Phenotypic and genotypic risk factors for invasive melanoma by sex and body site

BACKGROUND

Cutaneous melanoma incidence varies consistently across body sites between men and women, but the underlying causes of the differences remain unclear. To date, no prospective studies have examined risk factors for melanoma separately for men and women according to body site.

METHODS

We compared the association between constitutional, genetic and environmental risk factors for invasive melanoma on different body sites separately for men and women in a population-based prospective cohort study of 17,774 men and 21,070 women aged between 40 and 69 years and residents of Queensland, Australia at baseline in 2011. Participants were followed until December 2021.We examined risk factors including hair colour, tanning ability, naevus density, and proxies for high cumulative sun exposure, all self-reported at baseline. We also examined polygenic risk score (PRS) derived from summary statistics from a melanoma genome-wide association study meta-analysis.

RESULTS

During a median 10.4 years of follow-up, 455 men and 331 women developed an incident invasive melanoma; the mean age at diagnosis was lower in women than in men (62.6 vs. 65.0, respectively). The most common body site was the trunk in men (45.1%), and the upper (36.8%) and lower limbs (27.4%) in women. High naevus density and proxy measures of high cumulative sun exposure were similarly associated with melanoma at all sites in men and women. In both sexes, high genetic risk was associated with melanoma on all body sites except the head and neck. We observed differences between men and women in the association between PRS and melanoma of the trunk (highest vs. lowest tertile of PRS: HR 2.78, 95% CI 1.64-4.69 for men; 1.55, 95% CI 0.63-3.80 for women), and non-significant but large differences for the lower limbs (HR 5.25, 95% CI 1.80-15.27 for men; 1.75, 95% CI 0.88-3.47 for women).

CONCLUSIONS

While there are a number of potential explanations for these findings, this raises the possibility that genetic factors other than those related to pigmentation and naevus phenotypes may play a role in the predilection for melanoma to arise on different sites between the sexes.

Conversion of a Validated Melanoma Risk Stratification Tool Into a Tablet-Based Patient Questionnaire for Targeted Melanoma Screening in Primary Care Settings: A Pilot Study

BACKGROUND

Risk stratification can identify individuals in primary care settings who are at increased risk of developing melanoma.

OBJECTIVE

Converting and implementing a validated risk stratification tool as a patient self-administered tablet-based survey.

METHODS

Mackie risk stratification tool was transformed into a patient questionnaire. The questionnaire was completed in academic dermatologist practices by patients and dermatologists and revised to optimize sensitivity and specificity using physician assessment as gold standard. The optimized survey was administered before routine primary care visits during 2019 to 2021. High-risk patients were referred to dermatology. The number needed to screen (NNS), sensitivity, specificity, positive predictive value, and negative predictive value to identify a melanoma were calculated.

RESULTS

Of the 7,893 respondents, 5,842 (74%) and 2,051 (26%) patients were categorized as low-risk and high-risk population, respectively. The NNS to identify 1 melanoma was 64 in the high-risk population.

CONCLUSION

Incorporating self-administered patient-risk stratification tools in primary care settings can identify high-risk individuals for targeted melanoma screening. Further studies are needed to optimize specificity and sensitivity in more targeted populations.

Artificial intelligence and skin cancer

Artificial intelligence is poised to rapidly reshape many fields, including that of skin cancer screening and diagnosis, both as a disruptive and assistive technology. Together with the collection and availability of large medical data sets, artificial intelligence will become a powerful tool that can be leveraged by physicians in their diagnoses and treatment plans for patients. This comprehensive review focuses on current progress toward AI applications for patients, primary care providers, dermatologists, and dermatopathologists, explores the diverse applications of image and molecular processing for skin cancer, and highlights AI's potential for patient self-screening and improving diagnostic accuracy for non-dermatologists. We additionally delve into the challenges and barriers to clinical implementation, paths forward for implementation and areas of active research.

Acceptability and appropriateness of a risk-tailored organised melanoma screening program: Qualitative interviews with key informants

INTRODUCTION

In Australia, opportunistic screening (occurring as skin checks) for the early detection of melanoma is common, and overdiagnosis is a recognised concern. Risk-tailored cancer screening is an approach to cancer control that aims to provide personalised screening tailored to individual risk. This study aimed to explore the views of key informants in Australia on the acceptability and appropriateness of risk-tailored organised screening for melanoma, and to identify barriers, facilitators and strategies to inform potential future implementation. Acceptability and appropriateness are crucial, as successful implementation will require a change of practice for clinicians and consumers.

METHODS

This was a qualitative study using semi-structured interviews. Key informants were purposively selected to ensure expertise in melanoma early detection and screening, prioritising senior or executive perspectives. Consumers were expert representatives. Data were analysed deductively using the Tailored Implementation for Chronic Diseases (TICD) checklist.

RESULTS

Thirty-six participants were interviewed (10 policy makers; 9 consumers; 10 health professionals; 7 researchers). Key informants perceived risk-tailored screening for melanoma to be acceptable and appropriate in principle. Barriers to implementation included lack of trial data, reluctance for low-risk groups to not screen, variable skill level in general practice, differing views on who to conduct screening tests, confusing public health messaging, and competing health costs. Key facilitators included the perceived opportunity to improve health equity and the potential cost-effectiveness of a risk-tailored screening approach. A range of implementation strategies were identified including strengthening the evidence for cost-effectiveness, engaging stakeholders, developing pathways for people at low risk, evaluating different risk assessment criteria and screening delivery models and targeted public messaging.

CONCLUSION

Key informants were supportive in principle of risk-tailored melanoma screening, highlighting important next steps. Considerations around risk assessment, policy and modelling the costs of current verses future approaches will help inform possible future implementation of risk-tailored population screening for melanoma.

