Process guide for inferential studies using healthcare data from routine clinical practice to evaluate causal effects of drugs (PRINCIPLED): considerations from the FDA Sentinel Innovation Center

Rishi J Desai¹, Shirley V Wang¹, Sushama Kattinakere Sreedhara¹, Luke Zabotka¹, Farzin Khosrow-Khavar¹, Jennifer C Nelson², Xu Shi³, Sengwee Toh⁴, Richard Wyss¹, Elisabetta Patorno¹, Sarah Dutcher⁵, Jie Li⁵, Hana Lee⁵, Robert Ball⁵, Gerald Dal Pan⁵, Jodi B Segal⁶, Samy Suissa⁷, Kenneth J Rothman⁸, Sander Greenland⁹, Miguel A Hernán¹⁰, Patrick J Heagerty¹¹, Sebastian Schneeweiss¹

Affiliations

¹ Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, USA.
² Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
³ Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
⁴ Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
⁵ US Food and Drug Administration, Silver Spring, MD, USA.
⁶ Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁷ Departments of Epidemiology and Biostatistics, and Medicine, McGill University, Montreal, QC, Canada.
⁸ Boston University School of Public Health, Boston, MA, USA.
⁹ Department of Epidemiology and Department of Statistics, University of California, Los Angeles, CA, USA.
¹⁰ CAUSALab and Departments of Epidemiology and Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA.
¹¹ Department of Biostatistics, University of Washington, Seattle, WA, USA.

PMID: 38346815
DOI: 10.1136/bmj-2023-076460

Process guide for inferential studies using healthcare data from routine clinical practice to evaluate causal effects of drugs (PRINCIPLED): considerations from the FDA Sentinel Innovation Center

Rishi J Desai et al. BMJ. 2024.

. 2024 Feb 12:384:e076460.

doi: 10.1136/bmj-2023-076460.

Authors

Affiliations

¹ Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, USA.
² Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
³ Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
⁴ Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
⁵ US Food and Drug Administration, Silver Spring, MD, USA.
⁶ Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁷ Departments of Epidemiology and Biostatistics, and Medicine, McGill University, Montreal, QC, Canada.
⁸ Boston University School of Public Health, Boston, MA, USA.
⁹ Department of Epidemiology and Department of Statistics, University of California, Los Angeles, CA, USA.
¹⁰ CAUSALab and Departments of Epidemiology and Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA.
¹¹ Department of Biostatistics, University of Washington, Seattle, WA, USA.

PMID: 38346815
DOI: 10.1136/bmj-2023-076460

No abstract available

PubMed Disclaimer

Conflict of interest statement

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: support from the FDA for the submitted work. RJD reports serving as principal investigator on investigator initiated grants to the Brigham and Women’s Hospital from Novartis, Vertex, and Bayer on unrelated projects. SS is co-principal investigator of an investigator initiated grant to the Brigham and Women’s Hospital from Boehringer Ingelheim unrelated to the topic of this study, and is a consultant to Aetion, a software manufacturer of which he owns equity; his interests were declared, reviewed, and approved by the Brigham and Women’s Hospital and Mass General Brigham HealthCare System in accordance with their institutional compliance policies. RB is an author on US Patent 9 075 796 (on text mining for large medical text datasets and corresponding medical text classification using informative feature selection), which at present is not licensed and does not generate royalties. JCN reports research funding from Moderna for service on their safety monitoring committee.

MeSH terms

Actions
Actions
Actions

Grants and funding

U01 FD007213/FD/FDA HHS/United States

LinkOut - more resources

Full Text Sources
- HighWire
- Ovid Technologies, Inc.
Medical
- MedlinePlus Health Information

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Process guide for inferential studies using healthcare data from routine clinical practice to evaluate causal effects of drugs (PRINCIPLED): considerations from the FDA Sentinel Innovation Center

Affiliations

Process guide for inferential studies using healthcare data from routine clinical practice to evaluate causal effects of drugs (PRINCIPLED): considerations from the FDA Sentinel Innovation Center

Authors

Affiliations

Conflict of interest statement

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical