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Keywords:

  • actinic damage;
  • solar lentigo;
  • wrinkling;
  • pigmentation phenotype;
  • melanoma risk;
  • central Europe

Summary

  1. Top of page
  2. Summary
  3. Significance
  4. Introduction
  5. Results
  6. Discussion
  7. Methods
  8. Acknowledgements
  9. References
  10. Supporting Information

Sun exposure is causal for melanoma but is subject to bias of recall so that it is difficult to dissect the role of particular patterns of sun exposure. In this hospital-based case-control study (n = 1991), we aimed to analyze pigmentation traits and signs of actinic damage at different anatomic locations as markers of melanoma risk in central European patients. Although all signs of actinic damage (freckling, wrinkling and solar lentigos) were significantly associated with melanoma risk in multivariate logistic regression models adjusting for age and sex, the strongest associations were observed for the dorsal parts of the body: adjusted odds ratios [OR] were 4.22 for wrinkling on the neck, 3.43 for solar lentigos and 3.37 for freckling on the back (all P < 0.001), respectively. These associations were independent of age, sex and pigmentation traits. Our results indicate that signs of actinic damage are predictors of melanoma risk, particularly on the back.


Significance

  1. Top of page
  2. Summary
  3. Significance
  4. Introduction
  5. Results
  6. Discussion
  7. Methods
  8. Acknowledgements
  9. References
  10. Supporting Information

Signs of actinic damage are markers of both susceptibility to melanoma and causal exposure. In this study, we provide evidence for a more potent role of actinic damage as risk factors than traits such as skin phototype or hair color. Among all signs of actinic damage, those on the back were most strongly associated with melanoma, stressing the importance of intermittent sun exposure in a central European population.

Introduction

  1. Top of page
  2. Summary
  3. Significance
  4. Introduction
  5. Results
  6. Discussion
  7. Methods
  8. Acknowledgements
  9. References
  10. Supporting Information

Pigmentation phenotypes such as eye color, hair color and skin phototype have been established as risk factors for melanoma in various populations (Bliss et al., 1995; Gandini et al., 2005b; Han et al., 2006; Landi et al., 2001; Naldi et al., 2000; Olsen et al., 2010). These findings support the concept that ultraviolet (UV) radiation is the main cause of melanoma development, as the phenotypes are indicative of sensitivity to the sun and sunburn, which have been found to be robust risk factors for melanoma in many studies (Chang et al., 2009). The relevance of pigmentation phenotypes is emphasized as the most common susceptibility genes identified by recent genome wide association studies are genes known to have a role in determining pigmentation (Bishop et al., 2009; Han et al., 2008).

Although sunburn is an unequivocal risk factor for melanoma, the type of sun exposure which is most strongly associated with risk remains of interest. There is evidence that recreational sun exposure on holidays is the most important risk factor in all northern latitude populations, whereas large cumulative sun exposures play the clearest role in very sunny countries (Chang et al., 2009). However, occupational sun exposure has been thought to be protective for melanoma at higher latitudes (Gandini et al., 2005a) and a recent study from the UK reported a protective effect of regular weekend sun exposure on melanoma risk (Newton-Bishop et al., 2011). The relationship between sun exposure and risk is therefore complex and in particular the role of chronic sun exposure in Europe remains least well understood.

Cutaneous signs of actinic damage are markers of both susceptibility and sun exposure and this study was designed to study these as markers of risk in more detail than previously reported, particularly in Europe (Bataille et al., 1998; Derancourt et al., 2007). Other authors have reported significantly smaller studies of actinic damage and risk, looking at single measures at single body sites (Derancourt et al., 2007; Garbe et al., 1994; Monestier et al., 2006; Reguiaï et al., 2008; Richtig et al., 2008; Schäfer et al., 2006; Suppa et al., 2011). However, body sites such as face, hands and back are exposed differently to ambient sunlight, and the significance of actinic damage might therefore differ from site to site. We report the association of different measures of actinic damage in different body sites, and melanoma risk in order to further elucidate this relationship. Information on the value of various types of actinic damage as risk factors are important, as they are easily visible and reflect exposure to UV radiation independent of patient’s information or memory on sun exposure history.

