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.

Academic dermatology in Australia and New Zealand between 2017 and 2022: A cross‐sectional bibliometric analysis

INTRODUCTION

Academic dermatologists in Australia and New Zealand provide high-quality and meaningful contributions to the understanding of disease and therapeutic translational research. Concerns have been raised by the Australian Medical Association regarding the decline of clinical academics in Australia as a whole, however, such trends in scholarly output have not previously been analysed for Australasian dermatologists.

METHODS

A bibliometric analysis of dermatologists in Australia and New Zealand was conducted in January and February 2023. Available Scopus profiles for all dermatologists were used to measure lifetime H index, scholarly output, citation counts and field-weighted citation impact (FWCI) in the last 5 years (2017-2022). Trends in output over time were measured using non-parametric tests. Differences in output between subgroups stratified by gender and academic leadership positions (associate professor or professor) were measured using Wilcoxon rank-sum and one-way ANOVA tests. The scholarly output of recent College graduates was also analysed as a subgroup, comparing the same bibliographic variables in the 5 years preceding and 5 years following awarding of their fellowships.

RESULTS

From the 463 practising dermatologists in Australia and New Zealand, 372 (80%) were successfully matched to Scopus researcher profiles. Of these dermatologists, 167 were male (45%) and 205 (55%) were female, and 31 (8%) held academic leadership positions. Most dermatologists (67%) published at least one paper in the last 5 years. The median lifetime H index was 4, and between 2017 and 2022 median scholarly output was 3, the median citations were 14 and the median FWCI was 0.64. There was a non-significant trend towards fewer publications per year, however, citation count and FWCI decreased significantly. By subgroups, female dermatologists published significantly more papers between 2017 and 2022, and other bibliographic variables were comparable to male dermatologists. However, women were underrepresented in positions of academic leadership-comprising only 32% of this cohort despite representing 55% of dermatologists. Professors were also significantly more likely to have higher bibliographic outcomes than associate professors. Finally, analysis of recent College graduates highlighted a significant decline in bibliometric outcomes pre- and post-fellowship.

CONCLUSION

Overall, our analysis identifies a trend towards decreased research output by dermatologists in Australia and New Zealand in the last 5 years. Strategies to support dermatologists in research endeavours, particularly women and recent graduates, will be essential in maintaining strong scholarly output among Australasian dermatologists and thereby sustaining optimal evidence-based patient care.

Factors for not performing total body skin examinations in primary care in association with teledermoscopy

PURPOSE

To investigate factors related to omitted total body skin examination (TBSE) in skin cancer diagnostics while managing patients using teledermoscopy (TDS) in Swedish primary care.

METHODS

4,987 TDS referrals from primary care centers were analyzed to identify factors associated with failing to perform TBSE. Data collected included age, gender of patient and physician, and reason for a visit. Logistic regression was used to test the association between the variables and risk of failing to complete a TBSE.

RESULTS

The risk for omitted TBSE is higher in older patients, females, patients whose primary reason for seeking care was not specifically for a complete skin check, and with female physician. Patients > 80 years had more than four times increased risk of not undergoing TBSE compared to the youngest (< 30 y). The strongest correlation to omitting TBSE was with other reasons for primary care visits than "skin check". Male gender of the patient and being examined by male physicians decreased the risk of omitted TBSE by 20% and 30%, respectively. There was no evidence of interaction between the gender of the patient and the physician.

CONCLUSION

Since TDS reduces the opportunities to have a TBSE by dermatologists, the standard management of patients with suspicious skin lesions in primary care must be revised and evidence-based. TBSE is strongly recommended for patients with increased risk of skin cancer, for example old persons with fair skin and a history of skin cancer, when managing them with TDS.

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.

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.

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.

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.

Predictive value of global dermoscopic pattern in patients diagnosed with cutaneous melanoma

Introduction

Dermoscopy is one of the most commonly used methods in early diagnosis of melanoma. It is conducted to differentiate between benign and malignant patterns in melanocytic lesions.

Aim

To determine if there is a predominance of one dermoscopic pattern in patients with melanoma and if there is a significant difference in dominant global dermoscopic pattern in patients with cutaneous melanomas correlated with patients’ sex and the location of the primary tumor.