ACEMID cohort study: protocol of a prospective cohort study using 3D total body photography for melanoma imaging and diagnosis

INTRODUCTION

Three-dimensional (3D) total body photography may improve early detection of melanoma and facilitate surveillance, leading to better prognosis and lower healthcare costs. The Australian Centre of Excellence in Melanoma Imaging and Diagnosis (ACEMID) cohort study will assess long-term outcomes from delivery of a precision strategy of monitoring skin lesions using skin surface imaging technology embedded into health services across Australia.

METHODS AND ANALYSIS

A prospective cohort study will enrol 15 000 participants aged 18 years and above, across 15 Australian sites. Participants will attend study visits according to their melanoma risk category: very high risk, high risk or low/average risk, every 6, 12 and 24 months, respectively, over 3 years. Participants will undergo 3D total body photography and dermoscopy imaging at study visits. A baseline questionnaire will be administered to collect sociodemographic, phenotypic, quality of life and sun behaviour data. A follow-up questionnaire will be administered every 12 months to obtain changes in sun behaviour and quality of life. A saliva sample will be collected at the baseline visit from a subsample.

ETHICS AND DISSEMINATION

The ACEMID cohort study was approved by the Metro South Health Human Research Ethics Committee (approval number: HREC/2019/QMS/57206) and the University of Queensland Human Research Ethics Committee (approval number: 2019003077). The findings will be reported through peer-reviewed and lay publications and presentations at conferences.

TRIAL REGISTRATION NUMBER

ACTRN12619001706167.

The diagnosis and initial management of melanoma in Australia: findings from the prospective, population-based QSkin study

OBJECTIVES

To determine the proportions of newly diagnosed melanomas treated by different medical specialist types, to describe the types of excisions performed, and to investigate factors associated with treating practitioner specialty and excision type.

DESIGN, SETTING

Prospective cohort study; analysis of linked data: baseline surveys, hospital, pathology, Queensland Cancer Register, and Medical Benefits Schedule databases.

PARTICIPANTS

Random sample of 43 764 Queensland residents aged 40-69 years recruited during 2011, with initial diagnoses of in situ or invasive melanoma diagnosed to 31 December 2019.

MAIN OUTCOME MEASURES

Treating practitioner type and treatment modality for first incident melanoma; second and subsequent treatment events for the primary melanoma.

RESULTS

During a median follow-up of 8.4 years (interquartile range, 8.3-8.8 years), 1683 eligible participants (720 women, 963 men) developed at least one primary melanoma (in situ melanoma, 1125; invasive melanoma, 558), 1296 of which (77.1%) were initially managed in primary care; 248 were diagnosed by dermatologists (14.8%), 83 by plastic surgeons (4.9%), 43 by general surgeons (2.6%), and ten by other specialists (0.6%). The most frequent initial procedures leading to histologically confirmed melanoma diagnosis were first excision (854, 50.7%), shave biopsy (549, 32.6%), and punch biopsy (178, 10.6%); 1339 melanomas (79.6%) required two procedures, 187 (11.1%) three. Larger proportions of melanomas diagnosed by dermatologists (87%) or plastic surgeons (71%) were in people living in urban areas than of those diagnosed in primary care (63%); larger proportions of melanomas diagnosed by dermatologists or plastic surgeons than of those diagnosed in primary care were in people with university degrees (45%, 42% v 23%) or upper quartile clinical risk scores (63%, 59% v 47%).

CONCLUSIONS

Most incident melanomas in Queensland are diagnosed in primary care, and nearly half are initially managed by partial excision (shave or punch biopsy). Second or third, wider excisions are undertaken in about 90% of cases.

Inter-Rater Agreement in Assessing Risk of Bias in Melanoma Prediction Studies Using the Prediction Model Risk of Bias Assessment Tool (PROBAST): Results from a Controlled Experiment on the Effect of Specific Rater Training

Assessing the risk of bias (ROB) of studies is an important part of the conduct of systematic reviews and meta-analyses in clinical medicine. Among the many existing ROB tools, the Prediction Model Risk of Bias Assessment Tool (PROBAST) is a rather new instrument specifically designed to assess the ROB of prediction studies. In our study we analyzed the inter-rater reliability (IRR) of PROBAST and the effect of specialized training on the IRR. Six raters independently assessed the risk of bias (ROB) of all melanoma risk prediction studies published until 2021 (n = 42) using the PROBAST instrument. The raters evaluated the ROB of the first 20 studies without any guidance other than the published PROBAST literature. The remaining 22 studies were assessed after receiving customized training and guidance. Gwet's AC₁ was used as the primary measure to quantify the pairwise and multi-rater IRR. Depending on the PROBAST domain, results before training showed a slight to moderate IRR (multi-rater AC₁ ranging from 0.071 to 0.535). After training, the multi-rater AC₁ ranged from 0.294 to 0.780 with a significant improvement for the overall ROB rating and two of the four domains. The largest net gain was achieved in the overall ROB rating (difference in multi-rater AC₁: 0.405, 95%-CI 0.149-0.630). In conclusion, without targeted guidance, the IRR of PROBAST is low, questioning its use as an appropriate ROB instrument for prediction studies. Intensive training and guidance manuals with context-specific decision rules are needed to correctly apply and interpret the PROBAST instrument and to ensure consistency of ROB ratings.

