Whilst it is true that Juul is not exactly popular with those on either side of the fence this article fails to address the major issue.
The impending regulation which Juul is said to have brought down on the vapor industry helps Juul by eliminating the competition. Only they, and other brands owned by tobacco companies have any hope of being able to afford the process to keep their products on the market. Independent manufacturers and the retailers who sell their products will simply be obliterated.
Considering that these are people who who have dedicated their lives and often their life savings to helping people switch to safer alternatives, and who are by far and away the most efficient at enforcing strict age verification for purchases, this is a tragedy, not something to be celebrated.
Lastly, as if it still needs to be said, the outbreak of acute lung injury in the US has not been linked with Juul, or any other commercially available nicotine vaping product.
I 100% understand the general good intent of this paper. I also must say that I am Cherokee but not "fullblooded" Cherokee. I did grow up in the heart of the Nation, though. However, could people please stop using the term "American Indian"? Indians are from India. Columbus got lost (even though he was a navigator), ran the one ship he captained aground where he was found by the Native population of the island he smashed into (which for the record was not anywhere near North America). He looked around and thought, "I'm on a beach, I was trying to find India, India has a beach. These people are not white, they are tan, Indians are tan! I'm in India!" He then spread his stupid to the world. Now every tan person originating from any American continent (which are when put together the same land mass as the entire "known" world at that time) are all Indians... Please stop. It's just offensive.
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David Levy and colleagues’ paper “Examining the relationship of vaping to smoking initiation among US youth and young adults: a reality check” used data from all the surveys over time that measured youth and young adult e-cigarette use and smoking and concluded there was a substantial increase in youth vaping prevalence beginning in about 2014. Time trend analyses showed that the decline in past 30-day smoking prevalence accelerated by two to four times after 2014. Indicators of more established smoking rates, including the proportion of daily smokers among past 30-day smokers, also decreased more rapidly as vaping became more prevalent.
The inverse relationship between vaping and smoking was robust across different data sets for both youth and young adults and for current and more established smoking. While trying electronic cigarettes may causally increase smoking among some youth, the aggregate effect at the population level appears to be negligible given the reduction in smoking initiation during the period of vaping's ascendance.
The good news is that Levy and colleagues are finally accepting the overwhelming evidence that kids who start with e-cigarettes are more likely to end up smoking cigarettes, the so-called “gateway effect.”
Now they have fallen back to arguing that the gateway effect is not big enough to overcome the benefits of e-cigs as substitutes for cigarettes.
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David Levy and colleagues’ paper “Examining the relationship of vaping to smoking initiation among US youth and young adults: a reality check” used data from all the surveys over time that measured youth and young adult e-cigarette use and smoking and concluded there was a substantial increase in youth vaping prevalence beginning in about 2014. Time trend analyses showed that the decline in past 30-day smoking prevalence accelerated by two to four times after 2014. Indicators of more established smoking rates, including the proportion of daily smokers among past 30-day smokers, also decreased more rapidly as vaping became more prevalent.
The inverse relationship between vaping and smoking was robust across different data sets for both youth and young adults and for current and more established smoking. While trying electronic cigarettes may causally increase smoking among some youth, the aggregate effect at the population level appears to be negligible given the reduction in smoking initiation during the period of vaping's ascendance.
The good news is that Levy and colleagues are finally accepting the overwhelming evidence that kids who start with e-cigarettes are more likely to end up smoking cigarettes, the so-called “gateway effect.”
Now they have fallen back to arguing that the gateway effect is not big enough to overcome the benefits of e-cigs as substitutes for cigarettes.
The approach they used, interrupted time series analysis, estimates the declining trend in cigarette use over time, then tests whether this trend changes (in this case, they generally tested for a slope change) after the advent of e-cigarettes.
Interrupted time series is a well-established method for analyzing changes in trends. Indeed Lauren Dutra and I (1) used interrupted time series to do a similar analysis of the effect that the advent of e-cigarettes had on cigarette smoking among youth using the National Youth Tobacco Survey from 2004 to 2014. Based on data over that time, we found that the advent of e-cigarettes (using a start date of 2009 for e-cigs) did not affect the declining trend in cigarette smoking, but led to an increase in total tobacco product use (Figure 1 in our paper).
Lauren and I also used individual-level data (something Levy and colleagues did not consider in their analysis) and found that about one-third of the kids using e-cigarettes had risk profiles that made them unlikely to start using nicotine with conventional cigarettes. Thus, e-cigarettes are expanding the tobacco market.
Levy and colleagues expand the time period of analysis up to 2016 or 2017 (depending on the data source). This is an important addition because, as they note, e-cigarette use has continued to grow since 2014 (their Figure 1).
I have several concerns about the analysis and interpretation of the data that Levy and colleagues present.
The assumption in interrupted time series analysis as they (and we) do it is that the underlying trend is linear (a straight line). The figures in the supplementary file suggest that many of the time histories are curved. Failing to account for this curvature can distort the results and also make the results highly sensitive to the break year (i.e., where the line bends) in the analysis.
A related concern because of the curvature in the data is that the break year they use in their analysis is 2014. They justify this by arguing that 2014 is when e-cigarette use took off. But, if you look at their Figure 1, you could also argue for using 2009 as the break year because that is where the data they have on e-cig use extrapolated back to zero. While e-cig use was lower before 2014, an increasing effect of e-cigs would be captured in the slope change in an interrupted time series model (assuming that the linear assumption is met).
The specific shape of the data curve is especially important in most recent years where e-cigarette use has increased so much among youth and young adults. This fact, combined with the gateway effect, would lead one to predict that historical drops in cigarette smoking would stop or even reverse. Indeed, looking at the detailed data in the supplementary figures shows this in several (but not all) cases:
• The Monitoring the Future (MTF) data showed increases in 10th grade 30 day and daily cigarette smoking (Supplementary Figures 1 and 8) and essentially flat 12th grade smoking between 2016 and 2017 (Supplementary Figure 2).
• The National Youth Tobacco Survey showed flat 30 day cigarette smoking from 2014 to 2017 (Supplementary Figure 3), the first time that there was not a drop in cigarette smoking since NYTS started in 2004. (I also do not understand why Levy and colleagues did not use the NYTS back to 2004; they started in 2011.)
• The National Health Interview Survey showed flat young adult smoking prevalence from 2015 to 2016 for both males and females (Supplementary Figures 13 and 14).
Another important omission in Levy and colleagues’ paper is that they only present data on cigarette smoking rather than total tobacco product use. This is an exceptionally important variable because if e-cigarettes are increasing nicotine use among youth, that is a bad thing.
And that is what Lauren Dutra and I found through 2014 (figure above). The rapid increase in e -cigarette use after 2014 in Levy’s Figure 1 reinforces this concern.
New data for 2018 released by the CDC in the November 16, 2018 MMWR (2) reinforces how serious this problem is. They documented continuing increases in e-cigarette use through 2018 (figure in MMWR) and, more important, increases in any tobacco use.
That is the real reality.