Material and methods

The study included 162 patients with prior diagnosis of cutaneous melanoma. Dermoscopic and videodermoscopic pictures and patient data were analyzed with regard to the pattern: reticular, globular, homogeneous and mixed pattern (two-component pattern; reticular-globular pattern) with central or peripheral globules and multicomponent (mixed – at least 3 types of structures in one nevus).

Results

The reticular pattern was significantly more prevalent in male patients (38.57%, 27 patients) in comparison to female patients (18.45%, 17 patients). We also found a statistically significant lower prevalence of reticular pattern in patients diagnosed with melanomas located on upper limbs. The homogeneous pattern was statistically significantly more prevalent in patients in whom primary tumors were located on the head and upper limbs.

Conclusions

Our study suggests that predominant complex patterns are more commonly observed in patients diagnosed with cutaneous melanoma, although there is a significant number of patients with predominant reticular and homogeneous patterns, which are not often associated with an increased risk of development of melanoma.

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.

Using an electronic self-completion tool to identify patients at increased risk of melanoma in Australian primary care

BACKGROUND/OBJECTIVES

Some international guidelines recommend a risk-based approach to screening for melanoma, but few suggest how to account for multiple risk factors or how to implement risk-based screening in practice. This study investigated the acceptability and feasibility of identifying patients at increased risk of melanoma in Australian general practice using a self-completed risk assessment tool. Stratification of risk was based on the validated Williams melanoma risk prediction model.

METHODS

Patients and companions aged 18 or older in Australian general practices were approached in the waiting room and invited to enter information about their melanoma risk factors into the tool using an iPad. Acceptability was measured by the proportion of people willing to participate from those invited and feasibility by the number of people able to complete the tool unaided. Risk of developing melanoma was stratified into four risk categories using the Williams model.

RESULTS

1535 (90.4%) participants were recruited from two general practices. Only 200 participants (13%) needed assistance to complete the tool. The mean risk score for participants was 15.2 (±SD 9.8). The Williams model estimated between 5% and 19% of the sample were at increased risk accounting for an estimated 30% to 60% of future incident melanomas.

CONCLUSIONS

A risk-stratified tool using the Williams model was acceptable and feasible for patients to self-complete in general practice clinics. This could be an effective way to identify people in primary care for implementing risk-based targeted melanoma screening and prevention.

Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma

Melanoma heritability is among the highest for cancer and single nucleotide polymorphisms (SNPs) contribute to it. To date, only SNPs that reached statistical significance in genome-wide association studies or few candidate SNPs have been included in melanoma risk prediction models. We compared four approaches for building polygenic risk scores (PRS) using 12 874 melanoma cases and 23 203 controls from Melanoma Meta-Analysis Consortium as a training set, and newly genotyped 3102 cases and 2301 controls from the MelaNostrum consortium for validation. We estimated adjusted odds ratios (ORs) for melanoma risk using traditional melanoma risk factors and the PRS with the largest area under the receiver operator characteristics curve (AUC). We estimated absolute risks combining the PRS and other risk factors, with age- and sex-specific melanoma incidence and competing mortality rates from Italy as an example. The best PRS, including 204 SNPs (AUC = 64.4%; 95% confidence interval (CI) = 63-65.8%), developed using winner's curse estimate corrections, had a per-quintile OR = 1.35 (95% CI = 1.30-1.41), corresponding to a 3.33-fold increase comparing the 5th to the 1st PRS quintile. The AUC improvement by adding the PRS was up to 7%, depending on adjusted factors and country. The 20-year absolute risk estimates based on the PRS, nevus count and pigmentation characteristics for a 60-year-old Italian man ranged from 0.5 to 11.8% (relative risk  = 26.34), indicating good separation.

Epidemiological and histopathological aspects of primary cutaneous melanoma in residents of Joinville, 2003-2014

BACKGROUND

The worldwide incidence of cutaneous melanoma (CM) has been continuously increasing over the last decades. Primary and secondary prevention, with attention to risk factors and early diagnosis, remain the cornerstone for reducing the burden of cutaneous melanoma. Detailed information with respect to clinical and pathological data on cutaneous melanoma is scarce in Brazil.

OBJECTIVE

The purpose of our study was to analyze epidemiological and pathological characteristics of primary cutaneous melanoma in Joinville, southern Brazil.

