Skip to main content
NCBI home page
Dermatology Practical & Conceptual logoLink to Dermatology Practical & Conceptual
. 2021 Oct 1;11(4):e2021106. doi: 10.5826/dpc.1104a106

Body Mass Index and Melanoma Prognosis

Nicoletta Cassano 1,2, Stefano Caccavale 3,✉, Gino A Vena 1,2, Giuseppe Argenziano 3
PMCID: PMC8480463  PMID: 34631264

Abstract

Introduction

Obesity has been suggested as a risk factor in the progression of malignancies, including melanoma. Most studies defined obesity using body mass index (BMI), although the index is considered an imperfect measure of body composition.

Objective

The aim of this article is to examine whether BMI can impact on the prognosis of cutaneous melanoma, regardless of anti-tumor therapy. The relationship between BMI and specific prognostic factors in melanoma patients has been reviewed.

Methods

Literature search was conducted on PubMed using the terms “melanoma” and “body mass index” or “obesity”. We selected articles, published up to 30 November 2020, examining the prognostic aspects of melanoma. Articles evaluating the risk and incidence of melanoma were excluded as well as studies regarding morbidity and complications following surgical procedures, or those performed in metastatic melanoma patients treated with anti-tumor therapies.

Results

Mixed results have emerged from studies assessing the clinical outcomes in melanoma patients in relation to BMI. More consistent data seem to support the relationship between BMI and Breslow thickness.

Conclusions

Studies that focus specifically on the link between obesity and melanoma prognosis are limited; further research is needed to deepen our knowledge on this link.

Keywords: cutaneous melanoma, body mass index, Breslow thickness, obesity

Introduction

There is a growing interest in exploring the relationship between cancer and anthropometric measures, including body mass index (BMI). Excess body weight, accounting for both overweight (BMI within the range of 25–29.9 kg/m2) and obesity (BMI≥30 kg/m2), has notably increased worldwide over the last decades and has been associated with a higher risk for cancer of several anatomic sites [1].

Obese status is characterized by the occurrence of systemic and tissue processes that might influence malignancies, such as release of cytokines and hormones from adipose tissues, chronic low-grade inflammation, increased estrogen levels, insulin resistance and hyperinsulinemia [2–4]. Obesity has also been suggested to contribute to the risk and progression of cutaneous melanoma, whose major environmental risk factor is ultraviolet radiation (UV), especially as intermittent intense exposures. However, the analysis of the association between obesity and risk of melanoma has provided conflicting data so far [4,5].

Recent studies have shown that increased BMI might improve outcomes in melanoma patients treated with targeted therapy and immunotherapy, providing further hints on the phenomenon known as the “obesity paradox”, although a lack of consistency has emerged from the currently available results and the issue is still under debate [6–9].

The aim of this article is to examine whether BMI can impact on the prognosis of cutaneous melanoma, regardless of anti-tumor therapy. For this purpose, the relationship between BMI and specific prognostic factors in melanoma patients has been reviewed.

Methods

Articles in English published up to 30 November 2020 were obtained from the PubMed database. A literature search was conducted using the terms “melanoma” and “body mass index” or “obesity”. We collected full article copies that were considered potentially eligible, including review articles as appropriate. The reference lists of retrieved manuscripts were also checked to find other eligible papers. We selected articles focused on prognostic aspects of melanoma (e.g., mortality/survival, relapse, metastases, progression, and histologic prognostic factors). Articles investigating the risk and incidence of melanoma were excluded, as well as those on morbidity and complications after surgical procedures. Studies regarding patients with metastatic melanoma treated with anti-tumor therapies have also been excluded from our review process, as this topic was beyond the purposes of this manuscript and would deserve a separate wide discussion.

Results

Melanoma Outcomes

Only a limited number of studies have evaluated the survival rate and/or the risk of recurrence or progression in relation to BMI among melanoma patients. As previously specified, our analysis did not include studies assessing outcomes in patients with metastatic melanoma who received targeted therapy, immunotherapy, or chemotherapy.

No significant variations in the overall risk of mortality for melanoma according to BMI were detected in a prospective cohort study involving nearly 1.2 million UK women aged 50–64 years who were recruited into the Million Women Study during the period 1996–2001 and followed up, on average, for 5.4 years [10]. Similarly, a study on more than 900,000 adults in the USA showed no increased mortality rates from melanoma for higher categories of BMI in males or females [11].

In a total of 340 Italian melanoma patients (mean Breslow thickness=0.4 mm), prognosis was found to be similar in normal weight patients and in overweight/obese patients [12].

