Literature DB >> 30447006

Challenges in assessing the sunscreen-melanoma association.

Corina S Rueegg1, Jo S Stenehjem2, Matthias Egger3, Reza Ghiasvand1, Eunyoung Cho4,5,6, Eiliv Lund7, Elisabete Weiderpass2,7,8,9, Adele C Green10,11, Marit B Veierød1.   

Abstract

Whether sunscreen use affects melanoma risk has been widely studied with contradictory results. To answer this question we performed a systematic review of all published studies, accounting for sources of heterogeneity and bias. We searched for original articles investigating the sunscreen-melanoma association in humans to February 28, 2018. We then used random-effects meta-analysis to combine estimates of the association, stratified by study design. Stratified meta-analysis and meta-regression were used to identify sources of heterogeneity. We included 21,069 melanoma cases from 28 studies published 1979-2018: 23 case-control (11 hospital-based, 12 population-based), 1 ecological, 3 cohort and 1 randomised controlled trial (RCT). There was marked heterogeneity across study designs and among case-control studies but adjustment for confounding by sun exposure, sunburns and phenotype systematically moved estimates toward decreased melanoma risk among sunscreen users. Ever- vs. never-use of sunscreen was inversely associated with melanoma in hospital-based case-control studies (adjusted odds ratio (OR) = 0.57, 95%confidence interval (CI) 0.37-0.87, pheterogeneity < 0.001), the ecological study (rate ratio = 0.48, 95%CI 0.35-0.66), and the RCT (hazard ratio (HR) = 0.49, 95%CI 0.24-1.01). It was not associated in population-based case-control studies (OR = 1.17, 95%CI 0.90-1.51, pheterogeneity < 0.001) and was positively associated in the cohort studies (HR = 1.27, 95%CI 1.07-1.51, pheterogeneity = 0.236). The association differed by latitude (pinteraction = 0.042), region (pinteraction = 0.008), adjustment for naevi/freckling (pinteraction = 0.035), and proportion of never-sunscreen-users (pinteraction = 0·012). Evidence from observational studies on sunscreen use and melanoma risk was weak and heterogeneous, consistent with the challenges of controlling for innate confounding by indication. The only RCT showed a protective effect of sunscreen.
© 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.

Entities:  

Keywords:  melanoma; meta-analysis; skin cancer; sun protection; sunscreen

Mesh:

Substances:

Year:  2019        PMID: 30447006      PMCID: PMC6451658          DOI: 10.1002/ijc.31997

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


confidence interval grading of recommendations assessment, development and evaluation hazard ratio Nord Newcastle‐Ottawa scale odds ratio p Value randomised controlled trial rate ratio summary estimate sun protection factor United States of America ultraviolet

Introduction

Cutaneous melanoma is the leading cause of skin cancer death,1 accounting for 1–2% of all cancer deaths.2, 3 In 2015, melanoma occurred in 351,880 people and resulted in 59,782 deaths worldwide.4 The aetiology of cutaneous melanoma (hereafter termed melanoma) is a complex interaction of genetic, epigenetic and environmental risk factors.5, 6 Melanoma is mainly caused by ultraviolet (UV) radiation exposure in sun‐sensitive subjects and it is estimated that more than 85% of melanoma cases in Europe are attributed to sun exposure.7, 8, 9, 10 Genomic sequencing confirms that the majority of the mutations in melanomas are caused by UV radiation.11, 12 It follows that melanoma is preventable through reduction of UV exposure, making primary prevention highly cost‐effective.10, 13 Use of sunscreen is generally regarded as a major primary prevention measure alongside seeking shade, wearing protective clothes, and avoiding sunbeds,14, 15, 16, 17 and is a popular method of sun protection.18 However effectiveness of sunscreen to reduce UV‐induced damage to the skin has been proven only in experimental studies,19 and evidence of its effectiveness in preventing melanoma in humans is inconclusive. Only one randomised controlled trial (RCT) of daily sunscreen application to prevent skin cancer has been performed, showing a reduced risk of melanoma (hazard ratio = 0.50, p value = 0.051) in those randomly assigned to daily compared to discretionary sunscreen use.20, 21 The compliance to daily sunscreen application was approximately 75%; the majority of participants in the discretionary sunscreen group either did not apply sunscreen (38%) or applied at most once or twice a week (35%).21 All other studies of sunscreen and melanoma risk have been observational, mainly case–control, yielding contradictory results.22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 The main problem with investigating this question with observational studies is confounding by indication, i.e. sunscreen users tend to be more susceptible to melanoma and more exposed to the sun than non‐users a priori.41 The contradictory and heterogeneous results of previous systematic reviews reflect this problem.42, 43, 44, 45, 46, 47, 48 In the current study we aimed to overcome these known limitations by performing in‐depth statistical analyses, comparing different patterns of sunscreen use and identifying the major sources of heterogeneity. Furthermore we wanted to update the field with new evidence. Specifically, we aimed to 1) systematically summarise the existing literature on sunscreen use and melanoma in humans; 2) investigate the effect of ever‐ vs. never‐use on melanoma risk; 3) assess the effect of different levels and patterns of sunscreen use; 4) identify sources of bias and between‐study heterogeneity; and 5) describe the relationship between site of sunscreen application and site of melanoma.

Methods

The study protocol of this systematic review (PROSPERO ID: CRD4201706398049) was written according to PRISMA‐P50, 51 and the reporting in this article follows the PRISMA recommendations.52

Data sources and searches

We searched the electronic databases PubMed (including Medline), Embase and Cochrane Database of Systematic Reviews with search terms adapted for each of them (Supporting Information Appendix ). In addition, we searched the protocol database PROSPERO to identify relevant ongoing reviews and screen their reference lists. To ensure literature saturation we also screened the reference lists of relevant published reviews.

Study selection

We included all original articles published by 28.02.2018 in peer‐reviewed journals arising from case–control studies, ecological studies (population‐level rather than individual‐level observational studies), cohort studies, intervention studies and clinical trials performed in humans with melanoma as endpoint and sunscreen use as exposure. We only included studies where the exposure clearly preceded the outcome. We had no restrictions regarding length of follow‐up or language. Studies on childhood melanoma were included in the qualitative synthesis but excluded from the meta‐analyses because UV exposure does not seem to be a risk factor in the aetiology of melanoma occurring before 15 years of age.53 All records from the literature research were imported into EndNote (Thomson Reuters, version X8), de‐duplicated and then imported to Microsoft Excel (version 2010) to perform the selection process. Study selection was performed by two independent reviewers (CSR and JSS) by first screening titles and abstracts, then screening full texts. We calculated the proportion of agreement between the two reviewers for each of the two selection steps. Discrepancies were solved by discussion between the two reviewers. References were excluded based on the hierarchical exclusion criteria displayed in Figure 1 .
Figure 1

Flow diagram on inclusion of studies. The figure shows the process of selecting eligible studies for the current review and meta‐analysis. [Color figure can be viewed at wileyonlinelibrary.com]

Flow diagram on inclusion of studies. The figure shows the process of selecting eligible studies for the current review and meta‐analysis. [Color figure can be viewed at wileyonlinelibrary.com]

