National Targeted Skin Cancer Screening Roadmap · Methodological framework

At what risk scoredo you draw the line between screen and don't screen?

ATOF is a decision-analytic framework that integrates clinical net benefit, overdiagnosis harms, and regional workforce capacity into a single answer to that question — for every region of Australia, under every plausible workforce scenario.

Validated models

45 and Up Study

AUC range

0.66–0.76

external validation

In situ overdiagnosis

67–76%

Lindsay 2024

QLD SA4s with zero derms

53%

Lindsay 2026

Risk threshold

3.0%

Workforce scenario

Workforce capacity vs screening demand

Each SA4 coloured by capacity utilisation at the selected threshold. Drag the slider above and watch Australia respond.

88 SA4 regions

Component 1 · Decision Curve Analysis

Net benefit at every threshold

Decision curve analysis (Vickers & Elkin 2006) plots the population-level net benefit of using a risk model at each threshold, against screen everyone and screen no one. Curves are modelled from published AUCs using a binormal approximation.

Overdiagnosis adjustmentUseful range 0.5–15.0%

10-yr melanoma prevalence2.0%

0.5%5%

Models shown

Primary model

QSkin MP16

At threshold

3.0%

Sensitivity

55%

False positive rate

14.9%

Number needed to screen

Decision curves modelled from published AUCs using a binormal approximation (Vickers & Elkin 2006). Final ATOF analysis will reconstruct curves from individual-level 45 and Up Study data.

Component 3 · Threshold Optimiser

Where can screening start tomorrow?

For every SA4, the minimum feasible thresholdis the lowest risk cut-point at which the region's annual screening flow stays within available workforce capacity. Regions below the current national slider can run screening today; regions above it cannot, regardless of willingness.

≤2%24%

21 / 88

High capacity

2–5%59%

52 / 88

Moderate

5–7%11%

10 / 88

Constrained

>7%6%

5 / 88

Tight workforce

Unfeasible0%

0 / 88

Workforce ≈ 0

What this means for the Roadmap

Under the combined (derm + gp) scenario, a uniform national threshold of 3.0% 10-year risk is feasible in 55 of 88 SA4 regions. The remaining 33 would either need to be excluded from the program or accept demand that exceeds their workforce. 15 regions require thresholds above 5%, primarily where dermatologist density is zero or skin-cancer GP supply is thin.

Minimum feasible threshold by SA4 — strip plot

n = 88 SA4s · sorted within each state

feasible at ≤2% 2–5% 5–7% >7% current threshold (3.0%)

Hardest 5 regions to screen

Region	State	Remoteness	Min threshold	Source
Moreton Bay - North	QLD	MM1	10.7%	Lindsay 2026 (real)
Brisbane - East	QLD	MM1	10.2%	Lindsay 2026 (real)
Wide Bay	QLD	MM3	9.8%	Lindsay 2026 (real)
Darling Downs - Maranoa	QLD	MM4	7.9%	Lindsay 2026 (real)
Toowoomba	QLD	MM3	7.3%	Lindsay 2026 (real)

Capacity model uses adjusted FTE × annual consultation rates ÷ 2-year screening cadence. Lindsay et al. 2026 (PMID:41674191) values for QLD; Blake et al. 2023 (PMID:37353974) anchors for NSW; AIHW NHWDS + ACD workforce snapshot for other states.

Component 4 · Equity reveal

Who bears the burden of a uniform threshold?

A single national threshold is mathematically simple but pretends that workforce is evenly distributed. ATOF makes the trade-off explicit: every region's min feasible threshold, stratified by SEIFA disadvantage or ARIA+ remoteness.

What this means for equity

Under the current scenario, the median minimum feasible threshold for SEIFA Q1 (most disadvantaged) regions is 2.8%, compared with 1.9% for Q5 (most advantaged) — a 1.5× disparity. At the current uniform threshold of 3.0%, 847k Q1 residents live in regions whose workforce cannot deliver screening, versus 199k in Q5. A uniform threshold systematically transfers the under-supply burden to disadvantaged communities.

SEIFA quintile	SA4s	Population	Median min	Mean min	Pop in over-capacity SA4s
Q1 (most disadvantaged)	10	1.38M	2.8%	3.3%	847k(61%)
Q2	28	6.12M	3.1%	3.5%	2967k(49%)
Q3	26	8.85M	2.7%	3.5%	2581k(29%)
Q4	10	3.91M	2.6%	4.2%	1306k(33%)
Q5 (most advantaged)	14	4.22M	1.9%	2.2%	199k(5%)

Distribution of minimum thresholds within each stratum

one dot per SA4

SEIFA quintile is the ABS Index of Relative Socio-Economic Disadvantage applied to each SA4 (1 = most disadvantaged, 5 = most advantaged). ARIA+ remoteness uses the Modified Monash Model (MM1 metropolitan → MM7 very remote). Min feasible threshold reflects the current workforce scenario setting at the top of the page.