Prognosis for people with multiple primary melanomas compared with a single primary melanoma

To the Editor: People with a history of melanoma have a higher risk of developing subsequent primary melanomas than the general population; however, a difference in outcome between those with multiple primary melanomas (MPMs) and a single primary melanoma (SPM) is not established.1Peek G. Olsen C.M. Baade P. et al.Survival in patients with multiple primary melanomas: systematic review and meta-analysis.J Am Acad Dermatol. 2020; 83: 1406-1414Abstract Full Text Full Text PDF PubMed Scopus (5) Google Scholar Using a comprehensive, population-based dataset with long-term follow-up, we compared 10-year melanoma-specific mortality and overall mortality between people with MPMs and SPM. The Melanoma Patterns of Care study is a population-based observational study of residents in the state of New South Wales, Australia, who had a melanoma reported to the state cancer registry over 12 months in 2006-07, with follow-up until 2018 (median 11.9 years).2Watts C.G. McLoughlin K. Goumas C. et al.Association between melanoma detected during routine skin checks and mortality.JAMA Dermatol. 2021; 157: 1425-1436Crossref PubMed Scopus (26) Google Scholar People with a melanoma before study entry were excluded. Logistic regression analyses were performed to assess 10-year melanoma-specific mortality difference between groups. The analyzed data were from 3404 people (2830 had SPM, 574 developed a MPM during the follow-up period). Supplementary Table I, available via Mendeley at https://doi.org/10.17632/yknjyk9tfz.1 shows the patient and lesion characteristics for the first and thickest melanomas stratified by SPM and MPMs. The multivariable regression adjusted for pathological characteristics of the thickest lesion in the MPM group showed no significant differences in 10-year melanoma-specific mortality between the two groups (odds ratio 0.85, 95% confidence interval: 0.58-1.24, P = .40, Table I). These findings were consistent with the sensitivity analyses using parameters of the first primary melanoma among patients with MPMs (odds ratio 1.34, 95% confidence interval: 0.92-1.96, P = .12), although using first lesion characteristics may introduce survival bias.1Peek G. Olsen C.M. Baade P. et al.Survival in patients with multiple primary melanomas: systematic review and meta-analysis.J Am Acad Dermatol. 2020; 83: 1406-1414Abstract Full Text Full Text PDF PubMed Scopus (5) Google Scholar Other factors independently associated with higher melanoma-specific mortality in the multivariable analysis using data from the thickest lesion were male sex, disadvantaged socioeconomic status (based on location of residence), and Breslow thickness; and there were borderline-significant associations with body site, ulceration, and mitotic rate (Table I). The 10-year overall mortality results are presented in Supplementary Table II, available via Mendeley at https://doi.org/10.17632/yknjyk9tfz.1.Table ILogistic regression model for 10-year melanoma-specific mortality, using pathological factors from the first and thickest primary melanoma (selected factors)CharacteristicsNThickest lesionFirst lesionUnivariableMultivariable∗Variables with a P value of <0.2 in the univariable analysis were included in multivariable models as adjustment factors.UnivariableMultivariabsle∗Variables with a P value of <0.2 in the univariable analysis were included in multivariable models as adjustment factors.Odds ratio (95% CI)P valueOdds ratio (95% CI)P valueOdds ratio (95% CI)P valueOdds ratio (95%)P valueStatus SPM28301.00.661.00.401.00.661.00.12 MPM5741.08 (0.77-1.51)0.85 (0.58-1.24)1.08 (0.77-1.51)1.34 (0.92-1.96)Gender Males20491.00<.011.00.031.00<.011.00.03 Females13550.58 (0.44-0.77)0.70 (0.51-0.97)0.58 (0.44-0.77)0.70 (0.51-0.96)Age categories Quintile 19091.00<.011.00.121.000.011.000.22 Quintile 28581.37 (0.93-2.03)1.29 (0.84-1.98)1.37 (0.93-2.03)1.27 (0.83-1.95) Quintile 38001.59 (1.08-2.33)1.33 (0.86-2.05)1.59 (1.08-2.33)1.33 (0.86-2.06) Quintile 48371.84 (1.27-2.68)0.88 (0.57-1.35)1.84 (1.27-2.68)0.93 (0.61-1.44)Socioeconomic status†Socioeconomic status is based on postcode of residence. Quintile 1 represents the most disadvantaged status and quintile 5 represents the least disadvantaged status. Quintile 12901.00<.011.00<.011.00<.011.00<.01 Quintile 25231.58 (0.95-2.63)1.72 (0.97-3.04)1.58 (0.95-2.63)1.62 (0.92-2.86) Quintile 310660.75 (0.45-1.25)0.78 (0.45-1.36)0.75 (0.45-1.25)0.75 (0.43-1.30) Quintile 46371.02 (0.60-1.71)1.13 (0.63-2.04)1.02 (0.60-1.71)1.06 (0.59-1.89) Quintile 58880.87 (0.52-1.44)1.02 (0.58-1.80)0.87 (0.52-1.44)0.91 (0.51-1.59)Family history‡These characteristics were collected by clinician questionnaire and were not available for every patient. Absent15951.00.191.00.691.00.191.00.64 Present1920.84 (0.44-1.59)0.88 (0.44-1.78)0.84 (0.44-1.59)0.90 (0.45-1.81) Unknown16171.23 (0.95-1.61)1.15 (0.79-1.66)1.23 (0.95-1.61)1.17 (0.81-1.70)Breslow thickness In situ (0)3991.00<.011.00<.011.00<.011.00<.01 0-0.815901.63 (0.48-5.51)1.26 (0.34-4.64)1.37 (0.52-3.58)1.18 (0.41-3.40) 0.9-1.02316.64 (1.85-23.77)3.89 (0.98-15.38)5.47 (1.96-15.26)3.54 (1.14-11.03) 1.1-2.057412.54 (3.89-40.38)5.88 (1.63-21.21)8.18 (3.24-20.65)4.10 (1.42-11.82) 2.1-4.037029.27 (9.14-93.72)11.80 (3.24-42.98)19.50 (7.78-48.86)8.15 (2.79-23.77) >4.023160.94 (18.99-195.53)22.40 (6.04-83.12)38.13 (15.13-96.07)14.56 (4.87-43.58)Body site Head and neck7081.00.031.00.071.00.031.00.02 Trunk11950.95 (0.68-1.33)1.23 (0.83-1.83)1.10 (0.78-1.55)1.56 (1.04-2.35) Upper limbs8540.58 (0.39-0.88)0.72 (0.46-1.14)0.65 (0.43-0.98)0.86 (0.54-1.36) Lower limbs6471.02 (0.70-1.50)1.17 (0.75-1.83)1.11 (0.75-1.64)1.34 (0.85-2.11)Melanoma subtype Superficial spreading16101.00<.011.00.551.00<.011.00.82 Nodular4645.69 (4.14-7.82)1.17 (0.79-1.73)5.32 (3.86-7.34)1.18 (0.80-1.75) Lentigo4410.52 (0.27-0.98)0.88 (0.43-1.81)0.62 (0.35-1.11)1.16 (0.60-2.25) Other2153.79 (2.46-5.84)1.19 (0.72-1.97)3.52 (2.27-5.45)1.35 (0.81-2.24) Not specified6740.91 (0.59-1.41)0.78 (0.47-1.29)1.06 (0.70-1.60)1.13 (0.71-1.80)Ulceration Absent23651.00<.011.00.061.00<.011.00.07 Present4294.84 (3.65-6.42)1.35 (0.96-1.91)4.70 (3.52-6.27)1.42 (1.00-2.02) Missing6100.41 (0.24-0.70)0.62 (0.31-1.24)0.49 (0.30-0.79)0.78 (0.41-1.46)Regression Absent12021.00<.011.00.121.00<.011.00.56 Present11890.32 (0.23-0.45)0.79 (0.53-1.15)0.37 (0.27-0.52)0.86 (0.59-1.25) Missing10130.55 (0.40-0.74)1.26 (0.85-1.85)0.53 (0.39-0.72)1.09 (0.73-1.62)Mitotic rate (n/mm2) <110101.00<.011.00.061.00<.011.00<.01 1-26805.04 (2.90-8.77)1.88 (1.02-3.48)5.44 (3.14-9.46)2.46 (1.34-4.50) 3-1054713.71 (8.11-23.17)2.31 (1.23-4.34)14.57 (8.61-24.64)3.24 (1.73-6.07) >1015520.31 (11.16-36.99)1.88 (0.91-3.90)20.86 (11.32- 38.46)2.67 (1.27-5.62) Missing10122.22 (1.24-3.96)1.31 (0.66-2.59)2.32 (1.31-4.12)1.48 (0.77-2.87)Pathological factors are from the thickest and first primary melanoma diagnosed during the study period. The survival time starts from their first melanoma diagnosed in the period between October 2006 and October 2007. A missing category was set for Breslow thickness to keep the samples consistent between models.CI, Confidence interval; MPM, multiple primary melanomas; SPM, single primary melanoma.