REFERENCES
(1) Dutra L, Glantz S. E-cigarettes and National Adolescent Cigarette Use: 2004-2014. Pediatrics. 2017 Feb;139(2). pii: e20162450. doi: 10.1542/peds.2016-2450.
(2) Cullen KA, Ambrose BK, Gentzke AS, Apelberg BJ, Jamal A, King BA. Notes from the Field: Use of Electronic Cigarettes and Any Tobacco Product Among Middle and High School Students — United States, 2011–2018. MMWR Morb Mortal Wkly Rep 2018;67:1276–1277. DOI: http://dx.doi.org/10.15585/mmwr.mm6745a5
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We would like to clear up some misconceptions in Dr. Glantz’s reply to our recent article (1). First, our analytic approach did not assume linearity as the title of Dr. Glantz’s response implies. On the contrary, we applied a log linear form, which not only better fit the data, but also incorporates non-linearities. Additionally, we also conducted and provided results using a linear form in the supplementary material, which yielded similar results.
In his reply to our paper, Dr. Glantz claims that we should have started the vaping period in 2009 rather than in 2014 or 2013. However, we feel this criticism is wrong since we provided extensive data in the paper showing that vaping among youth was minimal until at least 2013.
Consequently, we focused on when vaping became more widespread and, by most accounts, became a concern. Further, we conducted analyses that considered changes in trend for other years and obtained qualitatively similar results when the transition was specified as dating back to 2013 or 2012. We also conducted analyses which allowed for changes in trend in both 2009 and 2014 and found no change in trend from 2009 onward, whereas the change in trend from 2014 onward continued to hold. We understand that Dr. Glantz and colleagues in another paper (2) used 2009 as a base year for vaping. However, we feel this choice was a poor one since virtually no students were using e-cigarettes in 2009, and hence vaping would not be...
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We would like to clear up some misconceptions in Dr. Glantz’s reply to our recent article (1). First, our analytic approach did not assume linearity as the title of Dr. Glantz’s response implies. On the contrary, we applied a log linear form, which not only better fit the data, but also incorporates non-linearities. Additionally, we also conducted and provided results using a linear form in the supplementary material, which yielded similar results.
In his reply to our paper, Dr. Glantz claims that we should have started the vaping period in 2009 rather than in 2014 or 2013. However, we feel this criticism is wrong since we provided extensive data in the paper showing that vaping among youth was minimal until at least 2013.
Consequently, we focused on when vaping became more widespread and, by most accounts, became a concern. Further, we conducted analyses that considered changes in trend for other years and obtained qualitatively similar results when the transition was specified as dating back to 2013 or 2012. We also conducted analyses which allowed for changes in trend in both 2009 and 2014 and found no change in trend from 2009 onward, whereas the change in trend from 2014 onward continued to hold. We understand that Dr. Glantz and colleagues in another paper (2) used 2009 as a base year for vaping. However, we feel this choice was a poor one since virtually no students were using e-cigarettes in 2009, and hence vaping would not be a factor influencing adolescent smoking.
Dr. Glantz also criticizes our study by pointing out several years during the vaping period when smoking prevalence did not decline. While it is true that smoking did not decline in some years during the vaping period, exceptions do not prove the rule. Indeed, the point of statistical analysis is to distinguish salient trends. Our aim was to provide straightforward analyses of the trends in cigarette smoking replicated across six different surveys. We estimated equations which allowed for long-term trends and changes in trend, and corrected for autocorrelation in the error terms where tests indicated a problem. Across six separate surveys, we obtained remarkably consistent results showing that the downward trend in smoking rates were greatly accelerated since vaping became more widespread.
In his criticism of our study Dr. Glantz focused particular attention on our results from the NYTS. We began our analysis of these data in 2011 because data became publicly available on an annual basis beginning in that year. Further, these data show that, while high school smoking rates fell from 15.8% to 12.7% between 2011 and 2013, representing a 20% drop in that three-year period, smoking rates declined to 9.8% in 2014 representing a 25% decline in just one year. Smoking prevalence further declined to 7.6% in 2017, representing a 40% drop since 2013. Nonetheless, the NYTS data provides the weakest indication of the change in trend during the vaping period due to the limited ability to detect pre-vaping trends.
Since our study was completed, more recent data have been published on youth and young adult smoking and vaping. In particular, the just released Monitoring the Future data indicate that last 30 day prevalence of smoking by 12th graders fell from 9.7% in 2017 to 7.6% in 2018, a 22% drop in just one year. In addition, NHIS data indicate that smoking prevalence for 18-24 year olds (both genders) fell from 13.1% in 2016 to 10.4% in 2017, a 21% drop in one year. These new data are consistent with the trends we describe in our paper.
Finally, we disagree in three ways with Dr. Glantz’s criticism that our paper only narrowly focused on cigarette use while ignoring total tobacco product use, including e-cigarettes. First, our decision to focus on the associations between e-cigarettes and cigarettes was based on concerns that e-cigarette use leads to increased smoking (3). Second, we think it is inappropriate to combine e-cigarettes and cigarettes in the same category of health risk, since virtually all scholarly evidence reviews have concluded that e-cigarettes are likely substantially less harmful than cigarettes and other combustible tobacco products, including the NASEM (3), PHE (4), and RCP (5) reports. Third, despite FDA’s legal classification of e-cigarettes as tobacco products, a strong argument can be made that e-cigarettes are not tobacco products at all, but rather a specific type of nicotine delivery product, just as nicotine patches, gum, and lozenges are also nicotine delivery products. No one would classify nicotine patches, gum, and lozenges as tobacco products. Indeed, classifying e-cigarettes as tobacco is the reason that Dr. Glantz can make his final claim that total tobacco use has risen with the introduction of e-cigarettes. While this conclusion is true under the classification scheme that Dr. Glantz uses, it is irrelevant to the arguments we made. Our arguments hinge on whether the increase in vaping is offset by a greater decrease in smoking (and other tobacco use) than would be expected in a world without e-cigarettes. We have never suggested better than one for one substitution, and would agree that vaping has substantially increased.
The data presented by Dr. Glantz on e-cigarette use are based on any last 30 day use. An important advance in our study over prior analyses, including the earlier study by Dr. Glantz and colleagues (2), was that we also considered measures of more established use, such as having smoked 100 cigarettes, daily smoking and smoking half a pack a day. These are more valid measures of regular smoking and are thus more directly related to public health impacts. Our study found that the conclusions about trends in vaping and smoking were robust across different measures of smoking. Indeed, we considered the ratio of daily to last 30 day smoking as an indicator of transitions from experimental to more regular cigarette smoking. We again found more rapidly declining rates during the period after vaping became more widespread.
It will be important to carefully monitor trends in the use of cigarettes, e-cigarettes and other nicotine delivery products to inform the kinds of policies that are likely to yield beneficial health outcomes for the population.
