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

Abstract

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. ConclusionThe 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.

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

“…Numerous skin cancer risk prediction models have been developed for research purposes 9 ; however, only a few of them have been validated in a real‐life clinical setting. The results reported in the study of Shetty et al 4 provide a starting point for real‐life implementation of one of them, and support its clinical utility, at least for selecting patients for high risk of keratinocyte cancers. Larger population‐based studies are needed to confirm the clinical utility of the proposed risk assessment tool; results of this study may provide significant implications for health policymakers.…”

“…In the May issue of the Journal, Shetty et al 4 prospectively investigated the clinical utility of risk assessment tools derived from the QSkin Study 5 to identify individuals with skin cancers, at an outpatient clinic on Hamilton Island, Queensland (Australia), during the annual yachting race. 507 of 789 (64%) patients, including both competitors with high sun exposure and subjects of the island community, completed a paper‐based self‐assessment questionnaire consisting of 16 items derived from the Melanoma Risk Stratification Tool and the Keratinocyte Cancer Risk Stratification Tool 6‐7 .…”

“…We must acknowledge that in the study of Shetty et al 4 a high‐risk population was selected on the basis of fair skin individuals with a high level of sun exposure. Nevertheless, study limitations include the recall bias due to a self‐reported questionnaire and the fact that participants are not representative of the general Queensland population.…”

Skin cancer excisions and histopathology outcomes when following a contemporary population‐based cohort longitudinally with 3D total‐body photography

“…In a spot‐clinic screening in 2019, 100 biopsies were performed in 507 participants (19.7%). 12 Participants were invited randomly from the Australian Electoral Roll, but this study's novel technology may have attracted individuals at increased skin cancer risk or already concerned about a skin lesion. This is consistent with demographic and phenotypic characteristics of our participants, with 25% family history of melanoma and 7% previous melanoma.…”

Skin Cancer Research Goes Digital: Looking for Biomarkers within the Droplets

“…However, the latter might be a gross underestimation of the real number, due to challenges related to NMSC diagnosis and reporting [ 6 ]. The increased rate of fatality in skin cancer is mainly attributed to late diagnosis, due to non-specific symptoms [ 7 , 8 ], the absence of effective screening methods [ 9 ], the lack of sensitive and specific biomarkers for early diagnosis, prognosis, and treatment follow-up [ 10 ], as well as to a limited understanding of drug resistance mechanisms in these tumors [ 11 ]. Hence, in the last two years, the COVID-19 pandemic, which has become the epicenter of daily clinical practice, restricted access to healthcare facilities and delayed the diagnosis of patients with CM and other skin cancers, resulting in increased rates of morbidity, mortality, and, consequently, a greater financial burden on the health system [ 12 ].…”