Cutaneous Melanin Density of Caucasians Measured by Spectrophotometry and Risk of Malignant Melanoma, Basal Cell Carcinoma, and Squamous Cell Carcinoma of the Skin
Terence Dwyer1,
Leigh Blizzard1,
Rosemary Ashbolt1,
Juliet Plumb1,
Marianne Berwick2 and
James M. Stankovich1
1 Menzies Centre for Population Health Research, University of Tasmania, Hobart, Tasmania, Australia.
2 Memorial Sloan-Kettering Cancer Center, New York, NY.
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ABSTRACT
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Recent advances have enabled quite accurate estimation by spectrophotometry of the density of cutaneous melanin. The relation between skin cancers and this objective measure of skin phenotype is examined here. For this purpose, a population-based case-control study of subjects aged 2059 years of northern European ancestry was conducted in Tasmania, Australia. Cases (n = 244) of cutaneous malignant melanoma during 19981999, and a sample of cases of basal cell carcinoma (n = 220) and squamous cell carcinoma (n = 195) of the skin were identified from cancer registrations. Controls (n = 483) were selected from a comprehensive population listing. Melanin at the upper inner arm was estimated from skin reflectance of light of 400 and 420 nm wavelengths. For melanoma, basal cell carcinoma, and squamous cell carcinoma, respectively, the odds ratios comparing the least with the highest of four melanin categories were 6.2 (95% confidence interval (CI): 2.3, 16.6), 6.3 (95% CI: 2.6, 15.1), and 4.2 (95% CI: 1.7, 10.8) for men and 1.9 (95% CI: 1.0, 3.7), 1.4 (95% CI: 0.7, 3.0), and 0.7 (95% CI: 0.3, 1.7) for women. The gender differences were not due to disparities in site of occurrence or (for melanoma) in thickness of the lesion. The authors conclude that, particularly for men, cutaneous melanin density at the upper inner arm is a strong predictor of risk of skin cancer.
case-control studies;; melanins;; melanoma;; population;; skin neoplasms
Abbreviations:
BCC, basal cell carcinoma of the skin;; CI, confidence interval;; CMM, cutaneous malignant melanoma;; ICD-9, International Classification of Diseases, Ninth Revision;; SCC, squamous cell carcinoma
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INTRODUCTION
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Previous research on the etiology of cutaneous malignant melanoma (CMM), basal cell carcinoma (BCC), and squamous cell carcinoma (SCC) has suggested that skin phenotype and sun exposure are independent contributors to risk. The very large, measured differences in risk between persons of African and European descent, for example, provide strong evidence for the importance of skin phenotype. However, in research involving measures of phenotype in the population group most at risk of skin cancer, those of northern European descent, only weak associations have been detected. This may reflect a lack of precision in the measures of phenotype that have been available or that the wrong measure of phenotype was chosen.
The commonly used markers for skin phenotype have been eye, hair, and skin color. The various measures of skin color have included self-report, interviewer appraisal using skin tone charts or prosthesis (1
3
) or by personal assessment (4
), and skin reflectance of light at the infrared end of the visible light spectrum (5
). These phenotype properties have been selected for research because they appear to be markers for the biologic differences that distinguish northern Europeans from lower risk populations. While the biologic basis for these measures has not usually been made explicit, it is likely that they have been used as proxies for the density or type of melanin in the skin.
We recently reported that melanin density in the epidermis could be estimated quite accurately using a spectrophotometer (6
). The calculation is based on the difference in reflectance by the skin of wave bands of light centered at 400 and 420 nm. The correlation coefficient for linear association of spectrophotometric measure of melanin and the histopathologic measurement of melanin for the upper inner arm was r = 0.68.
The association of nevi in adolescents with this spectrophotometric measure of cutaneous melanin density has since been investigated (7
). The risk estimates we obtained for melanin density were higher than those for other commonly used measures of phenotype such as hair or eye color and were also higher than those for melanin type estimated from hair samples.
In this report, we describe the relation between cutaneous malignancy and skin phenotype assessed using this direct measure of cutaneous melanin density. The study sample consisted of 659 cases of malignant melanoma and nonmelanocytic skin cancer and 483 community controls aged 2059 years of northern European ancestry.
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MATERIALS AND METHODS
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Subjects
The study population consisted of subjects aged 2059 years of northern European ancestry who were residents of Tasmania, Australia, and who had never been diagnosed previously with a histologically confirmed CMM. The study population was limited to the predominant ethnic group in Tasmania (approximately 90 percent trace their ancestry to the British Isles), which is the group at highest risk of skin cancer. The restriction to those never diagnosed with CMM was made to limit recall bias in reporting of previous sun exposure. Recruitment procedures and study protocols were approved by the Human Research Ethics Committee of the University of Tasmania.
Melanoma cases.
There were 285 cases (119 males and 166 females) of histologically confirmed primary in situ and invasive CMM (International Classification of Diseases, Ninth Revision (ICD-9) code 172) identified from registrations by the Tasmanian Cancer Registry for the period January 1, 1998, to December 31, 1999, and 258 were interviewed. After interview, 13 cases were excluded as not being of northern European ancestry (n = 7) or having previously been diagnosed with CMM (n = 6). The response from eligible cases was 90.1 percent (245 of 272).
Nonmelanoma skin cancer cases.
Histologically confirmed cases of BCC (ICD-9 code 173; International Classification of Diseases for Oncology code 80903) and SCC (ICD-9 code 173; International Classification of Diseases for Oncology code 80703) were sampled from registrations by the Tasmanian Cancer Registry for the period April 1, 1998, to March 31, 1999. They were selected at random from within strata of 5-year age group, sex, and month of diagnosis to approximately match the historical age, sex, and monthly incidence of CMM cases. This was done so that all cases could be compared with the common set of controls. In practice, all cases younger than age 35 years (BCC), 50 years (SCC males), or 60 years (SCC females) were included. When there were multiple diagnoses on the same selected date, each different lesion was recorded separately.
There were 268 cases of BCC selected, and 238 were interviewed. After interview, 14 cases were excluded as not being of northern European ancestry (n = 12) or having previously been diagnosed with CMM (n = 2). The response from eligible BCC cases was 88.2 percent (224 of 254).
There were 240 cases of SCC selected, and after exclusion of two persons noted on the pathology form as having had an organ transplant, 211 were interviewed. After interview, 12 cases were excluded as not being of northern European ancestry (n = 6) and/or having previously been diagnosed with a CMM (n = 8). The response from eligible SCC cases was 88.1 percent (199 of 226).
Controls.
Controls were selected from the roll of registered electors, a comprehensive listing of the population maintained by the State Electoral Office of Tasmania. They were selected at random from within strata of 5-year age groups and frequency matched to CMM cases. Selection as a control did not preclude subsequent inclusion as a case (8
). One control was also subsequently included as a SCC case, and another was subsequently included also as a CMM case.
In total, 644 persons were selected. Of these, 25 were not approached because they had been diagnosed with a CMM (n = 9), were men with southern European or Asian surnames (n = 10), lived on one of the small islands (n = 2), and/or had been interviewed as a BCC or SCC case (n = 6). Among the remainder, 503 were interviewed. After interview, 13 persons were excluded as either not being of northern European ancestry (n = 12) or being age 60 years (n = 1). The response from eligible controls was 80.7 percent (490 of 607).
Measurements
Cutaneous melanin.
The estimation of melanin density from skin reflectance was based on previous results (6
). Skin reflectance was measured with a handheld Minolta 508 spectrophotometer (Minolta Camera Company, Ltd., Osaka, Japan) (figure 1). The equation used was:
where MD400 is an estimate of the percentage of the epidermis of the skin at the upper inner arm that contains melanin, and R400 and R420 denote the averages of three measurements of reflectance at 400 and 420 nm made at that site, respectively. Approximately 2 percent of the estimates in this sample took small negative estimated values, but we did not truncate at zero. As evidence of the high reproducibility of measurements made by a single measurer, the percentage of total variation in MD400 in this sample attributed to within-person variation in the three measurements was 0.7 percent (intraclass correlation = 0.99, calculated from a one-way random effects model using formula R1 of reference 9
). The melanin measurements are also reproducible by different measurers. In a study of 20 subjects each measured by two of the research assistants responsible for spectrophotometric measurements at our institution, the measurers accounted for only 2.1 percent of the variance in MD400 (intraclass correlation = 0.98 for the average of three measurements, calculated from a two-way random effects model using formula R3 of reference 9
).