Vitamin D and Sun Exposure: A Community Survey in Australia

Sun exposure carries both harms and benefits. Exposing the skin to the sun is the main modifiable cause of skin cancers, which exert a considerable health and economic burden in Australia. The most well-established benefit of exposure to ultraviolet (UV) radiation is vitamin D production. Australia has the highest incidence of skin cancer in the world but, despite the high ambient UV radiation, approximately one quarter of the population is estimated to be vitamin D deficient. Balancing the risks and benefits is challenging and requires effective communication. We sought to provide a snapshot of public knowledge and attitudes regarding sun exposure and vitamin D and to examine the associations between these factors and sun protective behaviors. In 2020 we administered an online survey; 4824 participants with self-reported fair or medium skin color were included in this analysis. Only 25% and 34% of participants were able to identify the amount of time outdoors needed to maintain adequate vitamin D status in summer and winter, respectively and 25% were concerned that sunscreen use inhibits vitamin D synthesis. This lack of knowledge was associated with suboptimal sun protection practices. Public education is warranted to prevent over-exposure, while supporting natural vitamin D production.

Risk Factors Associated With First and Second Primary Melanomas in a High-Incidence Population

Importance

An increasing number of people develop more than 1 primary melanoma, yet to date, no population-based prospective cohort studies have reported on risk factors for developing first vs second primary melanomas.

Objective

To compare the clinical characteristics of first and second melanomas and then to estimate the relative risks of developing 1 vs multiple melanomas associated with demographic, phenotypic, sun exposure, and genetic factors.

Design, Setting, and Participants

This population-based prospective cohort study included men and women aged 40 to 69 years recruited in 2011 and followed up until December 2018 in Queensland, Australia. Data analysis was performed from February to July 2022.

Exposures

Self-reported information about demographic, phenotypic, and sun exposure measures captured using a survey completed at baseline, and polygenic risk score for melanoma.

Main Outcomes and Measures

Incident first or second primary melanoma diagnosis, and histologic and clinical characteristics thereof. The Wei-Lin-Weissfeld model for recurrent events was used to estimate the association of each factor with the risks of first and second primary melanoma.

Results

A total of 38 845 patients (mean [SD] age at baseline, 56.1 [8.2] years; 17 775 men and 21 070 women) were included in the study. During a median follow-up period of 7.4 years, 1212 (3.1%) participants had a single primary melanoma diagnosis, and 245 (0.6%) had a second primary melanoma diagnosis. Second melanomas were more likely than first melanomas to be in situ; for invasive tumors, second melanomas were more likely to be thin (ie, ≤1 mm) than first melanomas. Having many moles at age 21 years (self-reported using visual scoring tool) was more strongly associated with second (hazard ratio [HR], 6.36; 95% CI, 3.77-10.75) than first primary melanoma (HR, 3.46; 95% CI, 2.72-4.40) (P value for difference between the HRs = .01). A high genetic predisposition (ie, polygenic risk score in tertile 3) was also more strongly associated with second (HR, 3.28; 95% CI, 2.06-5.23) than first melanoma (HR, 2.06; 95% CI, 1.71-2.49; P = .03). Second melanomas were more strongly associated with a history of multiple skin cancer excisions (HR, 2.63; 95% CI, 1.80-3.83) than first melanomas (HR, 1.86; 95% CI, 1.61-2.16; P = .05). For all other phenotypic characteristics and sun exposure measures, similarly elevated associations with first vs second melanomas were observed.

Conclusions and Relevance

Findings of this cohort study suggest that within the general population, the presence of many nevi and having a high genetic predisposition to melanoma were associated with the highest risks of developing second primary melanomas.

The effect of screening on melanoma incidence and biopsy rates

BACKGROUND

Cutaneous melanomas are common cancers in white-skinned populations, and early detection is promoted as a means of reducing morbidity and mortality. There is concern that increased skin screening is leading to overdiagnosis of indolent melanomas with low risk of lethality. The extent of melanoma overdiagnosis associated with screening is unknown.

OBJECTIVES

To estimate possible overdiagnosis by comparing subsequent melanoma incidence and biopsy rates among people subjected to skin screening those who were not.

METHODS

We recruited 43 762 residents of Queensland, Australia, aged 40-69 years, with no prior history of melanoma, selected at random from a population register in 2010. At baseline, participants completed a comprehensive melanoma risk factor survey and were asked if their skin had been examined by a doctor in the 3 years prior to baseline. We calculated incidence and relative risk of histologically confirmed melanoma (invasive and in situ) in years 2-7 of follow-up, obtained through linkage to the cancer registry. In secondary analyses, we measured biopsy rates in years 2-6 of follow-up. We used propensity score analysis to calculate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs).

RESULTS

In total, 28 155 participants underwent skin screening prior to baseline. We observed 967 first-incident melanomas (381 invasive) during 197 191 person-years of follow-up. Those screened had higher rates of melanoma (aHR 1·29, 95% CI 1·02-1·63) and subsequent skin biopses (aHR 1·85, 95% CI 1·69-2·04) than unscreened participants. The higher risk associated with skin screening was evident for in situ melanoma (aHR 1·45, 95% CI 1·09-1·92) but not invasive melanoma (aHR 1·05, 95% CI 0·72-1·54). In secondary analyses, where screening was defined as having a skin biopsy in the first year after baseline, we observed significantly increased risks of melanoma (aHR 1·53, 95% CI 1·23-1·89) and subsequent biopsies (aHR 2·64, 95% CI 2·46-2·84) relative to those who did not have a biopsy.

CONCLUSIONS

People who undergo skin screening subsequently experience higher rates of biopsies and melanoma (especially in situ melanoma), even after adjusting for all known risk factors, consistent with overdiagnosis. What is already known about this topic? Cutaneous melanomas are common cancers in white-skinned populations for which early detection is promoted as a means of reducing morbidity and mortality. There is concern that increased surveillance is leading to the overdiagnosis of indolent melanomas that are not destined to be lethal. The extent of melanoma overdiagnosis associated with surveillance is not known. What does this study add? People subjected to skin examinations by a doctor or who undergo skin biopsies subsequently have higher numbers of biopsies and higher rates of melanoma than people not subjected to either, even after adjusting for all known risk factors. These findings suggest that heightened surveillance leads to a proportion of melanomas being diagnosed that otherwise may not have come to clinical attention.

Using the Prediction Model Risk of Bias Assessment Tool (PROBAST) to Evaluate Melanoma Prediction Studies

Simple Summary

The rising incidence of cutaneous melanoma over recent decades, combined with a general interest in cancer risk prediction, has led to a high number of published melanoma risk prediction models. The aim of our work was to assess the validity of these models in order to discuss the current state of knowledge about how to predict incident cutaneous melanoma. To assess the risk of bias, we used a standardized procedure based on PROBAST (Prediction model Risk Of Bias ASsessment Tool). Only one of the 42 studies identified was rated as having a low risk of bias. However, it was encouraging to observe a recent reduction of problematic statistical methods used in the analyses. Nevertheless, the evidence base of high-quality studies that can be used to draw conclusions on the prediction of incident cutaneous melanoma is currently much weaker than the high number of studies on this topic would suggest.

Abstract

Rising incidences of cutaneous melanoma have fueled the development of statistical models that predict individual melanoma risk. Our aim was to assess the validity of published prediction models for incident cutaneous melanoma using a standardized procedure based on PROBAST (Prediction model Risk Of Bias ASsessment Tool). We included studies that were identified by a recent systematic review and updated the literature search to ensure that our PROBAST rating included all relevant studies. Six reviewers assessed the risk of bias (ROB) for each study using the published “PROBAST Assessment Form” that consists of four domains and an overall ROB rating. We further examined a temporal effect regarding changes in overall and domain-specific ROB rating distributions. Altogether, 42 studies were assessed, of which the vast majority (n = 34; 81%) was rated as having high ROB. Only one study was judged as having low ROB. The main reasons for high ROB ratings were the use of hospital controls in case-control studies and the omission of any validation of prediction models. However, our temporal analysis results showed a significant reduction in the number of studies with high ROB for the domain “analysis”. Nevertheless, the evidence base of high-quality studies that can be used to draw conclusions on the prediction of incident cutaneous melanoma is currently much weaker than the high number of studies on this topic would suggest.

Polygenic risk scores to stratify cancer screening should predict mortality not incidence

Population-based cancer screening programs such as mammography or colonscopy generally directed at all healthy individuals in a given age stratum. It has recently been proposed that cancer screening could be restricted to a high-risk subgroup based on polygenic risk scores (PRSs) using panels of single-nucleotide polymorphisms (SNPs). These PRSs were, however, generated to predict cancer incidence rather than cancer mortality and will not necessarily address overdiagnosis, a major problem associated with cancer screening programs. We develop a simple net-benefit framework for evaluating screening approaches that incorporates overdiagnosis. We use this methodology to demonstrate that if a PRS does not differentially discriminate between incident and lethal cancer, restricting screening to a subgroup with high scores will only improve screening outcomes in a small number of scenarios. In contrast, restricting screening to a subgroup defined as high-risk based on a marker that is more strongly predictive of mortality than incidence will often afford greater net benefit than screening all eligible individuals. If PRS-based cancer screening is to be effective, research needs to focus on identifying PRSs associated with cancer mortality, an unchartered and clinically-relevant area of research, with a much higher potential to improve screening outcomes.

Sensitivity of two Australian melanoma risk tools to identify high-risk individuals among people presenting with their first primary melanoma

AIMS

Regular skin examinations for early detection of melanoma are recommended for high-risk individuals, but there is minimal consensus regarding what constitutes 'high-risk'. Melanoma risk prediction models may guide this. We compared two online melanoma risk prediction tools: Victorian Melanoma Service (VMS) and Melanoma Institute Australia (MIA) risk tools; to assess classification differences of patients at high-risk of a first primary melanoma.

METHODS

Risk factor data for 357 patients presenting with their first primary melanoma were entered into both risk tools. Predicted risks were recorded: 5-year absolute risk (VMS tool and MIA tool); 10-year, lifetime, and relative risk estimates (MIA tool). Sensitivities for each tool were calculated using the same high-risk thresholds. The MIA risk tool showed greater sensitivity on comparison of 5-year absolute risks (90% MIA vs 78% VMS). Patients had significantly higher odds of being classified as high or very-high risk using the MIA risk tool overall, and for each patient subgroup. Using either tool, patients of male gender or with synchronous multiple first primary melanomas were more likely to be correctly classified as high- or very-high risk using 5-year absolute risk thresholds; but tumour invasiveness was unrelated to risk. Classification differed when using the MIA risk categories based on relative risk.

CONCLUSIONS

Both melanoma risk prediction tools had high sensitivity for identifying individuals at high-risk and could be used for optimising prevention campaigns. The choice of which risk tool, measure, and threshold for risk stratification depends on the intended purpose of risk prediction, and ideally requires information on specificity.

Self-Assessment Questionnaire on Patient-Physician Concordance on Nevus Self-Count and Models Development to Predict High-Risk Phenotype >50 Nevi

BACKGROUND

Cutaneous melanoma accounts for the majority of skin cancer-related deaths. Readily identifiable phenotypic characteristics and total body nevus count (TBNC) >50 are among the most important risk factors for cutaneous melanoma. Implementation of nevus self-count procedures and self-assessment of phenotypic traits as part of skin self-examination could be an excellent screening tool for identifying an at-risk target population.

OBJECTIVES

Objectives of the study were to assess the skills of a central Italian and eastern Spanish population sample to recognize their skin lesions via the submission of a self-assessment questionnaire and to explore which self-assessment questionnaire item combination best predicts the high-risk condition of TBNC >50.

