Question 1

What is target trial emulation?

Accepted Answer

Target trial emulation is a framework for analyzing observational data as though it were a randomized trial. You specify the trial you would have run — eligibility, treatment strategies, assignment, follow-up, outcome, and analysis plan — and then emulate each component in the observational data, which makes the assumptions explicit and exposes design errors such as immortal time bias.

Question 2

How closely do emulations reproduce their target trials?

Accepted Answer

Across 279 benchmarked comparisons, the pooled hazard ratio of emulation to trial estimate is 1.02 (95% credible interval 0.96 to 1.07): no systematic bias on average. Agreement in individual comparisons is much looser — the emulation confidence interval contains the trial estimate in 53% of comparisons, and the prediction interval for a new comparison spans 0.68 to 1.52.

Question 3

Why are some comparisons excluded from the pooled analysis?

Accepted Answer

Every extracted comparison is shown, but only those whose randomized benchmark could be verified against the trial’s primary report enter the pooled models. Comparisons are held back when the benchmark is unverifiable, when the emulation and trial report incompatible effect scales, or when the reference trial had not reported before the emulation was published. Each excluded comparison states its reason.

Question 4

Is XeraTTE open access?

Accepted Answer

Yes. Every study, comparison and analysis result is browsable and downloadable as CSV or JSON with no registration, and the API is public.

Study	Outcome & target trial	Trial vs emulation	Agreement
Baptiste 2024 Cardiology	Cough vs ONTARGET·RR·Safety	0.260.21–0.33 1.291.16–1.43	no overlap12.61 SE apart
Garry 2022 Critical care	28-day mortality vs RECOVERY·HR·Efficacy	0.820.72–0.94 1.321.21–1.45	no overlap5.79 SE apart
Hu 2024 Endocrinology	Anemia event occurrence or anemia treatment initiation vs DAPA-CKD·HR·Efficacy	0.390.31–0.48 0.800.72–0.90	no overlapMajor deviation5.74 SE apart
Wang 2023 All areas	Moderate or severe COPD exacerbation vs IMPACT·HR·Efficacy	0.850.80–0.91 1.131.04–1.23	no overlapPartial alignment5.28 SE apart
Suissa 2024 Pulmonology	Exacerbations vs IMPACT·HR·Efficacy	0.850.80–0.91 1.131.04–1.23	no overlapMajor deviation5.28 SE apart
Suissa 2024 Pulmonology	Exacerbations vs IMPACT·HR·Efficacy	0.840.78–0.91 1.081.00–1.17	no overlapMajor deviation4.48 SE apart
Kong 2025 Oncology	Overall survival vs MONALEESA-2·HR·Efficacy	0.760.63–0.93 2.751.62–4.69	no overlapClose alignment4.45 SE apart
Merola 2024 Oncology	12-month overall survival vs KEYNOTE-189·HR·Efficacy	0.490.38–0.64 0.950.78–1.16	no overlap3.96 SE apart
Szummer 2020 Cardiology	(readmission for) major bleeding vs PLATO·HR·Efficacy	1.040.95–1.13 1.481.25–1.76	no overlapMajor deviation3.60 SE apart
Yoon 2023 Hematology	Major bleeding vs AMPLIFY·RR·Safety	0.310.17–0.55 0.990.73–1.37	no overlap3.42 SE apart
Garry 2022 Critical care	28-day mortality vs RECOVERY·HR·Efficacy	0.640.51–0.81 1.020.89–1.18	no overlap3.37 SE apart
Wang 2023 All areas	Hospitalization for heart failure / mortality vs PARADIGM-HF·HR·Efficacy	0.800.73–0.87 1.020.91–1.14	no overlap3.33 SE apart
Wang 2023 All areas	Moderate or severe COPD exacerbation vs POET-COPD·HR·Efficacy	0.830.77–0.90 1.020.93–1.12	no overlap3.33 SE apart
Suissa 2024 Pulmonology	Moderate or severe exacerbations vs POET-COPD·HR·Efficacy	0.830.77–0.90 1.020.93–1.12	no overlap3.33 SE apart
Althunian 2020 Cardiology	Stroke, systemic embolism, or vascular death vs Rocket AF·HR·Efficacy	0.860.74–0.99 1.181.03–1.34	no overlapPartial alignment3.16 SE apart
Jiao 2023 Cardiology	Congestive heart failure vs SPRINT·HR·Efficacy	0.620.45–0.84 1.010.96–1.06	no overlap3.03 SE apart
Wakabayashi 2023 Endocrinology	Change in HbA1c, % vs Onishi et al.·MD·Efficacy	-0.28-0.46–-0.10 0.46-0.01–0.94	no overlap2.86 SE apart
Gallivan 2023 Opthalmology	Mean change in ETDRS BCVA letters vs VIEW 1·MD·Efficacy	-2.80-5.11–-0.49 0.90-0.16–1.96	no overlap2.85 SE apart
Jiao 2023 Cardiology	MACE (major adverse cardiovascular events) vs SPRINT·HR·Efficacy	0.750.64–0.89 0.960.92–1.00	no overlap2.84 SE apart
Deng 2023 Endocrinology	Major adverse cardiovascular events (MACE) vs GRADE·HR·Efficacy	0.700.48–1.01 1.381.01–1.90	overlap2.73 SE apart
An 2026 Oncology	Metastasis vs ProtecT·HR·Efficacy	0.470.29–0.76 0.990.77–1.29	no overlapMajor deviation2.67 SE apart
Jiao 2023 Cardiology	Death from any cause vs SPRINT·HR·Efficacy	0.730.60–0.90 0.960.95–0.98	no overlap2.64 SE apart
Keyhani 2020 Cardiology	Fatal and non-fatal stroke within 5 years vs ACST-1·RD·Efficacy	-5.90-7.80–-4.00 -2.10-4.40–-0.20	overlap2.63 SE apart
Deng 2023 Endocrinology	Time to HbA1c ≥7.0% vs GRADE·HR·Efficacy	0.690.63–0.76 0.900.75–1.08	overlap2.54 SE apart
Powell 2024 Cardiology	Major bleeding vs ARISTOTLE·HR·Safety	0.690.60–0.80 0.880.77–1.00	overlap2.45 SE apart