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Multi-national ACNU protocol builder

Active-comparator new-user design under a target trial emulation framework. The active comparator behaves as an 'emulated placebo' from the same therapeutic context — minimising confounding by indication and addressing immortal-time / prevalent-user bias. Tick the boxes for the operational pieces; export as Word (.docx) or Markdown.

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1 · Study identification

Study title Short ID Version · Date Lead investigator(s)

2 · Research question (one-line summary)

Population Exposure Comparator Primary outcome Emulated target trial (optional) If this ACNU study emulates a specific RCT, name it here. The methods section then opens with the target-trial framing.

3 · Sites

Tick every database (not just country) you want to include. The feature chips next to each show what each database can support — only tick a site whose features cover what your outcome / exposure / covariates need (e.g., a lab-defined outcome needs Lab; an all-cause mortality endpoint needs Mor).

Legend Rx Prescriptions Dx Diagnoses Lab Lab results Img Imaging Mor Mortality linkage Can Cancer-registry linkage Preg Pregnancy / birth linkage Gen Genomics / biobank linkage

Taiwan

CGRD RxDxLabImg NHIRD RxDxLabImgMorCanPreg TWB LabGen

South Korea

HIRA RxDx NHIS-NHID RxDxLabMorCan

Japan

JMDC Claims Database RxDxLab Medical Data Vision (MDV) Database RxDxLab NDB RxDx

Hong Kong

CDARS RxDxLabImgMorCan

Australia

PBS Rx VLHD RxDxMor

Finland

FinReg RxDxMorCanPreg

United Kingdom

CPRD RxDxMorCanPreg ISD RxDxLabMorCanPreg THIN RxDx UKB LabImgMorCanGen

Netherlands

PHARMO Database Network RxDxLabMorCan

United States

20% sample RxDxMorCan Medicaid RxDxMor

Others (one per line)

⚠ Feasibility heads-up — not a blocker

Your study question implies data features that some selected sites don't carry. Multi-country protocols often accommodate this (other sites cover what some miss); just be explicit in the per-site analytic plan.

4 · Cohort definition

Indication / cohort entry condition

Age range Sex

Inclusion criteria — tick those to apply

Adult (≥18 years) at index date Continuous enrolment in the source database for ≥365 d before index ≥1 outpatient visit in the 365 d before index (engagement with care) ≥1 prior dispensing of indication-defining drug class in look-back Available primary-care record (CPRD / linked EHR studies only)

Custom inclusion criteria (one per line)

Exclusion criteria — tick those to apply

Prior dispensing of EITHER exposure or comparator within the washout window Type 1 diabetes (ICD-10 E10.x) ever before index Pregnancy at or in the 90 d before index eGFR <30 ml/min/1.73m² at index (where available) End-stage renal disease / chronic dialysis ever Active cancer in the 365 d before index (solid or haematologic) Hospice or palliative-care enrolment in the 90 d before index Severe liver disease ever (cirrhosis, decompensated) Type 2 MI / unstable angina in the 30 d before index (if CV outcome) In-hospital at index date

Custom exclusion criteria (one per line)

5 · Exposure & comparator

Exposure — name Exposure — code set Comparator — name Comparator — code set Washout (days)

Index date definition

6 · Outcome ascertainment

Fills definition + codes; the validation citation is added to the References section automatically on export.

Operational definition Code set

Secondary outcomes — tick those to include

All-cause mortality Cardiovascular death Heart failure hospitalisation Non-fatal myocardial infarction Non-fatal ischemic stroke Acute kidney injury DKA Hip fracture Any fracture Pneumonia hospitalisation Intracranial haemorrhage GI bleeding

Custom secondary outcomes (one per line)

7 · Follow-up & censoring

Primary analysis Grace period (days)

Maximum follow-up

Censoring rules — tick those that apply

Discontinuation of index drug (gap > grace period) Switch to the comparator drug class Disenrolment from the source health-insurance database Death from a non-outcome cause End of database availability / study period Pregnancy Cancer diagnosis (if not an outcome) Hospice or palliative-care enrolment

Custom censoring rules (one per line)

8 · Confounding control

Auto-fills the method, its operational details, and adds the method citation to References on export.

