Advances in Early Detection of Melanoma and the Future of At-Home Testing
Abstract
:1. Introduction
2. Methods
3. Early Detection at Home
3.1. Naked Eye SSEs
3.2. The Ugly Duckling Method
4. Primary Care Physician and General Practitioner Methods
4.1. Dermatoscopes
4.2. Electronic Tools
5. Debate over Efficacy of the New Method and Overdiagnosis
6. Future of Early Melanoma Screening
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Saginala, K.; Barsouk, A.; Aluru, J.S.; Rawla, P.; Barsouk, A. Epidemiology of Melanoma. Med. Sci. 2021, 9, 63. [Google Scholar] [CrossRef]
- Carr, S.; Smith, C.; Wernberg, J. Epidemiology and risk factors of melanoma. Surg. Clin. N. Am. 2020, 100, 1–12. [Google Scholar] [CrossRef]
- Tripp, M.K.; Watson, M.; Balk, S.J.; Swetter, S.M.; Gershenwald, J.E. State of the science on prevention and screening to reduce melanoma incidence and mortality: The time is now. CA Cancer J. Clin. 2016, 66, 460–480. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pennie, M.L.; Soon, S.L.; Risser, J.B.; Veledar, E.; Culler, S.; Chen, S.C. Melanoma outcomes for Medicare patients: Association of stage and survival with detection by a dermatologist vs a nondermatologist. Arch. Derm. 2007, 143, 488–494. [Google Scholar] [CrossRef] [PubMed]
- Datzmann, T.; Schoffer, O.; Meier, F.; Seidler, A.; Schmitt, J. Are patients benefiting from participation in the German skin cancer screening programme? A large cohort study based on administrative data. Br. J. Derm. 2022, 186, 69–77. [Google Scholar] [CrossRef]
- Stang, A.; Jöckel, K.H. Does skin cancer screening save lives? A detailed analysis of mortality time trends in Schleswig-Holstein and Germany. Cancer 2016, 122, 432–437. [Google Scholar] [CrossRef] [PubMed]
- Leiter, U.; Buettner, P.G.; Eigentler, T.K.; Forschner, A.; Meier, F.; Garbe, C. Is detection of melanoma metastasis during surveillance in an early phase of development associated with a survival benefit? Melanoma Res. 2010, 20, 240–246. [Google Scholar] [CrossRef]
- Borland, R.; Marks, R.; Noy, S. Public knowledge about characteristics of moles and melanomas. Aust. J. Public Health 1992, 16, 370–375. [Google Scholar] [CrossRef]
- Lawson, D.D.; Moore, D.H.; Schneider, J.S.; Sagebiel, R.W. Nevus counting as a risk factor for melanoma: Comparison of self-count with count by physician. J. Am. Acad. Dermatol. 1994, 31, 438–444. [Google Scholar] [CrossRef]
- Hamidi, R.; Peng, D.; Cockburn, M. Efficacy of skin self-examination for the early detection of melanoma. Int. J. Dermatol. 2010, 49, 126–134. [Google Scholar] [CrossRef]
- Elliott, T.M.; Whiteman, D.C.; Olsen, C.M.; Gordon, L.G. Estimated Healthcare Costs of Melanoma in Australia over 3 Years Post-Diagnosis. Appl. Health Econ. Health Policy 2017, 15, 805–816. [Google Scholar] [CrossRef]
- Serra-Arbeloa, P.; Rabines-Juárez, Á.; Álvarez-Ruiz, M.; Guillén-Grima, F. Cost of Cutaneous Melanoma by Tumor Stage: A Descriptive Analysis. Estudio descriptivo de costes en melanoma cutáneo de diferentes estadios. Actas Dermosifiliogr. 2017, 108, 229–236. [Google Scholar] [CrossRef] [PubMed]
- Alexandrescu, D. Melanoma costs: A dynamic model comparing estimated overall costs of various clinical stages. Derm. Online J. 2009, 15, 1. [Google Scholar] [CrossRef]
