Introduction and Trends in Melanoma

In 2012, 9,180 individuals are estimated to die from melanoma in the United States [1]. As the most lethal form of skin cancer [2], the increasing incidence of cutaneous malignant melanoma (CMM) is an increasing burden to society [3]. As the fifth most common malignancy in men and sixth most common in women, CMM is expected to account for less than 5 % of all skin cancer diagnoses but will account for the vast majority of skin cancer deaths. Compared with all cancers, it remains one with a relatively high 5-year survival. Only prostate, thyroid, and testis cancer have better 5-year survival rates, whereas melanoma has a higher 5-year survival rate than 14 other malignancies reviewed [1].

The incidence of melanoma is growing more rapidly than nearly all other cancers in the United States [3]. In 2012, there will be an estimated 76,250 new cases of melanoma [1]. The incidence has been increasing steadily for the past 30 years, and since 2004, Caucasians have seen a 3 % increase each year [1]. A review of the Surveillance, Evaluation, and End Results (SEER) data found a similar increase in incidence to be further accentuated among young Americans, particularly amongst females aged 15–39 years [4]. A recent review of the population in Olmsted County, Minnesota, found a similar increase among young women aged 18–39 years, who saw an eightfold increase compared with the fourfold increase in young men [5]. However, this trend is extinguished among women after age 40 years, whereas incidence increases dramatically in men after this age [6]. Aside from behavioral factors (e.g., sunlamp use), hormonal influences have been posited to play a role in this finding [5, 6]. However, what is increasingly obvious is the complexity and heterogeneity of melanoma. Studies have shown an age-specific effect modification for gender, anatomic site, and histopathology [6].

Importantly, melanoma survival has steadily improved during the past few decades. Five-year survival has increased from 82 % to 91 % between 1979 and 2012 [1]. Arguably, the most important prognostic factor at time of CMM diagnosis remains tumor thickness, which unfortunately has not decreased in recent studies. The study from Olmsted County found that with time, there was a decrease in the level of invasion and stage of disease at time of diagnosis [5]. Although some may argue the undue influence of overdiagnosis of early lesions, the proportion of thick melanomas has remained relatively constant and it is possible that lesions are being identified early at a thin enough stage to be cured truly with surgical excision [6].

With the advent of newer therapeutic options, such as immunotherapies and targeted molecular therapies, progression-free survival has been shown to improve while the hope is that overall survival will soon follow. Both ipilimumab and vemurafenib have been investigated against dacarbazine and have been found to increase overall survival in metastatic melanoma [7]. Despite new developments in therapy, early detection and prevention will be the key factors to reduce the burden of CMM.

Economic Considerations

Whereas the burden of the loss of human life is one that is obvious, another burden that cannot be ignored is the economic cost of melanoma to the U.S. healthcare system. Unlike other malignancy diagnoses, the cost of melanoma is not as high at time of diagnosis, largely due to the outpatient nature of follow-up appointments and procedures [8]. However, when the cost of melanoma is focused on the period of time designated as the terminal phase (6 months before death), the cost of healthcare for the melanoma patient skyrockets and has been reported to cost as much as the cost for the care of a colorectal cancer patient [8]. Indeed, prior studies have quoted the cost spent during this 6-month terminal period to account for 90 % of the healthcare cost for any particular patient [9]. Undoubtedly, the cost of melanoma care will further increase with the use of newer targeted agents, not only because of drug charges, but also because of the management of complications and side effects now reported with these new treatment modalities (e.g., keratoacanthoma-like squamous cell carcinomas) [10].

Given the high cost that goes toward the care of the patient with advanced melanoma, it would stand to reason that early detection and prevention could be more cost effective; however, studies on the financial ramifications have not yet been instructive in this regard.

Risk Factors

Although a discussion of risk factors for CMM is important, it also is critical to differentiate behavioral versus heritable factors (Table 1). Clearly, there are complex interactions between the environment and genetics. We will begin our review of risk factors with those that are known physiologic risk factors.