A recent analysis of the Leeds Melanoma Cohort, with a median follow-up length of 6.7 years, showed that BMI was not associated with overall and melanoma-specific survival [13].

The comparison of 131 relapsed melanoma patients with 147 non-relapsers reported no effect of BMI on the risk of relapse [14].

In a small study that found a correlation between serum levels of leptin and sentinel lymph node metastases in melanoma patients, the mean BMI was identical for the sentinel node-positive and sentinel node-negative groups, ruling out obesity as an explanation for higher leptin values in patients with positive sentinel nodes [15].

Instead, other findings seemed to indicate a variable influence of BMI on melanoma outcomes.

A study of the Leeds Melanoma Cohort, comprising 2,182 melanoma patients enrolled in the period 2001–2013, has revealed that BMI was not significantly associated with survival when it was treated as a continuous variable [hazard ratio (HR) 1.04 per 5 units, 95% confidence interval (CI) 0.91–1.18; P = 0.6)] [16]. Instead, overweight individuals had better survival than subjects with normal weight after adjustment for age and sex, and after further adjustment for site and Breslow thickness. The protective effect was not observed in obese patients. An analysis of data from participants in the same cohort previously showed that BMI was predictive of relapse even when corrected for Breslow thickness [17].

Increased BMI has been associated with worse survival in an USA investigation of 1,186 patients with surgically resected melanoma, 75% of whom had stage I or II disease [18]. Overweight patients showed a trend towards elevated risks of disease recurrence and death; such risks were significantly increased in obese patients (P < 0.05). However, outcome associations were weakened or lost their significance following adjustment for C-reactive protein (CRP).

In a retrospective analysis of 261 Korean patients with primary cutaneous melanoma, overweight and obesity (BMI>23 kg/m2) were significantly associated with the development of metastases [odds ratio (OR)=2.10, 95% CI 1.2–3.6] and with shorter overall survival (P = 0.033) [19]. It should be high-lighted that the cut-off values for the definition of overweight and obesity are lower for Asian populations as recommended by the World Health Organization (WHO), and in the Korean study overweight status was defined as a BMI of 23 to 24.9 kg/m2, while a BMI≥25 kg/m2 defined the obesity status [19,20].

Breslow Thickness and Other Histological Prognostic Factors

Some studies have investigated the relationship between BMI and Breslow thickness. The characteristics of the largest and most important studies are summarized in Table 1.

Table 1.

Principal Studies Exploring the Relationship Between BMI and Breslow Thickness: General Aspects and Characteristics of Melanoma Cases

Authors De Giorgi et al [21] Gandini et al [22] Skowron et al [23] Stenehjem et al [24]
Study type Retrospective caseseries study (single center, Florence, Italy) Hospital-based multicenter study (Italy) Cross-sectional study in a prospective cohort (single center, Valence, France) Prospective population-based cohort study; linkage to National Cancer Registry (Norway)
Study period Jan 1998–Jan 2009 Dec 2010–Dec 2013 May 2007–May 2010 1972–2014
Cases of primary melanoma examined 605
86.4% thin melanomas (including in situ melanomas)		 2738
50% thin melanomas; 29% very thick melanomas; 25% ulcerated melanomas; 1% with distant metastases; 13% with lymph node involvement		 427
65% thin melanomas; 17.6% very thick melanomas		 2570
53.4% thin melanomas; 23.7% very thick melanomas; 4% with regional metastases, 1% with distant metastases; 16% unspecified
Excluded cases Patients < 40 yrs of age (when stratifying by age, because of their low number) ALM, mucosal, in situ and retrospective melanomas In situ, recurrent, ocular, mucosal and metastatic melanomas Not histologically verified or retrospective melanomas
Gender 55% women; 45% men 49% women; 51% men 50% women; 50% men 44.6% women; 55.4% men
Age, yrs Mean 53.06 (SD 16.02) Median 55 Mean 57.74 (SD 16.1) Mean age at diagnosis 60
Height and weight At the first visit, measured by a physician Collected through a self-administered questionnaire Measured (information not further specified) Measured by trained staff
Mean BMI (SD), kg/m2 24.78 (4.09) Not reported 25.38 (4.61) 24.7 (3.3)
BMI categories, kg/m2 (%) <25 (58%); ≥25 (42%) <25 (47%); ≥25 (53%) <25 (49%); 25–29.9 (38%); ≥30 (13%) < 18.5; 18.5–22.9; 23–24.9; 25–27.4; 27.5–29.9; ≥30 (% not reported)
Main statistical and methodological information Effect of BMI on the risk of thick melanoma estimated in terms of OR using a logistic regression analysis.
Stratification for sex and age classes, with adjustment for age (linear) within each age class and histological subtype.
Breslow thickness stratified into two groups: thick and thin		 Multivariate analyses with Breslow thickness as the response variable.
Multivariate random effects models, with center as a random factor; multivariate logistic models, taking into account possible confounding factors (including age, gender, educational and professional level, phenotype, residence, season of diagnosis, speciality of diagnosing doctor).
Breslow thickness stratified into two groups: thin and thick, considering also very thick melanoma and additionally evaluating Breslow thickness as a continuous measure		 Univariate and multivariate analyses, accounting for significant clinical and histopathological features. Breslow thickness stratified in four groups following the AJCCMS, 7th Ed. Linear regression with loge-transformed Breslow thickness (relationship with Breslow thickness as a continuous outcome).
Adjustment for age at diagnosis, sex, ambient UV radiation of residence, average intensity of sunburns, occupational UV exposure, physical activity, education, smoking status, height.
Use of adjusted mean values of Breslow thickness (in mm) by restricted cubic splines in generalized linear regression models (shape of the associations with Breslow thickness).
Site of melanoma, % Not reported Not reported Trunk 48%; head and neck 15%; upper limbs 13%; lower limbs 24% Trunk 51%; head and neck 11%; upper limbs 12.5%; lower limbs 24%; not specified 1.5%
Histopathological subtype of melanoma SSM 89.8%; UM 1.15%; LMM 3.3%; NM 2.65%; ALM 1.8%; RM 1.3% Not reported SSM 62%; UM 17%; LMM 13.5%; NM 4%; ALM 3.5% SSM 63%; NM 19%; other 4%; not specified 14%
Breslow thickness (mm) Mean 0.87 (SD 1.07) Not reported Mean 1.36 mm (SD 2.47) Median 1.0 (IQR 0.6–2)
Open in a new tab