Data extraction and quality assessment

Data were extracted using a data extraction form54 (Supporting Information Appendix ) after piloting the process with three studies of different design and publication year. Data extraction was performed by CSR and the estimates of interest were double‐checked by MBV. Discrepancies were discussed among a subgroup of the authors until consensus was reached. We contacted study authors and requested the estimate of interest if it was not reported but the respective analysis was described. If necessary, additional articles from the same study were used to complete data extraction. For each study we extracted the following estimates on the association of sunscreen use and melanoma, if reported: a) ever‐ vs. never‐use of sunscreen from minimally adjusted model; b) ever‐ vs. never‐use of sunscreen from maximally adjusted model; c) three‐level estimate of sunscreen use from maximally adjusted models for frequency of use, sun protection factor (SPF) used and duration of use (Supporting Information Table 1). The minimally and maximally adjusted model was the model with no or only basic adjustment and the model with most variables included, respectively, in the original study. We chose the ever‐ vs. never‐use label because most underlying studies analysed ever‐ vs. never‐use or use vs. no use of sunscreen based on their questionnaires. In addition, we extracted bibliographic and demographic information of the studies, assessment of sunscreen use, and study quality to identify sources of heterogeneity. Study quality was assessed based on the Cochrane Handbook‘s tool for assessing risk of bias54 and the Newcastle‐Ottawa Scale (NOS).55 Level of bias (high, medium, low) was rated by the data extractor (CSR) after reading the methods part of the study and blinded toward the study results.

Data synthesis and analysis

All analyses were performed in STATA (StataCorp LP, Release 14.1). In the analysis of ever‐ vs. never‐use of sunscreen we used the method of Hamling and colleagues to aggregate estimates if more than two categories of sunscreen use were reported.56 For example, if a study reported an estimate with three categories of sunscreen use: never, sometimes, and often, we aggregated ‘sometimes’ and ‘often’ into ever‐use. This was done to make the estimates across studies more comparable. Without this aggregation we would end up pooling estimates across studies where some estimates reflected the effect of the highest sunscreen category vs. no sunscreen use, while others reflected ever‐ vs. never use. The same method was used to change the reference category, if necessary. To investigate three‐level, different patterns and high sunscreen use, we extracted all estimates with at least three categories on frequency of sunscreen use, SPF used, and duration of use. For each study, the lowest and highest categories were categorised as lowest and highest groups, respectively and all intermediate categories were aggregated.57 We performed random‐effects meta‐analysis58 stratified by study design for the minimally and maximally adjusted estimates of ever‐ vs. never‐use of sunscreen, and for each three‐level variable on sunscreen use, comparing the intermediate to the lowest level and the highest to the lowest level. Heterogeneity between studies was tested with the Q‐test.59 The I2‐index was used to quantify the extent of heterogeneity, with I2‐values >50%, and > 75% being indicative of moderate and high heterogeneity, respectively.54 We included one case‐cohort study that was analysed together with the cohort studies because it was conducted prospectively. To explore sources of heterogeneity we performed random‐effects meta‐analyses stratified by important variables predefined in the protocol, and univariable random‐effects meta‐regression analyses, on the maximally adjusted ever‐ vs. never‐use estimate. We considered the following variables: study design; year of the end of the data collection (1975–1984, 1985–1999, 2000–2012); mean latitude (>42°N, ≤42°N); region; most frequent melanoma site in the study population (trunk, head/neck, lower limbs); duration of sunscreen use (not specified, specified period, lifetime); whether sunscreen use was assessed in detail or not; level of bias (high, medium, low); whether or not the estimate of interest was adjusted for nevi and/or freckles, history of sunburn, or sun exposure; and, the proportion of participants with blond/red hair (<30%, ≥30%), blue/green eyes (<50%, ≥50%), history of sunburn (<75%, ≥75%), and who never used sunscreen (<55%, ≥55%). The cut‐offs in the proportions were chosen based on the distribution of the respective characteristic across the studies. We used tau‐squared to estimate the remaining between‐study variance in the meta‐regression model by residual maximum likelihood.58 Publication bias was investigated by the funnel plot and Egger's regression test for the maximally‐adjusted ever‐never estimates.60 We used contour‐enhanced funnel plots to define regions of the plot in which a new study would have to be located to change the statistical significance of the meta‐analysis and thereby assess the robustness of the current meta‐analysis.61

Grading of the evidence

The confidence in the cumulative evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system.62 GRADE rates the quality of evidence across the domains risk of bias, consistency, directness, precision, and publication bias and rates it into one of the four categories high (further research is very unlikely to change our confidence in our effect estimate), moderate (further research is likely to change our confidence in our effect estimate), low (further research is very likely to change our effect estimate), or very low (our effect estimate is very uncertain).

Results

We identified 3,414 records in the three databases Pubmed (n = 1,054), Embase (n = 2,132), and Cochrane (n = 228), of which 761 were duplicates and 2,552 were rated as ineligible on first screening by two reviewers (agreement = 95%; Fig. 1). Eleven studies were identified through other sources resulting in the assessment of 112 full‐texts, of which 84 (agreement = 89%) were excluded, leaving 28 studies included in the qualitative synthesis and 27 studies in the meta‐analysis after exclusion of the childhood melanoma study.32

Characteristics of included studies

The 28 articles (11 hospital‐based case–control studies,22, 23, 31, 33, 34, 35, 37, 39, 63, 64, 65 12 population‐based case–control studies,24, 25, 26, 27, 28, 29, 30, 32, 36, 38, 40, 66 one ecological study,67 three cohort studies (one of them a case‐cohort study),68, 69, 70 and one RCT21) were published between 1979 and 2018, included 208 to 178,155 participants and 33 to 11,535 melanoma cases: in total, 21,069 melanoma cases, who originated from Australia (n = 4), Europe (n = 16), Brazil (n = 2) and the USA (n = 6; Table 1). The median latitude of the study locations was 43°N (range − 30°S‐65°N). On average, 21% of participants (range 9–61%) were blond or red‐haired, 47% (range 19–86%) blue or green eyed, 48% (range 28–70%) had freckles, and 55% (range 24–85%) were fair‐skinned (Supporting Information Table 2). Most studies only assessed sunscreen use or sunscreen use frequency (Table 1). Fourteen studies defined a timeframe for the sunscreen use,21, 24, 25, 29, 32, 35, 36, 38, 40, 63, 65, 66, 67, 68 eight studies assessed the SPF used,21, 35, 36, 37, 39, 40, 66, 69 three the reapplication,40, 65, 66 three the body sites or body coverage,21, 36, 40 two the product used,35, 69 two the thickness,21, 40 and one study the reasons for sunscreen use.36
Table 1

Overview of the studies included (n = 28)

First author (year)Data collectionCountryMatching1 Total no. of participantsNo. of casesProportion of males (%)Age range at dx (mean)Sunscreen information assessed2
Hospital‐based case–control studies
Klepp (1979)22 1974–1975NorwayUnmatched2097861>20 (nr)Questionnaire: sunscreen use frequency during solar irradiation
Graham (1985)23 1974–1980USAUnmatched420218100nr (nr)Interview: sunscreen use
Ródenas (1996)31 1989–1993SpainUnmatched2431053520–79 (52)Interview: sunscreen use frequency
Wolf (1998)33 1993–1994AustriaUnmatched5121934218–89 (54)Questionnaire: sunscreen use frequency before formation of melanoma
Espinosa A. (1999)34 1990–1994SpainIndividual (age, sex)3511164721–87 (56)Questionnaire: sunscreen use
Naldi (2000)35 1992–1995ItalyUnmatched1,08054242nr (nr)Interview: sunscreen use frequency and duration, product type used, SPF used
Bakos (2002)37 1995–1998BrazilIndividual (age, sex, Ethnic group, region)309103nr20–84 (53)Questionnaire: sunscreen use, SPF used
Nikolaou (2008)64 2000–2004GreeceIndividual (age, sex)4002004919–84 (53)Interview: sunscreen use
Klug (2010)39 1991–1992USAFrequency (age, sex, Ethnic group, study site)1,6627175520–79 (nr)Interview: sunscreen use, sunscreen use ≥8 SPF, regular use ≥8 SPF
Luiz (2012)63 2004–2008BrazilFrequency (age, sex)4242025015–79 (48)Interview: sunscreen use frequency in childhood, lifetime sunscreen use frequency
Vranova (2012)65 2010–2011Czech RepublicFrequency (age)51821646nr (54)Questionnaire: sunscreen use frequency in childhood, sunscreen use frequency in adulthood, number of sunscreen applications when sunbathing
Population‐based case–control studies
Holman (1986)24 1980–1981AustraliaIndividual (age, sex, electoral subdivision)1,0145074610–79 (nr)Interview: sunscreen use frequency and duration
Østerlind (1988)25 1982–1985DenmarkFrequency (age, sex)1,4004744120–79 (52)Interview: sunscreen use frequency and duration
Beitner (1990)26 1978–1983SwedenIndividual (age, sex)1,02852345nr (nr)Questionnaire: sunscreen use frequency
Herzfeld (1993)27 1982–1983USAUnmatched739324100>18 (nr)Interview: sunscreen use frequency
Autier (1995)28 <1990France, Germany, BelgiumIndividual (municipality)856418nrnr (nr)Questionnaire: sunscreen use
Holly (1955)29 nrUSAFrequency (age)1,382452025–59 (42)Questionnaire: sunscreen use frequency in 5 years previously
Westerdahl (1995)30 1988–1990SwedenIndividual (age, sex, parish)1,0404004915–75 (nr)Questionnaire: sunscreen use frequency when spending time in the sun
Whiteman3 (1997)32 1994AustraliaIndividual (sex, school, grade)20852nr3–14 (nr)Questionnaire: sunscreen use frequency at school and on holidays in childhood
Westerdahl (2000)36 1995–1997SwedenIndividual (age, sex, parish)1,4495585016–80 (nr)Questionnaire: sunscreen use frequency, regular use, age at first use, SPF used, body parts applied, reasons for sunscreen use
Youl4 (2002)38 1987–1994AustraliaIndividual (age, sex, region)4062015015–19 (17)Interview: sunscreen use frequency at school, at home, on holidays for ages 5–10, 10–15, ≥15 years
Lazovich (2011)40 2004–2009USAFrequency (age, sex)2,2681,1674025–59 (nr)Interview: lifetime sunscreen use frequency during outdoor activities, SPF used, thickness applied, amount of skin covered, reapplication, routine use
Savoye (2018)66 1989–2008FranceIndividual (age, birth county, education)1,2193660nr (57)Questionnaire: sunscreen use at ages <15, 15–25, >25 years, SPF used, re‐application
Prospective ecological study
Kojo (2006)67 1920–1985Finlandna11,53511,53547nr (nr)Sales of sunscreen preparations 5 and 10 years before diagnosis
Prospective cohort studies
Cho (2005)68 1976–2000USAna178,1555 5355 325 nr (53)Questionnaire: sunscreen use frequency at the pool or beach as a teenager and in the past summer
Ghiasvand (2016)69 1991–2012Norwayna143,844722042–83 (60)Questionnaire: sunscreen use in low and high latitudes, SPF used, brands of sunscreen used
Stenehjem6 (2017)70 1999–2012Norwayna1,75511210033–84 (58)Questionnaire: present sunscreen use frequency
Randomised controlled trial
Green (2011)21 1992–2006Australiana1,6213344nr (nr)Intervention to daily apply sunscreen on head, neck, arms and hands, weight of returned sunscreen bottles, questionnaire on weekly sunscreen use frequency

Abbreviations: dx, diagnosis; na, not applicable; nr, not reported; no., number; SPF, sun protection factor.

Only relevant for case–control studies; variables given as reported in the underlying article.

This column gives an overview of the sunscreen information assessed in the study. The detailed descriptions of the sunscreen estimates used in the meta‐analyses are given in Table 2 and Supporting Information Table 4.

Sunscreen and melanoma in childhood.

Sunscreen and melanoma in adolescence.

Data received upon author request with some differences to the article cited.

Case‐cohort study design.

Overview of the studies included (n = 28) Abbreviations: dx, diagnosis; na, not applicable; nr, not reported; no., number; SPF, sun protection factor. Only relevant for case–control studies; variables given as reported in the underlying article. This column gives an overview of the sunscreen information assessed in the study. The detailed descriptions of the sunscreen estimates used in the meta‐analyses are given in Table 2 and Supporting Information Table 4.
Table 2

Description of the two‐level estimates extracted for each study (described exactly as reported in the articles)

First author (Publ. year)Estimate reported in the publicationAggregated1 two‐level estimateEffect measureMinimally adjusted estimate (95% CI)Adjustment of minimally adjusted estimate2 Maximally adjusted estimate (95% CI)Adjustment of maximally adjusted estimate2
Hospital‐based case–control studies
Klepp (1979)22 Use of any kind of sun lotion/oil during solar irradiation: almost never ‐ very rarely ‐ sometimes ‐ quite often ‐ alwaysUse of any kind of sun lotion/oil during solar irradiation: almost never ‐ everOR2.05 (1.06–4.03)Nonenr
Graham (1985)23 Use of sun screening lotion: no ‐ yesUse of sun screening lotion: no ‐ yesOR2.20 (1.20–4.10)Agenr
Ródenas (1996)31 Sunscreen use: never ‐ sometimes ‐ alwaysSunscreen use: never ‐ everOR0.38 (0.20–0.70)None0.43 (0.21–0.90)Age, skin colour, skin type, recreational sun exposure, occupational sun exposure, nevi
Wolf (1998)33 Use of sunscreens: never ‐ rarely ‐ oftenUse of sunscreens: never ‐ everOR1.74 (1.18–2.57)Age, sex2.15 (1.37–3.37)Age, sex, skin colour, sunbaths, sunburns
Espinosa A. (1999)34 Use of sunscreens: no ‐ yesUse of sunscreens: no ‐ yesOR0.38 (0.28–0.63)3 None0.45 (0.33–0.67)3 Skin type, freckles, age
Naldi (2000)35 Sunscreen use: never ‐ sometimes ‐ oftenSunscreen use: never ‐ everOR1.14 (0.89–1.45)None0.90 (0.68–1.18)Age, sex, demographic area, education, skin colour, eye colour, hair colour, freckles, nevi, sunburns, tanning pattern, sunny holiday weeks per year
Bakos (2002)37 Sunscreen use habit: never ‐ SPF <8, SPF 8–15, SPF 15+Sunscreen use habit: never ‐ ever (all SPF)OR0.46 (0.29–0.74)3 None0.34 (0.18–0.63)3 Eye colour, hair colour, photo‐ type, freckles, nevi, dysplastic nevi, physical protection, sunburn
Nikolaou (2008)64 Sunscreen use: never/rarely ‐ during summer/sunny monthsSunscreen use: never/rarely ‐ during summer/sunny monthsOR0.56 (0.34–0.90)Conditional regression0.37 (0.14–0.98)Age, gender, phototype, skin colour, outdoor leisure activities, weeks/year of sun exposure, sunburns <20 years of age, common nevi, atypical nevi, lentigenes
Klug (2010)39 Sunscreen use: no use ‐ ever useSunscreen use: no use ‐ ever useOR1.05 (0.82–1.35)Matched logistic regression analysis0.90 (0.70–1.19)Gender, age, study site, Ethnic group, ambient resident UV, hours outdoors, tan type, sunburns, gender, age group, study site
Luiz (2012)63 Lifetime sunscreen use: never/almost never ‐ occasionally ‐ modified ‐ oftenLifetime sunscreen use: never/almost never ‐ everOR0.53 (0.22–1.24)Age, sex, education0.34 (0.11–1.01)Age, sex, education, ethnicity, eye colour, history of pigmented lesion removal, sunburns age 5–19, severe lifetime sunburns
Vranova (2012)65 Use of the sunscreen in the adulthood: never ‐ occasionally ‐ regularlyUse of the sunscreen in the adulthood: never ‐ everOR0.63 (0.36–1.12)4 None0.19 (0.09–0.43)4 Freckles/nevi, sunburns in childhood, sunscreen in childhood, sunbathing in adulthood, sun exposure, time of day of sun exposure, holidays at seaside, holidays in mountains, solarium use
Population‐based case–control studies
Holman (1986)24 Use of sunscreens: never ‐ <10 years ‐ ≥10 yearsUse of sunscreens: never ‐ everORnr1.11 (0.82–1.49)Age, sex, electoral subdivision, chronic and acute skin reaction to sunlight, hair colour, ethnic origin, age at arrival in Australia
Østerlind (1988)25 Use of sunscreens: never ‐ <10 years ‐ ≥10 yearsUse of sunscreens: never ‐ everOR1.23 (0.98–1.55)4 Nonenr
Beitner (1990)26 Employment of sun protection agents: never ‐ rarely ‐ often/very oftenEmployment of sun protection agents: never ‐ everORnr1.59 (1.17–2.15)3 Age, sex, hair colour
Herzfeld (1993)27 Using sunscreens: no ‐ yesUsing sunscreens: no ‐ yesOR0.81 (0.58–1.12)Nonenr
Autier (1995)28 Regular sunscreen use: never ‐ everRegular sunscreen use: never ‐ everOR1.59 (1.18–2.14)Conditional regression1.50 (1.09–2.06)Age, sex, hair colour, holiday weeks in sunny resorts, municipality
Holly (1995)29 Use of sunscreen 5 years before diagnosis: never ‐ sometimes ‐ almost alwaysUse of sunscreen 5 years before diagnosis: never ‐ everOR0.67 (0.51–0.87)4 None0.52 (0.37–0.73)Sunburns ≤12 years, skin reaction to sun, hair colour, nevi, complexion, maternal ethnicity, history of skin cancer, age
Westerdahl (1995)30 Use of sunscreens: never ‐ sometimes ‐ almost always Use of sunscreens: never ‐ ever OR 1.65 (1.24–2.20) Matched analysis 1.47 (1.08–2.01) Sunburns, sunbathing in summer, outdoor employment in summer, nevi, hair colour, eye colour, freckling, age, gender, parish
Whiteman5 (1997)32 Sunscreen use at school: never/rarely ‐ sometimes ‐ often ‐ alwaysSunscreen use at school: never/rarely ‐ everOR1.73 (0.97–3.08)Matched analysis1.01 (0.50–2.05)Tanning ability, freckling, nevi, sex, school, grade
Westerdahl (2000)36 Use of sunscreens: never ‐ sometimes ‐ always initially of the year then sometimes ‐ alwaysUse of sunscreens: never ‐ everOR1.35 (1.08–1.69)Conditional regression1.30 (0.90–1.90)Hair colour, sunburns, sunbathing in summer, duration of sunbathing, age, sex, parish
Youl6 (2002)38 Average lifetime index of sunscreen use at home: never/rarely ‐ sometimes ‐ often/alwaysAverage lifetime index of sunscreen use at home: never/rarely – everOR1.05 (0.63–1.74)Conditional regressionnr
Lazovich (2011)40 Routine sunscreen use: nonusers in both decades ‐ middle ‐ high in both decadesRoutine sunscreen use: nonusers in both decades ‐ users in both decadesOR1.33 (0.91–1.95)Age, gender1.12 (0.78–1.62)Age, gender, phenotype risk score, moles, income, education, family history, sunburns, sun exposure, solarium use
Savoye (2018)66 Sunscreen use since age 25: no protection ‐ SPF <8 ‐ SPF 8–15 ‐ SPF >15Sunscreen use since age 25: no protection ‐ SPF <8/SPF 8‐15/SPF >15OR1.71 (1.29–2.27)Conditional regression1.50 (1.10–2.06)Skin sensitivity, nevi, freckling, eye colour, skin colour, hair colour, hours of recreational sun exposure, recreational UV score, sunburns >25 years, age, birth county, education
Prospective ecological study
Kojo (2006)67 Rate ratio for CM per 1 euro increase per capita in sunscreen salesRate ratio per 1 euro increase per capita in sunscreen salesRRnr0.48 (0.35–0.66)Age, gender, 10 year lag time, sunny resort holidays, holiday duration
Prospective cohort studies
Cho7 (2005)68 Percent of time of sunscreen use when outside at the pool or beach in the past summer: 0–25 ‐ 50 ‐ 75 ‐ 100Percent of time sunscreen used outside at the pool or beach in past summer: 0 ‐ ≥25HR1.66 (1.41–1.96)Age1.42 (1.21–1.68)Age, alcohol consumption, sunburns, childhood reaction to sun, hair colour, smoking, BMI, exercise, UV flux, moles, caffeine, family history of CM
Ghiasvand (2016)69 Sunscreen use from time‐dependent analysis: never ‐ everSunscreen use from time‐dependent analysis: never ‐ everHR1.45 (1.11–1.90)Age, calendar year1.13 (0.85–1.50)Age, calendar year, hair colour, freckles, ambient UV, weeks sunbathing, sunburns, solarium use
Stenehjem8 (2017)70 Present sunscreen use: never/rarely ‐ often ‐ almost alwaysPresent sunscreen use: never/rarely ‐ often/almost alwaysHR1.11 (0.69–1.76)Age1.10 (0.77–1.57)Age, benzene exposure, education
Randomised controlled trial
Green (2011)21 Random assignment to daily or discretionary sunscreen application to head and arms Sunscreen application to head and arms: daily ‐ discretionaryHR0.50 (0.24–1.02)0.49 (0.24–1.02)Sex, skin type, nevi, history of cancer, sun exposure

Abbreviations: BMI, body mass index; CI, confidence interval; CM, cutaneous melanoma; HR, hazard ratio; nr, not reported; OR, odds ratio; Publ., publication; SPF, sun protection factor; RR, rate ratio; RCT, randomised controlled trial; UV, ultraviolet.

If sunscreen exposure was reported in more than two categories they were aggregated into two categories (ever‐ vs. never‐use).

As reported by the authors.

Estimate from individual‐matched case–control study that did not take the matching into account in the statistical analysis, or did not report it.