METHODS

Observational, cross-sectional, retrospective study in which 893 reports of primary cutaneous melanoma from the local population were analyzed in the period 2003-2014. The study was approved by the local Ethics and Research Committee.

RESULTS

We observed a female predominance of cutaneous melanoma (56.3%). The age standardized incidence rate of primary cutaneous melanoma for the world population in the period 2003-06 was 11.8 per 100,000 population (CI 95%, 10.3-13.4), and 17.5 (CI 95%, 15.7-19.3) in 2011-14, revealing a significant increase of 48.3% (p < 0,05). Six and a half percent of patients had multiple cutaneous melanomas (mean 2.2 years and a maximum of 10.0 years between diagnoses). We observed significant differences between the location head/neck and cutaneous melanoma in situ, lower limb with Breslow depth S III and upper limb with Breslow depth S I. The comparison of the characteristics of cutaneous melanoma in the elderly and non-elderly (< 60 years old) showed significant differences with respect to all the variables studied.

STUDY LIMITATIONS

Using secondary data source.

CONCLUSION

Joinville has high incidence coefficients for Brazilian standards, showing an increase in the incidence of cutaneous melanoma.

Predictors of sun protection behaviours and sunburn among Australian adolescents

BACKGROUND

Excessive sun exposure and sunburn increase individuals' risk of skin cancer. It is especially important to prevent sunburn in childhood due to the higher relative risk of skin cancer across the life span compared to risk associated with sunburn episodes experienced later in life. This study examined demographic and attitudinal factors associated with engagement in a range of sun protection behaviours (wearing a hat, wearing protective clothing, staying in the shade, and staying indoors during the middle of the day) and the frequency of sunburn among Western Australian adolescents to provide insights of relevance for future sun protection campaigns.

METHODS

Cross-sectional telephone surveys were conducted annually with Western Australians between 2005/06 and 2014/15. The results from 4150 adolescents aged 14-17 years were used to conduct a path analysis of factors predicting various sun protection behaviours and sunburn.

RESULTS

Significant primary predictors of the sun protection behaviours included in the study were skin type (sun sensitivity), gender, tanning-related attitudes and behaviours, and perceived relevance of public service advertisements that advocate sun protection. Of the four sun protection behaviours investigated, staying in the shade and staying indoors during the middle of the day were associated with a lower frequency of sunburn.

CONCLUSION

There is a particular need to target sun protection messages at adolescent males who are less likely to engage in the most effective sun protection behaviours and demonstrate an increased propensity to experience sunburn. The results suggest that such future sun protection messages should include a focus on the importance of staying in the shade or indoors during periods of high UV radiation to increase awareness of the efficacy of these methods of avoiding skin cancer.

Association of nevus count with prevention attitudes and behaviors before melanoma diagnosis

Although melanoma risk factors are commonly known to healthcare professionals, the extent to which the at-risk public is either aware of these factors or perceives their risk accordingly has rarely been studied. We sought to investigate whether the presence of known melanoma risk factors, such as high total nevus and atypical nevus counts, was associated with increased prevention attitudes and behaviors, such as skin self-examinations and physician skin examinations. This was a retrospective study of 566 individuals recently diagnosed with melanoma in two large academic centers. Most prevention attitudes and behaviors did not vary on the basis of total nevi or atypical nevi counts. However, younger patients (<60 years) with many total nevi (>50) were more likely than those with fewer nevi (<20) to believe that they were at-risk for melanoma (42 vs. 23%; P<0.05), and more likely to state that they had been instructed on the signs of melanoma (36 vs. 21%; P<0.05). Patient and health provider recognition of the impact of nevus count on melanoma risk presents a unique and mostly untapped opportunity for earlier detection.