Results

  1. Top of page
  2. Summary
  3. Significance
  4. Introduction
  5. Results
  6. Discussion
  7. Methods
  8. Acknowledgements
  9. References
  10. Supporting Information

Participants’ characteristics

A total of 1991 participants (934 cases and 1053 controls) were included in the analyses (Table 1). Cases were diagnosed for melanoma from 1967 to 2010: more than 95% of the cases were diagnosed after 1990. The mean age of melanoma patients at diagnosis was 54 yr (±15 yr) and the mean age of controls was 59 yr (±16 yr). Of the patients, 54% were male compared with 49% of controls. Males (n = 508, 54%) were older than females (n = 430, 46%) with a mean age of 57 ± 15 yr (versus 52 ± 15 yr for females) when diagnosed for melanoma. The most frequent histogenetic subtype of the primaries was superficial spreading melanoma (51.1%), followed by nodular melanoma (19.8%), lentigo maligna melanoma (7.2%) and other subtypes (3.9%, Table 1). Eighteen percent were not classified. Information about Breslow thickness was available for 911 primaries: The median Breslow thickness was 0.97 mm [interquartile range (IQR) = 0.50–1.80], with no significant difference between males and females (P = 0.190, Mann–Whitney U-test). The most frequently affected site for both sexes was the trunk (52.5%), followed by the lower extremities (25.2%), upper extremities (11.8%) and the head and neck region (10.5%). Males were at higher risk of developing melanomas on the trunk compared with females (OR = 2.45, 95% CI 1.89–3.19, P < 0.001).

Table 1.   Age, sex, site of tumor occurrence and melanoma subtype
 Cases (n = 938)Controls (n = 1053)
  1. SD, standard deviation; IQR, interquartile range; SSM, superficial spreading melanoma; NM, nodular melanoma; LMM, lentigo maligna melanoma.

  2. aAge = age at diagnosis for cases and age at recruitment for controls.

  3. bBreslow thickness was not assessed in 27 cases.

  4. cInformation was not available for one patient.

Sex
 Female430 (45.8)533 (50.6)
 Male508 (54.2)520 (49.4)
Agea (yr)
 Mean (±SD)54.42 (±15.23)58.70 (±16.20)
Age at recruitment (yr)
 Mean (±SD)60.38 (±14.79)58.70 (±16.20)
 All casesMalesFemales
Histogenetic subtype
 SSM471 (50.2)263 (51.8)208 (48.4)
 NM182 (19.4)95 (18.7)87 (20.2)
 LMM66 (7.0)41 (8.1)25 (5.8)
 Spitzoid17 (1.8)4 (0.8)13 (3.0)
 Nevoid11 (1.2)8 (1.6)3 (0.7)
 Desmoplastic6 (0.6)2 (0.4)4 (0.9)
 Spindle cell2 (0.2)1 (0.2)1 (0.2)
 Not classified183 (19.5)94 (18.5)83 (20.7)
Breslow thicknessb
 Median (IQR)0.97 (0.50–1.80)1.00 (0.59–1.80)0.95 (0.50–1.60)
Site of tumor occurrencec
 Head/Neck98 (10.5)66 (13.0)32 (7.5)
 Upper extremity111 (11.8)50 (9.8)61 (14.2)
 Trunk492 (52.5)318 (62.6)174 (40.5)
 Lower extremity236 (25.2)74 (14.6)162 (37.8)

Inter-rater variability

We next evaluated the inter-rater variability of the assessment of actinic damage. Consistency among the raters was either substantial (κ = 0.61–0.80) or almost perfect (κ = 0.81–1.00), as described previously (Landis and Koch, 1977). For facial damage, the kappa coefficients for inter-rater reliability were 0.83, 0.70 and 0.80 for freckling, wrinkling and solar lentigo, respectively. For actinic damage on the back and neck, the kappa coefficients for agreement were 0.83, 0.81 and 0.85 for freckling, wrinkling and solar lentigo, respectively. For freckling and solar lentigo on the hands, the κ values were 0.84 and 0.70, respectively.