Estimate from frequency‐matched case–control study that did not adjust for the matching variables in the statistical analysis, or did not report it.

Sunscreen and melanoma in childhood.

Sunscreen and melanoma in adolescence.

Estimates received upon author request because they were not reported in the cited article.

Case‐cohort study design.

Sunscreen and melanoma in childhood. Sunscreen and melanoma in adolescence. Data received upon author request with some differences to the article cited. Case‐cohort study design.

Methodological quality of included studies

The methodological quality of the case–control studies was very heterogeneous with 11 hospital‐based case–control studies based on non‐representative cases and controls (Supporting Information Table 3). The ecological study, cohort studies and RCT fulfilled almost all of the methodological requirements.54, 55 The method and detail of assessment of sunscreen use also varied greatly between the studies (Table 2); the same was true for the level of adjustment of the “maximally‐adjusted” estimate, though most studies adjusted in some way for UV exposure and some host factors of participants. Description of the two‐level estimates extracted for each study (described exactly as reported in the articles) Abbreviations: BMI, body mass index; CI, confidence interval; CM, cutaneous melanoma; HR, hazard ratio; nr, not reported; OR, odds ratio; Publ., publication; SPF, sun protection factor; RR, rate ratio; RCT, randomised controlled trial; UV, ultraviolet. If sunscreen exposure was reported in more than two categories they were aggregated into two categories (ever‐ vs. never‐use). As reported by the authors. Estimate from individual‐matched case–control study that did not take the matching into account in the statistical analysis, or did not report it. Estimate from frequency‐matched case–control study that did not adjust for the matching variables in the statistical analysis, or did not report it. Sunscreen and melanoma in childhood. Sunscreen and melanoma in adolescence. Estimates received upon author request because they were not reported in the cited article. Case‐cohort study design.

Ever sunscreen use and melanoma risk

The forest plot of minimally‐adjusted estimates showed substantial heterogeneity both within hospital‐based (I 2 = 86%, p < 0.001) and population‐based case–control studies (I 2 = 80%, p < 0.001), and between the different study designs (Fig. 2).
Figure 2

Forest plot for ever‐ vs. never‐use of sunscreen and melanoma risk, minimally adjusted estimates stratified by study design. The figure shows the forest plot for melanoma risk comparing ever‐ vs. never‐use of sunscreen for all studies that reported a minimally adjusted estimate, stratified by study design. The estimates of the case–control studies are reported in odds ratios with 95% confidence intervals (CIs); and, the estimates of the cohort studies and the RCT as hazard ratios with 95% CIs. Minimal adjustment of some estimates (e.g. age and sex) and exact definition of the estimates is described in Table 2. Abbreviations: CI, confidence interval; ES, effect size; RCT, randomised controlled trial. * Not ever‐ vs. never‐use of sunscreen; see Table 2 for the exact definition of the estimate. **Case‐cohort study. [Color figure can be viewed at wileyonlinelibrary.com]

Forest plot for ever‐ vs. never‐use of sunscreen and melanoma risk, minimally adjusted estimates stratified by study design. The figure shows the forest plot for melanoma risk comparing ever‐ vs. never‐use of sunscreen for all studies that reported a minimally adjusted estimate, stratified by study design. The estimates of the case–control studies are reported in odds ratios with 95% confidence intervals (CIs); and, the estimates of the cohort studies and the RCT as hazard ratios with 95% CIs. Minimal adjustment of some estimates (e.g. age and sex) and exact definition of the estimates is described in Table 2. Abbreviations: CI, confidence interval; ES, effect size; RCT, randomised controlled trial. * Not ever‐ vs. never‐use of sunscreen; see Table 2 for the exact definition of the estimate. **Case‐cohort study. [Color figure can be viewed at wileyonlinelibrary.com] The forest plot of maximally‐adjusted estimates showed that adjustment moved most estimates toward a more reduced risk of melanoma among sunscreen users (Figs. 2 and 3) though substantial heterogeneity remained (Fig. 3), especially within case–control studies (I 2 = 86%, p < 0.001 for hospital‐based; 81%, p < 0.001 for population‐based) but also between study designs. We found an inverse sunscreen‐melanoma association in hospital‐based case–control studies (summary odds ratio (OR) = 0.57, 95%CI 0.37–0.87), the ecological study (rate ratio (RR) = 0.48, 95%CI 0.35–0.66), and the RCT (hazard ratio (HR) = 0.49, 95%CI 0.24–1.01). No association was found on summarising results from population‐based case–control studies (OR = 1.17, 95%CI 0.90–1.51) and a positive sunscreen‐melanoma association was seen on summarising the three cohort studies (HR = 1.27, 95%CI 1.07–1.51).
Figure 3

Forest plot for ever‐ vs. never‐use of sunscreen and melanoma risk, maximally adjusted estimates stratified by study design. The figure shows the forest plot for melanoma risk comparing ever‐ vs. never‐use of sunscreen for all studies that reported a maximally adjusted estimate, stratified by study design. The estimates of the case–control studies are reported as odds ratios with 95% confidence intervals (CIs); the estimates of the cohort studies and the RCT as hazard ratios with 95% CIs; and, the estimate of the ecological study as rate ratio with 95% CI. Adjustment and exact definition of the estimates is described in Table 2. Abbreviations: CI, confidence interval; ES, effect size; RCT, randomised controlled trial. *Not ever‐ vs. never‐use of sunscreen; see Table 2 for the exact definition of the estimate. **Case‐cohort study. [Color figure can be viewed at wileyonlinelibrary.com]

Forest plot for ever‐ vs. never‐use of sunscreen and melanoma risk, maximally adjusted estimates stratified by study design. The figure shows the forest plot for melanoma risk comparing ever‐ vs. never‐use of sunscreen for all studies that reported a maximally adjusted estimate, stratified by study design. The estimates of the case–control studies are reported as odds ratios with 95% confidence intervals (CIs); the estimates of the cohort studies and the RCT as hazard ratios with 95% CIs; and, the estimate of the ecological study as rate ratio with 95% CI. Adjustment and exact definition of the estimates is described in Table 2. Abbreviations: CI, confidence interval; ES, effect size; RCT, randomised controlled trial. *Not ever‐ vs. never‐use of sunscreen; see Table 2 for the exact definition of the estimate. **Case‐cohort study. [Color figure can be viewed at wileyonlinelibrary.com]

Three‐level estimates of sunscreen use and melanoma risk

Sixteen studies reported at least a three‐level estimate on the frequency of sunscreen use (never, sometimes, often/always),22, 24, 25, 26, 29, 30, 31, 33, 35, 36, 38, 40, 63, 68, 69, 70 six studies distinguished low from high SPF sunscreen use (compared to no use),35, 36, 37, 40, 66, 69 and four studies distinguished short‐ from long‐term use of sunscreen (compared to no use)24, 25, 35, 36 (Supporting Information Table 4). We did not observe a trend or U‐shaped association comparing the intermediate‐ and high‐users of sunscreen to the non‐users for each of the three‐level estimates (Supporting Information Fig. 1). The summary estimates comparing sometimes‐ to never‐use were 1.07 (95%CI 0.80–1.42) in the hospital‐based case–control studies, 1.13 (95%CI 0.98–1.30) in the population‐based case–control studies, and 1.38 (95%CI 1.17–1·62) in the cohort studies. The summary estimates comparing often/always‐ to never‐use were 1.01 (95%CI 0.38–2.67) in the hospital‐based case–control studies, 1.01 (95%CI 0.67–1.52) in the population‐based case–control studies, and 1.32 (95%CI 1.10–1.59) in the cohort studies (Supporting Information Fig. 1A).

