Good test–retest reproducibility for an instrument to capture self-reported melanoma risk factors

Morze, C.; Olsen, Catherine M.; Perry, Susan; Jackman, Louisa; Ranieri, Barbara A; O’Brien, Suzanne; Cicero, Rebekah A; Whiteman, David C.

doi:10.1016/j.jclinepi.2012.06.014

Cited by 49 publications

(95 citation statements)

References 23 publications

(35 reference statements)

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“…However, discrimination was modest between the ‘none’ and ‘few’ categories and thus consideration should be given to combining these categories in future risk analyses. Other studies that have used similar diagrams for classifying self-reports of whole-body nevus density have found comparable agreement with clinical assessment (25, 31). Interestingly, in the Queensland study (25), the number of clinically measured nevi corresponding to each descriptive nevus category was less than half that recorded for the same categories in our study.…”

Section: Discussionmentioning

confidence: 66%

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Accuracy of Self-Reported Nevus and Pigmentation Phenotype Compared with Clinical Assessment in a Population-Based Study of Young Australian Adults

Cust

Pickles

Goumas

et al. 2015

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background Awareness of individual risk may encourage improved prevention and early detection of melanoma. Methods We evaluated the accuracy of self-reported pigmentation and nevus phenotype compared to clinical assessment, and examined agreement between nevus counts from selected anatomical regions. The sample included 456 cases with invasive cutaneous melanoma diagnosed between ages 18-39 years and 538 controls from the population-based Australian Melanoma Family Study. Participants completed a questionnaire regarding their pigmentation and nevus phenotype, and attended a dermatologic skin examination. Results There was strong agreement between self-reported and clinical assessment of eye color (kappa, κ, =0.78, 95% confidence interval (CI) 0.74-0.81); and moderate agreement for hair color (κ =0.46, 95% CI 0.42-0.50). Agreement between self-reported skin color and spectrophotometer-derived measurements was poor (κ =0.12, 95% CI 0.08-0.16) to moderate (Spearman correlation rs=-0.37, 95% CI -0.32- to -0.42). Participants tended to under-estimate their nevus counts and pigmentation; men were more likely to under-report their skin color. The rs was 0.43 (95% CI 0.38-0.49) comparing clinical total body nevus counts with self-reported nevus categories. There was good agreement of quartile distributions of total body nevus counts with site-specific nevus counts, particularly on both arms. Conclusions Young adults have sub-optimal accuracy when assessing important risk characteristics including nevus numbers and pigmentation. Measuring nevus count on the arms is a good predictor of full body nevus count. Impact These results have implications for the likely success of targeted public health programs that rely on self-assessment of these factors.

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Section: Discussionmentioning

confidence: 66%

“…A study of 114 participants aged 40-69 years from a cohort in Queensland, Australia, reported moderate agreement for eye color (κ = 0.58) and hair color (κ = 0.63) (25). In the United Kingdom, Melia et al (26) also found moderate agreement for self-report versus dermatologist assessment of hair color.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of Self-Reported Nevus and Pigmentation Phenotype Compared with Clinical Assessment in a Population-Based Study of Young Australian Adults

Cust

Pickles

Goumas

et al. 2015

Cancer Epidemiology, Biomarkers &Amp; Prevention

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“…Secondly, in populations exposed to high levels of ambient solar ultraviolet radiation (such as Australia or southern USA), the role of pigmentation factors risk is likely accentuated because these factors strongly determine the actual dose of ultraviolet radiation received at the level of the target cell. Thirdly, because phenotypic measures are reported with higher reproducibility than sun exposure (both in this sample (Morze et al, 2012) and others (English et al, 1998;van der Mei et al, 2006;Yu et al, 2009)), they are less prone to misclassification and thus, on average, more likely to discriminate cases from controls. The models described here are conceived to be clinical aids for stratifying patients according to their probability of developing skin cancer requiring surgical excision.…”

Section: Discussionmentioning

confidence: 68%

“…The characteristics of the questionnaire have been published, including measures of repeatability for study survey items (Morze et al, 2012).…”