Skin phototype and pigmentation phenotype as melanoma risk factors

Skin phototype and pigmentation phenotype (burning tendency, tanning ability, eye color, hair color, freckles in childhood, number of nevi) were assessed as predictors of melanoma risk (Table 2,Figure 1). After adjusting for age and sex, participants reporting a high tendency to burn had an increased risk (OR = 2.74, 95% CI 2.07–3.64, P < 0.001 compared with low tendency to burn), followed by the absence of tanning ability (OR = 2.10, 95% CI 1.43–3.09, P < 0.001 compared to high tanning ability), red hair color (OR = 1.97, 95% CI 1.33–2.90, P = 0.001 compared with brown/black hair), skin phototype I/II (OR = 1.94, 95% CI 1.50–2.52, P < 0.001 compared with IV/V), a past history of 10 or more sunburns during the first two decades in life (OR = 1.94, 95% CI 1.55–2.43, P < 0.001 compared to no sunburns during this time), fair eye color (OR = 1.66, 95% CI 1.35–2.04, P < 0.001 compared to dark eye color), the presence of more than 30 small nevi (OR = 1.63, 95% CI 1.07–2.48, P = 0.023 compared to less than 10 small nevi) and the presence of freckles in childhood (OR = 1.42, 95% CI 1.16–1.73, P = 0.001 versus no freckles). When we adjusted each variable for the others in a multivariate analysis, we identified the following variables as independent predictors of melanoma risk: high burning tendency (OR = 1.90, 95% CI 1.30–2.78, P = 0.001), red and blond hair color (OR = 1.74, 95% CI 1.09–2.77, P = 0.020 and OR = 1.49, 95% CI 1.13–1.97, P = 0.005 respectively) and a past history of 10 or more sunburns (OR = 1.46, 95% CI 1.13–1.88, P = 0.004; last column in Table 2).

Table 2.   Skin phototype and phenotypical traits
VariableaCases (n = 938)Controls (n = 1053)UnadjustedAORbAORc
n (%)n (%)OR (95% CI)P-valueOR (95% CI)P-valueOR (95% CI)P-value
  1. OR, odds ratio; AOR, adjusted odds ratio; CI, confidence interval; Ref, reference category.

  2. aThe single variables do not add up to the total number of cases and controls because of missing data.

  3. bAdjusted for sex and age.

  4. cEach variable is adjusted for each other at the same time (and for sex and age).

  5. dHigh burning tendency = 5, intermediate burning tendency = 3 + 4, low burning tendency = 1 + 2.

  6. eNo tanning ability = 1, intermediate tanning ability = 2 + 3, high tanning ability = 4 + 5.

  7. fFair = blue, green-gray and green; dark = brown.

Burning tendencyd
 High202 (21.6)123 (11.7)2.78 (2.10–3.68)<0.0012.74 (2.07–3.64)<0.0011.90 (1.30–2.78)0.001
 Intermediate517 (55.2)559 (53.2)1.57 (1.27–1.92)<0.0011.49 (1.21–1.84)<0.0011.30 (0.98–1.72)0.071
 Low218 (23.3)369 (35.1)Ref Ref Ref 
Tanning abilitye
 No96 (10.2)79 (7.5)1.95 (1.34–2.85)0.0012.10 (1.43–3.09)<0.0010.97 (0.59–1.59)0.898
 Intermediate727 (77.6)790 (75.1)1.48 (1.15–1.91)0.0031.49 (1.15–1.93)0.0020.94 (0.69–1.28)0.673
 High114 (12.2)183 (17.4)Ref Ref Ref 
Hair color
 Red73 (7.8)50 (4.7)1.87 (1.27–2.74)0.0011.97 (1.33–2.90)0.0011.74 (1.09–2.77)0.020
 Blond243 (25.9)185 (17.6)1.68 (1.33–2.12)<0.0011.82 (1.44–2.30)<0.0011.49 (1.13–1.97)0.005
 Light brown225 (24.0)311 (29.5)0.93 (0.75–1.15)0.4870.96 (0.77–1.19)0.6890.88 (0.69–1.13)0.331
 Brown/black396 (42.3)507 (48.1)Ref Ref Ref 
Skin phototype
 I/II656 (72.6)625 (61.3)2.07 (1.60–2.68)<0.0011.94 (1.50–2.52)<0.0011.31 (0.92–1.87)0.130
 III140 (15.5)184 (18.0)1.50 (1.09–2.07)0.0131.37 (0.99–1.89)0.0581.32 (0.92–1.89)0.138
 IV/V107 (11.8)211 (20.7)Ref Ref Ref 
Frequency of sunburns between 0 and 20 yr
 ≥ 10479 (51.7)359 (34.3)2.27 (1.83–2.81)<0.0011.94 (1.55–2.43)<0.0011.46 (1.13–1.88)0.004
 1–9225 (24.3)309 (29.5)1.24 (0.97–1.57)0.0801.08 (0.84–1.38)0.5411.01 (0.77–1.32)0.969
 0223 (24.1)379 (36.2)Ref Ref Ref 
Eye colorf
 Fair738 (78.7)732 (69.5)1.62 (1.32–1.98)<0.0011.66 (1.35–2.04)<0.0011.26 (0.99–1.61)0.059
 Dark200 (21.3)321 (30.5)Ref Ref Ref 
Nevi small
 >3067 (7.3)41 (4.0)2.11 (1.40–3.17)<0.0011.63 (1.07–2.48)0.0231.42 (0.88–2.29)0.156
 10–30386 (42.1)377 (37.1)1.32 (1.10–1.59)0.0031.12 (0.92–1.37)0.2451.12 (0.90–1.40)0.312
 <10463 (50.5)598 (58.9)Ref Ref Ref 
Freckles in childhood
 Yes304 (34.8)268 (26.7)1.47 (1.20–1.78)<0.0011.42 (1.16–1.73)0.0011.07 (0.85–1.34)0.586
 No569 (65.2)735 (73.3)Ref Ref Ref 
Nevi large
 >10107 (11.7)80 (7.9)1.54 (1.13–2.08)0.0061.29 (0.95–1.77)0.1061.19 (0.83–1.71)0.350
 <10808 (88.3)928 (92.1)Ref Ref Ref 
image