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FIGURE 1. Spectrophotometric assessment of cutaneous melanin density, Tasmania, Australia, 19981999. The handheld Minolta 508 spectrophotometer is shown in A. It was used to measure reflectance by the skin of wave bands of light centered at 400 and 420 nm, from which density of cutaneous melanin was estimated. B and C are views of 4 µm sections of skin biopsies fixed in 10 percent phosphate-buffered formalin, embedded in paraffin, and stained using the Mason Fontana method for melanin. The view in B is from a subject with relatively little melanin in the basal layers. The subject in C has more melanin.
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Other measurements of skin reflectance were made at the top of the buttocks (another unexposed site) and, for about half of the subjects, on the fleshy part of the upper aspect of the hand nearest the thumb (an exposed site). Melanin density at those other sites was calculated in the same way from R400 and R420 at those sites.
Other study factors. The research assistants assessed eye color, and subjects completed a standardized, interviewer-administered questionnaire, which included questions on ethnicity of grandparents, natural hair color, skin type (10
) by self-assessment, and usual sun exposure and outdoor activities as a child, teenager, and adult. The questions on skin type asked about skin reaction to unaccustomed sun, tendency to burn when in the sun, and end-of- vacation tan. The questions on sun exposure were based on the two questions that were established, using polysulphone badge readings as the comparison method, to be the most reliable and valid measures of habitual sun exposure by teenagers in this climate (11
). They asked about time spent in the sun each day during vacations or weekends and frequency of outdoor activities.
Data analysis
Excluded from data analysis were three subjects with skin conditions (epidermoid bullosa, xeroderma pigmentosum, and psoriasis), six subjects who had a renal transplant, five subjects who had recently used a solarium, one case with CMM who had a chemically induced tan on the arm, and one control who reported changes in skin color from medication with prednisolone for a liver complaint. These exclusions reduced the data set to 244 CMM cases, 220 BCC cases, 195 SCC cases, and 483 controls.
Spearman rank correlation coefficients were calculated as measures of association. Odds ratio estimates of the relative risks of skin cancer (CMM, BCC, or SCC) were estimated by logistic regression for categories of density of cutaneous melanin (MD400), and 95 percent confidence intervals were calculated from the standard errors of the estimated coefficients of the binary (zero of one) predictors used. Tests of trend were undertaken by replacing the three binary predictors with a single linear predictor, taking rank scores for the four categories. Binary (zero of one) predictors were included for the 5-year age-groups used in matching other than the two youngest age groups (the age groups 3034 and 3539 years were combined as the reference group because of paucity of numbers). To adjust for self-reported sun exposure, we added a linear predictor taking rank scores for the categories given in the questionnaire to the regression model.
In site-specific analyses, lesions were classified by whether they had occurred on generally exposed sites (head, neck, and limbs, including the feet) or on the trunk. Because some cases had multiple lesions of the same type at different sites, one CMM case and 11 BCC cases were included in analyses as both a head, neck, and limb lesion and a trunk lesion.
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RESULTS
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Several characteristics of the samples of cases and controls are summarized in table 1. The study samples varied somewhat in age, with the group of SCC cases, in particular, containing fewer younger subjects. The density of cutaneous melanin (MD400) at the upper inner arm correlated with measures of skin type and most strongly with end-of-summer tan graded from "dark tan" to "practically no tan" (male controls: r = -0.44, p < 0.01; female controls: r = -0.56, p < 0.010).
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TABLE 1. Characteristics of participants in the case-control study of cutaneous malignant melanoma, basal cell carcinoma and squamous cell carcinoma of the skin in Tasmania, Australia, 19981999
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The case groups differed from the control groups in measures of skin phenotype, including MD400. Male cases had less melanin at the upper inner arm and buttocks than did male controls. For women, the differences were significant only for CMM cases at the upper inner arm and SCC cases at the buttocks. There were no differences in the mean concentrations of melanin at the dorsum of the hand, an exposed site.