Thin melanoma = Breslow thickness ≤1 mm; thick melanoma = Breslow thickness > 1 mm; very thick melanoma = Breslow thickness > 2 mm

AJCCMS= American Joint Committee on Cancer Melanoma Staging; ALM= acral lentiginous melanoma; BMI= body mass index; IQR= interquartile range; LMM= lentigo maligna melanoma; NM= nodular melanoma; OR= odds ratio; RM= rare melanoma; SD= standard deviation; SSM= superficial spreading melanoma; UM= unclassifiable/unclassified melanoma; UV= ultraviolet

De Giorgi et al reported no association between over-weight status (BMI≥25 kg/m2) and the risk of thick melanoma (Breslow thickness more than 1 mm) in the total sample or men, whereas a trend towards association between BMI≥25 kg/m2 and the risk of thick melanoma was shown among women (OR=1.64, 95% CI 0.82–3.28), and especially post-menopausal women (OR=2.50, 95% CI 1.06–5.88) [21].

In the report by Gandini et al [22], BMI was independently identified as significantly associated with Breslow thickness. In the multivariate random effects model, median Breslow thickness was 1.2 for BMI≥25 kg/m2 versus 0.8 for BMI<25 kg/m2 (P = 0.0008), and the multivariate logistic model disclosed a significant association of higher BMI with thick melanoma [the comparison of BMI≥25 kg/m2 vs. BMI<25 kg/m2 produced an OR of 1.34 (95% CI 1.12–1.59; P = 0.001)].

Skowron et al reported that BMI≥30 kg/m2 was associated with the risk of higher Breslow thickness (OR=2.78, 95% CI 1.55–4.94; P = 0.001) [23]. In the multivariate analysis of significant clinical and histological criteria, these authors found that obesity had an increased risk of higher tumor thickness (OR=1.86, 95% CI 0.91–3.77), but without any statistical significance (P = 0.086). When considering only clinical features in the model, obesity was significantly associated with a risk of higher Breslow thickness (OR=2.33, 95% CI 1.21–4.49; P = 0.011). The clinical characteristics of melanoma, its topography and visibility were not associated with the distribution of BMI categories. Instead, melanoma subtypes were differently distributed according to BMI categories (P = 0.007), with superficial spreading, lentigo maligna, and unclassified melanomas mostly found in patients with normal BMI, acral lentiginous melanoma in preobese patients and nodular melanoma in the obese patients [23].