- Girgis, A.; Clarke, P.; Burton, R.C.; Sanson—Fisher, R.W. Screening for melanoma by primary health care physicians: A cost-effectiveness analysis. J. Med. Screen. 1996, 3, 47–53. [Google Scholar] [CrossRef]
- Freedberg, K.A.; Geller, A.C.; Miller, D.R.; Lew, R.A.; Koh, H.K. Screening for malignant melanoma: A cost-effectiveness analysis. J. Am. Acad. Dermatol. 1999, 41 (Pt 1), 738–745. [Google Scholar] [CrossRef]
- Losina, E.; Walensky, R.P.; Geller, A.; Beddingfield, F.C.; Wolf, L.L.; Gilchrest, B.A.; Freedberg, K.A. Visual screening for malignant melanoma: A cost-effectiveness analysis. Arch. Derm. 2007, 143, 21–28. [Google Scholar] [CrossRef]
- van der Leest, R.; de Vries, E.; Bulliard, J.-L.; Paoli, J.; Peris, K.; Stratigos, A.; Trakatelli, M.; Maselis, T.; Šitum, M.; Pallouras, A.; et al. The Euromelanoma skin cancer prevention campaign in Europe: Characteristics and results of 2009 and 2010. J. Eur. Acad. Derm. Venereol. 2011, 25, 1455–1465. [Google Scholar] [CrossRef] [PubMed]
- Geller, A.C.; Zhang, Z.; Sober, A.J.; Halpern, A.C.; Weinstock, M.A.; Daniels, S.; Miller, D.R.; Demierre, M.-F.; Brooks, D.; Gilchrest, B.A. The first 15 years of the American Academy of Dermatology skin cancer screening programs: 1985–1999. J. Am. Acad. Derm. 2003, 48, 34–41. [Google Scholar] [CrossRef]
- Paulson, K.G.; Gupta, D.; Kim, T.S.; Veatch, J.R.; Byrd, D.R.; Bhatia, S.; Wojcik, K.; Chapuis, A.G.; Thompson, J.A.; Madeleine, M.M.; et al. Age-Specific Incidence of Melanoma in the United States. JAMA Dermatol. 2020, 156, 57–64. [Google Scholar] [CrossRef]
- Liu-Smith, F.; Ziogas, A. Age-dependent interaction between sex and geographic ultraviolet index in melanoma risk. J. Am. Acad. Dermatol. 2020, 82, 1102–1108.e3. [Google Scholar] [CrossRef] [Green Version]
- Cancer Research UK. Melanoma Skin Cancer Incidence Statistics. Available online: https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/melanoma-skin-cancer/incidence#heading-Zero (accessed on 23 January 2023).
- Bellenghi, M.; Puglisi, R.; Pontecorvi, G.; De Feo, A.; Carè, A.; Mattia, G. Sex and Gender Disparities in Melanoma. Cancers 2020, 12, 1819. [Google Scholar] [CrossRef] [PubMed]
- Paddock, L.E.; Lu, S.E.; Bandera, E.V.; Rhoads, G.G.; Fine, J.; Paine, S.; Barnhill, R.; Berwick, M. Skin self-examination and long-term melanoma survival. Melanoma Res. 2016, 26, 401–408. [Google Scholar] [CrossRef] [PubMed]
- David, J. Men’s Health and the Primary Care Physician; CRC Press: Boca Raton, FL, USA, 2021; pp. 424–427. [Google Scholar] [CrossRef]
- Melanoma Research Alliance. Early Warning Signs of Melanoma and Other Skin Cancers. Available online: https://www.curemelanoma.org/about-melanoma/educate-yourself/know-what-to-look-for (accessed on 10 January 2023).
- AIM at Melanoma Foundation. How to Do a Skin Self-Examination. Available online: https://www.aimatmelanoma.org/melanoma-101/early-detection-of-melanoma/how-to-do-a-skin-self-examination (accessed on 10 January 2023).
- Melanoma Research Foundation. What Melanoma Looks Like. Available online: https://melanoma.org/melanoma-education/what-melanoma-looks-like (accessed on 10 January 2023).
- The American Melanoma Foundation. Available online: https://melanomafoundation.org (accessed on 10 January 2023).