References
(1) Levy DT, Warner KE, Cummings KM, et al., Examining the relationship of vaping to smoking initiation among US youth and young adults: a reality check. Tob Control. 2018 Nov 20. pii: tobaccocontrol-2018-054446. doi: 10.1136/tobaccocontrol-2018-054446. [Epub ahead of print]
(2) Dutra L, Glantz S. E-cigarettes and national adolescent cigarette use: 2004-2014. Pediatrics. 2017 Feb;139(2). pii: e20162450. doi: 10.1542/peds.2016-2450.
(3) National Academy of Sciences Engineering and Medicine. Public health consequences of e-cigarettes. Washington, DC: The National Academies Press, 2018.
(4) Public Health England. E-cigarettes and vaping: policy, regulation and guidance. London: PHE;2018.
(5) Royal College of Physicians. Nicotine without smoke: Tobacco harm reduction. London: RCP;2016.
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The authors state "These stores have largely stopped carrying e-cigarettes at the same time as starting to stock IQOS HEETS (HEATSTICKS), the cigarette-like component that is smoked in the IQOS device,..." but provide no insight into why that is. Are these retailers being incentivised to stop selling e-cigs by PMI?
While the risk profile of IQOS is uncertain, the product is highly likely to be much more harmful than vaping e-cigs. Commercial tactics that promote IQOS over vaping devices, excluding the latter from retail chains, would be of major concern for tobacco control.
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PMI finally responded to my paper in Tobacco Control1 showing that the data submitted in their MRTP application to the FDA to market IQOS with reduced risk claims did not actually support claims of reduced risks.
Specifically, PMI’s MRTP application included their 3-month study of 24 non-cancer biomarkers of potential harm (which PMI calls “clinical risk endpoints,” CRE) in humans using IQOS compared to conventional cigarettes. These biomarkers include measures of inflammation, oxidative stress, lipids, blood pressure, and lung function. (PMI did separate studies of biomarkers of exposure, several of which are carcinogens.) While PMI’s application emphasizes that these biomarkers generally changed in positive directions, my examination of the data revealed no statistically detectable difference between IQOS and conventional cigarettes for 23 of the 24 BOPH in Americans and 10 of 13 in Japanese. Moreover, it is likely that the few significant differences were false positives. Thus, despite delivering lower levels of some toxicants, PMI’s own data failed to show consistently lower risks of harm in humans using IQOS compared to conventional cigarettes.
Their undated response, “The Difference between IQOS and Continued Smoking,”2 presents two arguments:
• The original study submitted to FDA was “NOT DESIGNED to serve as the sole pivotal evidence with regards to CRE’s and to show statistically significant changes in the CREs.”...
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PMI finally responded to my paper in Tobacco Control1 showing that the data submitted in their MRTP application to the FDA to market IQOS with reduced risk claims did not actually support claims of reduced risks.
Specifically, PMI’s MRTP application included their 3-month study of 24 non-cancer biomarkers of potential harm (which PMI calls “clinical risk endpoints,” CRE) in humans using IQOS compared to conventional cigarettes. These biomarkers include measures of inflammation, oxidative stress, lipids, blood pressure, and lung function. (PMI did separate studies of biomarkers of exposure, several of which are carcinogens.) While PMI’s application emphasizes that these biomarkers generally changed in positive directions, my examination of the data revealed no statistically detectable difference between IQOS and conventional cigarettes for 23 of the 24 BOPH in Americans and 10 of 13 in Japanese. Moreover, it is likely that the few significant differences were false positives. Thus, despite delivering lower levels of some toxicants, PMI’s own data failed to show consistently lower risks of harm in humans using IQOS compared to conventional cigarettes.
Their undated response, “The Difference between IQOS and Continued Smoking,”2 presents two arguments:
• The original study submitted to FDA was “NOT DESIGNED to serve as the sole pivotal evidence with regards to CRE’s and to show statistically significant changes in the CREs.”
• PMI has a new, larger study 6-month human study comparing IQOS with conventional cigarettes that concluded that IQOS is less risky than conventional cigarettes.3
With regard to the first point, one is left with the question of why PMI submitted and represented data in the original MRTP application, when it now admits that the study was not designed to provide key evidence. They did not question the specific conclusions that I drew in my paper.
The new 6-month study differs from the study presented in the original MRTP application in several important ways.
First, it is much larger (984 people in the new study compared to 79 in the US study and 112 in the Japanese study cited in the MRTP application). Making the study larger increases statistical power and makes it more likely to declare a difference statistically significant. This is a good thing.
Second, and of greater concern, the new study only considers 6 of the 24 non-cancer biomarkers in the earlier study, leaving the question of why PMI did not measure the other 18. (The 2 other biomarkers in the new study are biomarkers of exposure [CO and NNAL], which were not included in the earlier study and are not at issue in my paper.) Most of the things that they leave out are determined from blood tests, but they had to draw blood to measure the biomarkers they do report. The others are more detailed measures of lung function than the one reported in the new study and easily measured measures of blood pressure.
PMI should be expanding, not dropping, clinical endpoints because of evidence that IQOS is different from cigarettes.4,5 Indeed, the data they presented in the MRTP application suggested that IQOS may be causing liver damage not observed in cigarettes.6
Given the millions of dollars PMI’s application represents, cost does not justify dropping these routine clinical measures. Their detailed presentation on the new study3 does not address this question.
Third, PMI uses an arcane, little-used statistical method, the Hailperin-Rüger method, that was developed to confirm earlier studies.7 (Neither I nor two biostatistics colleagues have seen this used in any recent clinical trials. A PubMed search with the keyword “Hailperin-Rüger” conducted on December 19, 2018, resulted in just one study.8 The basic argument of the Hailperin-Rüger method is that it is overly cautious to require that all observed changes be statistically significant in order to confirm that a therapy works, and that if some lesser number of the variables change significantly, that should be good enough for a global test. The number of significant changes is specified in advance and the probability of a chance finding is adjusted.
PMI decided that if 5 of the 8 biomarkers (6 clinical risk and 2 exposure) changed in the direction of less risk, that would be enough to conclude that IQOS was less risky than conventional cigarettes. They do not provide a clear explanation of why they used 5, other than it was “more than half.”
PMI justified using Hailperin-Rüger because “the probability of finding five significant tests (p<0.05) by chance alone is extremely low (0.006%).” This is a misleading statement because this low probability would only be the case a chance finding if none of the five variables actually changed. The probabilities are much higher when there are real changes.
So, in the new study, PMI went from considering changes in 24 clinical risk biomarkers in the original study to 8 in the new study to only requiring 5 to be statistically significant.
That is a pretty major drop in the level of evidence PMI now suggests is sufficient to demonstrate that IQOS is less risky than cigarettes.
In the new study 5 of the changes were statistically significant, so PMI concluded that, overall, IQOS was better. Had they picked 6 in their plan, the overall results would not have been significant, even under the Hailperin-Rüger method’s relaxed standards.
