Available online 9 May 2023

Author links open overlay panel, , , , , ABSTRACT

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

Section snippetsINTRODUCTION

While drug-cancer associations may be identified from preclinical studies and randomized controlled trials (RCTs), preclinical studies do not necessarily translate to humans [1], and RCTs are usually too small and short to detect rare outcomes with long latency periods such as cancer [2], [3]. As such, large, methodologically robust pharmacoepidemiologic studies with extended follow-up are needed to examine the potential carcinogenic effects of medications. One important methodological

Cancer latency

Carcinogenesis is widely accepted to be a multistage biological process of cellular transformation, with mutational and epigenetic changes driving progression through key stages, including initiation, promotion, progression, invasion, and metastases [4]. A carcinogen can act at any stage of carcinogenesis. In general, it is believed to take many years from exposure to a causative agent to cancer development and subsequent clinical manifestation and diagnosis [8].

This period includes two

Challenges in the application of lag times in studies of drug-cancer associations

Given the complexities outlined above, defining the most appropriate lag time for a given study may not be straightforward and depends on the specific drug-cancer association being studied. The choice of lag time is an important design consideration as biologically misspecified lag periods may affect results. The long induction periods for drug cancer associations can have implications as exposure measured at different points along the pathway e.g., during the latent period may result in

Other considerations: the interaction between lags and dose-response analyses

In addition to lagged analyses, duration/dose-response analyses are also of importance for the interpretation of drug-cancer associations. For most cancer associations, we do not expect the hazard function to be proportional over time, and averaged estimates may not give a meaningful representation of how risk varies over time [3]. Duration or dose-response analyses provide insight into the potential mechanisms of associations, identify potential biases, including reverse causality and

Recommendations

As outlined above, the typically long induction and latent period of most cancers, the potential for reverse causality, and detection bias justify the application of lags in drug-cancer studies. We make the below recommendations for researchers undertaking studies of drug-cancer associations.

1.

In studies of drug-cancer associations, the relevant latency periods of cancer and the issues of reverse causality and detection bias should always be considered in the planning of the design and analyses,

FUNDING

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

ACKNOWLEDGMENTS

Conflicts of interest: the authors report no conflicts of interest relevant to the manuscript.

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