Odds ratio estimates of the relative risk for categories of arm melanin are shown in table 2. The odds ratios shown in the top panel of the table are adjusted only for age, the matching factor. The associations with lower levels of melanin for men are strong, with clear evidence of dose response. For women, the risk estimates are much lower.
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TABLE 2. Age-adjusted odds ratios of cutaneous malignant melanoma, basal cell carcinoma, and squamous cell carcinoma of the skin, for density of cutaneous melanin at the upper inner arm, Australia, 19981999
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The lack of a strong association for women may be due to negative confounding by sun exposure. This could happen if the fairer subjects, who are most at risk, avoided the sun. There was some evidence of this in our data. Measurements of melanin on the dorsum of the hand, an exposed site, were available for 406 cases and 319 controls. The distributions of values for the 158 male and 161 female controls are shown in figure 2. The means were almost identical (both 3.8 percent), but more of the women had very high or very low values, and the variance was 2.21 times greater (p < 0.01) for women than for men. In comparison, the variation in arm melanin values for the women in this sample was 1.07 times that of the men, and the difference was not significant (p = 0.66).

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FIGURE 2. Distribution of hand melanin among controls in the Tasmanian case-control study of melanoma and nonmelanoma skin cancer, Tasmania, Australia, 19981999.
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Adjustment for one measure of sun exposuretime spent outdoors on activities as a teenager or an adult ("sun activities")nevertheless produced only minor increases in the estimated risks of skin cancer (table 2). The increases using other measures of sun exposure, or measures of sun exposure for other periods of life, were less. The increase in risk on adjustment was greatest for BCC and SCC because the sun activities measure was linearly associated with increased risk of BCC (men, p = 0.24; women, p < 0.01) and SCC (men, p < 0.01; women, p = 0.02). It was not associated with risk of CMM (men, p = 0.53; women, p = 0.35).
Table 3 shows the effect estimates for some of the other measures of phenotype that have been used in skin cancer research. The highest risk estimates were those for MD400 among men. Only for inability to tan, which was reported by only 12 male controls, did an alternative measure of phenotype produce a higher risk estimate, and then it was only for male cases of BCC. The relative risk estimates were generally lower for women, and none of the measures of their phenotype had a consistent advantage over the others.
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TABLE 3. Adjusted odds ratios of cutaneous malignant melanoma, basal cell carcinoma, and squamous cell carcinoma of the skin, for extreme categories of measures of phenotype, Australia, 19981999
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To this point, we have presented data for all body sites combined. However, the distribution of skin cancers by body site differed for men and women. To examine whether the differences in the effect estimates for men and women were due to factors associated with body site, the odds ratios for CMM and BCC were calculated separately for lesions located on generally exposed sites (head, neck, and limbs) and those on the trunk. For men, the odds ratios comparing the extreme categories of MD400 were 5.5 (95 percent confidence interval (CI): 1.7, 18.1) for CMM, 6.6 (95 percent CI: 2.3, 19.0) for BCC on the head, neck, and limbs, 7.3 (95 percent CI: 1.5, 35.0) for CMM, and 5.5 (95 percent CI: 1.7, 18.2) for BCC on the trunk. For women, the odds ratios were 1.9 (95 percent CI: 0.9, 3.7) for CMM, 1.3 (95 percent CI: 0.5, 3.1) for BCC on the head, neck, and limbs, and 2.6 (95 percent CI: 0.6, 11.2) for CMM and 1.5 (95 percent CI: 0.6, 3.8) for BCC on the trunk. There were too few SCC on the trunk of men (n = 7) or women (n = 13) to make meaningful comparisons.
For CMM, we were able to examine the risk estimates for lesions of different thickness. In this sample, 38 percent (90 of 240) of the lesions with a Clark's level classification were in situ lesions. Combining them with 49 other lesions less than 0.5 mm in thickness (40 of 49 of these were Clark's level 2), the odds ratios were calculated separately for lesions less than 0.5 mm in thickness and those at least 0.5 mm in thickness. The results are shown in figure 3. The relative risk estimates were higher for the thicker lesions, but the gender difference in relative risk was maintained because similar percentages of male (39 percent (39 of 100)) and female (43 percent (60 of 141)) cases had lesions less than 0.5 mm in diameter.