Sources of heterogeneity

The association between sunscreen use and melanoma from stratified analyses is presented in Table 3 and Supporting Information Figure 2. Studies conducted in lower latitudes showed an inverse association between sunscreen use and melanoma (summary estimate = 0.64, 95%CI 0.47–0.89 for studies ≤42°N) but there was no association in studies from higher latitudes (summary estimate = 1.09, 95%CI 0.83–1.44, p interaction = 0·042). Further statistically significant interactions were observed between the association of sunscreen use and 1) the region of the study (p interaction = 0.008); 2) adjustment for nevi and/or freckles (with an inverse association only in studies adjusting; p interaction = 0.035); and, 3) the proportion of sunscreen users in the study (with an inverse association of sunscreen use and melanoma only in studies where ≥55% of participants never used sunscreen; p interaction = 0.012). Remaining between‐study variance was generally high after all stratifications (0.131 ≤ tau‐squared ≤ 0.492).
Table 3

Association between sunscreen use and melanoma from stratified analyses

No1 Estimate95% CI p 2 Tau2 3
Study design0.0690.221
Hospital‐based case–control studies90.570.37–0.87
Population‐based case–control studies81.170.91–1.51
Ecological study10.480.35–0.66
Cohort studies31.271.07–1.51
Randomised controlled trial10.490.24–1.01
Year of the end of data collection0.3194 0.320
1975–198421.330.93–1.89
1985–1999100.860.61–1.21
2000–201290.820.60–1.13
Mean latitude of the study0.0420.248
> 42° N111.090.83–1.44
≤ 42° N110.640.47–0.89
Region of the study0.0080.131
Northern Europe61.100.78–1.57
Northern America40.890.59–1.34
Eastern Europe10.190.09–0.42
Western Europe31.611.32–1.97
Southern Europe40.550.33–0.89
Southern America20.340.20–0.59
Australia20.790.36–1.74
Most frequent melanoma site0.8250.256
Trunk80.720.49–1.05
Head/neck30.930.57–1.54
Lower limbs20.740.29–1.90
Duration of sunscreen use0.4820.313
Not specified (general habit)110.940.69–1.28
Specified period100.810.60–1.10
Lifetime10.340.11–1.03
More detailed assessment than “sunscreen yes‐no”0.4930.319
No (only sunscreen yes‐no)100.930.66–1.32
Yes (more than sunscreen yes‐no)120.800.60–1.05
Level of bias0.8840.345
High60.760.42–1.40
Medium120.840.64–1.12
Low41.020.73–1.41
Adjusted for nevi/freckling0.0350.238
No81.250.99–1.56
Yes140.690.51–0.92
Adjusted for history of sunburn0.5870.323
No60.950.63–1.44
Yes160.820.64–1.05
Adjusted for sun exposure0.2530.295
No60.640.38–1.09
Yes160.950.77–1.18
Proportion with blond/red hair0.1500.411
< 30%100.650.44–0.97
≥ 30%31.240.80–1.93
Proportion with blue/green eyes0.3260.492
< 50%70.570.35–0.93
≥ 50%40.930.48–1.79
Proportion with history of sunburn0.4060.429
< 75%60.620.33–1.15
≥ 75%70.980.72–1.31
Proportion of never5 sunscreen user0.0120.164
< 55%131.030.83–1.28
≥ 55%40.420.32–0.55

Abbreviations: CI, confidence interval; No, number; p, p value.

Number of studies in each group.

p Value for interaction from univariable meta‐regression model.

Remaining between‐study variance estimated by residual maximum likelihood.

p Value for trend.

A few studies included rare sunscreen users in the “never user” category. See Table 2 for the exact definition of the sunscreen variable.

Association between sunscreen use and melanoma from stratified analyses Abbreviations: CI, confidence interval; No, number; p, p value. Number of studies in each group. p Value for interaction from univariable meta‐regression model. Remaining between‐study variance estimated by residual maximum likelihood. p Value for trend. A few studies included rare sunscreen users in the “never user” category. See Table 2 for the exact definition of the sunscreen variable.

Site of sunscreen application and site of melanoma

Two studies21, 36 assessed the body site of sunscreen application but neither related this to the site of melanoma.

Meta bias and quality of the cumulative evidence

The funnel plot (Supporting Information Fig. 3) shows the effect estimates from the individual studies against the precision of the studies (standard error in reversed scale), placing the largest studies toward the top. In the absence of bias and between‐study heterogeneity, the plot would have resembled a symmetric inverted funnel, while our plot showed evidence of asymmetry confirmed by an Egger's test for small‐study effects (p = 0.010). The funnel plot with contours of statistical significance (Supporting Information Fig. 4) shows which combinations of effect size and standard error would be required in an additional study, to change or maintain the statistical significance of the current summary estimate. In our meta‐analysis, the plot showed that all of the current studies were lying in the area where future studies (if lying in the same area) would change the current effect estimate toward a significantly positive association between sunscreen use and melanoma risk (significant effect estimate >1). The GRADE assessment resulted in an overall very low quality of evidence from the case–control studies, ecological study and cohort studies, and in a moderate quality of evidence from the RCT (Supporting Information Table 5).

Discussion

We assessed the sunscreen‐melanoma association in 21,068 melanoma patients based on 28 studies in this comprehensive systematic review. The main body of evidence came from observational studies with high between‐study heterogeneity. We found an inverse association between sunscreen use and melanoma in hospital‐based case–control studies, the ecological study and the RCT. There was no association in the population‐based case–control studies and positive association between sunscreen use and melanoma in the cohort studies. No clear pattern resulted when comparing the few studies that reported three‐level estimates of sunscreen use regarding frequency of use, SPF of sunscreen used or duration of use. The association between sunscreen use and melanoma differed by latitude, region, adjustment for nevi/freckling, and proportion of never sunscreen users.

Comparison with previous meta‐analyses

Our study is the first systematic review and meta‐analysis to present results from four different study designs, the first to include five prospective studies, and the first to stratify the case–control studies into hospital‐based and population‐based studies. Five meta‐analyses of the association of sunscreen use and melanoma have been published (in 200243, 200344, 200745, 201546, and 201848). Only Dennis and colleagues (2003)44 aggregated three‐level estimates of sunscreen use into ever‐ vs. never‐use, as we did, but the final estimate (pooled OR = 1.0, 95%CI 0.8–1.2, from 18 case–control studies) was unadjusted for confounding factors. Consistent with our findings, they showed that adjustment moved estimates toward a reduced risk of melanoma in sunscreen users, by pooling only the nine studies that adjusted for sun sensitivity (OR = 0.8, 95%CI 0.6–1.0).44 Similar to our approach, Dennis and colleagues tried to go beyond “ever‐use” of sunscreen and pooled 12 case–control studies that reported at least a three‐level estimate on the frequency of sunscreen use (aggregated by ordered regression models) but found no association.44 Despite high heterogeneity, the other four meta‐analyses pooled results using quite different definitions of sunscreen use into one estimate (for example always‐ vs. never‐use and ever‐ vs. never‐use), across very different study designs or different types of skin cancer, and across estimates from adjusted and unadjusted models. The earliest meta‐analysis (2002)43 included 11 case–control studies but pooled only the four registry‐based, resulting in no association (OR = 1.01). Gorham and colleagues (2007)45 included 17 case–control studies with a pooled OR = 1.2 (95%CI 0.9–1.6). Similar to our review, they found statistically significant interaction with study latitude. Xie and colleagues (2015)46 included 21 studies and calculated a summary estimate of 1.15 (95%CI 0.91–1.44; I2 = 84%, p heterogeneity < 0.001). This review46 also tried to identify sources of heterogeneity by meta‐regression but found no significant interactions. The most recent meta‐analysis (2018)48 included 30 studies but only 25 were related to melanoma. They included only two prospective studies compared to five in our review, included cross‐sectional study designs and calculated a summary estimate despite high heterogeneity (summary estimate = 1.08, 95%CI 0.91–1.29, including melanoma and other skin cancers). It is not possible to directly compare the aggregated estimates of association from these previous meta‐analyses with our sorted and stratified estimates.