METHODS

Patients aged ≥18 years filled a self-assessment questionnaire, autonomously and prior to the dermatological visit. Subsequently, dermatologists performed total body skin examination and reported patients' skin lesions on a separate questionnaire.

RESULTS

We reported fair to moderate patient-dermatologist agreement for skin lesion self-assessment. The item number of nevi on the back was the single questionnaire item most accurately predicting TBNC >50. The high-sensitivity and high-specificity classification and regression tree models for the prediction of TBNC >50 displayed different items combinations; the item nevus on the back was always the first and most important predictor in both our models.

CONCLUSIONS

Patients were partially able to provide correct estimation of their whole-body nevus self-count. The item nevi on the back seems to be the first and most important predictor of TBNC >50 across our models. Delivery of high-sensitivity and high-specificity prediction models based on our questionnaire item combination may help defining a high-risk target population.

Reporting Quality of Studies Developing and Validating Melanoma Prediction Models: An Assessment Based on the TRIPOD Statement

Transparent and accurate reporting is essential to evaluate the validity and applicability of risk prediction models. Our aim was to evaluate the reporting quality of studies developing and validating risk prediction models for melanoma according to the TRIPOD (Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis) checklist. We included studies that were identified by a recent systematic review and updated the literature search to ensure that our TRIPOD rating included all relevant studies. Six reviewers assessed compliance with all 37 TRIPOD components for each study using the published “TRIPOD Adherence Assessment Form”. We further examined a potential temporal effect of the reporting quality. Altogether 42 studies were assessed including 35 studies reporting the development of a prediction model and seven studies reporting both development and validation. The median adherence to TRIPOD was 57% (range 29% to 78%). Study components that were least likely to be fully reported were related to model specification, title and abstract. Although the reporting quality has slightly increased over the past 35 years, there is still much room for improvement. Adherence to reporting guidelines such as TRIPOD in the publication of study results must be adopted as a matter of course to achieve a sufficient level of reporting quality necessary to foster the use of the prediction models in applications.

Melanoma Risk Factors and Prevention

In the Western population, 1 out of every 50 individuals will develop melanoma. The incidence of melanoma is increasing faster than any other malignancy. The development of melanoma is multifactorial arising from an interaction between genetic susceptibility and environmental exposures. Sixty to seventy percent of melanomas are thought to be caused by ultraviolet radiation. Most cutaneous melanomas are of increased risk. Prevention strategies involve mitigating the environmental risk factors and identifying individuals with phenotypic risk factors for increased surveillance.

Impact of personal genomic risk information on melanoma prevention behaviors and psychological outcomes: a randomized controlled trial

Purpose

We evaluated the impact of personal melanoma genomic risk information on sun-related behaviors and psychological outcomes.

Methods

In this parallel group, open, randomized controlled trial, 1,025 Australians of European ancestry without melanoma and aged 18–69 years were recruited via the Medicare database (3% consent). Participants were randomized to the intervention (n = 513; saliva sample for genetic testing, personalized melanoma risk booklet based on a 40-variant polygenic risk score, telephone-based genetic counseling, educational booklet) or control (n = 512; educational booklet). Wrist-worn ultraviolet (UV) radiation dosimeters (10-day wear) and questionnaires were administered at baseline, 1 month postintervention, and 12 months postbaseline.

Results

At 12 months, 948 (92%) participants completed dosimetry and 973 (95%) the questionnaire. For the primary outcome, there was no effect of the genomic risk intervention on objectively measured UV exposure at 12 months, irrespective of traditional risk factors. For secondary outcomes at 12 months, the intervention reduced sunburns (risk ratio: 0.72, 95% confidence interval: 0.54–0.96), and increased skin examinations among women. Melanoma-related worry was reduced. There was no overall impact on general psychological distress.

Conclusion

Personalized genomic risk information did not influence sun exposure patterns but did improve some skin cancer prevention and early detection behaviors, suggesting it may be useful for precision prevention. There was no evidence of psychological harm.

Reproducible Naevus Counts Using 3D Total Body Photography and Convolutional Neural Networks

BACKGROUND

The number of naevi on a person is the strongest risk factor for melanoma; however, naevus counting is highly variable due to lack of consistent methodology and lack of inter-rater agreement. Machine learning has been shown to be a valuable tool for image classification in dermatology.

OBJECTIVES

To test whether automated, reproducible naevus counts are possible through the combination of convolutional neural networks (CNN) and three-dimensional (3D) total body imaging.

METHODS

Total body images from a study of naevi in the general population were used for the training (82 subjects, 57,742 lesions) and testing (10 subjects; 4,868 lesions) datasets for the development of a CNN. Lesions were labelled as naevi, or not ("non-naevi"), by a senior dermatologist as the gold standard. Performance of the CNN was assessed using sensitivity, specificity, and Cohen's kappa, and evaluated at the lesion level and person level.

RESULTS

Lesion-level analysis comparing the automated counts to the gold standard showed a sensitivity and specificity of 79% (76-83%) and 91% (90-92%), respectively, for lesions ≥2 mm, and 84% (75-91%) and 91% (88-94%) for lesions ≥5 mm. Cohen's kappa was 0.56 (0.53-0.59) indicating moderate agreement for naevi ≥2 mm, and substantial agreement (0.72, 0.63-0.80) for naevi ≥5 mm. For the 10 individuals in the test set, person-level agreement was assessed as categories with 70% agreement between the automated and gold standard counts. Agreement was lower in subjects with numerous seborrhoeic keratoses.

CONCLUSION

Automated naevus counts with reasonable agreement to those of an expert clinician are possible through the combination of 3D total body photography and CNNs. Such an algorithm may provide a faster, reproducible method over the traditional in person total body naevus counts.

