ebmdatalab / screeningviz

Helping visualise potential problems with screening programmes
MIT License
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Review previous visualisation work #1

Open sebbacon opened 5 years ago

sebbacon commented 5 years ago

This smiley faces approach (from Tom at North Devon) is a common approach (original) image

There is a similar, animated version here, which couches it in terms of Bayes' Theorem, and includes the classic "finding terrorists" example among others: image

North Devon also piloted a diabetes test in a single practice (full write up), showing each patient their test results in context, and found a significant drop in HbA1c in patients with the intervention:

image

sebbacon commented 5 years ago

CRUK have a PSA infographic which doesn't address all the numbers, but is visually quite nice.

image

It is an illustration of the Cochrane Review that finds no reduction in prostate-cancer-related mortality, so doesn't indicate (for reasonable didactic purposes) the number of extra true cancer cases found, and doesn't attempt to illustrate harm from over-treatment (which is just a footnote).

sebbacon commented 5 years ago

There are some interesting (if unrelated) approaches to statistical visualisation here

sebbacon commented 5 years ago

An excel tool for visualising the relationships between odds rations and sensitivity / selectivity

sebbacon commented 5 years ago

Another tool combining screening and relative risk into data tables

sebbacon commented 5 years ago

From Jessica's paper:

image

jamesscottbrown commented 4 years ago

Luana Micallef had a 2012 paper comparing the effectiveness of 6 visualizations (more data):

bayes-vis

It is cited by a couple of papers by Karin Binder et al that may be of interest:

sebbacon commented 4 years ago

Fab, thanks!

sebbacon commented 4 years ago

Tangentially related: we found this RCT recently, which compares GP understanding of post-test probability based on (a) text summary of sensitivity and specificity, (b) Fagan’s nomogram, (c) probability-modifying plot (PMP), (d) natural frequency tree. Spoiler: (c) and (d) won.

sebbacon commented 4 years ago

A useful nomenclature from here:

image

sebbacon commented 4 years ago

@jamesscottbrown my hypothesis is that an interactive tool with sliders to change the prior probabilities might be helpful. You've obviously been thinking about the problem too. Any thoughts yourself?

sebbacon commented 4 years ago

A website currently under development:

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sebbacon commented 4 years ago

Same website has these posters:

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