Table 1 Summary of relative risks and odds ratios**
Full size table

Known Phenotypic Risk Factors

Nevi

A meta-analysis published in 2005 investigated the increased risk of CMM given a particular patient’s propensity to develop nevi, both common and atypical [11]. Case–control, cohort, and cross-sectional studies were included and reviewed. For common nevi, the meta-analysis found that the number a patient has is a risk factor for developing CMM. A dose–response pattern was seen with an increase in relative risk (RR) for developing CMM as a patient’s number of common nevi increased [11]. When those with 0–15 common nevi on the entire body were treated as baseline, the RR was reported to be 1.47 (1.36, 1.59) for patients with 16–40 common nevi, 2.24 (1.90, 2.64) for 41–60 common nevi, 3.26 (2.55, 4.15) for 61–80 nevi, 4.74 (3.44, 6.53) for 81–100 nevi, and finally 6.89 (4.63, 10.25) for patient with 101–120 common nevi [11]. When common nevi were only counted on arms, patients with 1–5 common nevi showed a RR of 1.44 (1.29, 1.6) compared with those without any nevi on the arms. The same dose response curve was exhibited when those with 5–10 common nevi on the arms showed a RR of 2.48 (1.9, 3.23), and those with 11–15 nevi had a RR of 4.82 (3.05, 7.62) [11].

When analyzing atypical nevi, a similar density-risk curve was demonstrated. Patients with a history of one atypical nevus showed a RR for developing CMM of 1.45 (1.31, 1.6) compared with those with no atypical nevi. Patients with two atypical nevi showed a RR of 2.1 (1.71, 2.54), with three a RR of 3.03 (2.23, 4.06), with four a RR of 4.39 (2.91, 6.47), and finally with five a RR of 6.36 (3.8, 10.33) [11].

A more recent meta-analysis performed in 2010 found that having more than 25 nevi also may be a risk factor for CMM diagnosis [12]. In this particular study, 42 % of CMM cases were associated with having over 25 nevi, with a population attributable fraction of 0.15 [12]. Unfortunately, because this was a meta-analysis, the studies did not uniformly perform subgroup analyses by age, gender, and skin type. Therefore, it is difficult to make conclusions about these subgroups.

Hair and Eye Color

A similar meta-analysis by the same group evaluated 37 studies that reported eye color and risk of melanoma [13]. Comparisons were made between different eye color groups and the “dark” eye color group. Blue eye color was found to have a RR of 1.47 (1.28, 1.69) compared with dark eye color for melanoma. For green eye color, the RR was reported as 1.61 (1.06, 2.45). Finally, for hazel, the RR was reported as 1.52 (1.26, 1.83). When all groups were combined as “fair eye color,” the RR for melanoma was 1.62 (1.44, 1.81) compared with “dark eye color.”[13]

As for hair color, 45 studies were reviewed and similarly to eye color, different hair colors were compared to “dark hair color” for RR for melanoma [13]. Red hair was found to have a RR of 3.64 (2.56, 5.37), blond hair a RR of 1.96 (1.41, 2.74), and light brown a RR of 1.62 (1.11, 2.34). When the blond, red, and light brown hair groups were collapsed into “light” hair color and compared with the “medium dark, brown” group, the RR of melanoma was 1.78 (1.63, 1.95).

Family History

A meta-analysis of 14 individual case–control studies evaluating the association of family history (defined as a first degree relative with the diagnosis of CMM) was performed. Those with a positive family history, compared with those without, had a RR of 1.74 (1.41, 2.14) for developing CMM [13].

Personal History of Nonmelanoma Skin Cancer

Multiple publications have explored the risk of malignancy after having a diagnosis of nonmelanoma skin cancer (NMSC). One systematic review explored the possible associations and cited both anecdotal evidence that those with NMSC seem to have an increased risk of other malignancies, as well as the conjecture that those with NMSC history may have higher levels of vitamin D secondary to sun exposure, perhaps eliciting a protective effect [14]. When dealing with the possible association with development of CMM, one would expect to see a positive association given the similar risk factors, namely fair skin and excessive sun exposure. Indeed, that is what was seen with a summary RR of 2.74 (2.49, 3.02) for developing CMM in the NMSC population compared with controls without a history of NMSC [14]. When further subdivided into type of NMSC, there was no large difference seen. In those with history of squamous cell carcinoma (SCC), the RR of CMM diagnosis was 2.84 (2.45, 3.29); for basal cell carcinoma (BCC) the RR was reported as 2.75 (2.39, 3.16). Similarly, the RR of CMM diagnosis after NMSC was similar across genders. In males, the RR was 2.73 (2.52, 2.96), and in females, RR was 2.61 (2.24, 3.05) [14]. It is worth noting that patients with NMSC may be scrutinized to a greater extent and therefore the apparent elevations in risk could result from a detection bias.