Commentary to Shetty A, Janda M, Fry K et al. Clinical utility of skin cancer and melanoma risk scores for population screening: TRoPICS study

Linked article: A. Shetty et al.J Eur Acad Dermatol Venereol 2021; 35: 1094–1098. https://doi.org/10.1111/jdv.17062.

Can patient-led surveillance detect subsequent new primary or recurrent melanomas and reduce the need for routinely scheduled follow-up? A protocol for the MEL-SELF randomised controlled trial

BACKGROUND

Most subsequent new primary or recurrent melanomas might be self-detected if patients are trained to systematically self-examine their skin and have access to timely medical review (patient-led surveillance). Routinely scheduled clinic visits (clinician-led surveillance) is resource-intensive and has not been shown to improve health outcomes; fewer visits may be possible if patient-led surveillance is shown to be safe and effective. The MEL-SELF trial is a randomised controlled trial comparing patient-led surveillance with clinician-led surveillance in people who have been previously treated for localised melanoma.

METHODS

Stage 0/I/II melanoma patients (n = 600) from dermatology, surgical, or general practice clinics in NSW Australia, will be randomised (1:1) to the intervention (patient-led surveillance, n = 300) or control (usual care, n = 300). Patients in the intervention will undergo a second randomisation 1:1 to polarised (n = 150) or non-polarised (n = 150) dermatoscope. Patient-led surveillance comprises an educational booklet, skin self-examination (SSE) instructional videos; 3-monthly email/SMS reminders to perform SSE; patient-performed dermoscopy with teledermatologist feedback; clinical review of positive teledermoscopy through fast-tracked unscheduled clinic visits; and routinely scheduled clinic visits following each clinician's usual practice. Clinician-led surveillance comprises an educational booklet and routinely scheduled clinic visits following each clinician's usual practice. The primary outcome, measured at 12 months, is the proportion of participants diagnosed with a subsequent new primary or recurrent melanoma at an unscheduled clinic visit. Secondary outcomes include time from randomisation to diagnosis (of a subsequent new primary or recurrent melanoma and of a new keratinocyte cancer), clinicopathological characteristics of subsequent new primary or recurrent melanomas (including AJCC stage), psychological outcomes, and healthcare use. A nested qualitative study will include interviews with patients and clinicians, and a costing study we will compare costs from a societal perspective. We will compare the technical performance of two different models of dermatoscope (polarised vs non-polarised).

DISCUSSION

The findings from this study may inform guidance on evidence-based follow-up care, that maximises early detection of subsequent new primary or recurrent melanoma and patient wellbeing, while minimising costs to patients, health systems, and society.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12621000176864 . Registered on 18 February 2021.

Clinical utility of skin cancer and melanoma risk scores for population screening: TRoPICS study

BACKGROUND

Screening for skin cancer can be cost-effective if focused on high-risk groups. Risk prediction tools have been developed for keratinocyte cancers and melanoma to optimize advice and management. However, few have been validated in a clinical setting over the past few years.

OBJECTIVES

To assess the clinical utility of risk assessment tools to identify individuals with prevalent skin cancers in a volunteer-based screening clinic.

METHODS

Participants were adults presenting for a skin check at a volunteer-based skin cancer screening facility. We used previously published tools, based on questionnaire responses, to predict melanoma and keratinocyte cancers [KCs; basal cell carcinoma (BCC) and squamous cell carcinoma (SCC)] and classified each participant into one of five risk categories. Participants subsequently underwent a full skin examination by a dermatologist. All suspicious lesions were biopsied, and all cancers were histopathologically confirmed.

RESULTS

Of 789 people who presented to the clinic, 507 (64%) consented to the study. Twenty-two BCCs, 19 SCCs and eight melanomas were diagnosed. The proportion of keratinocyte cancers diagnosed increased according to risk category from <1% in the lowest to 24% in the highest risk category (P < 0.001). Subtype analysis revealed similar proportionate increases in BCC or SCC prevalence according to risk category. However, a similar proportion of melanoma cases were detected in the low-risk and high-risk groups.

CONCLUSION

The risk prediction model for keratinocyte cancers can reliably identify individuals with a significant skin cancer burden prior to a skin examination in the community setting. The prediction tool for melanoma needs to be tested in a larger sample exposed to a wider range of environmental risk factors.

Risk Prediction Models for Melanoma: A Systematic Review on the Heterogeneity in Model Development and Validation

The rising incidence of cutaneous melanoma over the past few decades has prompted substantial efforts to develop risk prediction models identifying people at high risk of developing melanoma to facilitate targeted screening programs. We review these models, regarding study characteristics, differences in risk factor selection and assessment, evaluation, and validation methods. Our systematic literature search revealed 40 studies comprising 46 different risk prediction models eligible for the review. Altogether, 35 different risk factors were part of the models with nevi being the most common one (n = 35, 78%); little consistency in other risk factors was observed. Results of an internal validation were reported for less than half of the studies (n = 18, 45%), and only 6 performed external validation. In terms of model performance, 29 studies assessed the discriminative ability of their models; other performance measures, e.g., regarding calibration or clinical usefulness, were rarely reported. Due to the substantial heterogeneity in risk factor selection and assessment as well as methodologic aspects of model development, direct comparisons between models are hardly possible. Uniform methodologic standards for the development and validation of risk prediction models for melanoma and reporting standards for the accompanying publications are necessary and need to be obligatory for that reason.