Following these publications, the study of Stenehjem et al was the first to model Breslow thickness as a continuous outcome in relation to anthropometric measures which were obtained prediagnostically [24]. Breslow thickness was found to be significantly increased with increasing values of BMI (Ptrend = 0.009). A BMI>30 kg/m2 was associated with significantly higher tumor thickness as compared to normal weight patients (geometric mean ratio 1.16, 95% CI 1.04–1.30). When melanomas were stratified by anatomical site and histological variants, significant positive trends were seen for continuous variables of BMI in trunk and lower limb melanomas and in superficial spreading melanomas, respectively, but not in melanomas localized in other sites or in other histological subtypes. The shape of the exposure–response curves indicated that mean Breslow thickness increased until a BMI of 29 kg/m2, then plateaued at a mean of approximately 2.5 mm before declining for the highest values. In addition, when Breslow thickness was examined as a dichotomous outcome according to BMI in overweight and postmenopausal women, as previously done by De Giorgi et al [21], Stenehjem et al did not confirm a significant association; however they did not stratify by menopausal status owing to the low number of postmenopausal participants at baseline [24].

The relationship between BMI and Breslow thickness has been examined in other investigations.

Fang et al enrolled 1,804 patients with melanoma from 1998 to 2008, and BMI information was available for 1,186 patients. They found that increased BMI was weakly associated with increased tumor thickness, and also with older age and increased log [CRP] [18].

In a retrospective study of 261 patients diagnosed with primary cutaneous melanoma in 7 Korean centers between 1997 and 2017, overweight and obesity statuses (BMI>23 kg/m2) were significantly associated with increased Breslow thickness [19]. A multivariate Cox’s proportional hazards analysis gave a HR value of 25.62 (95% CI 5.44–120.65; P < 0.001) for the association between Breslow thickness and BMI categories more than 25 kg/m2.

In 100 melanoma patients enrolled within days of their melanoma diagnosis in Brisbane, Australia, there was a positive association between BMI and Breslow thickness (OR 1.12, 95% CI 1.01–1.26; P = 0.04 per unit increase in BMI) [25].

In a total of 340 Italian patients with melanoma (mean Breslow thickness of 0.4 mm), a significant correlation between BMI and Breslow thickness (P < 0.01) was noted [12].

A recent analysis of the Leeds Melanoma Cohort has evidenced that BMI was independently associated with thicker melanomas [13].

There are few data regarding the association of BMI with other histological features that have a prognostic value.

Skowron et al, in their study focusing on Breslow thickness, observed that ulceration was more frequent in obese patients, although the trend was not significant [23]. Similarly, von Schuckmann et al noted that overweight/obese status was positively associated with ulcerated melanoma, but, again, not significantly [26].

The evaluation of the Leeds Melanoma Cohort showed that higher BMI was associated with ulceration, in the univariable analysis, but this association did not persist in the multivariable analysis. Ulceration was also associated with lower vitamin D levels [16].

In an Italian cohort, a significant correlation between BMI and mitotic rate (P = 0.02) was seen [12].

In another Italian study, absence of tumor infiltrating lymphocytes, a finding that appears to predispose to metastatic melanoma, was detected more frequently in obese than in non-obese melanoma patients (OR=3.92, 95% CI 1.31–11.7; P = 0.010) [27].

Discussion

The relationship between obesity and melanoma appears to be complex.

There are conflicting findings regarding the association between obesity and risk of cutaneous melanoma [4,5]. Some cohort and case-control studies showed a variable positive correlation between obesity and melanoma risk, at least in men, while other studies found no convincing proofs of any association [5,10,28–32]. Caution should be used for the interpretation of such data. First, evidence for an association does not necessarily support a causal relationship. Moreover, methodological aspects differ between studies and could explain such divergences. It has been suggested to consider the possible effect of residual confounding by environmental and lifestyle risk factors, such as sunlight exposure, among obese and overweight subjects, as well as the variation of both BMI and other factors over time [29].

The assessment of the association between BMI and different clinical outcomes in melanoma patients (mortality/survival, risk for recurrence, sentinel node positivity, and metastases) yielded mixed results, with absence of any apparent influence according to some studies [10–16], better prognosis for overweight subjects but not for obese patients shown in one study [16], and worse outcomes for increased BMI values found by other authors [17–19]. The unfavourable outcome associations observed by Fang et al were weakened or lost their significance after adjustment for CRP, suggesting that elevated BMI can affect melanoma progression through mechanisms related to metabolic syndrome and/or chronic systemic inflammation, as indicated by CRP concentration [18].

Various reports have highlighted the link between BMI and Breslow thickness [12,13,18,19,21–25], a well-established prognostic factor of cutaneous melanoma [33].

A great part of the literature exploring the obesity-melanoma connection is based on studies that adopted BMI levels to define obesity. Nevertheless, BMI is thought to be an imperfect measure of body composition that is not able to differentiate between muscle and adipose tissues or to provide information on the distribution of adipose tissues, whether central, peripheral or in the context or proximity of target organs [2,34]. It is increasingly accepted that other parameters (eg, hip circumference, waist circumference, waist-to-height ratio and waist-to-hip ratio) may more accurately reflect body fat distribution. Furthermore, BMI can be a less accurate marker of adiposity among older people, due to the natural trends toward reduction in height, loss of muscle and increase of adipose tissue in ageing, especially in post-menopausal women [2]. Regardless of the above-mentioned limitations and the need of further studies specifically designed to overcome such limitations, BMI may be interpreted as a marker reflecting, at least partially, the effect of genetic and biological mechanisms, as well as lifestyle and environmental factors.

The biological mechanisms underlying the obesity-cancer link seem to be intricate and are still unclear. Ever-growing evidence supports the involvement of adipose tissue in tumor development and progression via endocrine and/or paracrine pathways, secreting a variety of molecules that alter systemic and local microenvironments [1]. The obesity-related dysfunctional adipose tissue and the active cross talk between adipocytes and melanoma cells can contribute to melanoma aggressiveness and progression through the release of pro-inflammatory, pro-angiogenic and lymphangiogenic factors, as well as extracellular matrix remodelling molecules, fatty acids, and probably other substances contained into the adipocyte exosomes [4,35–40].

The obesity-related changes include a chronic state of low-grade inflammation, adipokine imbalances, elevated levels of growth factors, and hormones, such as insulin, insulin-like growth factor (IGF)-1, and estrogens [1,3]. The cytokine profile of adipose tissue includes specific adipokines that may interfere with cellular processes by acting on signaling pathways, such as PI3K/Akt, MAPK, and JAK/STAT [41]. In obesity, adipocytes produce less adiponectin, that has anti-inflammatory and anti-neoplastic effects, but more leptin, that can contribute to melanoma growth and metastases [4,5,15].

Experimental findings suggest the association between obesity and aggressive tumor biology with a “meta-inflammatory” state, increased immune aging and T cell dysfunction [7].

A direct role of obesity on melanoma growth and progression has been documented by investigations in animal models. Diet-induced obesity has been demonstrated to increase melanoma progression in mice [42], while controlling obesity has proved to reverse the effect on melanoma progression [43].

The association between obesity and melanoma might be conditioned by many other factors, such as genetic mechanisms and insulin resistance, as well as the increased body surface, gut microbiota dysbiosis, and decreased levels of vitamin D [5,29,44,45].

Several data were suggestive of an inverse association between vitamin D serum levels and melanoma thickness at diagnosis [17,25,45,46]. A recent study reported that BMI and low vitamin D levels were independently associated with thicker tumors [13]. Moreover, Moreno-Arrones et al, while registering decreased vitamin D serum levels at melanoma diagnosis, described a significant association of this finding with both tumor mitotic rate and ulceration and a borderline association with Breslow thickness and BMI [47].

Genetic mechanisms have also been implicated, although the available data are still inconclusive. A genetic link between obesity and pigmentation has been proposed, as well as the role of obesity susceptibility loci in determining the risk and aggressiveness of melanoma, involving, for instance, certain vitamin D receptor polymorphisms and genetic variations in IGF-1 or estrogen receptor pathways [5,45,48,49]. A strong association between Breslow index and the IGF-1(CA)19 repeat frequency was found (P < 0.001) in one study [50]. Fang et al investigated some BMI-associated single-nucleotide polymorphisms (SNPs) in relation with melanoma risk or outcome. In particular, the C allele in the rs17782313 SNP (within the melanocortin-4 receptor) was associated with increased BMI and poorer overall and melanoma-specific survival among patients with stage I/II melanoma, showing a trend towards the association with elevated CRP [18].

Beyond biological mechanisms underlying the relationship between BMI and melanoma thickness, Stenehjem et al tried to explain their results also based on behavioural mechanisms [24]. In particular, obesity and body dissatisfaction have been associated with reduced skin self-examination and consequently with the risk of delayed detection of lesions, whereas the decline in adjusted mean Breslow thickness for the highest anthropometric values observed by those authors in their study might reflect a less sun-seeking attitude. Moreover, according to Skowron et al [23], obese people could be at higher risk of hidden melanomas because of their larger skin surface and folds or may be reluctant to undergo dermatological examinations. Nevertheless, the results of the study performed by Skowron et al did not confirm any association between BMI categorization and either the visibility of melanoma or the mode of melanoma identification [23].

