Integrating Causal Inference into Pharmacovigilance: Target Trial Emulations for Proactive Signal Detection of Atorvastatin Initiation in Medicare Beneficiaries
- 1Veritas Research Foundation, San Clemente, CA, USA
Abstract
ImportanceAdverse drug events (ADEs) in older adults are a substantial public health burden, yet spontaneous reporting systems detect them poorly owing to underreporting and the lack of a defined population. These limitations are of particular concern for older adults, who are underrepresented in pre-approval trials yet at elevated ADE risk owing to polypharmacy, multimorbidity, and age-related changes in drug metabolism.
ObjectiveTo develop and apply an active, claims-based pharmacovigilance framework using sequential target trial emulation to detect ADE signals in older adults, with atorvastatin as the initial application.
MethodsUsing Medicare fee-for-service claims (2017-2019), we studied statin-naive beneficiaries aged 65 years or older following hospitalization for myocardial or cerebral infarction. We emulated up to 14 daily sequential trials from the discharge date, classifying patients as initiating atorvastatin (A1), initiating a different medication (A2), or no new medication (A0); the primary contrast was A1 versus A2. For each trial, incident ADEs were ascertained and classified into 552 outcomes based on the Clinical Classifications Software Refined categories. Per-protocol effect estimates were measured over a 6-month follow-up period using Fine-Gray regression weighted by the inverse probability of treatment (IPT) and censoring, treating death as a competing risk, with the false discovery rate controlled via the Benjamini-Hochberg procedure. A signal was declared when the q-value was [≤] 0.10 and the subdistribution hazard ratio (sHR) was [≥] 1.20 in any prespecified analytic stratum (sensitivity analyses used thresholds of q [≤] 0.20 and sHR [≥] 1.20).
ResultsOf 70,130 eligible patients, 39,948 initiated atorvastatin (A1), 19,182 initiated another new medication (A2); after IPT-weighting, baseline characteristics were closely balanced. After excluding outcomes with sparse cell counts, 295 outcomes were analyzed; five met the primary signal detection criteria: valve disorders (sHR 1.71, 1.20-2.43); sprains and strains (sHR 1.79, 1.26-2.54); general sensation/perception symptoms (sHR 1.23, 95% CI 1.11-1.36); abnormal findings without diagnosis (sHR 1.55, 1.18-2.05); and prediabetes (sHR 1.71, 1.24-2.36). In the sensitivity analysis, we additionally detected: posthemorrhagic anemia, hemorrhagic stroke, varicose veins, other circulatory and skin conditions.
ConclusionsA claims-based framework using sequential target trial emulations detected both expected and previously unrecognized ADE signals following atorvastatin initiation in older adults, offering a systematic alternative to passive surveillance that can be extended to other commonly prescribed medications. Confirmatory analyses with disaggregated outcomes and narrower comparators are underway and will be reported separately.
KEY POINTSO_ST_ABSQuestionC_ST_ABSCan an active, claims-based pharmacovigilance framework using sequential target trial emulation detect adverse drug event signals among older Medicare beneficiaries who initiated atorvastatin?
FindingsIn this cohort study of 59,130 Medicare beneficiaries discharged after myocardial or cerebral infarction, a hypothesis-free scan across hundreds of prespecified outcomes detected five primary signals (valve disorders, sprains and strains, sensory symptoms including dizziness, abnormal laboratory findings, and prediabetes) and additional signals in sensitivity analyses (including hemorrhagic stroke), several of which align with known or labeled statin adverse effects (serving as positive controls that validate the framework) while others remain uncertain.
MeaningThis framework offers a systematic, quantitative, and proactive alternative to spontaneous reporting for detecting medication safety signals in high-risk older adults.
PLAIN LANGUAGE SUMMARYOlder adults use more prescription drugs than any other age group, yet they are often left out of clinical trials conducted before a drug is approved. As a result, the safety of many medications in older patients is poorly understood until the drugs are already in wide use. The main system for detecting new drug safety problems in the United States, the FDA Adverse Event Reporting System, relies on voluntary reports and captures only a small fraction of harms, which limits its usefulness.
Using Medicare reimbursement records, the researchers developed an active monitoring method and tested it on a commonly used cholesterol-lowering medication (atorvastatin) - that is frequently prescribed after a heart attack or stroke. They followed thousands of patients for six months, statistically balancing those who started atorvastatin with those who started a different new drug, and screened for hundreds of possible side effects. Evidence of potential medication harm emerged along a clear range of how likely the drug caused each problem. This ranged from well-known side effects (such as diabetes and sprains and strains) and outcomes already noted in the product labeling or prior research (such as hemorrhagic stroke and dizziness) to more uncertain associations (such as cardiac valve disorders) that are difficult to interpret. Overall, atorvastatin appeared largely safe in this older population, and the same method can now be used to study other widely used drugs.