Childhood Cancer History

Having a history of cancer in childhood is a risk factor for subsequent malignancy [15]. Prior studies have reported the overall increased risk of subsequent malignancy to be sixfold. When a group of childhood cancer survivors were reviewed for subsequent CMM risk, the standardized incidence ratio (SIR) was found to be 2.42 (1.77, 3.23) [15]. The childhood cancer cases that preceded CMM diagnosis included soft tissue and bone sarcoma, leukemia, lymphoma, central nervous system malignancy, Wilm’s tumor, and neuroblastoma [15].

Parkinson’s Disease

A large systematic meta-analysis published in early 2010 reviewed the associations of Parkinson’s disease (PD) with various malignancies [16]. Among the reported malignancies was CMM, which showed that after evaluation of eight studies (which was unfortunately a small portion of available literature), the RR for patients with PD for the development of CMM was 1.56 (1.27, 1.91) [16]. Interestingly, melanoma was the only malignancy reviewed with an increased RR. In fact, overall, PD was found to be protective with a decrease of 27 % in the risk of cancer [16]. When CMM was taken out of the analysis, the protective effect increased to a 38 % difference. It seems that PD is a unique risk factor for CMM, as opposed to a protective factor for other malignancies studied. Many studies have posed that perhaps the relationship between CMM and PD may be in the opposite direction or perhaps it is a bidirectional relationship.

This association was further explored in a study published in the neurology literature 1 year later [17]. Fourteen papers were identified with 13 used for analysis. This study reports on the possible association between the two entities and attempts to explore the directionality of the association by subdividing the papers by temporal association [17]. Overall, the odds ratio (OR) for association of PD and CMM was reported as 2.11 (1.26, 3.54) [17]. When the papers were subdivided by temporal relationship, the statistically significant relationship was reported in cases where PD preceded CMM, where OR was 3.61 (1.49, 8.77). On the other hand, if CMM preceded PD, the OR was reported as 1.07 (0.62, 1.84) [17]. The authors pose that this loss of statistical significance is due to one study and, when removed, the OR increased to 1.44 (1.06, 1.96). Although it may be tempting to try to make inferences about possible causation, one should be careful in assuming this type of relationship as many of these studies are case–control studies, limiting our ability to infer a causal relationship. When the group was stratified by gender, statistical significance was seen in men, where the OR of the association was reported as 2.04 (1.55, 2.69). However, there was a lack of statistical significance in women, where the OR was 1.52 (0.85, 2.75) [17].

The evidence for the association of CMM with PD is less convincing. One concern regarding this potential relationship relates to the population that is most at risk for PD. As hair color has been associated with variable risks for PD, one could argue that perhaps the association of PD and CMM may actually be confounded by ethnicity [18]. Although speculative, the substantia nigra, which undergoes attrition in PD, is composed of highly melanized dopaminergic neurons and thus deficiencies in eumelanization or increases in pheomelanin may account for the predisposition to both melanoma and PD. As such, future studies will need larger sample sizes, more carefully designed and defined prospective designs, possibly culminating in more sophisticated meta-analyses.

Pregnancy and Hormones

A systematic review by the Gandini group sought to explore the possible association of hormonal factors with CMM, given the many case studies and anecdotal reports of CMM in the setting of pregnancy [19]. Thirty-six publications were reviewed to explore this possible association. Given the conjectured mechanism through hormonal mediators, the systematic review analyzed research that sought to find associations between hormone replacement therapy (HRT) or oral contraceptives (OC) with CMM. When pooled, the RR for those on OC for development of CMM was a RR of 1.04 (0.92, 1.18). For HRT, the RR was 1.16 (0.93, 1.44). The lack of statistical significant was similarly seen despite subgroup analysis of different time courses of these therapies [19]. This corroborates evidence published earlier regarding the lack of association between OC use and CMM [20].

There also has been no detectable association between CMM and other reproductive factors (e.g., age at menarche, evaluation of fertility, use of fertility drugs, parity, menopausal status, or age at menopause). There was a small statistically significant association of an increased 10 % risk found for women whose first pregnancy was at age 30 years or older compared with those whose first pregnancy was at age 20 years or younger [19]. This association, however, was found to have been possibly confounded by socioeconomic status (SES) [19].