Conclusions

There are several hints suggesting the potential influence of obesity on malignancies, including melanoma. Most studies defined obesity based on BMI, although this is considered an imperfect measure of body composition. Mixed results have been obtained from studies assessing clinical outcomes in patients with melanoma in relation to BMI. More consistent data seem to support the relationship between BMI and Breslow thickness. Multiple biological and behavioural mechanisms might contribute to the effects of obesity on melanoma progression and outcome and some of these have been outlined, although the obesity-melanoma relationship deserves further investigations.

Footnotes

Funding: None.

Competing interests: The authors have no conflicts of interest to disclose.

Authorship: All authors have contributed significantly to this publication.

References

  • 1.Avgerinos KI, Spyrou N, Mantzoros CS, Dalamaga M, et al. Obesity and cancer risk: Emerging biological mechanisms and perspectives. Metabolism. 2019;92:121–135. doi: 10.1016/j.metabol.2018.11.001. [DOI] [PubMed] [Google Scholar]
  • 2.Bandera EV, Fay SH, Giovannucci E, et al. World Cancer Research Fund International Continuous Update Project Panel. 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. [DOI] [PubMed] [Google Scholar]
  • 3.Hopkins BD, Goncalves MD, Cantley LC, et al. Obesity and cancer mechanisms: Cancer metabolism. J Clin Oncol. 2016;34(35):4277–4283. doi: 10.1200/JCO.2016.67.9712. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Smith LK, Arabi S, Lelliott EJ, McArthur GA, Sheppard KE, et al. Obesity and the impact on cutaneous melanoma: Friend or foe? Cancers (Basel) 2020;12(6):1583. doi: 10.3390/cancers12061583. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Clement E, Lazar I, Muller C, Nieto L, et al. Obesity and melanoma: could fat be fueling malignancy? Pigment Cell Melanoma Res. 2017;30(3):294–306. doi: 10.1111/pcmr.12584. [DOI] [PubMed] [Google Scholar]
  • 6.McQuade J, Daniel C, 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. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Wang Z, Aguilar E, Luna J, et al. Paradoxical effects of obesity on T cell function during tumor progression and PD-1 checkpoint blockade. Nat Med. 2019;25(1):141–151. doi: 10.1038/s41591-018-0221-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Donnelly D, Bajaj S, Yu J, et al. The complex relationship between body mass index and response to immune checkpoint inhibition in metastatic melanoma patients. J Immunother Cancer. 2019;7(1):222. doi: 10.1186/s40425-019-0699-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Rutkowski P, Indini A, De Luca M, et al. Body mass index (BMI) and outcome of metastatic melanoma patients receiving targeted therapy and immunotherapy: a multicenter international retrospective study. J Immunother Cancer. 2020;8(2):e001117. doi: 10.1136/jitc-2020-001117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Reeves GK, Pirie K, Beral V, Green J, Spencer E, Bull D Million Women Study Collaboration. Cancer incidence and mortality in relation to body mass index in the Million Women Study: cohort study. BMJ. 2007;335(7630):1134. doi: 10.1136/bmj.39367.495995.AE. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Calle EE, Rodriguez C, Walker-Thurmond K, Thun MJ, et al. Over-weight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults. N Engl J Med. 2003;348(17):1625–1638. doi: 10.1056/NEJMoa021423. [DOI] [PubMed] [Google Scholar]
  • 12.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. G Ital Dermatol Venereol. 2018;153(5):732–733. doi: 10.23736/S0392-0488.17.05652-8. [DOI] [PubMed] [Google Scholar]