Primary confounding-control method Secondary / alternative methods can be ticked under Sensitivity analyses. Covariate look-back (days)

Method operational details

Baseline covariates — tick those to adjust for

Demographics

Age (continuous) Sex Year of index Insurance type Region / urbanicity

Comorbidities (binary, ever in look-back)

Hypertension Dyslipidaemia Chronic kidney disease Prior myocardial infarction Prior stroke / TIA Heart failure Atrial fibrillation COPD Depression Active cancer Liver disease Peripheral artery disease Charlson Comorbidity Index (CCI)

Medications (binary, dispensed in look-back)

ACEi / ARB Beta-blockers Calcium channel blockers Diuretics Statins Antiplatelets Anticoagulants NSAIDs Glucocorticoids Metformin Sulfonylureas TZDs Insulin GLP-1 receptor agonists

Healthcare utilisation

Outpatient visit count Inpatient admission count ED visit count Polypharmacy (≥5 drug classes)

Clinical / lab (where available)

HbA1c BMI eGFR Smoking status Blood pressure

Custom covariates (one per line)

9 · Statistical analysis

Effect estimate Meta-analysis

Subgroup analyses — tick those to perform

Age (≥65 vs <65 years) Sex (male vs female) Baseline CKD (eGFR <60 vs ≥60) Prior CV disease (yes vs no) Country / site Index year (e.g., before vs after 2018) Insulin use at baseline Baseline HbA1c (≥8% vs <8%)

Custom subgroups (one per line)

Sensitivity analyses — tick those to include

PS trimming to area of common support Alternative washout period (180 d, 730 d) Alternative grace period (0, 60, 90 d) ITT vs on-treatment (whichever is not the primary) Active-comparator restriction to a single agent Negative-control outcome (e.g., fracture or skin infection) Exclude first 30 days of follow-up (latency analysis) High-dimensional propensity score (HDPS) Restrict to incident users only (≥1 year look-back required) Exclude pregnant patients E-value for unmeasured confounding

Custom sensitivity analyses (one per line)

10 · Execution & timeline

Architecture CDM

Timeline preset

Milestones (one per line)

11 · Ethics, dissemination, references (optional)

Ethics Dissemination Key references (one per line)

Cashin AG, Hansford HJ, Hernán MA, Swanson SA, Lee H, Jones MD, et al. Transparent Reporting of Observational Studies Emulating a Target Trial: The TARGET Statement. JAMA 2025. PMID: 40899949. (Reporting framework anchoring this protocol — see also https://target-guideline.org/)
Tsai DHT, Chuang ATM, Liu KH, Shao SC, Lai ECC. SGLT2 inhibitors and risk of CKD-mineral and bone disorders in patients with type 2 diabetes mellitus and stage 1-3 CKD. CMAJ 2025;197(7):E178-E189. PMID: 39993818. (AsPEN ACNU + target trial emulation exemplar.)
Hernán MA, Robins JM. Using big data to emulate a target trial when a randomized trial is not available. Am J Epidemiol 2016;183(8):758-64.
Lund JL, Richardson DB, Stürmer T. The active comparator, new user study design in pharmacoepidemiology: historical foundations and contemporary application. Curr Epidemiol Rep 2015;2:221-8.
Andersen M, Pratt N, Sanfélix-Gimeno G et al. Pharmacoepidemiol Drug Saf 2013 (AsPEN founding methods paper).
Lai EC, Man KK, Chaiyakunapruk N et al. Epidemiology 2015 (AsPEN database survey).
Pratt NL, Mack CD, Meyer AM et al. Pharmacoepidemiol Drug Saf 2018 (AsPEN common data model framework).
Hsieh CY, Su CC, Shao SC, Sung SF, Lin SJ, Kao Yang YH, Lai EC. Taiwan's NHIRD: past and future. Clin Epidemiol 2019;11:349-358.
Shao SC, Chan YY, Kao Yang YH, Lin SJ, Hung MJ, Chien RN, Lai CC, Lai EC. The Chang Gung Research Database (CGRD). Pharmacoepidemiol Drug Saf 2019;28(5):593-600.
Tsai DHT, Wong ICK, Pratt N et al. Clin Epidemiol 2023 (NeuroGEN multi-database infrastructure).
Schneeweiss S et al. Epidemiology 2009 (high-dimensional propensity score).

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Validated phenotype library

Pick a phenotype

Code sets are starting points based on published literature — always confirm against your site's coding system version and indication-specific guidance before locking the protocol.

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Send protocol draft

Working title

Lead — name Lead — email

Description (summary from your draft)

Sites will be carried over from your draft.

Why this study? *