Figure 1.  The bars indicate the age and sex-adjusted odds ratios for pigmentation phenotype (see Table 2) and for moderate/severe signs of skin damage (see Table 3).

Download figure to PowerPoint

Signs of actinic damage as melanoma risk factors

We next studied the association of clinical signs of actinic damage (i.e. freckling and solar lentigos on the face, hands and back and wrinkling on face and neck) with melanoma in all participants (Supporting Information Table S1). Although all signs of actinic damage were associated with melanoma risk after adjusting for sex and age at recruitment, the strongest associations were found for the back and neck. To exclude a potential bias by patients with other types of cancer related to high UV radiation in the past and actinic damage, respectively, we repeated our analyses by excluding participants with non-melanoma skin cancer (NMSC). We excluded all controls who were diagnosed for NMSC anytime during their life (Supporting Information Table S2). Secondly, we excluded   melanoma patients who had ever been diagnosed for NMSC (Table 3). Despite these stringent criteria, actinic damage on the back remained most strongly associated with melanoma risk after adjusting for sex and age at recruitment: OR for moderate/severe wrinkling on the neck and face was 4.22 (95% CI 2.94–6.06, P < 0.001) and 1.38 (95% CI 0.93–2.03, P = 0.109), respectively. For moderate/severe solar lentigo on the back, hands and face, the age- and sex-adjusted ORs were 3.43 (95% CI 2.48–4.75, P < 0.001), 2.50 (95% CI 1.73–3.62, P < 0.001) and 1.99 (95% CI 1.39–2.86, P < 0.001), respectively. For freckling, the highest OR was again found for moderate/severe signs on the back (age- and sex-adjusted OR = 3.37, 95% CI 2.41–4.71, P < 0.001), compared with the hands (OR = 2.06, 95% CI 1.35–3.14, P = 0.001) and the face (OR = 1.17, 95% CI 0.85–1.62, P = 0.341). All associations of actinic damage on the back with melanoma remained significant even after adjusting for skin phototype, hair color and freckles in childhood in addition to age at recruitment and sex (Table 3) and after adjusting each sign of actinic damage for each other (last column in Table 3): ORs were 3.02 (95% CI 2.02–4.51, P < 0.001) for wrinkling, 1.74 (95% CI 1.19–2.54, P = 0.005) for solar lentigos and 1.93 (95% CI 1.28–2.92, P = 0.002) for freckling.

Table 3.   Signs of actinic damage (cases and controls who were diagnosed for NMSC were excluded)
VariableaCases (n = 718)Controls (n = 822)UnadjustedAORbAORcAORd
n (%)n (%)OR (95% CI)P-valueOR (95% CI)P-valueOR(95% CI)P-valueOR(95% CI)P-value
  1. OR, odds ratio; AOR, adjusted odds ratio; CI, confidence interval; Ref, reference category.

  2. aThe single variables do not add up to the total number of cases and controls because of missing data

  3. bAdjusted for sex and age at recruitment.

  4. cIncluding skin phototype, hair color, freckles in childhood.

  5. dEach variable is adjusted for the others at the same time (and for sex and age at recruitment).

