Inflammatory bowel disease (IBD) — Crohn’s disease and ulcerative colitis — affects roughly 3 million United States adults. Uncontrolled mucosal inflammation drives colectomy, colorectal cancer, venous thromboembolism, and hospitalisation. This oracle estimates the causal reduction in mucosal inflammation — the proximal mediator of these hard outcomes — achievable by combining advanced therapies, using effect sizes from named trials and network meta-analyses. Crucially, several of these agents carry their own serious harms, shown as competing-harm paths.
Tick the interventions to combine. Each shows its trial hazard ratio, 95% confidence interval (CI), E-value, mechanism, and citation. ★ = in the current Pareto effective set but not yet ticked.
Headline is the front-door estimate: shared inflammation-mediator overlap removed via dose-response saturation; residual direct-effect overlap removed via the eigenvalue model at ρ̄.
Under monotonicity + exogeneity (E-value bounds the exogeneity assumption).
Faithful causal directed acyclic graph (DAG). Each therapy is a distinct node; nearly all benefit flows through the shared mediator mucosal inflammation (fecal calprotectin), which drives colorectal cancer, colectomy and venous thromboembolism — each a route to mortality. Critically, anti-TNF, JAK inhibitors and thiopurines add a competing-harm path (infection, lymphoma, drug-induced thrombosis) that the efficacy hazard ratio does NOT capture. Named confounders open back-door paths (adjusted). Illustrative of structure, not yet the identification engine.
Eigenvalue diagnostics for the selected interventions under an equicorrelation matrix (off-diagonal ρ̄). A large λmax relative to k signals redundancy; n_eff is the effective number of independent interventions actually contributing.
On mechanistic grounds ρ̄ ≈ 0.30 is defensible for this domain: incretin drugs, surgery, diet, and activity overwhelmingly share the weight-loss / insulin-sensitivity pathway, so ~30% of their nominal effects overlap. A mediation analysis of semaglutide found ~80% of its MACE benefit is not mediated by weight loss, which is why ρ̄ is user-adjustable rather than fixed.
Minimum-effective-set analysis. Set a target combined risk reduction; the model finds the smallest set of interventions — accounting for front-door mediator overlap — that reaches it, and highlights them. If the target exceeds what all interventions together can achieve, the full set is shown (never an empty one). "Apply" ticks exactly that set.
Monte Carlo propagation. Each selected intervention's log-hazard-ratio is sampled from a normal distribution implied by its 95% CI; samples are combined with the same eigenvalue overlap discount. 5,000 draws.
Intervening on the selected set S with Pearl's do-operator (setting the interventions, not merely observing them). Contrast against do(∅) = no intervention.
For each intervention: "if not for this one, the combined front-door hazard ratio would be…". Isolates each intervention's marginal causal contribution after mediator-overlap removal, so shared-pathway agents are not double-credited.
| If not for… | HR without it | HR with full set | marginal RRR lost |
|---|
One-at-a-time sensitivity. Each intervention's hazard ratio is swung across its 95% confidence interval (others held at point estimate); the bar is the resulting swing in the combined front-door HR. A long bar means the combined estimate leans heavily on that single trial's precision.
Front-door (mediation) decomposition. Nearly every IBD therapy acts through one shared mediator — suppression of mucosal inflammation (fecal calprotectin / endoscopic healing). Each log-effect is split into an inflammation-mediated (indirect) and a small inflammation-independent (direct) part. Indirect parts are pooled through the mediator with dose-response saturation (you cannot suppress the same inflammation twice — combining a biologic with a second advanced therapy rarely doubles remission), removing the mediator cross-correlation; direct parts keep the residual eigenvalue correlation at ρ̄. The efficacy decomposition is SEPARATE from the competing-harm paths shown in the causal DAG.
| Intervention | HR | %inflam↓ | infl-med | indirect logHR | direct logHR |
|---|
Which % of cross-correlation is appropriate? Not one number. The mediator overlap is fixed empirically by the inflammation-suppression saturation (currently removing — of the summed inflammation-mediated effect when advanced therapies are stacked). Because every agent converges on the same inflammatory pathway, overlap is large — combination advanced therapy yields far less than additive remission. Inflammation-mediated fractions are transparent, adjustable priors.
Front-door caveat (antithesis): the cited endpoint is clinical remission / mucosal healing — a surrogate. Its link to colectomy and colorectal-cancer prevention is supported but the mortality translation is partly observational. Critically, this front-door captures only the BENEFIT arm: it does NOT subtract the competing harms (JAK thrombosis, thiopurine lymphoma, anti-TNF infection) shown as separate paths in the DAG. A high-efficacy hazard ratio is therefore NOT a net-benefit estimate.
Select interventions to generate a plain-language summary.