Vitamin D

Multiple case control studies from the United Kingdom have explored the possible association of vitamin D receptor (VDR) single nucleotide polymorphisms (SNPs) with CMM. Of six potential VDR SNPs under investigation, one in particular showed a positive association with CMM after meta-analysis [21]. The T allele of the FokI polymorphism showed an OR of 1.19 (1.05, 1.35) for CMM. Conversely, a different VDR SNP was found to possibly be protective. The BsmI A allele was found to have an OR of 0.81 (0.72, 0.92) for CMM [21].

Mechanistically, the T allele of the FokI gene is known to produce an alternative start site at the 5’ end, which leads to a protein that is 3 amino acids longer (427 aa) than the wild type protein (424 aa). In vitro studies have found a less efficient interaction with certain transcription factors with the mutant 427 amino acid protein and could help explain why this T-allele of FokI also is associated with colon and breast cancers [21].

Notably, in terms of vitamin D intake, a recent study in 2009 reviewed data from the SEER database that compared CMM diagnosis between the population in the top quartile of vitamin D intake and the population in the bottom quartile of vitamin D intake. This study did not show any association between CMM risk and vitamin D intake [22].

Recently Uncovered Genetic Factors

High Risk Loci

Suspicion for a hereditary cause of melanoma arises in three main situations: when CMM diagnosis occurs at an early age, when there are multiple diagnoses of CMM on one side of the family, or when an individual has multiple diagnoses of primary CMM [23•]. In familial atypical multiple mole-melanoma (FAMMM) syndrome, patients are identified based on diagnosis of melanoma, as well numerous atypical appearing nevi [23•]. Based on linkage analysis performed on patients and families with this phenotype, germline mutation in CDKN2A were first identified in the context of hereditary melanoma [23•].

This gene can code for two distinct proteins through alternative splicing mechanisms. The CDKN2A locus includes four exons, which code for p16/Ink4 or p14/Arf. Both products function as potent tumor suppressors, which when mutated, enable uncontrolled cell division and tumor development. p16/Ink4 in particular, when mutated, also has been associated with pancreatic cancer. When p16/Ink4 is wild-type and fully functional, it binds Cdk4 and prevents it from phosphorylating retinoblastoma (Rb), another tumor suppressor [23•]. A heavily phosphorylated Rb will release E2F1, a transcription factor responsible for switching on the synthesis of S phase genes [23•]. As such, a mutated p16/Ink4 (which would dis-inhibit Cdk4), or a mutation in Cdk4 (leading to a p16-resistant protein) both can lead to similar phenotypes, because these mutations hyperphosphorylate Rb, leading to release of E2F1 and subsequent transition of cells from G1 arrest into the S phase [23•]. There have been two reported mutations discovered in the CDK4 gene, whereas a whole host of mutations have been described in CDKN2A [23•]. The penetrance of these mutations in CDKN2A is variable and was when investigated within high risk families, it was reported to be 30 % at age 50 years, and 67 % at age 80 years globally [23•]. When subdivided by region, the variability was further elucidated, with 13 %, 50 %, and 32 % at age 50 years for Europe, the United States, and Australia respectively. At age 80 years, the penetrance was 58 %, 76 %, and 91 % for Europe, the United States, and Australia respectively [23•]. However, when penetrance was ascertained through the melanoma population in general, it was reported as 14 %, 24 %, and 28 % at ages 50, 70, and 80 years respectively [23•]. This disparity speaks to the possible influence of coinherited modifiers in families and also to the contribution of ambient sunlight in modulating overall risk among carriers.

CMM is not limited to the cutaneous surface but also can affect other organs. Ocular melanoma (OM) in particular has been noted to run in families, and a mutation in BRCA-associated protein 1 (BAP1) was found to occur in a large proportion of OM that also exhibited monosomy 3 [24]. This mutation does not occur in OM in isolation, but it also has been noted in families with multiple kindreds with cases of both OM and cutaneous CMM [24]. A recent study found that BAP1 was seen at a higher frequency in patients with metastatic OM compared with controls with nonmetastatic OM [24]. BAP1 also was found to occur at higher frequency in families with both cutaneous CMM and OM [24]. As such, BAP1 has been identified as the mutation with a newly named COMMON syndrome (cutaneous and ocular melanomas, melanocytic proliferations, and other neoplasms) [24]. Whereas the other neoplasms are not completely elucidated, the study families did include three patients with lung cancer, two of which had the BAP1 mutation. Also, BAP1 has emerged as a target for both somatic and germline mutations in mesothelioma [24].