Wrinkling neck
 ++, +++228 (32.5)150 (18.6)3.09 (2.33–4.11)<0.0014.22 (2.94–6.06)<0.0013.66 (2.48–5.41)<0.0013.02 (2.02–4.51)<0.001
 +324 (46.2)353 (43.8)1.87 (1.46–2.39)<0.0012.24 (1.69–2.96)<0.0012.11 (1.56–2.85)<0.0011.68 (1.24–2.29)0.001
 0149 (21.3)303 (37.6)Ref Ref Ref Ref 
Wrinkling face
 ++, +++278 (38.8)296 (36.1)1.54 (1.17–2.03)0.0021.38 (0.93–2.03)0.1091.14 (0.76–1.73)0.5240.67 (0.43–1.06)0.086
 +310 (43.2)311 (38.0)1.64 (1.25–2.14)<0.0011.53 (1.12–2.09)0.0071.33 (0.96–1.86)0.0910.93 (0.64–1.34)0.691
 0129 (18.0)212 (25.9)Ref Ref Ref Ref 
Solar lentigines back
 ++, +++268 (38.3)185 (23.1)3.01 (2.27–3.97)<0.0013.43 (2.48–4.75)<0.0013.17 (2.23–4.49)<0.0011.74 (1.19–2.54)0.005
 +298 (42.6)338 (42.2)1.83 (1.41–2.37)<0.0012.02 (1.52–2.68)<0.0011.92 (1.42–2.60)<0.0011.33 (0.97–1.82)0.082
 0134 (19.1)278 (34.7)Ref Ref Ref Ref 
Solar lentigines hands
 ++, +++171 (23.9)135 (16.7)2.04 (1.54–2.70<0.0012.50 (1.73–3.62)<0.0012.17 (1.46–3.22)<0.0011.45 (0.94–2.24)0.097
 +316 (44.1)303 (37.5)1.68 (1.34–2.11)<0.0011.91 (1.45–2.52)<0.0011.82 (1.35–2.44)<0.0011.26 (0.92–1.73)0.156
 0229 (32.0)369 (45.7)Ref Ref Ref Ref 
Solar lentigines face
 ++, +++124 (17.3)118 (14.5)1.86 (1.37–2.52)<0.0011.99 (1.39–2.86)<0.0011.93 (1.31–2.85)0.0011.53 (1.01–2.32)0.043
 +386 (54.0)331 (40.8)2.06 (1.65–2.59)<0.0012.16 (1.67–2.79)<0.0012.10 (1.60–2.76)<0.0011.73 (1.30–2.31)<0.001
 0205 (28.7)363 (44.7)Ref Ref Ref Ref 
Freckling back
 ++, +++297 (42.2)219 (27.2)3.06 (2.29–4.09)<0.0013.37 (2.41–4.71)<0.0012.68 (1.83–3.79)<0.0011.93 (1.28–2.92)0.002
 +304 (43.2)356 (44.2)1.93 (1.46–2.54)<0.0012.05 (1.52–2.77)<0.0011.88 (1.37–2.58)<0.0011.48 (1.04–2.08)0.027
 0102 (14.5)230 (28.6)Ref Ref Ref Ref 
Freckling hands
 ++, +++69 (9.6)48 (5.9)2.07 (1.39–3.06)<0.0012.06 (1.35–3.14)0.0011.65 (1.04–2.60)0.0331.34 (0.82–2.18)0.238
 +306 (42.7)273 (33.7)1.61 (1.30–1.99)<0.0011.60 (1.26–2.04)<0.0011.42 (1.09–1.84)0.0091.11 (0.84–1.47)0.449
 0341 (47.6)490 (60.4)Ref Ref Ref Ref 
Freckling face
 ++, +++212 (29.6)237 (29.1)1.33 (1.00–1.78)0.0511.17 (0.85–1.62)0.3410.86 (0.61–1.23)0.4210.60 (0.40–0.88)0.010
 +371 (51.8)379 (46.6)1.46 (1.12–1.89)0.0051.34 (1.01–1.77)0.0431.08 (0.80–1.46)0.6190.84 (0.60–1.16)0.284
 0133 (18.6)198 (24.3)Ref Ref Ref Ref 

To confirm the relevance of our findings in recently diagnosed patients, we repeated the analyses for the subgroup of 224 patients who had been diagnosed with melanoma after 2007 (Supporting Information Table S3). The ORs for actinic damage on the back and on the hands remained the highest of all analogous signs of actinic damage, which made it unlikely that our findings were due to selection bias or aging of patients who were diagnosed earlier (Supporting Information Table S4).