Interpretation of results

When interpreting our results, we needed to account for the different levels of evidence of the study designs included in our meta‐analyses. In the hierarchy of strength of evidence, ecological studies are the weakest, and cohort studies and RCTs are the strongest.71 Our funnel plot showed small‐study effects, meaning that the results in small studies differed from the results in large studies. We suspect that this funnel plot asymmetry is due to poor methodological quality in small studies rather than publication bias.60 This supports the fact that our results need to be interpreted taking the methodological quality and level of evidence into account as was done in the GRADE assessment. Careful interpretation of the results of the observational studies is essential because of their multiple methodological limitations when assessing the sunscreen‐melanoma association: recall bias (in the case–control studies); ecological fallacy (in the ecological study, where we do not know whether the specific individuals who used sunscreen were those with lower incidence of melanoma because the association was measured at the population level); difficulty in meaningfully assessing sunscreen use by ad hoc questionnaires; and, by far the most concerning, residual confounding since the determinants of sunscreen use and melanoma (susceptibility to sunburn and high sun exposure) are almost inseparable in observational studies.41 Furthermore, in their large population‐based cohort study,69 Ghiasvand and colleagues found significant differences between sunscreen users and non‐users in regard to phenotype and sun exposure. Our review highlights the profound influence of residual confounding by showing that increasing adjustment systematically moved effect estimates toward a more reduced risk of melanoma among sunscreen users. The problems incorporated in observational studies have also led to an overall very low quality of evidence in the GRADE rating.72 To overcome this problem we suggest performing cohort studies that also explore reasons for sunscreen use and non‐use, and how sunscreen users’ behaviour differs from that of non‐users,73 or analysing cohort studies using newer statistical methods (for example inverse probability weighting of using sunscreen) that can adjust for confounding by indication and mimic an RCT design.74 In observational studies, “treatment selection” (sunscreen use in our case) is often influenced by subject characteristics. As a result, baseline characteristics of subjects using sunscreen differ systematically from those not using sunscreen. A propensity score such as inverse probability weights is the probability of using sunscreen conditional on observed baseline characteristics. Applying such weights allows one to analyse an observational (nonrandomized) study so that it mimics an RCT by balancing the distribution of observed baseline covariates between sunscreen users and non‐users.75 The strongest existing evidence comes from the one RCT, as suggested by the pyramid of evidence.76 The RCT was performed in an Australian population with high year‐round sun exposure and skin cancer awareness.21, 77 There is therefore a need for additional high‐quality, large RCTs in countries of higher latitude, but these are highly unlikely to be conducted because of ethical constraints (vulnerable study participants cannot be denied regular use of sunscreen) and the need to enrol extremely large numbers of participants in order to prospectively assess the rare outcome of melanoma.19 However, future RCTs could examine intermediate endpoints (biomarkers, genetic mutations) to improve the evidence‐base for sunscreen use.19 Because of the imprecise definition of ever‐ vs. never‐use of sunscreen and highly variable assessment of sunscreen use across studies, we compared the studies reporting at least three‐levels and different patterns of sunscreen use. Unfortunately very few studies reported such estimates, and therefore we could not provide evidence about what pattern of use would be most effective and whether there is a discernible trend with increasing frequency of sunscreen use. We generally observed that very few studies assessed sunscreen use behaviour in depth such as exploring thickness of sunscreen applied, re‐application or proportion of body covered with sunscreen. Such information would be crucial to assess in future research in relation to melanoma risk since we know that most people do not apply sunscreen properly.78, 79 Of further concern is the high heterogeneity between studies that could not be fully explained by the variables we investigated in the meta‐regression analysis (see also heterogeneity between study participants in Supporting Information Table 2). We found a more protective effect of sunscreens in lower latitudes and Southern countries. This might be due to sun exposure being more homogeneous in these studies (everybody is exposed to some degree) and to sunscreen use being regarded as a routine preventive measure rather than being regarded as a means to prolong sun exposure by some at higher latitudes.80, 81 It would therefore be important to distinguish between studies where sunscreen was used for intentional sun exposure and tan acquisition versus for protection from sun damage. This was not possible with currently available evidence. Also, people from lower and higher latitude might differ in their interpretation of frequencies of sunscreen use. For example higher latitude participants might consider “often” using sunscreen means applying on sunny days, whereas lower latitude participants may think of “often” using sunscreen as daily application. We further found an inverse association between sunscreen use and melanoma in studies where the estimate was adjusted for number of naevi and/or freckling, while no association was found in studies without such adjustment. This might be due to the fact that number of naevi/freckling are especially important predictors of melanoma,82 and self‐reported assessment of number of naevi/freckling as confounding factor might be more valid than other factors (e.g. sun exposure or sunburns long time ago).83, 84 We found an inverse association of sunscreen use and melanoma in studies with a high proportion of never sunscreen users. This makes sense because of a better contrast between sunscreen users and non‐users, revealing the effect of sunscreen in populations where the majority is not using it.

Strengths and limitations

This systematic review has several strengths. Compared to previous reviews, it adds several new studies and study designs, including three large cohort studies, and performs in‐depth statistical analyses. We have extracted a variety of descriptive variables to identify sources of heterogeneity. To make the sunscreen variable as comparable as possible between studies, we attempted to aggregate or transform the estimates into ever‐ vs. never‐use of sunscreen in order to combine the studies, but this inherited the weakness that the sunscreen measure was very broad, further obscuring any true effect of sunscreen. Other limitations include the relatively low number of eligible studies, especially intervention studies and studies reporting three‐level estimates on sunscreen use, the difference in study designs, and the between‐study heterogeneity. Because of the high heterogeneity we could not calculate an overall summary estimate. Due to the limited number of studies we could not perform multivariable meta‐regression analysis, and were forced to collapse the meta‐regression and stratified meta‐analysis over the different study designs. Also, we could not identify enough studies to answer our last research question on a possible relationship between body sites of sunscreen application and of melanoma. Furthermore, we used the label ever‐ vs. never‐use because never or no use were the terms mostly used in the original studies included in the meta‐analysis. This might be somewhat misleading as the never‐users probably include some who used sunscreen rarely.

