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The application of lag times in cancer pharmacoepidemiology: a narrative review.
Hicks, Blánaid; Kaye, James A; Azoulay, Laurent; Kristensen, Kasper Bruun; Habel, Laurel A; Pottegård, Anton.
Affiliation
  • Hicks B; Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK. Electronic address: B.Hicks@qub.ac.uk.
  • Kaye JA; RTI Health Solutions, Waltham, MA.
  • Azoulay L; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada; Centre for Clinical Epidemiology, Lady Davis Institute, Montreal, QC, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, Canada.
  • Kristensen KB; Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark.
  • Habel LA; Division of Research, Kaiser Permanente Northern California, Oakland, CA.
  • Pottegård A; Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark.
Ann Epidemiol ; 84: 25-32, 2023 08.
Article in En | MEDLINE | ID: mdl-37169040
ABSTRACT

PURPOSE:

With the increasing utilization of medications worldwide, coupled with the increasing availability of long-term data, there is a growing opportunity and need for robust studies evaluating drug-cancer associations. One methodology of importance in such studies is the application of lag times.

METHODS:

In this narrative review, we discuss the main reasons for using lag times.

RESULTS:

Namely, we discuss the typically long latency period of cancer concerning both tumor promoter and initiator effects and outline why cancer latency is a key consideration when choosing a lag time. We also discuss how the use of lag times can help reduce protopathic and detection bias. Finally, we present practical advice for implementing lag periods.

CONCLUSIONS:

In general, we recommend that researchers consider the information that generated the hypothesis as well as clinical and biological knowledge to inform lag period selection. In addition, given that latency periods are usually unknown, we also advocate that researchers examine multiple lag periods in sensitivity analyses as well as duration analyses and flexible modeling approaches.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neoplasms / Antineoplastic Agents Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Ann Epidemiol Year: 2023 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neoplasms / Antineoplastic Agents Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Ann Epidemiol Year: 2023 Document type: Article