Discussion

  1. Top of page
  2. Summary
  3. Significance
  4. Introduction
  5. Results
  6. Discussion
  7. Methods
  8. Acknowledgements
  9. References
  10. Supporting Information

Melanoma is essentially a tumor of white-skinned peoples, with the highest incidence of melanoma worldwide to be found in Australia and New Zealand among peoples of northern European descent (Baade et al., 2012; Liang et al., 2010). This finding led to the view that melanoma is caused by sun exposure, which was supported by the fact that individuals with fair skin and a tendency to burn are at increased risk (Cress et al., 1995; Gallus et al., 2007; Palmer et al., 2000). The identification of pigmentation genes as the commonest susceptibility genes in genome-wide association studies provided conclusive evidence that pigmentation phenotypes are key to susceptibility (Bishop et al., 2009; Gudbjartsson et al., 2008). Raised public awareness and laws restricting the use of sunbeds for juveniles in many countries (Autier and Boyle, 2008; Cust et al., 2011; Gallagher, 2005; Héry et al., 2010; Thomson et al., 2010), have clearly resulted from the efforts of epidemiologists and public health teams to understand this relationship and convey the risk, but the incidence of melanoma still continues to rise worldwide (Lasithiotakis et al., 2006; Linos et al., 2009). This has evidently occurred because risk behaviors to continue, which might be due to some extent to the confusion concerning which types of sun exposure cause melanoma.

Understanding of the biology of melanoma has progressed dramatically in recent years, which might impact classification and even treatment strategies in the future (Bauer et al., 2011; Curtin et al., 2005; Fargnoli et al., 2008; Whiteman et al., 2011), but which also informs this debate. It has become apparent that there are distinct molecular subtypes of melanomas that have different site distributions. Whiteman et al. (1998, 2003) has proposed the ‘two routes to melanoma hypothesis’, one mediated by chronic and another by intermittent sun exposure, typified by driver BRAF mutations (Maldonado et al., 2003). The prevalence of BRAF mutations differs by body site (Curtin et al., 2005), being higher in intermittently sun-exposed sites and fewer signs of chronic sun exposure defined by elastosis. By studying clinical signs of actinic damage at various body sites, we aimed to provide the basis for developing a practical and improved assessment method of risk for diverse subtypes of melanomas, including information on sun sensitivity and signs of actinic damage on different body sites.

Although sun sensitivity is commonly assessed by an interview, the methods used to define ‘fair skin complexion’ have not been consistent in previous studies (Gandini et al., 2005b; Lock-Andersen et al., 1998; Reeder et al., 2010). Some authors assessed sun sensitivity by asking about a tendency to burn only and others used Fitzpatrick’s score, which is a composite of reported burning and tanning propensity in one category. To determine which of the applied methods is most informative regarding risk of melanoma, we asked our participants to score their tendency to burn and tan separately, besides assessing phototype according to Fitzpatrick. Although it is not surprising that burning tendency on a visual analog score was associated with melanoma, the fact that its association was stronger than Fitzpatrick’s score was not expected and indicates that asking for burning tendency alone is not only easier and faster and therefore more practical in the daily routine but even more informative with regard to melanoma risk.

As the exploration of previous sun exposure and its interpretation of its measure are very complex and laborious, we sought to analyze easily accessible markers to assess experienced sun exposure objectively. Due to different extents of sun exposure at different anatomic locations, the presence and degree of three different clinical signs of actinic damage were determined at three body sites: presence and severity of wrinkling (also known as facial Favre–Racouchot and cutis rhomboidalis nuchae), solar lentigos and freckling on the face, hands and back. In this comprehensive analysis, we showed that all dorsal signs of actinic damage are risk factors for melanoma, independent of age, sex and pigmentation traits including skin phototype, hair color and freckles in childhood (Table 3). As the dorsal trunk (in contrast to the face and hands) is usually covered by clothing, actinic damage on the back logically reflects intermittent rather than chronic or constant sun exposure. There was no association of occupational sun exposure with melanoma in our cohort. Therefore, our finding favors the idea that intermittent UV radiation is a stronger risk factor for melanoma than chronic sun exposure. This hypothesis is supported by the fact that dorsal actinic damage is associated with more than 10 sunburn episodes during the first two decades of life, which itself has been reported to increase melanoma risk (Bastiaens et al., 2004; Derancourt et al., 2007; Reguiaï et al., 2008). Previous reports have also indicated that recreational sun exposure is the main risk factor for melanoma (Chang et al., 2009; Newton-Bishop et al., 2011). We are currently studying the causes for actinic damage at different body sites in more detail and those results will be reported separately.