There are other problems with using the Hailperin-Rüger method. First, it is designed to confirm results of earlier studies. The earlier study did not convincingly show that IQOS was better than conventional cigarettes. Second, the usual way that Hailperin-Rüger is used is when you have several measures of the same thing. (For example, the one paper8 located in PubMed that used Hailperin-Rüger assessed 10 different measures of neurological function and pre-specified that if 5 of the 10 were statistically significant, the global test would be considered statistically significant.) The idea is that requiring all of them to change significantly is being too stringent a requirement to identify a change in lung function. In this case, PMI mixed apples and oranges by applying the text to a set of 6 clinical variables and 2 exposure that were measuring different underlying physiological processes.
PMI also used a one-tail test that assumes that one only need worry above improvements in the biomarkers without any concern for the possibility that they might worsen the biomarkers. (As noted above, PMI presented – but did not emphasize – other evidence in their MRTP application showing that IQOS caused problems not observed in cigarettes.6) I tell my students that, with rare exceptions, one should always do two-tail tests. Two-tail tests require larger differences to reach statistical significance, so by using a one-tail test, PMI made it easier to conclude changes were statistically significant. In this case the overall conclusion would have been the same with a two-tail test, so this bias did not make any practical difference, but they should have not used a one-tail test.
PMI’s use of a one-tailed test was especially hypocritical since back in the early 1990’s the tobacco companies sued the US EPA for using a one-tail test in their risk assessment that concluded that secondhand smoke caused lung cancer.9 EPA used a one-tail test because they said it was inconceivable that secondhand smoke exposure would protect against lung cancer (the other tail). The irony there was that EPA would have reached the same conclusion using a two-tailed test.
All this raises the question of whether PMI manipulated the experimental design and analysis to get the desired conclusion, as they have done in the past.10
The law requires the MRTP applicant PMI to demonstrate, among other things, that IQOS, as it is actually used by consumers, will “significantly reduce harm and the risk of tobacco-related disease to individual tobacco users.” Neither the original 3 month study nor the newer 6 month study meet this standard.
The bottom line: FDA and other regulatory agencies should not rely on PMI’s new study to support a conclusion that IQOS is less risky than conventional cigarettes.
As slightly reformatted version of this post has been submitted to the IQOS MRTP docket at FDA with tracking number 1k2-978f-eqmr. A PDF of the comment is available here.
References
1. Glantz S. PMI’s Own in vivo Clinical Data on Biomarkers of Potential Harm in Americans Show that IQOS is Not Detectably Different from Conventional Cigarettes. Tob Control. 2018;27(Suppl 1):s9-s12. doi: 10.1136/tobaccocontrol-2018-054413. Epub 052018 Aug 054421.
2. Baker G, Harris C, Hankins M, et al. The Difference between IQOS and Continued Smoking. 2018; https://www.pmiscience.com/resources/docs/default-source/news-documents/.... Accessed 19 Dec 2018.
3. PMI Research & Development. Study Results Overview: ZRHR-ERS-09 US (Evaluation of Biological and Functional Changes in Healthy Smokers After Switching to THS 2.2 for 26 Weeks. In PMI IQOS MRTP June 8, 2018 Amendment: Additional Information and Data from a Recently Completed Clinical Study (.zip – 1.3 GB) (added November 29, 2018). 2018; https://digitalmedia.hhs.gov/tobacco/static/mrtpa/PMP/June%208%2C%202018.... Accessed 18 Dec 2018.
4. Glantz S. Heated tobacco products: The example of IQOS. Tobacco Control. 2018;27(Suppl 1):s1-s6; DOI: 10.1136/tobaccocontrol-2018-054601.
5. St. Helen G, Jacob P, Nardone N, Benowitz N. IQOS: Examination of Philip Morris International’s claim of reduced exposure. Tob Control. 2018;27(Suppl 1):s30-s36. doi: 10.1136/tobaccocontrol-2018-054321. Epub 052018 Aug 054329.
6. Chun L, Moazed F, Matthay M, Calfee C, Gotts J. Possible Hepatotoxicity of IQOS. Tob Control. 2018;27(Suppl 1):s39-s40. doi: 10.1136/tobaccocontrol-2018-054320. Epub 052018 Aug 054321.
7. Koch GG, Gansky SA. Statistical Considerations for Multiplicity in Confirmatory Protocols. Drug Information Journal. 1996;30(2):523-534.
8. Schellenberg R, Todorova A, Wedekind W, Schober F, Dimpfel W. Pathophysiology and psychopharmacology of dementia--a new study design. 2. Cyclandelate treatment--a placebo-controlled double-blind clinical trial. Neuropsychobiology. 1997;35(3):132-142.
9. Schachtman NA. EPA Post Hoc Statistical Tests – One Tail vs Two. 2012; http://schachtmanlaw.com/epa-post-hoc-statistical-tests-one-tail-vs-two/. Accessed 19 Dec 2018.
10. Wertz MS, Kyriss T, Paranjape S, Glantz SA. The toxic effects of cigarette additives. Philip Morris' project mix reconsidered: an analysis of documents released through litigation. PLoS medicine. 2011;8(12):e1001145.
Berry et al (1) report an analysis of two waves of the Population Assessment of Tobacco and Health (PATH) study focused on the association between the initiation of e-cigarette use by Wave 2 and cigarette abstinence/reduction assessed at Wave 2. They conclude that daily e-cigarette use is associated with both cigarette abstinence and reduced consumption among continuing smokers. While this addresses an important question, we argue that such analyses should be adjusted for the reason e-cigarettes are being used.
From Wave 1 of PATH (2), we know that ~75% of smokers agreed that e-cigarettes were useful to help people quit. However, ~80% agreed that e-cigarettes allowed someone to replace a cigarette where smoking was prohibited. From the first reason, we can hypothesize that e-cigarette use might be associated with cigarette abstinence/reduction. However, from the second reason, we can also hypothesize that e-cigarettes would be associated with neither cigarette abstinence nor reduction. The recent National Academies report (3) recommended that any assessment of the role of e-cigarettes in cigarette cessation/reduction should focus on smokers who used e-cigarettes to help them quit.
PATH Wave 2 data does include information on whether smokers tried to quit in the previous year, as well as whether they used e-cigarettes to aid the last quit attempt. Previous research (4) has shown that over half of the smoking population will not ha...
Berry et al (1) report an analysis of two waves of the Population Assessment of Tobacco and Health (PATH) study focused on the association between the initiation of e-cigarette use by Wave 2 and cigarette abstinence/reduction assessed at Wave 2. They conclude that daily e-cigarette use is associated with both cigarette abstinence and reduced consumption among continuing smokers. While this addresses an important question, we argue that such analyses should be adjusted for the reason e-cigarettes are being used.
From Wave 1 of PATH (2), we know that ~75% of smokers agreed that e-cigarettes were useful to help people quit. However, ~80% agreed that e-cigarettes allowed someone to replace a cigarette where smoking was prohibited. From the first reason, we can hypothesize that e-cigarette use might be associated with cigarette abstinence/reduction. However, from the second reason, we can also hypothesize that e-cigarettes would be associated with neither cigarette abstinence nor reduction. The recent National Academies report (3) recommended that any assessment of the role of e-cigarettes in cigarette cessation/reduction should focus on smokers who used e-cigarettes to help them quit.