Low- to Moderate-Risk Alleles

Melanocortin-1-receptor (Mc1r) variants have been reported previously to be associated with CMM [25]. Phenotypically, it has been associated with the “red hair color” (RHC) phenotype [25]. When Mc1r is in its wild-type form, it binds alpha-melanocyte stimulating hormone (aMSH), which induces cAMP thereby triggering the production of eumelanin. However, Mc1r variants do not respond properly to aMSH and therefore pheomelanin accumulates [25]. A review from 2008 performed a meta-analysis on the nine most common variants in MC1R. Based on pooled results, authors identified multiple genetic variants of MC1R that were associated with development of melanoma, as well as RHC [25]. These included p.D84E, p.R142H, p.R151C, p.R160W, and p.D294H. Notably, the first two of these variants (p.D84E and p.R142H) were previously reported to not be associated with CMM and may have only surfaced given the aggregate power of the meta-analysis [25–28]. The authors also reported an association found for variants p.I155T and p.R163Q with CMM, however not with RHC, arguing that certain MC1R variants can increase risk of CMM outside of the pigmentary pathways [25]. Another meta-analysis of the same nine variants was published in 2011. In this study, the genetic variations were divided into those that were and those that were not associated with the RHC phenotype (non RHC, or NRHC) [29]. When pooled, those variants that are also in the RHC phenotype group increased the patient’s RR for CMM to 2.44 (1.72, 3.45) compared with individuals with wild-type Mc1r. There was a more modest increase in risk in the NRHC cohort with a RR for CMM of 1.29 (1.1, 1.51) [29]. Although the Raimondi et al. article from 2008 did not find an increased association for the pV60L nor pV92M alterations, these two variants were indeed found to have significantly increased ORs in the 2011 meta-analysis [25, 29].

Whereas those patients with a CDKN2A mutation may unfortunately be at great risk given the relatively high penetrance of those genetic mutations, Mc1r variants confer a lower risk [30••]; the estimated OR of developing melanoma among carriers of Mc1r variants compared with wild-type individuals is 2.2 to 3.9 [31]. What is interesting is the interplay between these two genes. When the MC1R variant is present, the penetrance of CDKN2A mutation increases, in some reports as much as by 34 percent [32]. Also, those families with a known CDKN2A mutation see a doubling of risk of CMM with the presence of an MC1R variant [33].

Genome-Wide Association Studies

With the advent of newer and more easily accessible technology, there have been many new reports of potential genetic associations with CMM, largely through the use of genome wide association studies (GWAS). This is in large part an effort to help explain the “missing heritability” of common diseases [6].

A GWAS from 2008 reviewing records from 2,019 cases and 2,105 controls found a new risk locus on chromosome 20 (20q11.22) and two single nucleotide polymorphisms (SNPs) (rs910873 and rs1885120) that are 1.5-Mb apart with a combined P < 1 × 10-15 [34]. A year later, a group reported a newly discovered SNP associated with CMM through GWAS performed on 1,650 cases and 4,336 controls. Five loci with SNPs reaching statistical significance were discovered, three of which were validated in two replication cohorts. rs258322 at 16q24 on the MC1R gene (P = 2.54 × 10-27), rs1393350 at 11q14-q21 at the tyrosinase (TYR) gene (P = 2.41 × 10-14), and rs7023329 at 9p21, adjacent to MTAP and flanking CDKN2A (P = 4.03 × 10-7) [35].

