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. 2022 Apr 17;12(5):1167–1179. doi: 10.1007/s13555-022-00720-2

Table 1.

Characteristics of included studies

Studies OR Study period Region Study design Age (years) Sex Participants Cancer Statistical analysis Adjustments NOS score
Milán et al. [9] 1.1 1976–1999 Finland Cohort study  ≥ 18 Male and female 666 BCC Conditional logistic regression analysis NA 8
Ming et al. [10] 0.85 1998–2001 USA Case–control study 66.4 versus 60.1* Male: 51.3% versus 39.9% 4591 NMSC Multivariable logistic regression Age, sex, topical steroid use, and ethnicity 7
Hagströmer et al. [7] 1.5 1965–1999 Sweden Cohort study 15.7* Male and female 15,666 NMSC, melanoma χ2 test NA 7
Olesen et al. [26] 2.4 1977–1996 Denmark Cohort study NA Male and female 6275 NMSC Poisson regression methods NA 7
Synnerstad et al. [27] 0.49 1986–2004 Sweden Cohort study 2.6 (5.5) to 39.3 (10.9)* Male and female 6280 Melanoma Poisson regression analysis Age group, sex, and year 8
Arana et al. [28] 1.74 1992–2006 UK Retrospective cohort study All ages Male and female 4,518,131 Melanoma, NMSC Mantel–Haenszel Age and sex 7
El-Zein et al. [11] 0.64 1979–1985 Canadian Case–control study 35–70 Males 3809 Melanoma Logistic regression Age, income, respondent status, ancestry, and sports and/or outdoor activities 6
Janković et al. [12] 4.17 2006–2007 Montenegro Case–control study NA Female 200 BCC Multivariate logistic regression analysis Age, sex, and marital status 7
Dyer et al. [13] 1.54 NA USA Cohort study Median age 72 Female 34 (3%) versus male 1097 (97%) 1131 BCC Multiple logistic regression Sex, age, education, basal cell carcinomas in prior 5 years, squamous cell carcinomas in prior 5 years, actinic keratoses at baseline, family history of skin cancer, current or former smoker 8
Jensen et al. [6] 0.59 1977–2006 Denmark Cohort study NA Male and female 31,330 Melanoma, BCC, SCC Byar’s approximation NA 8
Hajdarbegovic et al. [14] 1.05 2000–2010 Netherlands Case–control study 57 ± 14 versus 56 ± 14* Male and female 353 Melanoma Logistic multiple regression analysis Unadjusted OR 7
Cheng et al. [15] 1.83 NA USA Case–control study 25–74 Female 1312 SCC Multiple logistic regression Age, gender, and skin reaction to the first hour of sunlight during summer (blister, painful sunburn followed by peeling, mild sunburn followed by tanning, tanning with no sunburn) 8
1.52 NA USA Case–control study 25–74 Female NA BCC Multiple logistic regression Age, gender, and skin reaction to the first hour of sunlight during summer (blister, painful sunburn followed by peeling, mild sunburn followed by tanning, tanning with no sunburn) 8
Marasigan et al. [16] 0.46 NA Belgium Case–control study 57.4* for controls, 52.2* for cases Male and female 232 Melanoma Conditional logistic regression Age, sex, sunburn sensitivity, hair color, number of moles, sunburn as juvenile, ever sunbed use, familial melanoma 8
Cho et al. [8] 1.75 1996–2010 USA Case–control study 69.6 (13.5) versus 69.5 (13.5)* Female 1179 SCC Logistic regression analysis Race, smoking history, ionizing radiation exposure, corticosteroid and cyclosporine use, non-SCC skin cancers, odds ratio for SCC development 9
D'Arcy et al. [17] 1.07 1992–2013 USA Case–control study 66–99 Female 1,844,575 Melanoma Logistic regression analysis Sex, age, race, calendar year of selection, and measures of socioeconomic status and healthcare utilization 7
Mansfield et al. [31] 0.96 1998–2016 UK Cohort study 41.1 [24.9–60.7] versus 39.8 [25.9–58.4]# Female 2,711,745 Melanoma Cox proportional hazards regression model Sex, primary care practice, date, and age 8
1.1 1998–2016 UK Cohort study 41.1 [24.9–60.7] versus 39.8 [25.9–58.4]# Female NA NMSC Cox proportional hazards regression model Sex, primary care practice, date, and age 8
0.64 1982–2016 Denmark Cohort study 13.7 [1.7–21.1] versus 13.5 [1.7–20.8]# Female 490,618 Melanoma Cox proportional hazards regression model Sex, date, and age 8
1.17 1982–2016 Denmark Cohort study 13.7 [1.7–21.1] versus 13.5 [1.7–20.8]# Female NA NMSC Cox proportional hazards regression model Sex, date, and age 8

*Mean (SD); #median [IQR]