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Multi-national case-crossover builder

Each case acts as their own control across time. Compare exposure prevalence in a short hazard window immediately before the event with prevalence in matched control windows further back.

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1 · Study identification

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

2 · Research question

Population Exposure Outcome (defines case)

3 · Sites

Tick every database (not just country). Feature chips indicate what each database can support — case-crossover needs Rx (or whatever the exposure source is) and Dx (case ascertainment), and any extra data the case definition demands.

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 case-crossover protocols often accommodate this; just be explicit in the per-site analytic plan.

4 · Case definition (outcome)

Validation citation auto-appends to References on export.

Operational case definition Code set Index date for the case

5 · Exposure definition

Exposure — name Exposure — code set Exposure ascertainment rule

6 · Hazard (case) window

Hazard window length (days) End anchor (relative to event) Day -1 avoids reverse-causation where the exposure is dispensed because the event has occurred.

7 · Control window(s)

Number of control windows Offset to first control (days before event) Length of each control window

8 · Design variant

Case-crossover variant Time-stratified controls for secular trends in exposure prevalence. Symmetric requires post-event exposure not to be influenced by the event. CCTC (Huang WC, Yang ASH, Tsai DHT, Shao SC, Lin SJ, Lai ECC. BMJ 2023;382:e076045; PMID 37758279) computes OR_CCTC = OR_Case / OR_Control where the control crossover uses future cases to subtract out time-trends in exposure — strong when reverse causality between symptoms and prescribing is a concern.

9 · Statistical analysis

Primary model Effect estimate Meta-analysis

Subgroup analyses — tick those to perform

Age (≥65 vs <65 years) Age (≥75 vs <75 years) Sex (male vs female) Country / site First-ever vs repeated exposure Index calendar year stratum Baseline CV disease (yes vs no) Baseline CKD (eGFR <60 vs ≥60) Frailty / Charlson Comorbidity Index (high vs low) Concomitant exposure (yes vs no)

Custom subgroups (one per line)

10 · Sensitivity analyses

Alternative hazard window length (e.g., 1 d, 7 d, 14 d, 30 d) Alternative control window offset (30, 60, 90, 180 d before) Multiple control windows (e.g., 4 control periods to reduce variance) Restrict to incident exposure only (first ever dispensing) Time-stratified case-crossover (Janes et al 2005) — controls drawn from same calendar stratum Symmetric bidirectional sampling (control before and after event) Negative-control outcome — should show null Exclude events within 30 days of cohort entry to avoid prevalent-user bias Stratify by season to control for time-trends in exposure

Custom sensitivity analyses (one per line)

11 · Execution & timeline

Architecture

Timeline preset

Milestones (one per line)

12 · Ethics, dissemination, references (optional)

Ethics Dissemination Key references (one per line)

Maclure M. The case-crossover design: a method for studying transient effects on the risk of acute events. Am J Epidemiol 1991;133(2):144-53.
Mittleman MA, Maclure M, Robins JM. Control sampling strategies for the case-crossover design: an assessment of relative efficiency. Am J Epidemiol 1995;142(1):91-8.
Janes H, Sheppard L, Lumley T. Case-crossover analyses of air pollution exposure data: referent selection strategies and their implications for bias. Epidemiology 2005;16(6):717-26.
Huang WC, Yang ASH, Tsai DHT, Shao SC, Lin SJ, Lai ECC. Association between recently raised anticholinergic burden and risk of acute cardiovascular events: nationwide case-case-time-control study. BMJ 2023;382:e076045. PMID: 37758279. (AsPEN exemplar of the CCTC variant; hazard day -1 to -30, four 30-d reference periods in -61 to -180, 60-d washout.)
Wang SV, Schneeweiss S. A general propensity score for signal identification using tree-based scan statistics. Am J Epidemiol 2018 (case-case-time-control discussion).
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. Pharmacoepidemiol Drug Saf 2019;28(5):593-600.

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Working title

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Description (summary from your draft)

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