PATH Wave 2 data does include information on whether smokers tried to quit in the previous year, as well as whether they used e-cigarettes to aid the last quit attempt. Previous research (4) has shown that over half of the smoking population will not have tried to quit in the previous year. By including these non-attempters, who by definition cannot have quit, Berry et al (1) may have introduced an important bias toward finding a higher daily e-cigarette effect on abstinence. We expect that daily e-cigarette use at Wave 2 will be much higher among those who made a recent quit attempt than in those who did not.
In their supplement tables (TableS3), they include an analysis of those who made a quit attempt prior to Wave 1(rather than between Waves 1 and 2). Using this analysis, there is a drastic reduction in the effect size amplitude and in the absolute number of involved smokers. We would expect similar, or even larger, reduction in effect estimates were they to have restricted their analysis to those who made a quit attempt in the year prior to Wave 2 and included reason for using e-cigarettes.
In order to know the effect of e-cigarettes on cessation, those who used an e-cigarette to help them to quit should be contrasted with comparable non-users: those who used other aids to quit as well as to those who quit unaided. There are numerous important potential confounders for these comparisons as it is well known that those who are least likely to be successful in the quit attempt are the most likely to use an aid. (5) For unbiased analyses, the exposure of interest needs to be isolated and covariate balance achieved between exposed and unexposed. There is a role for methodological approaches that help achieve covariate balance, such as propensity score matching, in deciding whether e –cigarettes improve population smoking cessation.
References:
1. Berry KM, Reynolds LM, Collins JM, Siegel MB, Fetterman JL, Hamburg NM, Bhatnagar A, Benjamin EJ, Stokes A. E-cigarette initiation and associated changes in smoking cessation and reduction: the Population Assessment of Tobacco and Health Study, 2013-2015.Tob Control. 2018 Mar 24. pii: tobaccocontrol-2017-054108. doi: 10.1136/tobaccocontrol-2017-054108.
2. Coleman BN, Rostron B, Johnson SE, Ambrose BK, Pearson J, Stanton CA, et al. Electronic cigarette use among US adults in the Population Assessment of Tobacco and Health (PATH) Study, 2013–2014. Tobacco Control. 2017. doi: 10.1136/tobaccocontrol-2016-053462.
3. National Academies of Sciences Engineering, and Medicine,. Public Health Consequences of E-Cigarettes. Washington, DC: Health and Medicine Division, National Academies of Sciences, Engineering, and Medicine, 2018
4. Zhu S-H, Lee M, Zhuang Y, Gamst A, Wolfson T. Interventions to increase smoking cessation at the population level: How much progress has been made in the last two decades? Tob Control. 2012;212:110–118
5. Leas EC, Pierce JP, Benmarhnia T, White MM, Noble ML, Trinidad DR, Strong DR. Effectiveness of Pharmaceutical Smoking Cessation Aids in a Nationally Representative Cohort of American Smokers. J Natl Cancer Inst. 2017 Dec 21. doi: 10.1093/jnci/djx240
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Coleman et al’s important report [1] on transitions in the vaping and smoking status of a nationally representative cohort of American 18+ adults who use electronic cigarettes (EC) from the PATH study provides rich data that can greatly advance our understanding of the natural history of EC use and their potential in harm reduction.
However, we were struck by the absence of emphasis in the report of what is perhaps its most important finding. If we examine the report’s data and consider the net impact of vaping on the critical goals of having vapers stopping smoking and vaping non-smokers not starting to smoke, the findings are very disturbing and should strong reason for pause among those advocating e-cigarettes as a game-changing way of stopping smoking.
At Wave 2, 12 months on from Wave 1, of the cohort of 2036 dual users (EC + smoking) only 104 (5.1%) had transitioned to using only EC and another 143 (7%) had quit both EC and smoking for a combined total of 247 or 12.1%. Of the 896 exclusive EC users at Wave 1, 277 (30.9%) had stopped vaping at Wave 2. Together, 524 out of the 2932 EC users (17.9%) followed from Wave 1 might be considered to have had positive outcomes at Wave 2.
The other side of the coin however, shows that of the 2036 dual users at Wave 1, 886 (43.5%) relapsed to using cigarettes exclusively. In addition, among the 896 exclusive EC users from Wave 1, 109 (12.2%) had stopped vaping and were now smoking, wit...
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Coleman et al’s important report [1] on transitions in the vaping and smoking status of a nationally representative cohort of American 18+ adults who use electronic cigarettes (EC) from the PATH study provides rich data that can greatly advance our understanding of the natural history of EC use and their potential in harm reduction.
However, we were struck by the absence of emphasis in the report of what is perhaps its most important finding. If we examine the report’s data and consider the net impact of vaping on the critical goals of having vapers stopping smoking and vaping non-smokers not starting to smoke, the findings are very disturbing and should strong reason for pause among those advocating e-cigarettes as a game-changing way of stopping smoking.
At Wave 2, 12 months on from Wave 1, of the cohort of 2036 dual users (EC + smoking) only 104 (5.1%) had transitioned to using only EC and another 143 (7%) had quit both EC and smoking for a combined total of 247 or 12.1%. Of the 896 exclusive EC users at Wave 1, 277 (30.9%) had stopped vaping at Wave 2. Together, 524 out of the 2932 EC users (17.9%) followed from Wave 1 might be considered to have had positive outcomes at Wave 2.
The other side of the coin however, shows that of the 2036 dual users at Wave 1, 886 (43.5%) relapsed to using cigarettes exclusively. In addition, among the 896 exclusive EC users from Wave 1, 109 (12.2%) had stopped vaping and were now smoking, with another 121 having resumed smoking as well as using EC (i.e. became dual users). Importantly, 502 of 896 (56%) exclusive e-cigarette users were those who had never been established smokers prior to using e-cigarettes. Alarmingly, of these 502 adults, 120 (23.9%) progressed from using only e-cigarettes to either dual use (54 or 10.8%) or smoking only (66 or 13.2%).
Taken together, 886 dual users in Wave 1 relapsed to become exclusive cigarette smokers in Wave 2, and 230 exclusive vapers in Wave 1 took up cigarette smoking in Wave 2 (dual use or exclusively cigarettes). Undoubtedly, these should be considered as negative outcomes.
The table below shows that for every person vaping at Wave 1 who benefited across 12 months by quitting smoking, there are 2.1 who either relapsed to or took-up smoking. Most disturbingly, in this adult cohort nearly one in four of those who had never been established smokers took up smoking after first using EC. Concern about putative gateway effects of ECs to smoking have been dominated by concerns about youth. These data showing transitions from EC to smoking in nearly a quarter of exclusive adult EC users with no histories of established smoking should widen this debate to consider adult gateway effects too.
By far the largest proportion of those with negative outcomes are those dual users who relapsed to smoking (886 or 43.5% of dual users). As the authors note in their discussion, many of these were infrequent EC users, possibly involved in transitory experimentation at Wave 1. If we add the 902 who were still dual using at Wave 2, then 1788 of 2036 dual users (87.8%) in this sample might be said to have been held in smoking (dual using or exclusive smoking) 12 months later compared to 12.1% dual users who may have benefitted by using ECs.