∗ Variables with a P value of <0.2 in the univariable analysis were included in multivariable models as adjustment factors.† Socioeconomic status is based on postcode of residence. Quintile 1 represents the most disadvantaged status and quintile 5 represents the least disadvantaged status.‡ These characteristics were collected by clinician questionnaire and were not available for every patient. Open table in a new tab Pathological factors are from the thickest and first primary melanoma diagnosed during the study period. The survival time starts from their first melanoma diagnosed in the period between October 2006 and October 2007. A missing category was set for Breslow thickness to keep the samples consistent between models. CI, Confidence interval; MPM, multiple primary melanomas; SPM, single primary melanoma. Sex, Breslow thickness, ulceration status, and socioeconomic disadvantage have been identified in other studies as factors independently associated with melanoma-specific survival.3Kricker A. Armstrong B.K. Goumas C. et al.Survival for patients with single and multiple primary melanomas: the genes, environment, and melanoma study.JAMA Dermatol. 2013; 149: 921-927Crossref PubMed Scopus (30) Google Scholar,4Coory M. Smithers M. Aitken J. Baade P. Ring I. Urban-rural differences in survival from cutaneous melanoma in Queensland.Aust N Z J Public Health. 2006; 30: 71-74Crossref PubMed Scopus (38) Google Scholar The worse prognosis for patients living in socioeconomically disadvantaged areas may be related to poorer access to medical care or education. The main limitation is the lack of adjustment for treatment modality (eg systemic therapy) in the multivariable analysis. At the time of the baseline survey, effective systemic therapies were unavailable and survival rates for patients with advanced melanoma were very poor. Given that death from melanoma can occur many years after diagnosis,5Baade P.D. Whiteman D.C. Janda M. et al.Long-term deaths from melanoma according to tumor thickness at diagnosis.Int J Cancer. 2020; 147: 1391-1396Crossref PubMed Scopus (17) Google Scholar treatment during later years of follow-up may have improved survival outcomes. It is possible that this had more impact in the MPM group as people who developed a SPM in the earlier years may have died before developing a MPM and before systemic treatments became available. The results of our study suggest that the number of primary melanomas is not an independent risk factor for mortality. In addition, the detection of melanoma at an early stage (with a thin Breslow thickness) rather than an intrinsic biologic factor remains the biggest influence on melanoma mortality after diagnosis of 1 or more melanomas. Richard A Scolyer has received fees for professional services from MetaOptima Technology Inc., F. Hoffmann-La Roche Ltd, Evaxion, Provectus Biopharmaceuticals Australia, Qbiotics, Novartis, Merck Sharp & Dohme, NeraCare, AMGEN Inc., Bristol-Myers Squibb, Myriad Genetics, GlaxoSmithKline. Scott W Menzies has received fees for advisory board participation from MoleMap Australia and Scibase AB. John F Thompson has received honoraria for advisory board participation from BMS Australia, MSD Australia, GSK and Provectus Inc, and travel and conference support from GSK, Provectus Inc and Novartis. Yuan Ni, Caroline G Watts, Christine Madronio, Bruce K Armstrong, Rachael L Morton, Graham J Mann, Anne E Cust, and Serigne N Lo have no conflicts of interest to declare.