- Rigel, D.S.; Friedman, R.J.; Kopf, A.W.; Polsky, D. ABCDE—An Evolving Concept in the Early Detection of Melanoma. Arch. Dermatol. 2005, 141, 1032–1034. [Google Scholar] [CrossRef] [PubMed]
- Rigel, D.; Russak, J.; Friedman, R. The Evolution of Melanoma Diagnosis: 25 Years Beyond the ABCDs. CA Cancer J. Clin. 2010, 60, 301–316. [Google Scholar] [CrossRef]
- Aldridge, R.; Zanotto, M.; Ballerini, L.; Fisher, R.; Rees, J. Novice Identification of Melanoma: Not Quite as Straightforward as the ABCDs. Acta Derm. Venereol. 2011, 91, 125–130. [Google Scholar] [CrossRef] [Green Version]
- Healsmith, M.; Bourke, J.; Osborne, J.; Graham-Brown, R. An evaluation of the revised seven-point checklist for the early diagnosis of cutaneous malignant melanoma. Br. J. Dermatol. 1994, 130, 48–50. [Google Scholar] [CrossRef]
- Thomas, L.; Tranchand, P.; Berard, F.; Secchi, T.; Colin, C.; Moulin, G. Semiological Value of ABCDE Criteria in the Diagnosis of Cutaneous Pigmented Tumors. Dermatology 1998, 197, 11–17. [Google Scholar] [CrossRef]
- Titus, L.; Clough-Gorr, K.; Mackenzie, T.; Perry, A.; Spencer, S.; Weiss, J.; Abrahams-Gessel, S.; Ernstoff, M. Recent skin self-examination and doctor visits in relation to melanoma risk and tumour depth. Br. J. Dermatol. 2013, 168, 571–576. [Google Scholar] [CrossRef] [Green Version]
- Melanoma: Clinical Features and Diagnosis. Available online: https://www.medilib.ir/uptodate/show/15806 (accessed on 21 January 2023).
- Manne, S.L.; Heckman, C.J.; Kashy, D.; Lozada, C.; Gallo, J.; Ritterband, L.; Coups, E.J. Prevalence and correlates of skin self-examination practices among cutaneous malignant melanoma survivors. Prev. Med. Rep. 2020, 19, 101110. [Google Scholar] [CrossRef]
- De Giorgi, V.; Grazzini, M.; Rossari, S.; Gori, A.; Papi, F.; Scarfi, F.; Savarese, I.; Gandini, S. Is skin self-examination for cutaneous melanoma detection still adequate? A retrospective study. Dermatology 2012, 225, 31–36. [Google Scholar] [CrossRef]
- Jones, O.T.; Ranmuthu, C.K.I.; Hall, P.N.; Funston, G.; Walter, F.M. Recognising Skin Cancer in Primary Care. Adv. Ther. 2020, 37, 603–616. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pannebakker, M.M.; Mills, K.; Johnson, M.; Emery, J.D.; Walter, F.M. Understanding implementation and usefulness of electronic clinical decision support (eCDS) for melanoma in English primary care: A qualitative investigation. BJGP Open 2019, 3, bjgpopen18x101635. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Walter, F.M.; Prevost, A.T.; Vasconcelos, J.; Hall, P.N.; Burrows, N.P.; Morris, H.C.; Kinmonth, A.L.; Emery, J.D. Using the 7-point checklist as a diagnostic aid for pigmented skin lesions in general practice: A diagnostic validation study. Br. J. Gen. Pract. 2013, 63, e345–e353. [Google Scholar] [CrossRef] [Green Version]
- Mittal, A.; Pushpam, D.; Bakhshi, S. Management of advanced melanoma in the current era: A medical oncology perspective for the Indian scenario. Natl. Med. J. India 2020, 33, 89–98. [Google Scholar] [CrossRef]
- Graham-Brown, R.; Osborne, J.E.; London, S.P.; Fletcher, A.; Shaw, D.; Williams, B.; Bowry, V. The initial effects on workload and outcome of a public education campaign on early diagnosis and treatment of malignant melanoma in Leicestershire. Br. J. Dermatol. 1990, 122, 53–59. [Google Scholar] [CrossRef]
- Doherty, V.; MacKie, R. Experience of a public education programme on early detection of cutaneous malignant melanoma. Br. Med. J. 1988, 297, 388–391. [Google Scholar] [CrossRef] [Green Version]
- Cantisani, C.; Ambrosio, L.; Cucchi, C.; Meznerics, F.A.; Kiss, N.; Bánvölgyi, A.; Rega, F.; Grignaffini, F.; Barbuto, F.; Frezza, F.; et al. Melanoma Detection by Non-Specialists: An Untapped Potential for Triage? Diagnostics 2022, 12, 2821. [Google Scholar] [CrossRef] [PubMed]
- Zhang, Y.; Ali, K.; George, J.A.; Reichenberg, J.S.; Fox, M.C.; Adamson, A.S.; Tunnell, J.W.; Markey, M.K. Toward automated assessment of mole similarity on dermoscopic images. J. Med. Imaging 2021, 8, 014506. [Google Scholar] [CrossRef] [PubMed]
- Gaudy-Marqueste, C.; Wazaefi, Y.; Bruneu, Y.; Triller, R.; Thomas, L.; Pellacani, G.; Malvehy, J.; Avril, M.-F.; Monestier, S.; Richard, M.-A.; et al. Ugly Duckling Sign as a Major Factor of Efficiency in Melanoma Detection. JAMA Dermatol. 2017, 153, 279–284. [Google Scholar] [CrossRef] [Green Version]
- Jensen, J.D.; Elewski, B.E. The ABCDEF Rule: Combining the “ABCDE Rule” and the “Ugly Duckling Sign” in an Effort to Improve Patient Self-Screening Examinations. J. Clin. Aesthetic Dermatol. 2015, 8, 15. [Google Scholar]
- Ersser, S.; Effah, A.; Dyson, J.; Kellar, I.; Thomas, S.; McNichol, E.; Caperon, E.; Hewitt, C.; Muinonen-Martin, A. Effectiveness of interventions to support the early detection of skin cancer through skin self-examination: A systematic review and meta-analysis. Br. J. Dermatol. 2019, 180, 1339–1347. [Google Scholar] [CrossRef]
- Czajkowska, Z.; Hall, N.; Sewitch, M.; Wang, B.; Körner, A. The role of patient education and physician support in self-efficacy for skin self-examination among patients with melanoma. Patient Educ. Couns. 2017, 100, 1505–1510. [Google Scholar] [CrossRef]
- Duarte, A.F.; Sousa-Pinto, B.; Azevedo, L.F.; Barros, A.M.; Puig, S.; Malvehy, J.; Haneke, E.; Correia, O. Clinical ABCDE rule for early melanoma detection. Eur. J. Dermatol. 2021, 31, 771–778. [Google Scholar] [CrossRef] [PubMed]
- Coroiu, A.; Moran, C.; Bergeron, C.; Drapeau, M.; Wang, B.; Kezouh, A.; Ernst, J.; Batist, G.; Körner, A. Short and long-term barriers and facilitators of skin self-examination among individuals diagnosed with melanoma. BMC Cancer 2020, 20, 123. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- De Giorgi, V.; Papi, F.; Giorgi, L.; Savarese, I.; Verdelli, A.; Scarfì, F.; Gandini, S. Skin self-examination and the ABCDE rule in the early diagnosis of melanoma: Is the game over? Br. J. Dermatol. 2013, 168, 1370–1371. [Google Scholar] [CrossRef]
- Kulkarni, R.; Wesley, Y.; Leachman, S. To Improve Melanoma Outcomes, Focus on Risk Stratification, Not Overdiagnosis. JAMA Dermatol. 2022, 158, 485–487. [Google Scholar] [CrossRef]
- Robinson, J.K.; Wahood, S.; Ly, S.; Kirk, J.; Yoon, J.; Sterritt, J.; Gray, E.; Kwasny, M. Melanoma detection by skin self-examination targeting at-risk women: A randomized controlled trial with telemedicine support for concerning moles. Prev. Med. Rep. 2021, 24, 101532. [Google Scholar] [CrossRef]
- Sarikaya Solak, S.; Yondem, H.; Cicin, I. Evaluating sun protection behaviors and skin self-examination practices among the family members of melanoma patients in Turkey: A cross-sectional survey study. Dermatol. Ther. 2020, 33, e14268. [Google Scholar] [CrossRef]
- Koh, U.; Horsham, C.; Soyer, H.P.; Loescher, L.J.; Gillespie, N.; Vagenas, D.; Janda, M. Consumer Acceptance and Expectations of a Mobile Health Application to Photograph Skin Lesions for Early Detection of Melanoma. Dermatology 2019, 235, 4–10. [Google Scholar] [CrossRef] [PubMed]
- Manne, S.L.; Marchetti, M.A.; Kashy, D.A.; Heckman, C.J.; Ritterband, L.M.; Thorndike, F.P.; Viola, A.; Lozada, C.; Coups, E.J. mySmartCheck, a Digital Intervention to Promote Skin Self-examination Among Individuals Diagnosed with or at Risk for Melanoma: A Randomized Clinical Trial. Ann. Behav. Med. 2022, 56, 791–803. [Google Scholar] [CrossRef]
- Hubbard, G.; Kyle, R.G.; Neal, R.D.; Marmara, V.; Wang, Z.; Dombrowski, S.U. Promoting sunscreen use and skin self-examination to improve early detection and prevent skin cancer: Quasi-experimental trial of an adolescent psycho-educational intervention. BMC Public Health 2018, 18, 666. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Carcioppolo, N.; Kim, S.; Sanchez, M.; Mao, B.; Malova, E.; Ryan, A.; Lun, D.; Ewing, C.; Hu, S. Evaluating a game-based randomized experiment to increase melanoma identification among adults living in the US. Soc. Sci. Med. 2022, 310, 115281. [Google Scholar] [CrossRef] [PubMed]
- Swann, R.; McPhail, S.; Witt, J.; Shand, B.; Abel, G.; Hiom, S.; Rashbass, J.; Lyratzopoulos, G.; Rubin, G.; The National Cancer Diagnosis Audit Steering Group. Diagnosing cancer in primary care: Results from the national cancer diagnosis audit. Br. J. Gen. Pract. 2018, 68, e63–e72. [Google Scholar] [CrossRef]
- Katz, B.; Rabinovitz, H. Introduction to Dermoscopy. Dermatol. Clin. 2001, 19, 221–258. [Google Scholar] [CrossRef] [PubMed]
- Jones, O.T.; Jurascheck, L.C.; van Melle, M.; Hickman, S.; Burrows, N.P.; Hall, P.N.; Emery, J.; Walter, F. Dermoscopy for melanoma detection and triage in primary care: A systematic review. BMJ Open 2019, 9, e027529. [Google Scholar] [CrossRef]
- Dinnes, J.; Deeks, J.J.; Chuchu, N.; di Ruffano, L.F.; Matin, R.N.; Thomson, D.R.; Wong, K.Y.; Aldridge, R.B.; Abbott, R.; Fawzy, M.; et al. Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults. Cochrane Database Syst. Rev. 2018, 12, CD011902. [Google Scholar] [CrossRef] [PubMed]
- Vestergaard, M.; Macaskill, P.; Holt, P.; Menzies, S. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: A meta-analysis of studies performed in a clinical setting. Br. J. Dermatol. 2008, 159, 669–676. [Google Scholar] [CrossRef]
- Koelink, C.; Vermeulen, K.; Kollen, B.; de Bock, G.; Dekker, J.; Jonkman, M.; van der Heide, W. Diagnostic accuracy and cost-effectiveness of dermoscopy in primary care: A cluster randomized clinical trial. J. Eur. Acad. Dermatol. Venereol. 2014, 28, 1442–1449. [Google Scholar] [CrossRef]
- Jones, O.; Jurascheck, L.; Utukuri, M.; Pannebakker, M.; Emery, J.; Walter, F. Dermoscopy, use in UK Primary care: A survey of GP’s with a special interest in dermatology. J. Eur. Acad. Dermatol. Venerol. 2019, 33, 1706–1712. [Google Scholar] [CrossRef] [Green Version]
- Tromme, I.; Devleesschauwer, B.; Beutels, P.; Richez, P.; Praet, N.; Sacré, L.; Marot, L.; Van Eeckhout, P.; Theate, I.; Baurain, J.-F.; et al. Selective use of sequential digital dermoscopy imaging allows a cost reduction in the melanoma detection process: A belgian study of patients with a single or a small number of atypical nevi. PLoS ONE 2014, 9, e109339. [Google Scholar] [CrossRef] [Green Version]
- Menzies, S.; Emery, J.; Staples, M.; Davies, S.; McAvoy, B.; Fletcher, J.; Shahid, K.; Reid, G.; Avramidis, M.; Ward, A.; et al. Impact of dermoscopy and short-term sequential digital dermoscopy imaging for the management of pigmented lesions in primary care: A sequential intervention trial. Br. J. Dermatol. 2009, 161, 1270–1277. [Google Scholar] [CrossRef]
- Emery, J.D.; Hunter, J.; Hall, P.N.; Watson, A.J.; Moncrieff, M.; Walter, F.M. Accuracy of SIAscopy for pigmented skin lesions encountered in primary care: Development and validation of a new diagnostic algorithm. BMC Dermatol. 2010, 10, 9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sgouros, D.; Lallas, A.; Julian, Y.; Rigopoulos, D.; Zalaudek, I.; Longo, C.; Moscarella, E.; Simonetti, V.; Argenziano, G. Assessment of SIAscopy in the triage of suspicious skin tumours. Ski. Res. Technol. 2014, 20, 440–444. [Google Scholar] [CrossRef] [PubMed]
- Giavina-Bianchi, M.; Santos, A.P.; Cordioli, E. Teledermatology reduces dermatology referrals and improves access to specialists. EClinicalMedicine 2020, 29, 100641. [Google Scholar] [CrossRef]
- Marwaha, S.S.; Fevrier, H.; Alexeeff, S.; Crowley, E.; Haiman, M.; Pham, N.; Tuerk, M.J.; Wukda, D.; Hartmann, M.; Herrinton, L.J. Comparative effectiveness study of face-to-face and teledermatology workflows for diagnosing skin cancer. J. Am. Acad. Dermatol. 2019, 81, 1099–1106. [Google Scholar] [CrossRef]
- Mohan, G.; Molina, G.; Stavert, R. Store and forward teledermatology improves dermatology knowledge among referring primary care providers: A survey-based cohort study. J. Am. Acad. Dermatol. 2018, 79, 960–961. [Google Scholar] [CrossRef] [Green Version]
- Romero, G.; De Argila, D.; Ferrandiz, L.; Sánchez, M.; Vañó, S.; Taberner, R.; Pasquali, P.; De La Torre, C.; Alfageme, F.; Malvehy, J.; et al. Practice Models in Teledermatology in Spain: Longitudinal Study, 2009–2014. Modelos de práctica de la teledermatología en España. Estudio longitudinal 2009–2014. Actas Dermo-Sifiliográficas 2018, 109, 624–630. [Google Scholar] [CrossRef]
- CCHP. Telehealth Policy Trend Maps. Available online: https://www.cchpca.org/policy-trends (accessed on 9 January 2023).