We would expect commercial interests in both the tobacco and EC industries would be more than delighted with these findings. However, from a public health harm reduction perspective these results argue against EC being an effective harm reduction strategy, and point to their far stronger potential to both recruit smokers and hold many smokers in smoking.
Reference
1. Coleman B et al Transitions in electronic cigarette use among adults in the Population Assessment of Tobacco and Health (PATH) Study, Waves 1 and 2 (2013-2105). Tobacco Control 2018; doi:10.1136/tobaccocontrol-2017-054174
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The paper by Filippidis et al [1] provides data re-confirming the well-known fact that most ex-smokers attempt to quit without using any form of assistance, whether pharmaceutical, professional or via e-cigarettes. Moreover, the proportion of ex-smokers trying to quit unaided increased substantially in Europe between 2012-17 (ex-smokers using no assistance increased from 73.9% to 80.7%), a period where e-cigarette use accelerated in some nations.
Regrettably however, this study does not permit any comparison of success rates by method, as no data are reported on which method of cessation (assisted v unassisted) was used by ex-smokers on their last, final (and so successful) quit attempt.
The authors report that those “who successfully quit reported much lower use of cessation assistance compared with smokers who had tried to quit without success” and suggest that this might reflect indication bias, whereby those who find it harder to quit self-select to use assistance, leaving the low hanging fruit of non- or less addicted smokers to fall off the smoking tree using their own determination.
While this will be true for some, there are many former heavy smokers who quit without assistance. This argument also borrows assumptions from the discredited hardening hypothesis [2], which holds, in the face of evidence to the contrary, that as smoking prevalence falls the concentration of hardened, more deeply addicted smokers increase...
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The paper by Filippidis et al [1] provides data re-confirming the well-known fact that most ex-smokers attempt to quit without using any form of assistance, whether pharmaceutical, professional or via e-cigarettes. Moreover, the proportion of ex-smokers trying to quit unaided increased substantially in Europe between 2012-17 (ex-smokers using no assistance increased from 73.9% to 80.7%), a period where e-cigarette use accelerated in some nations.
Regrettably however, this study does not permit any comparison of success rates by method, as no data are reported on which method of cessation (assisted v unassisted) was used by ex-smokers on their last, final (and so successful) quit attempt.
The authors report that those “who successfully quit reported much lower use of cessation assistance compared with smokers who had tried to quit without success” and suggest that this might reflect indication bias, whereby those who find it harder to quit self-select to use assistance, leaving the low hanging fruit of non- or less addicted smokers to fall off the smoking tree using their own determination.
While this will be true for some, there are many former heavy smokers who quit without assistance. This argument also borrows assumptions from the discredited hardening hypothesis [2], which holds, in the face of evidence to the contrary, that as smoking prevalence falls the concentration of hardened, more deeply addicted smokers increases.
If our concern is (as it should be) to better understand the means of quitting that produce the largest net volume of ex-smokers across whole populations, studying the methods these former smokers used when they succeeded is critical. Yet the “inverse impact law of smoking cessation [3] shows that unassisted cessation, which undisputedly delivers more ex-smokers than any other method, is hugely neglected in smoking cessation research [4].
It is almost as if researchers want to turn away from learning more about the most successful route that has always delivered the largest number of successful quits. [5]
Rather than seeing the increase in unassisted quitting as something to be highlighted as a positive, motivating celebration of agency that could be megaphoned in campaigns to smokers imbued with pessimistic messages about how hard quitting is going to be, the authors conclude that their findings ”highlight the need for approaches to ensure that smokers get support”.
In 40 years of tobacco control, I cannot ever recall attending a meeting or conference on cessation where those whose living depended on them selling smoking cessation aids or providing professional cessation services did not reach similar conclusions. Yet 40 years on, the same cracked record is being played: we need to convince more smokers that they should not try foolishly to quit alone and that they need our help!
Analysis at the level of the success of quit “attempts” often shows that head-to-head, unassisted cessation attempts are less successful than those using assistance. But many so-called cessation attempts are empty gestures akin to those who attempt to get fit by buying an exercise bike, use it once or twice and then consign it to the corner. West and Sohal’s work on catastrophe theory noted that many who were not planning to quit at time 1, had succeeded at time 2. They suggested that “smokers have varying levels of motivational “tension” to stop and then “triggers” in the environment result in a switch in motivational state. If that switch involves immediate renunciation of cigarettes, this can signal a more complete transformation than if it involves a plan to quit at some future point.” [6]
The importance of continually stimulating the motivational tension to stop smoking and providing both informational and policy triggers for quitting cannot be over-emphasised.
It is long overdue that we gave far more attention to the net contribution of unassisted cessation at the population level. [7 ] Many smokers have little interest in being helped to quit. In this, they are very aware of many friends and acquaintances who quit alone when they were sufficiently motivated to do so. Over 40 years of professional hand-wringing, research and campaigning about how to undermine unaided quitting and sell more drugs and clinic appointments have thankfully done little to erode this.
References
1. Filippidis FT, Mons U, Jiminez-Ruiz C, Vardavas CI. Changes in smoking cessation assistance in the European Union between 2012 and 2017: pharmacotherapy versus counselling versus e-cigarettes. Tobacco Control http://dx.doi.org/10.1136/tobaccocontrol-2017-054117
2. Cohen JE, McDonald PW, Selby P. Softening up on the hardening hypothesis. Tobacco Control ttp://dx.doi.org/10.1136/tobaccocontrol-2011-050381
3. Chapman S. The Inverse Impact Law of Smoking Cessation. Lancet 2009; 373(9665):701-3.
4. Chapman S, Mackenzie R. The global research neglect of unassisted smoking cessation: causes and consequences. PLoS Medicine 2010; 7(2): e1000216. doi:10.1371/journal.pmed.1000216.
5. Smith A, Chapman S. Quitting unassisted: the 50 year neglect of a major health phenomenon. JAMA 2014;311(2):137-138. doi:10.1001/jama.2013.282618.
3. West R, Sohal T. “Catastrophic” pathways to smoking cessation: findings from national survey. BMJ. 2006 Feb 25; 332(7539): 458–460.
doi: 10.1136/bmj.38723.573866.AE
4. Smith A, Carter SM, Chapman S, Dunlop S, Freeman B. Why do smokers try to quit without medication or counseling? A qualitative study with ex-smokers. BMJ Open 5:e007301 doi:10.1136/bmjopen-2014-007301
Feliu et al’s conclusion “in the European Union countries with the higher scores in the Tobacco Control Scale, which indicates higher tobacco control efforts, have lower prevalence of smokers, higher quit ratios and higher relative decreases in their prevalence rates of smokers.” deserved comment.
First, it seems a tautology. Tobacco control policies are robustly evidence based. Accordingly, more efforts, less smokers.
