skin. Toxicol Appl Pharmacol. 2010;244(3):328–335. doi:10.1016/j.taap.2010.01.010

41. Santonocito C, Paradisi A, Capizzi R, et al. Insulin-like growth factor I (CA) repeats are associated with higher melanoma’s Breslow index but not associated with the presence of the melanoma. A pilot study. Clin Chim Acta. 2008;390(1–2):104–109. doi:10.1016/j.cca.2008.01.006

42. Capoluongo E. Insulin-like growth factor system and sporadic malignant melanoma. Am J Pathol. 2011;178(1):26–31. doi:10.1016/j.ajpath.2010.11.004

43. Pray R, Riskin S. The history and faults of the body mass index and where to look next: a literature review. Cureus. 2023;15(11). doi:10.7759/cureus.48230

44. Banack HR, Wactawski-Wende J, Hovey KM, Stokes A. Is BMI a valid measure of obesity in postmenopausal women? Menopause. 2018;25(3):307–313. doi:10.1097/GME.0000000000000989