Regarding the relationship between the locations of actinic damage and primary melanoma, we were not able to confirm any local association between actinic damage and tumor occurrence (data not shown). Only head and neck melanomas were associated with moderate/severe actinic damage on the face but this failed to remain significant after adjusting for age at recruitment. Although we do not have a definitive explanation for this missing association, this finding supports the concept that intrinsic factors might confer a risk for melanoma on specific biologic background and thereby determine risk for melanoma at specific body sites. It is commonly accepted that the development of melanoma is a complex interplay between genetic and environmental risk factors (Scherer et al., 2009). Further analyses including phenotype as well as genetic information are required to elucidate this interaction.

There are strengths as well as limitations to our study. The study utilized the collection of very detailed phenotype data from a large case-control study. But as a hospital-based case-control study, the possibility of selection bias towards high risk melanoma patients and controls, who may have experienced higher UV radiation in the past compared with the healthy average population, cannot be excluded. Indeed, 21.3% of our control patients were diagnosed for NMSC, which could be considered as a marker of past UV radiation. However, we excluded these patients from our analyses to minimize this bias, which strengthened our hypothesis (Tables S2 and S3).Our data is therefore useful to describe differences between cases and controls in a specialized clinic in central Europe. Therefore, our finding is of particular interest for specialized institutions as well as dermatological offices. Further studies in other latitudes would shed more light on the mechanisms involved in melanoma development and potentially reveal risk factors only detectable in larger cohorts.

In summary, we present here, to the best of our knowledge, for the first time a comprehensive case-control study analyzing various signs of actinic damage at different anatomic locations as risk factors for melanoma. Expecting a North–South divide of phenotypical traits, skin phototype and ambient UV radiation, Austria is particularly suitable to fill the gap between northern and southern European countries. Our current report would therefore help to complete Europe-wide information for identifying phenotypic risk factors for melanoma. Signs of actinic damage on the back are the most relevant clinical markers as risk factors for melanoma compared to analogous signs on chronically exposed sites such as face and hands. This information is useful to raise patients’ awareness of relevant signs of actinic damage and might be of educational and preventive value in the general public in terms of risk avoidance. The missing link between tumor site and sun-damaged skin in our population indicates the need for a stronger focus on further molecular and genetic analyses for a better understanding of melanoma development.

Methods

  1. Top of page
  2. Summary
  3. Significance
  4. Introduction
  5. Results
  6. Discussion
  7. Methods
  8. Acknowledgements
  9. References
  10. Supporting Information

Study population

Cases and controls were recruited as part of a continuous study aiming at the identification of molecular risk as well as prognostic factors (Molecular Markers of Melanoma, M3 study), which was established to collect data, genomic DNA and melanoma tissue to study molecular risk factors for melanoma in Austria. Between March 2008 and July 2010, 1184 melanoma patients with histopathologically confirmed primary melanoma were recruited to the study via the oncology clinic of the Department of Dermatology of the Medical University of Vienna as cases. As controls, 1073 patients visiting the outdoor clinic of the same department for general dermatological diseases other than melanoma and without any history of melanoma were invited to participate in the study (diagnoses of the controls are listed in Supporting Information Table S5). Written consent was obtained from all participants. This study was approved by the ethics committee of the Medical University of Vienna.

Only participants with central European ancestry were included in the current study: 93% (n = 2036) were born in Austria and 79% (n = 1741) had parents who were both born in Austria. The remaining participants or their ancestors were born in other central European countries such as Belgium, Czech Republic, Germany, Hungary, the Netherlands, Poland, Romania, Slovakia and Switzerland. In all, 208 melanoma patients were excluded as they were diagnosed for occult, mucosal, acral-lentiginous melanomas or in situ melanomas. Thus, 1991 participants were included in the final analyses (938 cases and 1053 controls).

All participants were interviewed by trained personnel for potential risk factors. Skin phototype was classified using Fitzpatrick’s score as reported elsewhere (Fitzpatrick, 1988). Additionally, self-reported tanning ability and burning tendency were classified on a visual analog score from 1 to 5 (1 = no tanning ability, 5 = high tanning ability and 1 = no burning tendency, 5 = high burning tendency, respectively). Self-reported presence of freckles in childhood was recorded using a freckle chart (adapted from Gallagher et al., 1990; Kricker et al., 1993). Freckles in childhood were defined as small, light brown spots during childhood whose occurrence is (reversibly) dependent on sun exposure (Hölzle, 1992). Additionally, information regarding sunburns was recorded (age, frequency of sunburns).