Second, a PubMed search with “"tobacco control scale" only retrieved 27 articles since 2006 and no validation published yet. Obviously, the Scale poorly correlated with smoking rate: r2 being .58 in 2002/3, .15 in 2006/7 and .06 in 2010/11.(From table 3 in 2; n= 11 European countries).
Third, why make simple stuff complex? This surrogate is complex to calculate and its items are subjective because issuing a decree is useless if no implementation were enforced. In contrast, the smoking rate and its evolution are simple and reliable! How France can be ranked 4th among 28 countries with a 57/100 score (1) while smoking prevalence has been plateauing for so long at more than 30%? In France, from 2004 to 2017 no relevant increase in tobacco taxes, no implementation of the legal smoking ban in cafés or of the ban of sale to minors despite sting operations by NGO showing evidence of serious breaches.(3)
Fourth, claiming “the European Union should continue implementing comprehensive tobacco control pol...
Feliu et al’s conclusion “in the European Union countries with the higher scores in the Tobacco Control Scale, which indicates higher tobacco control efforts, have lower prevalence of smokers, higher quit ratios and higher relative decreases in their prevalence rates of smokers.” deserved comment.
First, it seems a tautology. Tobacco control policies are robustly evidence based. Accordingly, more efforts, less smokers.
Second, a PubMed search with “"tobacco control scale" only retrieved 27 articles since 2006 and no validation published yet. Obviously, the Scale poorly correlated with smoking rate: r2 being .58 in 2002/3, .15 in 2006/7 and .06 in 2010/11.(From table 3 in 2; n= 11 European countries).
Third, why make simple stuff complex? This surrogate is complex to calculate and its items are subjective because issuing a decree is useless if no implementation were enforced. In contrast, the smoking rate and its evolution are simple and reliable! How France can be ranked 4th among 28 countries with a 57/100 score (1) while smoking prevalence has been plateauing for so long at more than 30%? In France, from 2004 to 2017 no relevant increase in tobacco taxes, no implementation of the legal smoking ban in cafés or of the ban of sale to minors despite sting operations by NGO showing evidence of serious breaches.(3)
Fourth, claiming “the European Union should continue implementing comprehensive tobacco control policies in Europe.”(1) is optimistic, at best. The European Union is the chimney of rich countries: smoking prevalence in Italy, France and Germany is almost twice that in Australia and 1.5 fold that in the US. Almost no tobacco control in the European Union but Finland! The Scale is a smokescreen for tricky politicians cherry picking the weakest measures without even providing tools for implementation or monitoring.
Last, I am not aware that a critical assessment of the Eurobarometer method is available, and the limitations of such surveys cannot be overlooked. This deserves scrutiny as other data from the European Union on such a topic are a cause for concern: eg. the European School Project on Alcohol and other Drugs estimates smoking prevalence only on a declarative basis, roughly 10% of the data are missing despite only recruiting those attending school and only 80 % of the students said that they thought that their classmates had answered the questions honestly.(4)
1 Feliu A, Filippidis FT, Joossens L et al. Impact of tobacco control policies on smoking prevalence and quit ratios in 27 European Union countries from 2006 to 2014. Online Feb 22.
2 Kuipers MA, Monshouwer K, van Laar M, Kunst AE. Tobacco control and socioeconomic inequalities in adolescent smoking in Europe. Am J Prev Med 2015;49:e64-e72.
3 Braillon A, Mereau AS, Dubois G. [Tobacco control in France: effects of public policy on mortality]. Presse Med 2012;41:679-81.
4 Hibell B, Molinaro S, Siciliano V, Kraus L. The 2013 ESPAD validity study. European Monitoring Centre for Drugs and Drug Addiction. Publications Office of the European Union. Luxembourg. 2015.
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Whilst it is true that Juul is not exactly popular with those on either side of the fence this article fails to address the major issue.
The impending regulation which Juul is said to have brought down on the vapor industry helps Juul by eliminating the competition. Only they, and other brands owned by tobacco companies have any hope of being able to afford the process to keep their products on the market. Independent manufacturers and the retailers who sell their products will simply be obliterated.
Considering that these are people who who have dedicated their lives and often their life savings to helping people switch to safer alternatives, and who are by far and away the most efficient at enforcing strict age verification for purchases, this is a tragedy, not something to be celebrated.
Lastly, as if it still needs to be said, the outbreak of acute lung injury in the US has not been linked with Juul, or any other commercially available nicotine vaping product.
I 100% understand the general good intent of this paper. I also must say that I am Cherokee but not "fullblooded" Cherokee. I did grow up in the heart of the Nation, though. However, could people please stop using the term "American Indian"? Indians are from India. Columbus got lost (even though he was a navigator), ran the one ship he captained aground where he was found by the Native population of the island he smashed into (which for the record was not anywhere near North America). He looked around and thought, "I'm on a beach, I was trying to find India, India has a beach. These people are not white, they are tan, Indians are tan! I'm in India!" He then spread his stupid to the world. Now every tan person originating from any American continent (which are when put together the same land mass as the entire "known" world at that time) are all Indians... Please stop. It's just offensive.
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David Levy and colleagues’ paper “Examining the relationship of vaping to smoking initiation among US youth and young adults: a reality check” used data from all the surveys over time that measured youth and young adult e-cigarette use and smoking and concluded there was a substantial increase in youth vaping prevalence beginning in about 2014. Time trend analyses showed that the decline in past 30-day smoking prevalence accelerated by two to four times after 2014. Indicators of more established smoking rates, including the proportion of daily smokers among past 30-day smokers, also decreased more rapidly as vaping became more prevalent.
The inverse relationship between vaping and smoking was robust across different data sets for both youth and young adults and for current and more established smoking. While trying electronic cigarettes may causally increase smoking among some youth, the aggregate effect at the population level appears to be negligible given the reduction in smoking initiation during the period of vaping's ascendance.
The good news is that Levy and colleagues are finally accepting the overwhelming evidence that kids who start with e-cigarettes are more likely to end up smoking cigarettes, the so-called “gateway effect.”
Now they have fallen back to arguing that the gateway effect is not big enough to overcome the benefits of e-cigs as substitutes for cigarettes.
The approach they used, interrupted ti...
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We would like to clear up some misconceptions in Dr. Glantz’s reply to our recent article (1). First, our analytic approach did not assume linearity as the title of Dr. Glantz’s response implies. On the contrary, we applied a log linear form, which not only better fit the data, but also incorporates non-linearities. Additionally, we also conducted and provided results using a linear form in the supplementary material, which yielded similar results.
In his reply to our paper, Dr. Glantz claims that we should have started the vaping period in 2009 rather than in 2014 or 2013. However, we feel this criticism is wrong since we provided extensive data in the paper showing that vaping among youth was minimal until at least 2013.
Show MoreConsequently, we focused on when vaping became more widespread and, by most accounts, became a concern. Further, we conducted analyses that considered changes in trend for other years and obtained qualitatively similar results when the transition was specified as dating back to 2013 or 2012. We also conducted analyses which allowed for changes in trend in both 2009 and 2014 and found no change in trend from 2009 onward, whereas the change in trend from 2014 onward continued to hold. We understand that Dr. Glantz and colleagues in another paper (2) used 2009 as a base year for vaping. However, we feel this choice was a poor one since virtually no students were using e-cigarettes in 2009, and hence vaping would not be...