Conclusion

We found overall weak and heterogeneous published evidence for an association between sunscreen use and melanoma. Observational studies showed an inverse association in hospital‐based case–control studies and the ecological study, no association in population‐based case–control studies and a positive association in the three cohort studies. A protective effect of sunscreen was found in the only RCT performed. We therefore advocate for studies examining intermediate (biological) endpoints to be used in high‐quality RCTs. The effectiveness of sunscreen to reduce UV radiation to the skin has been proven after acute exposure in human studies and in experimental studies.19 In our review, this translated into a reduced melanoma risk in the long‐term for only some studies and we attribute this to residual confounding of observational studies and the misuse of sunscreen to increase rather than decrease sun exposure in some high latitude populations. Public health recommendations should place greater emphasis on the proper use of sunscreen (for sun protection vs. to prolong time in the sun) in conjunction with other means of sun protection. Supplemental Figure 1 Forest plot comparing three levels of sunscreen use (no – medium – high) and melanoma risk, stratified by study design Supplemental Figure 2: Sources of heterogeneity: forest plot of summary estimates from stratified meta‐analyses Supplemental Figure 3: Funnel plot and Egger's regression to estimate publication bias Supplemental Figure 4: Funnel plot with statistical significance contours Click here for additional data file. Supplemental Table 1 Rules applied to choose the minimally and maximally adjusted estimate to be included in the meta‐analysis Supplemental Table 2: Skin cancer related characteristics of participants in the studies included (n = 28) Supplemental Table 3: Description of the methodological quality of the studies included (n = 28) Supplemental Table 4: Description of the three‐level estimates extracted for each study (described exactly as reported in the articles)* Supplemental Table 5: GRADE evidence profile for sunscreen use and melanoma risk, stratified by study design Click here for additional data file. Appendix S1: Supporting Information Click here for additional data file. Appendix S2: Supporting Information Click here for additional data file.
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Authors:  L Naldi; S Gallus; G L Imberti; T Cainelli; E Negri; C La Vecchia
Journal:  Int J Cancer       Date:  2000-06-15       Impact factor: 7.396

2.  Malignant melanoma: aetiological importance of individual pigmentation and sun exposure.

Authors:  H Beitner; S E Norell; U Ringborg; G Wennersten; B Mattson
Journal:  Br J Dermatol       Date:  1990-01       Impact factor: 9.302

3.  Meta-analysis in clinical trials.

Authors:  R DerSimonian; N Laird
Journal:  Control Clin Trials       Date:  1986-09

4.  Risk factors and individual probabilities of melanoma for whites.

Authors:  Eunyoung Cho; Bernard A Rosner; Diane Feskanich; Graham A Colditz
Journal:  J Clin Oncol       Date:  2005-04-20       Impact factor: 44.544

5.  Phenotypic markers, sunlight-related factors and sunscreen use in patients with cutaneous melanoma: an Austrian case-control study.

Authors:  P Wolf; F Quehenberger; R Müllegger; B Stranz; H Kerl
Journal:  Melanoma Res       Date:  1998-08       Impact factor: 3.599

Review 6.  Melanoma Epidemiology and Prevention.

Authors:  Marianne Berwick; David B Buller; Anne Cust; Richard Gallagher; Tim K Lee; Frank Meyskens; Shaily Pandey; Nancy E Thomas; Marit B Veierød; Sarah Ward
Journal:  Cancer Treat Res       Date:  2016

7.  Comparison of melanoma incidence and trends among youth under 25 years in Australia and England, 1990-2010.

Authors:  Sarah C Wallingford; Michelle R Iannacone; Danny R Youlden; Peter D Baade; Alexander Ives; Julia Verne; Joanne F Aitken; Adèle C Green
Journal:  Int J Cancer       Date:  2015-05-29       Impact factor: 7.396

8.  Sunscreen prevention of melanoma in man and mouse.

Authors:  Heather L P Klug; Janet A Tooze; Cari Graff-Cherry; Miriam R Anver; Frances P Noonan; Thomas R Fears; Margaret A Tucker; Edward C De Fabo; Glenn Merlino
Journal:  Pigment Cell Melanoma Res       Date:  2010-08-20       Impact factor: 4.693

9.  13. Cancers attributable to solar (ultraviolet) radiation exposure in the UK in 2010.

Authors:  D M Parkin; D Mesher; P Sasieni
Journal:  Br J Cancer       Date:  2011-12-06       Impact factor: 7.640

10.  New evidence pyramid.

Authors:  M Hassan Murad; Noor Asi; Mouaz Alsawas; Fares Alahdab
Journal:  Evid Based Med       Date:  2016-06-23
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  9 in total

Review 1.  The efficacy and safety of sunscreen use for the prevention of skin cancer.

Authors:  Megan Sander; Michael Sander; Toni Burbidge; Jennifer Beecker
Journal:  CMAJ       Date:  2020-12-14       Impact factor: 8.262

2.  Sex Differences in Melanoma.

Authors:  Matthew Robert Schwartz; Li Luo; Marianne Berwick
Journal:  Curr Epidemiol Rep       Date:  2019-05-31

3.  Cutaneous malignant melanoma incidence is strongly associated with European depigmented skin type regardless of ambient ultraviolet radiation levels: evidence from Worldwide population-based data.

Authors:  Wenpeng You; Renata Henneberg; Brendon J Coventry; Maciej Henneberg
Journal:  AIMS Public Health       Date:  2022-03-17

4.  An Ecological Study Indicates the Importance of Ultraviolet A Protection in Sunscreens.

Authors:  Samar Merhi; Pascale Salameh; Peter Kaplan; Shayak Banerjee; Mohamed Lajnef; Emmanuel L P Dumont; Khaled Ezzedine
Journal:  Acta Derm Venereol       Date:  2021-06-28       Impact factor: 3.875

5.  Effect of a Skin Self-monitoring Smartphone Application on Time to Physician Consultation Among Patients With Possible Melanoma: A Phase 2 Randomized Clinical Trial.

Authors:  Fiona M Walter; Merel M Pannebakker; Matthew E Barclay; Katie Mills; Catherine L Saunders; Peter Murchie; Pippa Corrie; Per Hall; Nigel Burrows; Jon D Emery
Journal:  JAMA Netw Open       Date:  2020-02-05

Review 6. 

Authors:  Megan Sander; Michael Sander; Toni Burbidge; Jennifer Beecker
Journal:  CMAJ       Date:  2021-03-08       Impact factor: 8.262

Review 7.  Towards a paradigm shift in environmental health decision-making: a case study of oxybenzone.

Authors:  Klara Matouskova; Laura N Vandenberg
Journal:  Environ Health       Date:  2022-01-08       Impact factor: 5.984

8.  Sunscreens With High Versus Low Sun Protection Factor and Cutaneous Squamous Cell Carcinoma Risk: A Population-Based Cohort Study.

Authors:  Simon Lergenmuller; Reza Ghiasvand; Trude E Robsahm; Adele C Green; Eiliv Lund; Corina S Rueegg; Marit B Veierød
Journal:  Am J Epidemiol       Date:  2022-01-01       Impact factor: 4.897

9.  Laboratory testing of sunscreens on the US market finds lower in vitro SPF values than on labels and even less UVA protection.

Authors:  David Q Andrews; Kali Rauhe; Carla Burns; Emily Spilman; Alexis M Temkin; Sean Perrone-Gray; Olga V Naidenko; Nneka Leiba
Journal:  Photodermatol Photoimmunol Photomed       Date:  2021-10-19       Impact factor: 3.254

  9 in total

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