  • 13.Hardie CM, Elliott F, Chan M, Rogers Z, Bishop DT, Newton-Bishop JA, et al. 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;140:327–337.e2. doi: 10.1016/j.jid.2019.05.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Beswick S, Affleck P, Elliott F, et al. Environmental risk factors for relapse of melanoma. Eur J Cancer. 2008;44(12):1717–1725. doi: 10.1016/j.ejca.2008.05.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Oba J, Wei W, Gershenwald JE, et al. Elevated serum leptin levels are associated with an increased risk of sentinel lymph node metastasis in cutaneous melanoma. Medicine (Baltimore) 2016;95(11):e3073. doi: 10.1097/MD.0000000000003073. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.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. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Newton-Bishop JA, Beswick S, Randerson-Moor J, et al. Serum 25-hydroxyvitamin D3 levels are associated with Breslow thickness at presentation and survival from melanoma. J Clin Oncol. 2009;27(32):5439–5444. doi: 10.1200/JCO.2009.22.1135. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Fang S, Wang Y, Dang Y, et al. Association between body mass index, C-reactive protein levels, and melanoma patient outcomes. J Invest Dermatol. 2017;137(8):1792–1795. doi: 10.1016/j.jid.2017.04.007. [DOI] [PubMed] [Google Scholar]
  • 19.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):e126. doi: 10.3346/jkms.2019.34.e126. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.World Health Organization IOTF. The Asian-Pacific perspective: Redefining obesity and its treatment. Geneva: WHO Western Pacific Region; 2000. [Google Scholar]
  • 21.de Giorgi V, Gori A, Papi F, et al. Excess body weight and increased Breslow thickness in melanoma patients: a retrospective study. Eur J Cancer Prev. 2013;22(5):480–485. doi: 10.1097/CEJ.0b013e32835f3b5d. [DOI] [PubMed] [Google Scholar]
  • 22.Gandini S, Montella M, Ayala F, et al. Clinical National Melanoma Registry Group. Sun exposure and melanoma prognostic factors. Oncol Lett. 2016;11(4):2706–2714. doi: 10.3892/ol.2016.4292. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Skowron F, Bérard F, Balme B, Maucort-Boulch D, et al. 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. [DOI] [PubMed] [Google Scholar]
  • 24.Stenehjem JS, Veierød MB, Nilsen LT, et al. Anthropometric factors and Breslow thickness: prospective data on 2570 cases of cutaneous melanoma in the population-based Janus Cohort. Br J Dermatol. 2018;179(3):632–641. doi: 10.1111/bjd.16825. [DOI] [PubMed] [Google Scholar]
  • 25.Wyatt C, Lucas RM, Hurst C, et al. Vitamin D deficiency at melanoma diagnosis is associated with higher Breslow thickness. PLoS One. 2015;10(5):e0126394. doi: 10.1371/journal.pone.0126394. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.von Schuckmann LA, Smith D, Hughes MCB, et al. Associations of statins and diabetes with diagnosis of ulcerated cutaneous melanoma. J Invest Dermatol. 2017;137(12):2599–2605. doi: 10.1016/j.jid.2017.07.836. [DOI] [PubMed] [Google Scholar]
  • 27.Cauci S, Maione V, Buligan C, Linussio M, Serraino D, Stinco G, et al. BsmI (rs1544410) and FokI (rs2228570) vitamin D receptor polymorphisms, smoking, and body mass index as risk factors of cutaneous malignant melanoma in northeast Italy. Cancer Biol Med. 2017;14(3):302–318. doi: 10.20892/j.issn.2095-3941.2017.0064. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M, et al. Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet. 2008;371(9612):569–578. doi: 10.1016/S0140-6736(08)60269-X. [DOI] [PubMed] [Google Scholar]
  • 29.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. [DOI] [PubMed] [Google Scholar]
  • 30.Dobbins M, Decorby K, Choi BC, et al. The association between obesity and cancer risk: a meta-analysis of observational studies from 1985 to 2011. ISRN Prev Med. 2013:680536. doi: 10.5402/2013/680536. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Præstegaard C, Kjær SK, Christensen J, Tjønneland A, Halkjær J, Jensen A, et al. Obesity and risks for malignant melanoma and non-melanoma skin cancer: results from a large Danish prospective cohort study. J Invest Dermatol. 2015;135(3):901–904. doi: 10.1038/jid.2014.438. [DOI] [PubMed] [Google Scholar]
  • 32.Choi EK, Park HB, Lee KH, et al. Body mass index and 20 specific cancers: Re-analyses of dose-response meta-analyses of observational studies. Ann Oncol. 2018;29(3):749–757. doi: 10.1093/annonc/mdx819. [DOI] [PubMed] [Google Scholar]
  • 33.Gershenwald JE, Scolyer RA, Hess KR, et al. Melanoma staging: evidence-based changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA Cancer J Clin. 2017;67(6):472–492. doi: 10.3322/caac.21409. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.McQuade JL, Daniel CR, Davies MA, et al. Body-mass index and metastatic melanoma outcomes - Authors’ reply. Lancet Oncol. 2018;19(5):e227–e228. doi: 10.1016/S1470-2045(18)30266-3. [DOI] [PubMed] [Google Scholar]