Two other studies in 2009 sought to link the SNPs associated with certain phenotypic characteristics with CMM. Three SNPs (rs28777, rs35391, and rs16891982) in the MATP gene locus (which mediates melanin synthesis and pigmentation) were associated with CMM; however, this association was attenuated when ancestry was controlled [36]. A separate study sought to link SNPs with one of the known risk factors for CMM, a high melanocytic nevi count [37]. In this study, using 1,524 healthy female twins and 297,108 candidate SNPs (>1 % minor allele frequency), the authors identified 12 SNPs that clustered to the 9p21 or 22q13 loci. These SNP associations were validated on a separate twin database. The strongest association was found with rs4636294 (combined P = 3.4 × 10-15), which maps to the MTAP gene at 9p21, next to CDKN2A [37]. The other SNP (rs2284063), which mapped to 22q13, had a P value of 3.4 x 10-8 [37]. By using these new candidate SNPs, the authors were able to explore the joint ORs of these SNPs in association with other previously described SNPs in the same loci [37]. At 9p21, rs10757257 with rs4636294 demonstrated a joint OR of 1.21 (1.14, 1.28) with a P = 3.7 × 10-8 [37]. For 22q13, rs132985 with rs2284063 had a joint OR of 1.19 (1.12, 1.27, P = 1.5 × 10-6) [37]. As such, the authors were able to demonstrate that not only are these SNPs associated with this particular phenotype of multiple melanocytic nevi but also able to show linkage with CMM [37]. Another study that sought to do the same analysis for SNPs associated with high melanocytic nevi count used an Australian twin database and identified multiple SNPs associated with the Interferon regulatory factor-4 (IRF4) gene [38]. rs12203592 was associated with high freckling in both adolescents and adults; however, only high nevus counts in adolescents. This SNP when investigated from melanoma case–control studies from Australia, the United Kingdom, and Sweden was found to have an increased OR for CMM at 1.15 (1.046, 1.264) [38]. Most recently, an article from 2011 reported rs12913832 (in conjunction with rs1129038), which mapped to 15q13.1 and has a profound association with eye and skin color [39].

On the other hand, other studies have found SNPs that do not seem to be associated with any phenotypic features. In 2011, Barrett et al. demonstrated rs1801516 that mapped to the ATM gene (P = 3.4 × 10-9), rs13016963 adjacent to CASP8 (P = 8.6 × 10-10, and rs45430 at the MX2 locus (P = 2.9 × 10-9) [40]. MacGregor et al. reported on rs7412746 at 1q21.3 (P = 9.0 × 10-11), as well as rs3219090 at 1q42.12 (P = 9.3 × 10-8), which corresponds to candidate loci ARNT and SETDB1, respectively [41]. These SNPs were not found to be associated with any phenotypic variant, such as a high density of nevi [41].

Finally, this year, an article also has explored the opposite: a protective effect of a SNP on CMM. At 5p15.33, rs401681 was previously reported as demonstrating a lower OR with CMM; however, in this study, two other SNPs also were identified in the same locus of the TERT-CLPTM1L. rs13356727 and rs4975616 were explored alongside rs401681, and when each SNP was covaried by the other two, on rs13356727 remained statistically significant, signifying that perhaps, this is the best marker for the protective effects at this locus [42]. The mechanism of this action is posed as a possible protective effect against excessive melanocytic nevi count [42].

Known Exogenous or Iatrogenic Factors

Sun Exposure

Exposure to UV radiation through sun exposure is arguably the most easily modified risk factor for CMM. Numerous studies published have linked sun exposure to the risk of CMM diagnosis. A recent meta-analysis in 2005 reviewed 57 studies published before 2002 found that both intermittent sun exposure and sunburn history played a crucial role as a risk factor for the development of CMM [43]. The relative risk for “total sun exposure” and resultant melanoma diagnosis was reported to be 1.34 (1.02, 1.77), suggesting a slight association. Interestingly, results were quite heterogeneous and stronger associations were found with more recently published studies [43]. The pooled estimate for the association between “intermittent sun exposure” and melanoma was more convincing at a RR of 1.61 (1.31, 1.99) [43]. Although there is a significant amount of heterogeneity in the studies used for the pooled RR, it was felt this was most likely secondary to the many differing definitions for “intermittent sun exposure.”[43] When two studies that included CMM in children that were previously removed from analysis were added back into the calculation of RR, the estimate did not change much and only increased to 1.62 (1.31, 1.99) [43]. Surprisingly, the RR for “chronic UV exposure” and melanoma was slightly protective, although not significantly (RR = 0.95; 95 % CI, 0.87, 1.04). Finally, this meta-analysis also reviewed the exposure of sunburn history, which demonstrated a RR of 2.03 (1.73, 2.37). Within this group, it was found that studies where the population was from latitude higher than 50 had a higher RR, reported as 2.54 (1.99, 3.24). Those studies whose population resided at a lower latitude still demonstrated a statistically significant RR of 1.91 (1.58, 2.31) [43]. Unfortunately, given the rare occurrence of melanoma in absolute terms, it is difficult to perform a prospective study, and as such, it is exceedingly difficult to characterize the pattern of sun exposure that places patients at greatest risk through these retrospective studies [43]. The possibility of recall bias is important in these retrospective studies, and prior investigations have found that certain exposures questioned, such as number of sunburns, is free from recall bias [44]. However, tanning ability does seem to be affected by recall bias [45]. Further studies in twins have attempted to further detail the effect of recall bias, which found the opposite to be true in regard to tanning ability (not affected by recall bias) and sunburn history (affected by recall bias) [46]. These discordant data indicate further study is required into the effect that recall bias may have with these retrospectively conducted studies on CMM.

The pathophysiology of melanoma development in concert with UV radiation has been proposed in prior studies. A mutated p53 tumor suppressor gene has been reported in many cases of melanoma, and UV radiation has been studied as a potential mutagen for the p53 gene [47]. Other associations between melanoma and high altitudes where higher UV fluences are found, and with certain body sites (legs in women, back in men) with higher UV exposure rates have been reported, further demonstrating a possible causal relationship [48–50].

The timing of the sun exposure may play a role as well. A study found that those born in Northern Europe but who moved to Australia, where the UV radiation environment is higher, had a lower rate of melanoma if the move occurred after age 10 years [51]. Alternatively, another study found that melanoma risk doubled with five sunburns, regardless of if these occurred before or after age 15 years [52].

Although it is safe to conclude that excessive exposure is the major environmental risk factor for melanoma, patterns of exposure and the interplay between sunlight and skin pigmentation makes the analysis more complicated and deserve further study.

Indoor Tanning/Artificial Sunlamps

As previously indicated, indoor tanning is thought to be a potential contributor to the increasing incidence of CMM among young women [5]. A large case–control study from the Nurses Health Study published in 2006 found an OR for “ever” versus “never” usage of tanning booths and melanoma to be 2.06 (1.3, 3.26) [53]. When stratified, another study by Lazovich et al. demonstrated an increased risk of melanoma diagnosis with increasing years, hours, and sessions of tanning behavior [54]. A more recent review by the Gandini group demonstrates that “ever” usage status of tanning booths before age 30 years portends an increase of melanoma risk by 75 % [55••].

A separate review from 2011 by the Cust group found that ever users of sunbeds were at an increased risk of CMM than never uses with an OR of 1.41 (1.01, 1.96). When further subdivided, those who had used sunbeds more than ten times had a higher OR of 2.01 (1.22, 3.31) [56]. A subgroup analysis further found that earlier age of first sunbed use also was increasingly associated with CMM diagnosis [56].

Most recently, a meta-analysis by Boniol et al. reviewed 27 articles concerning artificial UV exposure and association with CMM. Case–control, cross-sectional, and cohort studies were included; however, case reports were excluded. They report an overall summary RR of 1.2 (1.08, 1.34) for ever use of sunbeds compared with those without this exposure on association with CMM [57•]. When the population is further stratified to those younger than age 35 years, the summary RR is reported as 1.87 (1.41, 2.48) [57•].

Organ Transplant Recipients

Melanoma, which is an immune-responsive tumor, unsurprisingly behaves differently in the immunocompromised host. Patients who are recipients of organ transplants remain on immunosuppression for long-term to prevent graft rejection. As such, there are two groups of transplant patients for whom we must be mindful regarding their melanoma diagnosis: 1) those who were transplanted after a prior diagnosis of malignant melanoma, and 2) those who develop a melanoma after transplantation. A study from 2011 demonstrated that compared with expected survival rates for melanoma derived from the Surveillance, Epidemiology, and End Results (SEER) database, those with a history of transplantation had a poorer prognosis regardless of Breslow thickness or Clark level [58].

However, aside from prognosis after diagnosis of CMM, one also should be concerned for the potentially increased risk of CMM after organ transplant. A review of noninfection-related malignancies among those with organ transplants reported 381 cases observed in their cohort to the ~180 expected based on published rates in the general public applied to the registry population. The standardized incidence ratio (SIR) was reported as 2.38 (2.14, 2.63) in this population, indicating an increased risk of CMM [59].

