Longevityresearch.ca publishes cross-disease causal analysis quantifying endpoint reduction across 27 diseases

TORONTO - Rezul -- An open Bayesian Causal Atlas now reports, for every disease it covers — including non-fatal conditions — the best-case modelled reduction achievable when all applicable beneficial interventions are combined under a Pearl structural-causal framework.

Longevity Research (longevityresearch.ca), an independent quantitative-research project, today released a cross-oracle analysis that computes, for each disease in its Bayesian Causal Atlas, the maximum modelled reduction in that disease's own endpoint when every applicable beneficial intervention is combined at full dose under the project's causal model.

The analysis covers 27 disease models in a single comparable table — spanning all-cause mortality, cardiovascular disease (18 phenotypes), cancer (18 sites), kidney disease, immunology (45 conditions), pulmonary disease, brain tumours, organ transplant, and more — and, unlike most mortality-focused work, it deliberately includes endpoints that are not death: allergy flares, kidney-function decline, disability progression, and other quality-of-life outcomes.

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Longevity Research is an independent, non-commercial quantitative-research project that applies Bayesian causal inference to the leading causes of mortality and to chronic disease. Its Bayesian Causal Atlas is a free, open set of interactive analyses intended for people managing serious illness, their caregivers, and researchers. The site runs no advertising and collects no user data.

https://longevityresearch.ca/