- Glazer, A.M.; Winkelmann, R.R.; Farberg, A.S.; Rigel, D.S. Analysis of Trends in US Melanoma Incidence and Mortality. JAMA Dermatol. 2017, 153, 225–226. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Matsumoto, M.; Wack, S.; Weinstock, M.A.; Geller, A.; Wang, H.; Solano, F.X.; Kirkwood, J.M.; Ferris, L.K. Five-Year Outcomes of a Melanoma Screening Initiative in a Large Health Care System. JAMA Dermatol. 2022, 158, 504–512. [Google Scholar] [CrossRef]
- Welch, H.; Mazer, B.; Adamson, A. The rapid rise in cutaneous melanoma diagnoses. N. Engl. J. Med. 2021, 384, 72–79. [Google Scholar] [CrossRef]
- Herbert, A.; Koo, M.M.; Barclay, M.E.; Greenberg, D.C.; Abel, G.A.; Levell, N.J.; Lyratzopoulos, G. Stage-specific incidence trends of melanoma in an English region, 1996–2015: Longitudinal analyses of population-based data. Melanoma Res. 2020, 30, 279–285. [Google Scholar] [CrossRef] [PubMed]
- Watts, C.G.; McLoughlin, K.; Goumas, C.; van Kemenade, C.H.; Aitken, J.F.; Soyer, H.P.; Peñas, P.F.; Guitera, P.; Scolyer, R.A.; Morton, R.L.; et al. Association Between Melanoma Detected During Routine Skin Checks and Mortality. JAMA Dermatol. 2021, 157, 1425–1436. [Google Scholar] [CrossRef] [PubMed]
- Walter, F.M.; Morris, H.C.; Humphrys, E.; Hall, P.N.; Prevost, A.T.; Burrows, N.; Bradshaw, L.; Wilson, E.C.; Norris, P.; Walls, J.; et al. Effect of adding a diagnostic aid to best practice to manage suspicious pigmented suspicious pigmented lesions in primary care: Randomised controlled trial. Br. Med. J. 2012, 345, e4110. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Murchie, P.; Adam, R.; Khor, W.L.; Raja, E.A.; Iversen, L.; Brewster, D.; Lee, A.J. Impact of rurality on processes and outcomes in melanoma care: Results from a whole-Scotland melanoma cohort in primary and secondary care. Br. J. Gen. Pract. 2018, 68, e566–e575. [Google Scholar] [CrossRef] [Green Version]
- Privalle, A.; Havighurst, T.; Kim, K.; Bennett, D.D.; Xu, Y.G. Number of skin biopsies needed per malignancy: Comparing the use of skin biopsies among dermatologists and nondermatologist clinicians. J. Am. Acad. Dermatol. 2020, 82, 110–116. [Google Scholar] [CrossRef]
- Haenssle, H.A.; Fink, C.; Schneiderbauer, R.; Toberer, F.; Buhl, T.; Blum, A.; Kalloo, A.; Hassen, A.B.H.; Thomas, L.; Enk, A.; et al. Man against machine: Diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists. Ann. Oncol. 2018, 29, 1836–1842. [Google Scholar] [CrossRef]
- Phillips, M.; Marsden, H.; Jaffe, W.; Matin, R.N.; Wali, G.N.; Greenhalgh, J.; McGrath, E.; James, R.; Ladoyanni, E.; Bewley, A.; et al. Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions. JAMA Netw. Open 2019, 2, e1913436. [Google Scholar] [CrossRef] [Green Version]