Participants were examined for pigmentation phenotype: hair color (red, blond, light brown, brown/black) and eye color (dichotomized as fair = blue, green-gray and green; dark = brown).Skin alterations were defined as clinical signs of actinic damage (solar lentigos and freckling on face, back and hands and wrinkling/elastosis, also known as Favre–Racouchot on the face and cutis rhomboidalis nuchae) by two dermatologists (I.O., J.W.).Wrinkling on the face was defined as deep skin lines occurring on the forehead, peri-orbital and peri-oral region, whereas wrinkling on the neck was defined as deep skin lines, commonly appearing in a characteristic rhomboid pattern. Freckling was defined as persisting areas of hyperpigmentation, resulting in a mottled, irregular skin appearance (Marrett et al., 1992; Ortonne, 1990) and solar lentigos were defined as brown, macular lesions with sharp margins. Depending on their severity, these signs of actinic skin damage were graded as described previously (Schäfer et al., 2006): ‘0’ for absent, ‘+’ for mild, ‘++’ for moderate and ‘+++’ for severe. Melanocytic nevi with a diameter <0.6 cm and no clinical sign of malignancy were defined as ‘small nevi’; larger melanocytic nevi were defined as ‘large nevi’. Both types were counted on the back of each participant.

All participants were photographed in the photo laboratory of the department of dermatology under standardized conditions with a Nikon D700 camera. All signs of actinic damage were then re-evaluated with the photographs. To ensure consistency, the photographs of 50 recruited participants were additionally assessed by the two observers independently. An interobserver variability analysis was performed and consistency was expressed with κ-values (Landis and Koch, 1977).

Statistical analyses

All data were systematically entered in an electronic database (access, Microsoft Corp, Redmond, WA, USA). For all statistical analyses, skin phototype, tanning ability, burning tendency and signs of actinic damage were classified into three categories due to small numbers in some categories, i.e. ‘++’ and ‘+++’ were grouped together as ‘moderate/severe’. These factors were assessed in relation to melanoma risk using logistic regression to obtain ORs and 95% confidence intervals: first unadjusted, then adjusted for age and sex, and then adjusted for skin phototype, hair color and freckles in childhood. Finally, all variables were adjusted for each other to find independent melanoma risk factors. As phenotypical variables (such as skin phototype, burning tendency, tanning ability, eye and hair color) are highly correlated (Gandini et al., 2005b), some of them were excluded based on chi-squared calculations to avoid multicollinearity: only skin phototype and hair color were included in the analyses. Sunburn frequency was categorized into tertiles based on the control distribution. Mann–Whitney U-test was used to compare Breslow thickness data between males and females. A two-sided P-value < 0.05 was considered statistically significant. All statistical analyses (including figures) were performed using IBM spss Statistics 19.0 (SPSS IBM Inc., Chicago, IL, USA).

Acknowledgements

  1. Top of page
  2. Summary
  3. Significance
  4. Introduction
  5. Results
  6. Discussion
  7. Methods
  8. Acknowledgements
  9. References
  10. Supporting Information

This study was supported by grants from the ‘Österreichische Nationalbank’ (Nr. 13036) and the ‘Hans und Blanca Moser Stiftung’. We would like to thank Andreas Ebner and Ulrike Sattler for photographing the participants and all participants who contributed to this study.

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  4. Introduction
  5. Results
  6. Discussion
  7. Methods
  8. Acknowledgements
  9. References
  10. Supporting Information
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[correction added after online publication February 14th 2012: figure 1 and its legend were replaced between online Early View and issue publication of this article]

Supporting Information

  1. Top of page
  2. Summary
  3. Significance
  4. Introduction
  5. Results
  6. Discussion
  7. Methods
  8. Acknowledgements
  9. References
  10. Supporting Information

Table S1. Signs of actinic damage in all participants.

Table S2. Signs of actinic damage (Controls who were diagnosed for NMSC were excluded).

Table S3. Age and sex characteristics (only cases diagnosed since 2007 were included).

Table S4. Signs of actinic damage (only cases diagnosed since 2007 were included).

Table S5. Diagnoses of the controls.

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PCMR_946_sm_table2.xls43KSupporting info item
PCMR_946_sm_table3.xls35KSupporting info item
PCMR_946_sm_table4.xls41KSupporting info item
PCMR_946_sm_table5.xls35KSupporting info item

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