  • 35.Kushiro K, Chu RA, Verma A, Núñez NP, et al. Adipocytes promote B16BL6 melanoma cell invasion and the epithelial-to-mesenchymal transition. Cancer Microenviron. 2012;5(1):73–82. doi: 10.1007/s12307-011-0087-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Lazar I, Clement E, Dauvillier S, et al. Adipocyte exosomes promote melanoma aggressiveness through fatty acid oxidation: a novel mechanism linking obesity and cancer. Cancer Res. 2016;76(14):4051–4057. doi: 10.1158/0008-5472.CAN-16-0651. [DOI] [PubMed] [Google Scholar]
  • 37.Coelho P, Almeida J, Prudêncio C, Fernandes R, Soares R, et al. Effect of adipocyte secretome in melanoma progression and vasculogenic mimicry. J Cell Biochem. 2016;117(7):1697–1706. doi: 10.1002/jcb.25463. [DOI] [PubMed] [Google Scholar]
  • 38.Robado de Lope L, Alcíbar OL, Amor López A, Hergueta-Redondo M, Peinado H, et al. Tumour-adipose tissue crosstalk: fuelling tumour metastasis by extracellular vesicles. Philos Trans R Soc Lond B Biol Sci. 2018;373(1737) doi: 10.1098/rstb.2016.0485. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Zhang M, Di Martino JS, Bowman RL, et al. Adipocyte-derived lipids mediate melanoma progression via FATP proteins. Cancer Discov. 2018;8(8):1006–1025. doi: 10.1158/2159-8290.CD-17-1371. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Clement E, Lazar I, Attané C, et al. Adipocyte extracellular vesicles carry enzymes and fatty acids that stimulate mitochondrial metabolism and remodeling in tumor cells. EMBO J. 2020;39(3):e102525. doi: 10.15252/embj.2019102525. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Chen J, Chi M, Chen C, Zhang XD, et al. Obesity and melanoma: exploring molecular links. J Cell Biochem. 2013;114(9):1955–1961. doi: 10.1002/jcb.24549. [DOI] [PubMed] [Google Scholar]
  • 42.Pandey V, Vijayakumar MV, Ajay AK, Malvi P, Bhat MK, et al. Diet-induced obesity increases melanoma progression: involvement of Cav-1 and FASN. Int J Cancer. 2012;130(3):497–508. doi: 10.1002/ijc.26048. [DOI] [PubMed] [Google Scholar]
  • 43.Malvi P, Chaube B, Pandey V, et al. Obesity induced rapid melanoma progression is reversed by orlistat treatment and dietary intervention: role of adipokines. Mol Oncol. 2015;9(3):689–703. doi: 10.1016/j.molonc.2014.11.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Antoniadis AG, Petridou ET, Antonopoulos CN, et al. Insulin resistance in relation to melanoma risk. Melanoma Res. 2011;21(6):541–546. doi: 10.1097/CMR.0b013e32834b0eeb. [DOI] [PubMed] [Google Scholar]
  • 45.Randerson-Moor JA, Taylor JC, Elliott F, et al. Vitamin D receptor gene polymorphisms, serum 25-hydroxyvitamin D levels, and melanoma: UK case–control comparisons and a meta-analysis of published VDR data. Eur J Cancer. 2009;45(18):3271–3281. doi: 10.1016/j.ejca.2009.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Fang S, Sui D, Wang Y, et al. Association of vitamin D levels with outcome in patients with melanoma after adjustment for C-reactive protein. J Clin Oncol. 2016;34(15):1741–1747. doi: 10.1200/JCO.2015.64.1357. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Moreno-Arrones OM, Zegeer J, et al. Decreased vitamin D serum levels at melanoma diagnosis are associated with tumor ulceration and high tumor mitotic rate. Melanoma Res. 2019;29:664–667. doi: 10.1097/CMR.0000000000000638. [DOI] [PubMed] [Google Scholar]
  • 48.Li X, Liang LM, Zhang MF, et al. Obesity-related genetic variants, human pigmentation, and risk of melanoma. Hum Genet. 2013;132(7):793–801. doi: 10.1007/s00439-013-1293-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.de Giorgi V, Sestini S, Gori A, et al. Polymorphisms of estrogen receptors: risk factors for invasive melanoma - a prospective study. Oncology. 2011;80(3–4):232–237. doi: 10.1159/000328321. [DOI] [PubMed] [Google Scholar]
  • 50.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):104–9. doi: 10.1016/j.cca.2008.01.006. [DOI] [PubMed] [Google Scholar]

Articles from Dermatology Practical & Conceptual are provided here courtesy of Mattioli 1885

RESOURCES