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The authors state "These stores have largely stopped carrying e-cigarettes at the same time as starting to stock IQOS HEETS (HEATSTICKS), the cigarette-like component that is smoked in the IQOS device,..." but provide no insight into why that is. Are these retailers being incentivised to stop selling e-cigs by PMI?
While the risk profile of IQOS is uncertain, the product is highly likely to be much more harmful than vaping e-cigs. Commercial tactics that promote IQOS over vaping devices, excluding the latter from retail chains, would be of major concern for tobacco control.
Can the authors enlighten us?
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PMI finally responded to my paper in Tobacco Control1 showing that the data submitted in their MRTP application to the FDA to market IQOS with reduced risk claims did not actually support claims of reduced risks.
Specifically, PMI’s MRTP application included their 3-month study of 24 non-cancer biomarkers of potential harm (which PMI calls “clinical risk endpoints,” CRE) in humans using IQOS compared to conventional cigarettes. These biomarkers include measures of inflammation, oxidative stress, lipids, blood pressure, and lung function. (PMI did separate studies of biomarkers of exposure, several of which are carcinogens.) While PMI’s application emphasizes that these biomarkers generally changed in positive directions, my examination of the data revealed no statistically detectable difference between IQOS and conventional cigarettes for 23 of the 24 BOPH in Americans and 10 of 13 in Japanese. Moreover, it is likely that the few significant differences were false positives. Thus, despite delivering lower levels of some toxicants, PMI’s own data failed to show consistently lower risks of harm in humans using IQOS compared to conventional cigarettes.
Their undated response, “The Difference between IQOS and Continued Smoking,”2 presents two arguments:
• The original study submitted to FDA was “NOT DESIGNED to serve as the sole pivotal evidence with regards to CRE’s and to show statistically significant changes in the CREs.”...
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Berry et al (1) report an analysis of two waves of the Population Assessment of Tobacco and Health (PATH) study focused on the association between the initiation of e-cigarette use by Wave 2 and cigarette abstinence/reduction assessed at Wave 2. They conclude that daily e-cigarette use is associated with both cigarette abstinence and reduced consumption among continuing smokers. While this addresses an important question, we argue that such analyses should be adjusted for the reason e-cigarettes are being used.
From Wave 1 of PATH (2), we know that ~75% of smokers agreed that e-cigarettes were useful to help people quit. However, ~80% agreed that e-cigarettes allowed someone to replace a cigarette where smoking was prohibited. From the first reason, we can hypothesize that e-cigarette use might be associated with cigarette abstinence/reduction. However, from the second reason, we can also hypothesize that e-cigarettes would be associated with neither cigarette abstinence nor reduction. The recent National Academies report (3) recommended that any assessment of the role of e-cigarettes in cigarette cessation/reduction should focus on smokers who used e-cigarettes to help them quit.
Show MorePATH Wave 2 data does include information on whether smokers tried to quit in the previous year, as well as whether they used e-cigarettes to aid the last quit attempt. Previous research (4) has shown that over half of the smoking population will not ha...
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Coleman et al’s important report [1] on transitions in the vaping and smoking status of a nationally representative cohort of American 18+ adults who use electronic cigarettes (EC) from the PATH study provides rich data that can greatly advance our understanding of the natural history of EC use and their potential in harm reduction.
However, we were struck by the absence of emphasis in the report of what is perhaps its most important finding. If we examine the report’s data and consider the net impact of vaping on the critical goals of having vapers stopping smoking and vaping non-smokers not starting to smoke, the findings are very disturbing and should strong reason for pause among those advocating e-cigarettes as a game-changing way of stopping smoking.
At Wave 2, 12 months on from Wave 1, of the cohort of 2036 dual users (EC + smoking) only 104 (5.1%) had transitioned to using only EC and another 143 (7%) had quit both EC and smoking for a combined total of 247 or 12.1%. Of the 896 exclusive EC users at Wave 1, 277 (30.9%) had stopped vaping at Wave 2. Together, 524 out of the 2932 EC users (17.9%) followed from Wave 1 might be considered to have had positive outcomes at Wave 2.
The other side of the coin however, shows that of the 2036 dual users at Wave 1, 886 (43.5%) relapsed to using cigarettes exclusively. In addition, among the 896 exclusive EC users from Wave 1, 109 (12.2%) had stopped vaping and were now smoking, wit...
Show MoreNOT PEER REVIEWED
The paper by Filippidis et al [1] provides data re-confirming the well-known fact that most ex-smokers attempt to quit without using any form of assistance, whether pharmaceutical, professional or via e-cigarettes. Moreover, the proportion of ex-smokers trying to quit unaided increased substantially in Europe between 2012-17 (ex-smokers using no assistance increased from 73.9% to 80.7%), a period where e-cigarette use accelerated in some nations.
Regrettably however, this study does not permit any comparison of success rates by method, as no data are reported on which method of cessation (assisted v unassisted) was used by ex-smokers on their last, final (and so successful) quit attempt.
The authors report that those “who successfully quit reported much lower use of cessation assistance compared with smokers who had tried to quit without success” and suggest that this might reflect indication bias, whereby those who find it harder to quit self-select to use assistance, leaving the low hanging fruit of non- or less addicted smokers to fall off the smoking tree using their own determination.
While this will be true for some, there are many former heavy smokers who quit without assistance. This argument also borrows assumptions from the discredited hardening hypothesis [2], which holds, in the face of evidence to the contrary, that as smoking prevalence falls the concentration of hardened, more deeply addicted smokers increase...
Show MoreNOT PEER REVIEWED
Feliu et al’s conclusion “in the European Union countries with the higher scores in the Tobacco Control Scale, which indicates higher tobacco control efforts, have lower prevalence of smokers, higher quit ratios and higher relative decreases in their prevalence rates of smokers.” deserved comment.
First, it seems a tautology. Tobacco control policies are robustly evidence based. Accordingly, more efforts, less smokers.
Second, a PubMed search with “"tobacco control scale" only retrieved 27 articles since 2006 and no validation published yet. Obviously, the Scale poorly correlated with smoking rate: r2 being .58 in 2002/3, .15 in 2006/7 and .06 in 2010/11.(From table 3 in 2; n= 11 European countries).
Third, why make simple stuff complex? This surrogate is complex to calculate and its items are subjective because issuing a decree is useless if no implementation were enforced. In contrast, the smoking rate and its evolution are simple and reliable! How France can be ranked 4th among 28 countries with a 57/100 score (1) while smoking prevalence has been plateauing for so long at more than 30%? In France, from 2004 to 2017 no relevant increase in tobacco taxes, no implementation of the legal smoking ban in cafés or of the ban of sale to minors despite sting operations by NGO showing evidence of serious breaches.(3)
Fourth, claiming “the European Union should continue implementing comprehensive tobacco control pol...
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