The role of technology in melanoma screening and diagnosis

Melanoma presents challenges for timely and accurate diagnosis. Expert panels have issued risk-based screening guidelines, with recommended screening by visual inspection. To assess how recent technology can impact the risk/benefit considerations for melanoma screening, we comprehensively reviewed non-invasive visual-based technologies. Dermoscopy increases lesional diagnostic accuracy for both dermatologists and primary care providers; total body photography and sequential digital dermoscopic imaging also increase diagnostic accuracy, are supported by automated lesion detection and tracking, and may be best suited to use by dermatologists for longitudinal follow-up. Specialized imaging modalities using non-visible light technology have unproven benefit over dermoscopy and can be limited by cost, access, and training requirements. Mobile apps facilitate image capture and lesion tracking. Teledermatology has good concordance with face-to-face consultation and increases access, with increased accuracy using dermoscopy. Deep learning models can surpass dermatologist accuracy, but their clinical utility has yet to be demonstrated. Technology-aided diagnosis may change the calculus of screening; however, well-designed prospective trials are needed to assess the efficacy of these different technologies, alone and in combination to support refinement of guidelines for melanoma screening.

Sex and Gender Disparities in Melanoma

Worldwide, the total incidence of cutaneous melanoma is higher in men than in women, with some differences related to ethnicity and age and, above all, sex and gender. Differences exist in respect to the anatomic localization of melanoma, in that it is more frequent on the trunk in men and on the lower limbs in women. A debated issue is if-and to what extent-melanoma development can be attributed to gender-specific behaviors or to biologically intrinsic differences. In the search for factors responsible for the divergences, a pivotal role of sex hormones has been observed, although conflicting results indicate the involvement of other mechanisms. The presence on the X chromosome of numerous miRNAs and coding genes playing immunological roles represents another important factor, whose relevance can be even increased by the incomplete X chromosome random inactivation. Considering the known advantages of the female immune system, a different cancer immune surveillance efficacy was suggested to explain some sex disparities. Indeed, the complexity of this picture emerged when the recently developed immunotherapies unexpectedly showed better improvements in men than in women. Altogether, these data support the necessity of further studies, which consider enrolling a balanced number of men and women in clinical trials to better understand the differences and obtain actual gender-equitable healthcare.

Development and external validation study of a melanoma risk prediction model incorporating clinically assessed naevi and solar lentigines

BACKGROUND

Melanoma risk prediction models could be useful for matching preventive interventions to patients' risk.

OBJECTIVES

To develop and validate a model for incident first-primary cutaneous melanoma using clinically assessed risk factors.

METHODS

We used unconditional logistic regression with backward selection from the Australian Melanoma Family Study (461 cases and 329 controls) in which age, sex and city of recruitment were kept in each step, and we externally validated it using the Leeds Melanoma Case-Control Study (960 cases and 513 controls). Candidate predictors included clinically assessed whole-body naevi and solar lentigines, and self-assessed pigmentation phenotype, sun exposure, family history and history of keratinocyte cancer. We evaluated the predictive strength and discrimination of the model risk factors using odds per age- and sex-adjusted SD (OPERA) and the area under curve (AUC), and calibration using the Hosmer-Lemeshow test.

RESULTS

The final model included the number of naevi ≥ 2 mm in diameter on the whole body, solar lentigines on the upper back (a six-level scale), hair colour at age 18 years and personal history of keratinocyte cancer. Naevi was the strongest risk factor; the OPERA was 3·51 [95% confidence interval (CI) 2·71-4·54] in the Australian study and 2·56 (95% CI 2·23-2·95) in the Leeds study. The AUC was 0·79 (95% CI 0·76-0·83) in the Australian study and 0·73 (95% CI 0·70-0·75) in the Leeds study. The Hosmer-Lemeshow test P-value was 0·30 in the Australian study and < 0·001 in the Leeds study.

CONCLUSIONS

This model had good discrimination and could be used by clinicians to stratify patients by melanoma risk for the targeting of preventive interventions. What's already known about this topic? Melanoma risk prediction models may be useful in prevention by tailoring interventions to personalized risk levels. For reasons of feasibility, time and cost many melanoma prediction models use self-assessed risk factors. However, individuals tend to underestimate their naevus numbers. What does this study add? We present a melanoma risk prediction model, which includes clinically-assessed whole-body naevi and solar lentigines, and self-assessed risk factors including pigmentation phenotype and history of keratinocyte cancer. This model performs well on discrimination, the model's ability to distinguish between individuals with and without melanoma, and may assist clinicians to stratify patients by melanoma risk for targeted preventive interventions.

A risk prediction model for the development of subsequent primary melanoma in a population-based cohort

BACKGROUND

Guidelines for follow-up of patients with melanoma are based on limited evidence.

OBJECTIVES

To guide skin surveillance, we developed a risk prediction model for subsequent primary melanomas, using demographic, phenotypical, histopathological, sun exposure and genomic risk factors.

METHODS

Using Cox regression frailty models, we analysed data for 2613 primary melanomas from 1266 patients recruited to the population-based Genes, Environment and Melanoma study in New South Wales, Australia, with a median of 14 years' follow-up via the cancer registry. Discrimination and calibration were assessed.

RESULTS

The median time to diagnosis of a subsequent primary melanoma decreased with each new primary melanoma. The final model included 12 risk factors. Harrell's C-statistic was 0·73 [95% confidence interval (CI) 0·68-0·77], 0·65 (95% CI 0·62-0·68) and 0·65 (95% CI 0·61-0·69) for predicting second, third and fourth primary melanomas, respectively. The risk of a subsequent primary melanoma was 4·75 times higher (95% CI 3·87-5·82) for the highest vs. the lowest quintile of the risk score. The mean absolute risk of a subsequent primary melanoma within 5 years was 8·0 ± SD 4.1% after the first primary melanoma, and 46·8 ± 15·0% after the second, but varied substantially by risk score.