Independent validation of six melanoma risk prediction models

Identifying people at high risk of melanoma is important for targeted prevention activities and surveillance. Several tools have been developed to classify melanoma risk, but few have been independently validated. We assessed the discriminatory performance of six melanoma prediction tools by applying them to individuals from two independent data sets, one comprising 762 melanoma cases and the second a population-based sample of 42,116 people without melanoma. We compared the model predictions with actual melanoma status to measure sensitivity and specificity. The performance of the models was variable with sensitivity ranging from 97.7 to 10.5% and specificity from 99.6 to 1.3%. The ability of all the models to discriminate between cases and controls, however, was generally high. The model developed by MacKie et al. (1989) had higher sensitivity and specificity for men (0.89 and 0.88) than women (0.79 and 0.72). The tool developed by Cho et al. (2005) was highly specific (men, 0.92; women, 0.99) but considerably less sensitive (men, 0.64; women, 0.37). Other models were either highly specific but lacked sensitivity or had low to very low specificity and higher sensitivity. Poor performance was partly attributable to the use of non-standardized assessment items and various differing interpretations of what constitutes "high risk".

Screening, early detection, education, and trends for melanoma: current status (2007-2013) and future directions: Part I. Epidemiology, high-risk groups, clinical strategies, and diagnostic technology

While most cancers have shown both decreased incidence and mortality over the past several decades, the incidence of melanoma has continued to grow, and mortality has only recently stabilized in the United States and in many other countries. Certain populations, such as men >60 years of age and lower socioeconomic status groups, face a greater burden from disease. For any given stage and across all ages, men have shown worse melanoma survival than women, and low socioeconomic status groups have increased levels of mortality. Novel risk factors can help identify populations at greatest risk for melanoma and can aid in targeted early detection. Risk assessment tools have been created to identify high-risk patients based on various factors, and these tools can reduce the number of patients needed to screen for melanoma detection. Diagnostic techniques, such as dermatoscopy and total body photography, and new technologies, such as multispectral imaging, may increase the accuracy and reliability of early melanoma detection.

Predicting melanoma risk: theory, practice and future challenges

The incidence of melanoma continues to rise in most fair-skinned populations. Strategies to curb the toll from melanoma include targeting the patients who are at highest risk with the aim of either preventing the onset of cancer or intervening early in order to improve survival. The challenge has been to synthesize the available information on risk factors into prediction tools with clinical utility, such that 'high-risk' patients can be identified with accuracy. While a number of risk prediction tools for melanoma have been developed, few have undergone rigorous evaluation of their performance in order to assess calibration or discrimination, and even fewer have been validated in independent populations. Future research should assess the validity of existing tools and seek to integrate the increasing volumes of data being generated by genomic studies.

Melanoma: A new strategy to reduce morbidity and mortality

BACKGROUND

Public awareness campaigns could address risk factors for melanoma to reinforce their sun protection message. The objective of this study is to prioritise risk factors associated with malignant melanoma (MM) to improve public awareness.

METHOD

DESIGN

A cross-sectional study with retrospective data analysis from 2004 to 2010.

SETTING

Western Australian Melanoma Advisory Service (WAMAS), a tertiary referral multidisciplinary organisation providing MM management advice. WAMAS data files were analysed with histologically confirmed cutaneous MM. Forty- seven patients had two or more melanomas, but the patient file was counted only once. Six MM data files with missing or incomplete information were excluded.

MAIN OUTCOME MEASURES

The number of naevi, blood relatives with MM, and previous sunburns were the primary variables collected.

RESULTS

The results showed that 70.9 per cent (268/378) had previous sunburn; 40.2 per cent (152/378) had multiple naevi; and 22.5 per cent (85/378) had a positive family history. In the 110 MM data files not associated with sunburn, multiple naevi and a positive family history represented 34.5 per cent (38/110) and 20.0 per cent (22/110), respectively.

CONCLUSION

The results confirm the findings of previous studies that multiple naevi and a positive family history are important risk factors associated with MM. We suggest that MM can be detected earlier and its mortality decreased by focusing on these high-risk groups who are not targeted by current public awareness campaigns.

Development of a melanoma risk prediction model incorporating MC1R genotype and indoor tanning exposure: impact of mole phenotype on model performance

Background

Identifying individuals at increased risk for melanoma could potentially improve public health through targeted surveillance and early detection. Studies have separately demonstrated significant associations between melanoma risk, melanocortin receptor (MC1R) polymorphisms, and indoor ultraviolet light (UV) exposure. Existing melanoma risk prediction models do not include these factors; therefore, we investigated their potential to improve the performance of a risk model.

