A Study of the Frequency and Social Determinants of Exposure to Cancer-Related Direct-to-Consumer Advertising Among Breast, Prostate, and Colorectal Cancer Patients

Tan, Andy S.L.

doi:10.1080/10410236.2014.921752

Cited by 5 publications

(2 citation statements)

References 34 publications

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“…Factors cited as potential reasons for the unusually rapid funding of trastuzumab included media coverage and survivorship [19]. Breast cancer is a highly publicized disease [20][21][22][23][24]. We may hypothesize that the strong media presence around breast cancer may contribute to political pressure to fund breast cancer drugs more quickly than therapeutics for other tumor types that are less prevalent in modern media.…”

Section: Impact Of Tumor Typementioning

confidence: 99%

Determinants of the Cancer Drug Funding Process in Canada

et al. 2022

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Background: Canada has a publicly funded healthcare system with a complex drug funding process. After Health Canada approval to market a drug, the pan-Canadian Oncology Drug Review (pCODR) (now renamed the CADTH reimbursement review) makes a non-binding funding recommendation to the Canadian provinces (except Quebec), which each then decide whether the drug will be publicly funded. We identified the determinants of funding in this process. Methods: We analyzed drugs for advanced lung (n = 15), breast (n = 8), colorectal (CRC) (n = 7), melanoma (n = 10), and neuroendocrine (NET) (n = 3) cancers undergoing the funding decision process from 2011 to 2019. Determinants of funding assessed in the model included list price, cancer type, drug class, and pCODR recommendation. The primary outcome was the correlation between list price and time to funding (TTF: Health Canada approval to first provincial funding). Secondary outcomes included an exploratory analysis of predictors of drug funding. Results: We analyzed 43 drugs: targeted agents 72%, immunotherapy 20%, chemotherapy 7%. A total of 72% were funded in at least one province. Median TTF was 379 days (IQR 203–601). Median list price (28-day course) was CAD 8213 (IQR CAD 5391–9445). Higher list price was not correlated with TTF (correlation coefficient −0.20, p = 0.28). There was no association between list price and pCODR recommendation or the decision to fund in at least one province. A positive pCODR recommendation correlated with the provinces’ funding decisions (p < 0.001), where 89% of drugs with a positive recommendation were funded and 100% of drugs with a negative recommendation were not funded. Tumor type was predictive of TTF (p < 0.001): CRC drugs were the slowest at a median of 2541 days (IQR 702–4379), and NETs were the quickest at a median of 0 days (IQR 0–502). Cancer type predicted decision to fund in at least one province (p = 0.005), with funding for 100% of NET drugs at the high end and 29% of CRC drugs at the low end. Drug class was predictive of TTF (p = 0.01): 465 days (IQR 245–702) for targeted agents, 443 days (IQR 298–587) for chemotherapy, and 339 days (IQR 164–446) for immunotherapy. Conclusions: Determinants of drug funding included cancer type, drug class, and pCODR recommendation but not list price. Factors other than cost were more heavily weighted in the funding decisions of cancer drugs in Canadian provinces.

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Section: Impact Of Tumor Typementioning

confidence: 99%

Determinants of the Cancer Drug Funding Process in Canada

et al. 2022

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“…Another consideration is that there is an optimal number of exposures that prompt viewers curiosity about the product, therefore encouraging attention to the message. When studying the effects of DTCAs of cancer treatments, Tan (2015) argued that an exposure only counted if a message was attended to since attention is what would account for later recall. Though recall was not tested in this study, this argument should be explored further.…”

Section: Attentionmentioning

confidence: 99%

How the operationalization of exposure impacts studies on direct-to-consumer advertising of prescription drugs

Savelli

2020

IJPHM

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Purpose Without having a shared operationalization of what constitutes a direct-to-consumer advertising (DTCA) exposure, it is impossible to accurately generalize findings about their effects. First, it needs to be established how the variables involved in exposures impact outcomes. This will allow for more accurate operationalizations. Design/methodology/approach A sample of 216 participants were recruited from Amazon’s Mechanical Turk and randomly assigned into one of four conditions to take an online survey. A 2 × 2 experiment (active/passive attention × low/high exposure) was conducted to determine if the level of attention, otherwise known as attentiveness, and the number of exposures impacted preferences for a fictitious prescription sleep aid. Findings Results indicated a significant difference among active and passive conditions such that active exposures resulted in stronger positive preferences. Research limitations/implications Studies using different operationalizations should not be aggregated for generalizations about the effects of DTCA of prescription drugs. Originality/value This paper urges researchers to clearly operationalize their definitions for “exposure” and to be hesitant about generalizing findings studies using different definitions.

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