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A 3D Organotypic Melanoma Spheroid Skin Model
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A Risk Prediction Tool for Invasive Melanoma.
David C Whiteman1,2,3, Catherine M Olsen1,4, Huanwei Wang1
1Department of Population Health, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.
JAMA Dermatology
|September 10, 2025
Summary
This study developed an improved melanoma risk prediction tool using 10 years of data from the QSkin Study. The new tool enhances accuracy in identifying individuals at high risk for invasive melanoma.
Area of Science:
- Dermatology
- Epidemiology
- Oncology
Background:
- Targeted screening strategies for melanoma are increasingly employed, prioritizing high-risk individuals.
- Existing melanoma risk prediction tools often suffer from limited accuracy and potential biases.
Purpose of the Study:
- To develop an improved risk prediction tool for invasive melanoma.
- Enhance the accuracy of melanoma risk assessment for targeted screening.
Main Methods:
- A population-based prospective cohort study (QSkin Study) in Australia with 10 years of follow-up.
- Utilized Cox proportional hazards models with forward and backward selection to identify predictors of invasive melanoma.
- Included 41,919 participants aged 40-69, free of melanoma at baseline.
Main Results:
- The best-fitting model identified 14 predictors and 2 statistical terms, achieving a discriminatory accuracy of 0.74.
- Key predictors included age, sex, ancestry, nevus and freckling density, hair color, tanning ability, sunburns, family history, and prior skin conditions.
- A screening threshold capturing the top 40% of predicted risk identified 74% of invasive melanoma cases.
Conclusions:
- An improved invasive melanoma risk prediction tool has been developed.
- This tool demonstrates enhanced accuracy compared to existing prediction models.
- The findings support the use of this tool for more effective melanoma screening.