Section: Data Collectionmentioning

confidence: 99%

A Model to Predict the Risk of Keratinocyte Carcinomas

Thrift

Hughes

Muranushi

et al. 2016

Journal of Investigative Dermatology

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Basal cell and squamous cell carcinomas of the skin are the commonest cancers in humans, yet no validated tools exist to estimate future risks of developing keratinocyte carcinomas. To develop a prediction tool, we used baseline data from a prospective cohort study (n = 38,726) in Queensland, Australia, and used data linkage to capture all surgically excised keratinocyte carcinomas arising within the cohort. Predictive factors were identified through stepwise logistic regression models. In secondary analyses, we derived separate models within strata of prior skin cancer history, age, and sex. The primary model included terms for 10 items. Factors with the strongest effects were >20 prior skin cancers excised (odds ratio 8.57, 95% confidence interval [95% CI] 6.73-10.91), >50 skin lesions destroyed (odds ratio 3.37, 95% CI 2.85-3.99), age ≥ 70 years (odds ratio 3.47, 95% CI 2.53-4.77), and fair skin color (odds ratio 1.75, 95% CI 1.42-2.15). Discrimination in the validation dataset was high (area under the receiver operator characteristic curve 0.80, 95% CI 0.79-0.81) and the model appeared well calibrated. Among those reporting no prior history of skin cancer, a similar model with 10 factors predicted keratinocyte carcinoma events with reasonable discrimination (area under the receiver operator characteristic curve 0.72, 95% CI 0.70-0.75). Algorithms using self-reported patient data have high accuracy for predicting risks of keratinocyte carcinomas.

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“…The reliability of many of the items used in this study has been tested within a prospective cohort study of 43,794 Queensland residents currently being undertaken by the investigators (11). In that larger study, we performed reliability analyses on 114 participants surveyed on 2 occasions (average interval 188 days), and found agreement for items asking about numbers of previous skin cancers treated by surgery and numbers of solar keratoses treated by cryotherapy (the commonest modalities for these lesions in Queensland) were 0.79 (95% CI, 0.71-0.88) and 0.83 (95% CI, 0.76-0.90), respectively (12). Our finding that melanomas arising on the head or neck are less likely to have high nevus counts than trunk melanomas corroborates our previous results in an independent, substantially smaller case series (n ¼ 306), where patients with head/neck melanoma or LMM were significantly less likely to have high nevus counts than trunk melanoma patients (1).…”

Section: Discussionmentioning

confidence: 96%

Site-Specific Determinants of Cutaneous Melanoma: A Case–Case Comparison of Patients with Tumors Arising on the Head or Trunk

Kvaskoff

Pandeya

Green

et al. 2013

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background: Cutaneous melanomas have been hypothesized to arise through different pathways according to phenotype, body site, and sun exposure. To further test this hypothesis, we explored associations between phenotype and melanoma at different sites using a case-case comparative approach.Methods: Melanoma patients (n ¼ 762) aged 18 to 79 years and diagnosed from 2007 to 2010 were ascertained from pathology laboratories in Brisbane, Australia. Patients reported phenotypic information and a dermatologist counted melanocytic nevi and solar keratoses. We compared data for patients with trunk melanoma (n ¼ 541, the reference group), head/neck melanoma (n ¼ 122), or lentigo maligna melanoma (LMM) of the head/neck (n ¼ 69). ORs and 95% confidence intervals were calculated using classical or polytomous logistic regression models.Results: Compared with trunk melanoma patients, those with head/neck melanoma were significantly less likely to have high nevus counts (135: OR ¼ 0.27; P trend ¼ 0.0004). Associations between category of nevus count and LMM head/neck were weaker and significantly different (135: OR ¼ 1.09; P trend ¼ 0.69; P homogeneity ¼ 0.02). Patients with head/neck melanoma were more likely than those with truncal melanoma to have high solar keratosis counts (7: OR ¼ 1.78, P trend ¼ 0.04). Again, associations with LMM head/neck were weaker, albeit not significantly different (7: OR ¼ 1.61; P trend ¼ 0.42; P homogeneity ¼ 0.86).Conclusion: Trunk melanomas are more strongly associated with nevus counts than head/neck melanomas, but are less strongly associated with number of solar keratoses, a marker of chronic sun exposure.Impact: These findings underscore the notion that melanomas on the trunk typically arise through a causal pathway associated with nevus propensity, whereas melanomas on the head/neck arise through a pathway associated with cumulative sun exposure. Cancer Epidemiol Biomarkers Prev; 22(12); 2222-31. Ó2013 AACR.

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Good test–retest reproducibility for an instrument to capture self-reported melanoma risk factors

Cited by 49 publications

References 23 publications

Accuracy of Self-Reported Nevus and Pigmentation Phenotype Compared with Clinical Assessment in a Population-Based Study of Young Australian Adults

Accuracy of Self-Reported Nevus and Pigmentation Phenotype Compared with Clinical Assessment in a Population-Based Study of Young Australian Adults

A Model to Predict the Risk of Keratinocyte Carcinomas

Site-Specific Determinants of Cutaneous Melanoma: A Case–Case Comparison of Patients with Tumors Arising on the Head or Trunk

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