- Brinker, T.J.; Hekler, A.; Enk, A.H.; Berking, C.; Haferkamp, S.; Hauschild, A.; Weichenthal, M.; Klode, J.; Schadendorf, D.; Holland-Letz, T.; et al. Deep neural networks are superior to dermatologists in melanoma image classification. Eur. J. Cancer 2019, 119, 11–17. [Google Scholar] [CrossRef] [Green Version]
- Dick, V.; Sinz, C.; Mittlböck, M.; Kittler, H.; Tschandl, P. Accuracy of Computer-Aided Diagnosis of Melanoma: A Meta-analysis. JAMA Dermatol. 2019, 155, 1291–1299. [Google Scholar] [CrossRef]
- Phillips, M.; Greenhalgh, J.; Marsden, H.; Palamaras, I. Detection of malignant melanoma using artificial intelligence: An observational study of diagnostic accuracy. Dermatol. Pract. Concept 2020, 10, e2020011. [Google Scholar] [CrossRef]
- Dascalu, A.; David, E.O. Skin cancer detection by deep learning and sound analysis algorithms: A prospective clinical study of an elementary dermoscope. Discov. Sci. 2019, 43, 107–113. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Giavina-Bianchi, M.; de Sousa, R.M.; Paciello, V.Z.d.A.; Vitor, W.G.; Okita, A.L.; Prôa, R.; Severino, G.L.d.S.; Schinaid, A.A.; Santo, R.E.; Machado, B.S. Implementation of artificial intelligence algorithms for melanoma screening in a primary care setting. PLoS ONE 2021, 16, e0257006. [Google Scholar] [CrossRef] [PubMed]
- Jain, A.; Way, D.; Gupta, V.; Gao, Y.; Marinho, G.D.O.; Hartford, J.; Sayres, R.; Kanada, K.; Eng, C.; Nagpal, K.; et al. Development and Assessment of an Artificial Intelligence–Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices. JAMA Netw. Open 2021, 4, e217249. [Google Scholar] [CrossRef] [PubMed]
- Dildar, M.; Akram, S.; Irfan, M.; Khan, H.U.; Ramzan, M.; Mahmood, A.R.; Alsaiari, S.A.; Saeed, A.H.M.; Alraddadi, M.O.; Mahnashi, M.H. Skin Cancer Detection: A Review Using Deep Learning Techniques. Int. J. Environ. Res. Public Health 2021, 18, 5479. [Google Scholar] [CrossRef]
- Kassianos, A.; Emery, J.; Murchie, P.; Walter, F. Smartphone applications for melanoma detection by community, patient and generalist clinician users: A review. Br. J. Dermatol. 2015, 172, 1507–1518. [Google Scholar] [CrossRef] [PubMed]
- Kong, F.W.; Horsham, C.; Ngoo, A.; Soyer, H.P.; Janda, M. Review of smartphone mobile applications for skin cancer detection: What are the changes in availability, functionality, and costs to users over time. Int. J. Dermatol. 2020, 60, 289–308. [Google Scholar] [CrossRef]
- OHSU. War on Melanoma. Available online: https://www.ohsu.edu/war-on-melanoma/sklipr-home-dermoscopy (accessed on 24 January 2023).