CONCLUSIONS

The risk of developing a subsequent primary melanoma varies considerably between individuals and is particularly high for those with two or more primary melanomas. The risk prediction model and its associated nomograms enable estimation of the absolute risk of subsequent primary melanoma, on the basis of on an individual's risk factors, and can be used to tailor surveillance intensity, communicate risk and provide patient education. What's already known about this topic? Current guidelines for the frequency and length of follow-up to detect new primary melanomas in patients with one or more previous primary melanomas are based on limited evidence. People with one or more primary melanomas have, on average, a higher risk of developing another primary invasive melanoma, compared with the general population, but an accurate way of estimating individual risk is needed. What does this study add? We provide a comprehensive risk prediction model for subsequent primary melanomas, using data from 1266 participants with melanoma (2613 primary melanomas), over a median 14 years' follow-up. The model includes 12 risk factors comprising demographic, phenotypical, histopathological and genomic factors, and sun exposure. It enables estimation of the absolute risk of subsequent primary melanomas, and can be used to tailor surveillance intensity, communicate individual risk and provide patient education.

Genome-wide association studies and polygenic risk scores for skin cancer: clinically useful yet?

BACKGROUND

Genome-wide association studies (GWAS) have identified thousands of susceptibility variants, although most have been associated with small individual risk estimates that offer little predictive value. However, combining multiple variants into polygenic risk scores (PRS) may be more informative. Multiple studies have developed PRS composed of GWAS-identified variants for cutaneous cancers. This review highlights data from these studies.

OBJECTIVES

To review published GWAS and PRS studies for melanoma, cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC), and discuss their potential clinical utility.

METHODS

We searched PubMed and the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue to identify relevant studies.

RESULTS

Results from 21 GWAS (11 melanoma, 3 cSCC, 7 BCC) and 11 PRS studies are summarized. Six loci in pigmentation genes overlap between these three cancers (ASIP/RALY, IRF4, MC1R, OCA2, SLC45A2 and TYR). Additional loci overlap for cSCC/BCC and BCC/melanoma, but no other loci are shared between cSCC and melanoma. PRS for melanoma show roughly two-to-threefold increases in risk and modest improvements in risk prediction (2-7% increases). PRS are associated with twofold and threefold increases in risk of cSCC and BCC, respectively, with small improvements (2% increase) in predictive ability.

CONCLUSIONS

Existing data indicate that PRS may offer small, but potentially meaningful, improvements to risk prediction. Additional research is needed to clarify the potential utility of PRS in cutaneous carcinomas. Clinical translation will require well-powered validation studies incorporating known risk factors to evaluate PRS as tools for screening. What's already known about this topic? Over 50 susceptibility loci for melanoma, basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC) have been identified in genome-wide association studies (GWAS). Polygenic risk scores (PRS) using variants identified from GWAS have also been developed for melanoma, BCC and cSCC, and investigated with respect to clinical risk prediction. What does this study add? This review provides an overview of GWAS findings and the potential clinical utility of PRS for melanoma, BCC and cSCC.

Targeted Melanoma Screening: Risk Self-Assessment and Skin Self-Examination Education Delivered During Mammography of Women

Background

Melanoma, which is the sixth most common cancer in women, is visible on the surface of the skin; therefore, self-screening (skin self-examination [SSE]) may be beneficial.

Methods

A convenience sample of women undergoing mammography was sequentially assigned by week into this two-arm targeted melanoma screening intervention. Both groups saw an informational poster and received a brochure promoting risk self-identification and SSE education. One group received an additional 1-week SSE reminder. Participants completed baseline and 1- and 3-month follow-up surveys assessing SSE performance, identifying a concerning mole, scheduling a dermatology appointment, and anxiety due to the program. Performance of SSE between groups was compared using χ² analysis. The electronic medical record was reviewed for diagnosis of concerning moles.

Results

At 1 month, 384 of 420 (91.4% retention) women completed the survey. Of those, 311 (80.9%) performed SSE. Of those who performed SSE, 54 (14%) found a concerning mole at either 1 or 3 months. At 3 months, 346 (82.4% retention) women completed the survey. The number of women who performed SSE did not differ between groups at 1 month (χ² = 1.64, P = .17) or 3 months (χ² = 1.58, P = .12). Seven melanomas were found among 34 women who identified a concerning mole; examination of 4.8 women yielded one melanoma. Anxiety was low with a median score of 9.5 (range = 0–42.9).

Conclusions

Introducing melanoma risks and SSE education during mammography was feasible and did not demonstrate harms; thus, there is an opportunity to reach a large, at-risk population with limited burden for the participant and clinics.

Human health in relation to exposure to solar ultraviolet radiation under changing stratospheric ozone and climate

The Montreal Protocol has limited increases in the UV-B (280-315 nm) radiation reaching the Earth's surface as a result of depletion of stratospheric ozone. Nevertheless, the incidence of skin cancers continues to increase in most light-skinned populations, probably due mainly to risky sun exposure behaviour. In locations with strong sun protection programs of long duration, incidence is now reducing in younger age groups. Changes in the epidemiology of UV-induced eye diseases are less clear, due to a lack of data. Exposure to UV radiation plays a role in the development of cataracts, pterygium and possibly age-related macular degeneration; these are major causes of visual impairment world-wide. Photodermatoses and phototoxic reactions to drugs are not uncommon; management of the latter includes recognition of the risks by the prescribing physician. Exposure to UV radiation has benefits for health through the production of vitamin D in the skin and modulation of immune function. The latter has benefits for skin diseases such as psoriasis and possibly for systemic autoimmune diseases such as multiple sclerosis. The health risks of sun exposure can be mitigated through appropriate sun protection, such as clothing with both good UV-blocking characteristics and adequate skin coverage, sunglasses, shade, and sunscreen. New sunscreen preparations provide protection against a broader spectrum of solar radiation, but it is not clear that this has benefits for health. Gaps in knowledge make it difficult to derive evidence-based sun protection advice that balances the risks and benefits of sun exposure.