Methods

Using 875 melanoma cases and 765 controls from the population-based Minnesota Skin Health Study we compared the predictive ability of a clinical melanoma risk model (Model A) to an enhanced model (Model F) using receiver operating characteristic (ROC) curves. Model A used self-reported conventional risk factors including mole phenotype categorized as “none”, “few”, “some” or “many” moles. Model F added MC1R genotype and measures of indoor and outdoor UV exposure to Model A. We also assessed the predictive ability of these models in subgroups stratified by mole phenotype (e.g. nevus-resistant (“none” and “few” moles) and nevus-prone (“some” and “many” moles)).

Results

Model A (the reference model) yielded an area under the ROC curve (AUC) of 0.72 (95% CI = 0.69, 0.74). Model F was improved with an AUC = 0.74 (95% CI = 0.71–0.76, p<0.01). We also observed substantial variations in the AUCs of Models A & F when examined in the nevus-prone and nevus-resistant subgroups.

Conclusions

These results demonstrate that adding genotypic information and environmental exposure data can increase the predictive ability of a clinical melanoma risk model, especially among nevus-prone individuals.

Risk prediction models for melanoma: a systematic review

Melanoma incidence is increasing rapidly worldwide among white-skinned populations. Earlier diagnosis is the principal factor that can improve prognosis. Defining high-risk populations using risk prediction models may help targeted screening and early detection approaches. In this systematic review, we searched Medline, EMBASE, and the Cochrane Library for primary research studies reporting or validating models to predict risk of developing cutaneous melanoma. A total of 4,141 articles were identified from the literature search and six through citation searching. Twenty-five risk models were included. Between them, the models considered 144 possible risk factors, including 18 measures of number of nevi and 26 of sun/UV exposure. Those most frequently included in final risk models were number of nevi, presence of freckles, history of sunburn, hair color, and skin color. Despite the different factors included and different cutoff values for sensitivity and specificity, almost all models yielded sensitivities and specificities that fit along a summary ROC with area under the ROC (AUROC) of 0.755, suggesting that most models had similar discrimination. Only two models have been validated in separate populations and both also showed good discrimination with AUROC values of 0.79 (0.70-0.86) and 0.70 (0.64-0.77). Further research should focus on validating existing models rather than developing new ones.

Individual risk of cutaneous melanoma in New Zealand: developing a clinical prediction aid

Background

New Zealand and Australia have the highest melanoma incidence rates worldwide. In New Zealand, both the incidence and thickness have been increasing. Clinical decisions require accurate risk prediction but a simple list of genetic, phenotypic and behavioural risk factors is inadequate to estimate individual risk as the risk factors for melanoma have complex interactions. In order to offer tailored clinical management strategies, we developed a New Zealand prediction model to estimate individual 5-year absolute risk of melanoma.

Methods

A population-based case–control study (368 cases and 270 controls) of melanoma risk factors provided estimates of relative risks for fair-skinned New Zealanders aged 20–79 years. Model selection techniques and multivariate logistic regression were used to determine the important predictors. The relative risks for predictors were combined with baseline melanoma incidence rates and non-melanoma mortality rates to calculate individual probabilities of developing melanoma within 5 years.

Results

For women, the best model included skin colour, number of moles > =5 mm on the right arm, having a 1st degree relative with large moles, and a personal history of non-melanoma skin cancer (NMSC). The model correctly classified 68% of participants; the C-statistic was 0.74. For men, the best model included age, place of occupation up to age 18 years, number of moles > =5 mm on the right arm, birthplace, and a history of NMSC. The model correctly classified 67% of cases; the C-statistic was 0.71.

Conclusions

We have developed the first New Zealand risk prediction model that calculates individual absolute 5-year risk of melanoma. This model will aid physicians to identify individuals at high risk, allowing them to individually target surveillance and other management strategies, and thereby reduce the high melanoma burden in New Zealand.

Skin cancer: increasing awareness and screening in primary care

Skin cancer screening (SCS) promotes early detection and improves treatment. Primary care providers are strategically positioned to provide screenings, yet the frequency is low. Strategies to improve SCS include increasing skin cancer awareness, targeting high-risk patient populations, and advocating for primary care providers to conduct screenings.