- Kaushal, A.; Altman, R.; Langlotz, C. Geographic Distribution of US Cohorts Used to Train Deep Learning Algorithms. JAMA 2020, 324, 1212–1213. [Google Scholar] [CrossRef]
- Parikh, R.B.; Teeple, S.; Navathe, A.S. Addressing Bias in Artificial Intelligence in Health Care. JAMA 2019, 322, 2377–2378. [Google Scholar] [CrossRef]
- Dunn, B.K.; Woloshin, S.; Xie, H.; Kramer, B.S. Cancer overdiagnosis: A challenge in the era of screening. J. Natl. Cancer Cent. 2022, 2, 235–242. [Google Scholar] [CrossRef]
- Whiteman, D.C.; Olsen, C.M.; MacGregor, S.; Law, M.H.; Thompson, B.; Dusingize, J.C.; Green, A.C.; Neale, R.E.; Pandeya, N. The effect of screening on melanoma incidence and biopsy rates. Br. J. Dermatol. 2022, 187, 515–522. [Google Scholar] [CrossRef]
- Muzumdar, S.; Lin, G.; Kerr, P.; Grant-Kels, J.M. Evidence concerning the accusation that melanoma is overdiagnosed. J. Am. Acad. Dermatol. 2021, 85, 841–846. [Google Scholar] [CrossRef] [PubMed]
- Kurtansky, N.R.; Dusza, S.W.; Halpern, A.C.; Hartman, R.I.; Geller, A.C.; Marghoob, A.A.; Rotemberg, V.M.; Marchetti, M.A. An Epidemiologic Analysis of Melanoma Overdiagnosis in the United States 1975–2017. J. Investig. Dermatol. 2022, 142, 1804–1811.e6. [Google Scholar] [CrossRef] [PubMed]
- Rubin, R. Melanoma Diagnoses Rise While Mortality Stays Fairly Flat, Raising Concerns About Overdiagnosis. JAMA 2020, 323, 1429–1430. [Google Scholar] [CrossRef]
- Brunsgaard, E.; Jensen, J.; Grossman, D. Melanoma in Skin of Color: Part II. Racial disparities, role of UV, and interventions for earlier detection. J. Am. Acad. Dermatol. 2022; preproof. [Google Scholar] [CrossRef]
- Tripathi, R.; Archibald, L.K.; Mazmudar, R.S.; Conic, R.R.; Rothermel, L.D.; Scott, J.F.; Bordeaux, J.S. Racial differences in time to treatment for melanoma. J. Am. Acad. Dermatol. 2020, 83, 854–859. [Google Scholar] [CrossRef] [PubMed]
- Cortez, J.; Vasquez, J.; Wei, M. The impact of demographics, socioeconomics, and health care access on melanoma outcomes. J. Am. Acad. Dermatol. 2021, 84, 1677–1683. [Google Scholar] [CrossRef]
Method | Target Audience | Pros | Cons |
---|---|---|---|
Skin Self-Examinations (ABCDE/Seven-Point Glasgow/Ugly Duckling) | General public |
|
|
Dermatoscope Inspection | Primary care physicians |
|
|
Smartphone Apps | General public and primary care physicians |
|
|
Artificial Intelligence-Based Image Analysis | General public and primary care physicians |
|
|
Sequential Digital Dermoscopy | General Public and primary care physicians |
| |
Teledermatology | General public |
|
|
Letter | Characteristic |
---|---|
A | Asymmetry—benign moles typically have symmetric or uniform shapes, while cancerous moles are often asymmetric or irregular. |
B | Border—benign moles have round and distinct borders, whereas cancerous moles often have asymmetric or jagged borders. |
C | Color—benign moles tend to be a single color, while cancerous moles are often composed of multiple shades or colors at different parts of the mole. |
D | Diameter—cancerous moles are typically over six millimeters in diameter. This is approximately the diameter of a common pencil. |
E | Evolving—Unlike benign moles, cancerous moles often change in size, shape, and color over time. |
Characteristic | Weighted Score Value |
---|---|
Change in the size of a lesion | 2 points |
Irregularity in the shape of a lesion | 2 points |
Irregularity in the color of a lesion | 2 points |
Inflammation in or around the lesion | 1 point |
Alteration in sensation of the lesion | 1 point |
The lesion is large in size, or has a diameter larger than seven millimeters | 1 point |
Oozing or crusting on or around the lesion | 1 point |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Garrison, Z.R.; Hall, C.M.; Fey, R.M.; Clister, T.; Khan, N.; Nichols, R.; Kulkarni, R.P. Advances in Early Detection of Melanoma and the Future of At-Home Testing. Life 2023, 13, 974. https://doi.org/10.3390/life13040974
Garrison ZR, Hall CM, Fey RM, Clister T, Khan N, Nichols R, Kulkarni RP. Advances in Early Detection of Melanoma and the Future of At-Home Testing. Life. 2023; 13(4):974. https://doi.org/10.3390/life13040974
Chicago/Turabian StyleGarrison, Zachary R., Connor M. Hall, Rosalyn M. Fey, Terri Clister, Nabeela Khan, Rebecca Nichols, and Rajan P. Kulkarni. 2023. "Advances in Early Detection of Melanoma and the Future of At-Home Testing" Life 13, no. 4: 974. https://doi.org/10.3390/life13040974
APA StyleGarrison, Z. R., Hall, C. M., Fey, R. M., Clister, T., Khan, N., Nichols, R., & Kulkarni, R. P. (2023). Advances in Early Detection of Melanoma and the Future of At-Home Testing. Life, 13(4), 974. https://doi.org/10.3390/life13040974