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FIGURE 3. Odds ratio estimates of relative risk of melanoma for cutaneous melanin density (percent), classified by thickness of lesion, Tasmania, Australia, 19981999.
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DISCUSSION
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This is the first direct evidence that melanin density of the skin is a determinant of risk of melanoma and nonmelanocytic skin cancer. Our data show that cutaneous melanin density at the upper inner arm is a strong predictor of risk for all three types of skin cancer, particularly in males. The strength of the association was greater than those found previously in the high-risk group of northern European descent for the phenotype measures of eye or hair color or the various previous measures of skin color used in research on humans. Studies conducted in Denmark (3
), Canada (1
), the United Kingdom (12
, 13
), and Australia (2
, 14
, 15
), where the subjects were principally of northern European extraction, have produced odds ratios in the range of 1.03.0 for these previously used markers of phenotype.
Particularly for males, the data here suggest that the objective measure of melanin density we have developed (6
) is a stronger predictor than are those more subjective measures. The dose-response effects found further support the inference that the association is causal. It was also a stronger predictor than were measures of skin type, based on questions that form the basis of the Fitzpatrick classification (10
), the measure most commonly used by dermatologists. In addition, the link is one that has biologic plausibility. Melanin does have the capacity to absorb ultraviolet light, and it is found in greater density in the skin of racial groups that have the lowest incidence of skin cancers (16
).
The weaker association found between melanin density and risk of each skin cancer in women cannot be explained by differences in site of occurrence or thickness of lesions. However, it might be due to negative confounding with sun exposure. The distribution of hand melanin for women compared with that of men suggests a wider range of sun exposure by women. That very fair women might have less sun exposure than very fair men is supported by data we obtained from Tasmanian adolescents, showing that fairer females avoided the sun more than did males of similar skin phenotype (11
). However, in this study we were unable to remove the differences in risk between males and females by adjusting for their self-reported sun exposure. This leaves the possibility that there are biologic differences in the pathogenesis of skin cancers in men and women involving other causes or differences in skin response to ultraviolet radiation.
This demonstration that melanin density measured noninvasively by spectrophotometry at the skin's surface can predict risk of skin cancer, particularly melanoma, has important research implications. This new, objective measure is free from observer bias and errors associated with recall. Previous measures of skin phenotype used in epidemiologic studies have either been subjective or, if apparently objective, only weakly associated with risk. Some have been shown to be influenced by past experience of sun exposure, making them unsuitable in research where the goal is to separate the effects of sun exposure from phenotype or, alternatively, to estimate how phenotype modifies the effect of sun exposure (17
). This new measure appears to provide significant advantages for use in future research in this field.
It is also conceivable that the spectophotometric measure of cutaneous melanin could have a clinical application. High-risk persons could be identified in a valid and reproducible way and given advice on sun avoidance appropriate to their risk status. A determination of its predictive value in other populations would be desirable because in this study we examined its use in a population that included only persons of northern European descent.
A further issue remaining is whether this phenotype measure will prove to be preferable to measures of genotype for clinical screening or for use in research. A study by Valverde et al. (18
) has shown that the presence of mutations in the MC1R gene is associated with an increase in risk of melanoma. The odds ratio estimate was 3.9:1, suggesting that measure of this genotype does not have advantages (for males, at least) in prediction of risk over measurement of the melanin density phenotype using our methods. It is considerably more costly. Further development in genotyping may provide additional advantages.
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ACKNOWLEDGMENTS
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The National Health and Medical Research Council of Australia funded this study. Financial assistance with the program of research was received from The Medical Benefits Fund of Australia Limited, a registered health benefits organization.
The authors acknowledge the contribution of Dr. Anne-Louise Ponsonby, who commented on an earlier version of this paper. They thank also the research nurses who undertook the field measurements.
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NOTES
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Reprint requests to Prof. Terence Dwyer, Menzies Centre for Population Health Research, University of Tasmania, GPO Box 25223, Hobart 7001; Australia (e-mail: T.Dwyer{at}utas.edu.au).
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Received for publication December 22, 2000.
Accepted for publication September 26, 2001.