Related
- Beyond Signal Detection: Sequential Target Trial Emulations to Confirm Previously Detected Adverse Drug Event Signals for Atorvastatin in Older Medicare Beneficiaries
- Integrating pharmacovigilance and machine learning: bleeding signal detection and risk prediction for oral anticoagulants in cancer patients
- Use of SGLT2 Inhibitors, GLP‐1 Receptor Agonists, and DPP‐4 Inhibitors in Incident Hyponatremia in Patients with Type 2 Diabetes: Multicenter Target Trial Emulations
- Atorvastatin improves hyperlipidemia-induced erectile dysfunction via PKA-associated eNOS phosphorylation at the Ser633 site
- Atorvastatin Prevents Early Lipotoxic Remodelling in Right Ventricular Pacing–Induced Cardiomyopathy
BibTeX
@misc{rowan2026integrating,
title = {{Integrating Causal Inference into Pharmacovigilance: Target Trial Emulations for Proactive Signal Detection of Atorvastatin Initiation in Medicare Beneficiaries}},
author = {C. G. Rowan and J. Tazare and M. Tran and S. Srivastava and N. A. Dreyer and C. Maringe},
howpublished = {medRxiv},
year = {2026},
month = jul,
doi = {10.64898/2026.07.01.26356874},
url = {https://www.medrxiv.org/content/10.64898/2026.07.01.26356874v4},
note = {CC BY},
}
RIS
TY - UNPB
TI - Integrating Causal Inference into Pharmacovigilance: Target Trial Emulations for Proactive Signal Detection of Atorvastatin Initiation in Medicare Beneficiaries
AU - C. G. Rowan
AU - J. Tazare
AU - M. Tran
AU - S. Srivastava
AU - N. A. Dreyer
AU - C. Maringe
PY - 2026
DA - 2026/07/01
PB - medRxiv
DO - 10.64898/2026.07.01.26356874
UR - https://www.medrxiv.org/content/10.64898/2026.07.01.26356874v4
AB - ImportanceAdverse drug events (ADEs) in older adults are a substantial public health burden, yet spontaneous reporting systems detect them poorly owing to underreporting and the lack of a defined population. These limitations are of particular concern for older adults, who are underrepresented in pre-approval trials yet at elevated ADE risk owing to polypharmacy, multimorbidity, and age-related changes in drug metabolism. ObjectiveTo develop and apply an active, claims-based pharmacovigilance framework using sequential target trial emulation to detect ADE signals in older adults, with atorvastatin as the initial application. MethodsUsing Medicare fee-for-service claims (2017-2019), we studied statin-naive beneficiaries aged 65 years or older following hospitalization for myocardial or cerebral infarction. We emulated up to 14 daily sequential trials from the discharge date, classifying patients as initiating atorvastatin (A1), initiating a different medication (A2), or no new medication (A0); the primary contrast was A1 versus A2. For each trial, incident ADEs were ascertained and classified into 552 outcomes based on the Clinical Classifications Software Refined categories. Per-protocol effect estimates were measured over a 6-month follow-up period using Fine-Gray regression weighted by the inverse probability of treatment (IPT) and censoring, treating death as a competing risk, with the false discovery rate controlled via the Benjamini-Hochberg procedure. A signal was declared when the q-value was [≤] 0.10 and the subdistribution hazard ratio (sHR) was [≥] 1.20 in any prespecified analytic stratum (sensitivity analyses used thresholds of q [≤] 0.20 and sHR [≥] 1.20). ResultsOf 70,130 eligible patients, 39,948 initiated atorvastatin (A1), 19,182 initiated another new medication (A2); after IPT-weighting, baseline characteristics were closely balanced. After excluding outcomes with sparse cell counts, 295 outcomes were analyzed; five met the primary signal detection criteria: valve disorders (sHR 1.71, 1.20-2.43); sprains and strains (sHR 1.79, 1.26-2.54); general sensation/perception symptoms (sHR 1.23, 95% CI 1.11-1.36); abnormal findings without diagnosis (sHR 1.55, 1.18-2.05); and prediabetes (sHR 1.71, 1.24-2.36). In the sensitivity analysis, we additionally detected: posthemorrhagic anemia, hemorrhagic stroke, varicose veins, other circulatory and skin conditions. ConclusionsA claims-based framework using sequential target trial emulations detected both expected and previously unrecognized ADE signals following atorvastatin initiation in older adults, offering a systematic alternative to passive surveillance that can be extended to other commonly prescribed medications. Confirmatory analyses with disaggregated outcomes and narrower comparators are underway and will be reported separately. KEY POINTSO_ST_ABSQuestionC_ST_ABSCan an active, claims-based pharmacovigilance framework using sequential target trial emulation detect adverse drug event signals among older Medicare beneficiaries who initiated atorvastatin? FindingsIn this cohort study of 59,130 Medicare beneficiaries discharged after myocardial or cerebral infarction, a hypothesis-free scan across hundreds of prespecified outcomes detected five primary signals (valve disorders, sprains and strains, sensory symptoms including dizziness, abnormal laboratory findings, and prediabetes) and additional signals in sensitivity analyses (including hemorrhagic stroke), several of which align with known or labeled statin adverse effects (serving as positive controls that validate the framework) while others remain uncertain. MeaningThis framework offers a systematic, quantitative, and proactive alternative to spontaneous reporting for detecting medication safety signals in high-risk older adults. PLAIN LANGUAGE SUMMARYOlder adults use more prescription drugs than any other age group, yet they are often left out of clinical trials conducted before a drug is approved. As a result, the safety of many medications in older patients is poorly understood until the drugs are already in wide use. The main system for detecting new drug safety problems in the United States, the FDA Adverse Event Reporting System, relies on voluntary reports and captures only a small fraction of harms, which limits its usefulness. Using Medicare reimbursement records, the researchers developed an active monitoring method and tested it on a commonly used cholesterol-lowering medication (atorvastatin) - that is frequently prescribed after a heart attack or stroke. They followed thousands of patients for six months, statistically balancing those who started atorvastatin with those who started a different new drug, and screened for hundreds of possible side effects. Evidence of potential medication harm emerged along a clear range of how likely the drug caused each problem. This ranged from well-known side effects (such as diabetes and sprains and strains) and outcomes already noted in the product labeling or prior research (such as hemorrhagic stroke and dizziness) to more uncertain associations (such as cardiac valve disorders) that are difficult to interpret. Overall, atorvastatin appeared largely safe in this older population, and the same method can now be used to study other widely used drugs.
ER -