Nonsteroidal Anti-Inflammatory Drug Use

A recent study explored the possible protective effects of nonsteroidal anti-inflammatory drug (NSAID) intake on skin cancer risk. All skin cancer cases were recorded for northern Denmark, and controls were taken from the population matching ten controls for each case. Exposure was defined as ever use of NSAIDs (>2 prescriptions) versus controls that were defined as never use of NSAIDs (≤2 prescriptions). The incident rate ratio (IRR) for these group and CMM was reported as 0.87 (0.8, 0.95), indicating a possible protective effect on CMM [60].

TNF-α Inhibitor Use

A study from the gastroenterology literature also highlighted the potential risk of CMM diagnosis after usage of TNF-α inhibitors in a population of inflammatory bowel disease (IBD) patients [61]. In a nested case–control study, use of TNF-α inhibitors in the setting of IBD showed an odds ratio of 1.88 (1.08, 3.29) compared with nonuse. However, when subdivided by length of therapy, this association was not seen when TNF-α inhibitors were used for fewer than 120 days. When the opposite is investigated, “long term use” of TNF-α inhibitors saw an OR of 3.93 (182, 8.5) compared with “non-long term use” of TNF-α inhibitors for CMM diagnosis [61].

Screening and Prevention

Most experts agree that prevention is a key component to decrease melanoma mortality. Whereas primary prevention revolves around sun protection in hopes of decreasing the incidence of melanoma development, one also can consider the importance of secondary prevention, the hope of diagnosing melanoma early enough to mitigate the risk of mortality from the disease. The most obvious example is our frequent surveillance of those who we deem at high risk; however, it would be prudent to explore whether this action, taken by almost all dermatologists, actually diminishes mortality.

A large-scale skin cancer screening program of more than 360,000 residents in the German Federal State of Schleswig-Holstein from July 1, 2003 to June 30, 2004 utilized both dermatologists and nondermatologists. Incidence increased by 30 % in the screened area relative to the rest of Germany and 50 % of all melanomas reported to the Schleswig-Holstein registry arose from the formal screening program [62]. Most notably, mortality rates from CMM in Schleswig-Holstein decreased by 50 % compared with Denmark to the north and all other areas of Germany. Overall, there was a decrease of 7.4 % per year (7.5 % decrease in men, 7.1 % in women), which was not seen in other areas in Germany and Denmark [63•]. Although these results need to be interpreted cautiously, because the authors indicate there are other factors at play, such as a heightened awareness, this certainly raises important implications for the possibility of decreasing CMM mortality with skin cancer screening programs. Because of the success of the Schleswig-Holstein study, a national screening program is currently taking place in Germany: more than 20 million residents have been screened and 77 % of German physicians have taken part in an 8-hour training program (Dr. Eckhard Breitbart; personal communication, August 15, 2012).

Although secondary prevention is important, an even more attractive option may actually be primary prevention. The ability to completely prevent a new case of melanoma is an attractive proposition. As such, the possibility of chemoprevention has been raised. A recent study from Cancer in 2012 investigated the possibility of an association between statin usage and a lower risk of melanoma based on data that suggested simvastatin may be able to decrease the melanoma cell’s ability to adhere to laminin and collagen type IV [64]. Unfortunately, the data from the study did not support the possible decrease of melanoma risk from statin usage, despite prior in vitro data supporting a salutary effect [64]. More exciting are the data presented above regarding the possible protective effects of NSAIDs on CMM risk [60].

In terms of sun protection with sunscreens for prevention of CMM, a study that was started in 1992 randomized 1,621 participants to either daily or discretionary application of broad-spectrum sunscreen to the head and neck revealed that although statistical significance was not seen, there is certainly a suggestion of a trend toward protection against CMM diagnosis at any body site in the daily application of sunscreen group. The overall HR was marginally significant 0.5 (0.24, 1.02), whereas the decrease of invasive melanomas was substantial (HR = 0.27, 0.08-0.97) [65•]. With the results of this randomized trial, it is difficult to ignore these data in our daily counseling of patients for improved sun protection to prevent not only NMSC, but also CMM. Future studies may show more convincing data to the contrary, however currently, protection and avoidance from UV remains the only reliable type of primary prevention for CMM.

Conclusions

Full control of the “melanoma epidemic” will require efforts, and successes, in both early detection/prevention and disease-mitigating drugs. New trends have emerged (e.g., increasing incidence among young women), novel associations are being explored (e.g., Parkinson’s disease and melanoma), population-based screening studies have been conducted and predisposing alleles have been uncovered through GWAS. It is certainly an exciting time in the field of melanoma epidemiology.