Association between in-vitro fertilization, birth and melanoma

A link between reproductive hormones and melanoma has long been suspected, and has been examined for numerous hormonal exposures, but the association between in-vitro fertilization (IVF) and melanoma has not been studied in depth. We used whole-population linked hospital and registry data to carry out a cohort study of women aged 20-44 years seeking hospital investigation and treatment for infertility in Western Australia from 1982 to 2002 with follow-up to 2010. The cohort comprised a total of 21 604 women followed for an average of 17.2 years. Of these, 7524 had IVF treatment, 14 870 gave birth and 149 women were diagnosed with an incident invasive melanoma. Using Cox regression analysis, we estimated hazard ratios (HRs) for melanoma associated with IVF and parity. Women who had IVF and gave birth had an increased rate of invasive melanoma compared with women who had IVF and remained nulliparous (HR 3.61; 95% confidence interval 1.79-7.26). There was little or no increase in the rate of invasive melanoma associated with giving birth in women who had non-IVF infertility treatment (HR 1.39; 95% confidence interval 0.88-2.20). These results suggest an association between reproductive factors and melanoma in the subgroup of women undergoing IVF treatment.

Can we really predict risk of cancer?

BACKGROUND

Growing awareness of the potential to predict a person's future risk of cancer has resulted in the development of numerous algorithms. Such algorithms aim to improve the ability of policy makers, doctors and patients to make rational decisions about behaviour modification or surveillance, with the expectation that this activity will lead to overall benefit. There remains debate however, about whether accurate risk prediction is achievable for most cancers.

METHODS

We conducted a brief narrative review of the literature regarding the history and challenges of risk prediction, highlighting our own recent experiences in developing tools for oesophageal adenocarcinoma.

RESULTS AND CONCLUSIONS

While tools for predicting future risk of cardiovascular outcomes have been translated successfully to clinical practice, the experience with cancer risk prediction has been mixed. Models have now been developed and validated for predicting risk of melanoma and cancers of the breast, colo-rectum, lung, liver, oesophagus and prostate, and while several of these have adequate performance at the population-level, none to date have adequate discrimination for predicting risk in individual patients. Challenges of individual risk prediction for cancer are many, and include long latency, multiple risk factors of mostly small effect, and incomplete knowledge of the causal pathways.

Screening and prevention measures for melanoma: is there a survival advantage?

Controversy has emerged over the past decades regarding the value and impact of melanoma screening to detect early stage disease for improved prognosis. Those questioning the benefits of prevention efforts base their arguments on the absence of prospective, randomized studies demonstrating decreased melanoma mortality to justify the cost associated with screening and educational campaigns. For those in favor of melanoma screening, the lack of proven survival benefit is not a justification to abandon this approach, but rather a reflection of the lack of resources necessary to conduct a long-term trial. In 2009, the US Preventive Services Task Force (USPSTF)report did not recommend routine primary care screening for the general population given the absence of evidence. However, since the USPSTF report, a series of new studies are available, which support the potential benefit of screening and have the potential to significantly impact current policies regarding skin cancer screening, particularly for melanoma.

Identifying Persons at Highest Risk of Melanoma Using Self-Assessed Risk Factors

OBJECTIVE: To develop a self-assessed melanoma risk score to identify high-risk persons for screening METHODS: We used data from a 1997 melanoma case-control study from Washington State, USA, where 386 cases with invasive cutaneous melanoma and 727 controls were interviewed by telephone. A logistic regression prediction model was developed on 75% of the data and validated in the remaining 25% by calculating the area under the receiver operating characteristic curve (AUC), a measure of predictive accuracy from 0.5-1 (higher scores indicating better prediction). A risk score was calculated for each individual, and sensitivities for various risk cutoffs were calculated. RESULTS: The final model included sex, age, hair color, density of freckles, number of severe sunburns in childhood and adolescence, number of raised moles on the arms, and history of non-melanoma skin cancer. The area under the receiver operating characteristic curve(AUC) was 0.70 (95% CI: 0.64, 0.77). The top 15% risk group included 50% of melanomas (sensitivity 50%). CONCLUSIONS: This self-assessed score could be used as part of a comprehensive melanoma screening and public education program to identify high-risk individuals in the general population. This study suggests it may be possible to capture a large proportion of melanomas by screening a small high-risk group. Further study is needed to determine the costs, feasibility, and risks of this approach.