New Melanoma Risk Prediction Tool Superior in Accuracy to Previous Tools

This instrument, comprised of seven predictors and known as MP7, was evaluated by a sequence of investigators in an evaluation authored by such researchers as David C. Whiteman, MBBS, PhD, of the Department of Population Health at QIMR Berghofer Medical Research Institute in Australia.

In their evaluation’s introduction, Whiteman and colleagues highlighted that focus on approaches are more and more getting used to systematically detect melanomas, and people at highest threat are prioritized for screenings.²

“Moreover, the number of newly diagnosed invasive melanomas in the QSkin cohort has almost tripled, providing substantially greater statistical power than previously,” Whiteman and coauthors wrote.¹ “Herein, we describe the development and validation of a new prediction model for invasive melanoma in the QSkin cohort over 10 years to inform risk-stratification strategies.”

Cohort Study Design

The investigative crew applied knowledge for his or her evaluation drawn from the QSkin Sun and Health Study. QSkin was a big population-based potential cohort primarily based in Queensland, Australia. QSkin had recruited people of grownup age, particularly aged 40–69 years, between November 2010 – December 2011 utilizing a random sampling of their state’s inhabitants.

Those who had been proven to have a registry-confirmed historical past of melanoma (both in situ or invasive) earlier than their enrollment weren’t included by Whiteman et al. Ethical approval was granted by the Human Research Ethics Committee of the QIMR Berghofer Medical Research Institute, with all topics offering their written knowledgeable consent.

For the investigation, individuals had been adopted for a decade after the 2011 baseline survey. Only people who had been listed as melanoma-free at recruitment and who accomplished the great baseline threat issue questionnaire had been included on this evaluation. Whiteman and colleagues’ nalyses had been carried out within the interval between October 2024 – April 2025.

At the examine’s entry, 31 baseline variables had been prespecified as potential predictors of subsequent occurrences of invasive melanoma. Incident circumstances of invasive melanoma amongst individuals, decided histologically, had been discovered by the investigators through report linkage with the Queensland Cancer Register for diagnoses. Censoring of individuals on the time of melanoma occurred in situ prognosis or dying. To construct the prediction mannequin, Whiteman and collagues used Cox proportional hazards regression with each ahead and backward variable choice methods.

Melanoma Prediction Accuracy Findings

Among the 41,919 individuals deemed eligible for inclusion, Whiteman and coauthors famous that 55% had been feminine and that the imply age at baseline was 55.4 years. Across 401,356 person-years of commentary, there have been 706 people who developed a brand new invasive melanoma.

In the ultimate mannequin, there have been 14 baseline predictors: intercourse, age, affected person ancestry, nevus density, hair shade, freckling density, tanning response, historical past of sunburns in maturity, household melanoma historical past, earlier prognosis of one other most cancers, pores and skin most cancers excision historical past, smoking standing, earlier actinic keratoses, and top. There had been additionally 2 extra phrases: age squared and an age-by-sex interplay.

The investigative crew concluded that the prediction instrument attained a discrimination index (C statistic) of 0.74 (95% CI, 0.73–0.76).¹ Through using the Youden index, the optimum screening threshold was famous as having corresponded to concentrating on the highest 40% at predicted threat. This would establish 74% of future melanoma circumstances, with a quantity wanted to display screen of 32.

Overall, the crew’s cohort examine recognized the instrument as an possibility permitting for enhanced accuracy for the prediction of 1’s future threat of invasive melanoma in contrast with different present instruments.

“In future research, we will assess the benefit of adding genetic information to the tool, and we have recently recruited a second, independent cohort in which to validate the tool externally in the years ahead,” Whiteman and colleagues concluded.¹ “In the meantime, we see strong merit in assessing the performance of this tool independently in other settings.”

References

1. Whiteman DC, Olsen CM, Pandeya N, et al. A Risk Prediction Tool for Invasive Melanoma. JAMA Dermatol. Published on-line September 10, 2025. doi:10.1001/jamadermatol.2025.3028.

2. Collins GS, Dhiman P, Ma J, et al. Evaluation of medical prediction fashions (half 1): from growth to exterior validation. BMJ. 2024;384:e074819. doi:10.1136/bmj-2023-074819.