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We read with interest a recent publication by Li, et. al, entitled Association of smoking and electronic cigarette use with wheezing and related respiratory problems in adults: cross-sectional results from the Population Assessment of Tobacco and Health (PATH) study, wave 2. The primary finding, reported in the abstract, was that risk of wheezing and related respiratory symptoms was significantly increased in current exclusive e-cigarette users compared to never users, with an adjusted odds ratio of 1.67 (1.23, 2.15). We think the report is misleading for several reasons.
First, the main multivariable analysis (Table 2) did not adequately adjust for important confounders that impact wheeze, most importantly, cigarette smoking history. In most analyses of medical outcomes in adults, pack-years of smoking has a strong relation to smoking-related diseases, over-and-above current smoking status. Since three quarters of vapers in the main model were ex-smokers, cigarette smoking history is almost certainly contributing to the size and significance of the main reported finding. Other combustible tobacco use and current marijuana smoking would also be expected to exacerbate cough and wheeze. Our bet is that large numbers of e-cigarette users also use marijuana.
The authors partially addressed smoking history with a secondary analysis (Table 3), in which they stratified by former smoking status. In that analysis, vaping was not significantl...
We read with interest a recent publication by Li, et. al, entitled Association of smoking and electronic cigarette use with wheezing and related respiratory problems in adults: cross-sectional results from the Population Assessment of Tobacco and Health (PATH) study, wave 2. The primary finding, reported in the abstract, was that risk of wheezing and related respiratory symptoms was significantly increased in current exclusive e-cigarette users compared to never users, with an adjusted odds ratio of 1.67 (1.23, 2.15). We think the report is misleading for several reasons.
First, the main multivariable analysis (Table 2) did not adequately adjust for important confounders that impact wheeze, most importantly, cigarette smoking history. In most analyses of medical outcomes in adults, pack-years of smoking has a strong relation to smoking-related diseases, over-and-above current smoking status. Since three quarters of vapers in the main model were ex-smokers, cigarette smoking history is almost certainly contributing to the size and significance of the main reported finding. Other combustible tobacco use and current marijuana smoking would also be expected to exacerbate cough and wheeze. Our bet is that large numbers of e-cigarette users also use marijuana.
The authors partially addressed smoking history with a secondary analysis (Table 3), in which they stratified by former smoking status. In that analysis, vaping was not significantly associated with any respiratory symptom among persons with no previous cigarette smoking history. The secondary analysis strongly suggests that if a measure capturing extent of former smoking was entered as a covariate in the main model, the primary reported finding of an association between e-cigarette use and pulmonary symptoms would have been null.
Second, the analyses did not adjust for conditions that exacerbate wheeze (chronic obstructive pulmonary disease, congestive heart failure and certain cardiac medications), another potential source of residual confounding. These conditions may also cause declining health, prompting the person to quit smoking or switch from smoking to vaping, adding to a cross sectional association through reverse causality.
While addressing this last issue requires longitudinal data, we believe adding former smoking status and marijuana smoking to the main analysis should be done. The inclusion of these covariates would provide a less biased estimate of the cross-sectional association between vaping and respiratory symptoms and perhaps reach entirely different conclusions. We hope the authors will publish updated results in their response to this comment.
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A key finding of this paper does not find its way into the abstract namely, "no significant differences in wheezing and related respiratory symptoms was found when comparing current vapers who never smoked with never smokers. " This tends to suggest, unsurprisingly, that it is the prior smoking history that is the critical factor in current wheeze. The paper supports the harm reduction hypothesis for switching to vaping completely from smoking as per the conclusion. But the conclusion also states in the first line, "Vaping was associated with increased risk of wheezing and related respiratory symptoms, " which is incorrect without adding "in current smokers." Vapers who previously smoked have lower risk than those who continue to smoke, including dual users, and those who never smoked have no increased risk.
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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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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.
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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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In view of the rising prevalence of adolescent smoking worldwide, it makes a lot of sense to strictly limit cigarette sales only to alcohol licensed premises, particularly, in countries where there are minimum age requirements for buying alcohol. In a previous letter (1) to Lancet Global Health we had argued in favor of the same as we believe that restricting sale of cigarettes or other tobacco products will bring about a decrease in consumption by adolescents.
Smoking addictions are usually acquired during adolescence and this usually happens due to an apparently unregulated sale of tobacco products. Regulation is difficult when the number of tobacco selling establishments far exceeds the managing capacity of local administration. In India, adolescents have unrestricted access to tobacco products as small vendors, whose only source of income is by selling tobacco products, tend not to compromise on any business opportunity.
Although there is a positive association between alcohol and smoking, as the authors have pointed out “tobacco sales are not financially important for the majority of alcohol-licensed tobacco retailers”, so it is a win-win situation for preventing initiation of cigarette smoking by adolescents as alcohol vendors will have no incentive to bypass regulations by selling tobacco products to those who do not qualify as per legal age restrictions. In India, smoking and consumption of alcohol are also social taboos and th...
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In view of the rising prevalence of adolescent smoking worldwide, it makes a lot of sense to strictly limit cigarette sales only to alcohol licensed premises, particularly, in countries where there are minimum age requirements for buying alcohol. In a previous letter (1) to Lancet Global Health we had argued in favor of the same as we believe that restricting sale of cigarettes or other tobacco products will bring about a decrease in consumption by adolescents.
Smoking addictions are usually acquired during adolescence and this usually happens due to an apparently unregulated sale of tobacco products. Regulation is difficult when the number of tobacco selling establishments far exceeds the managing capacity of local administration. In India, adolescents have unrestricted access to tobacco products as small vendors, whose only source of income is by selling tobacco products, tend not to compromise on any business opportunity.
Although there is a positive association between alcohol and smoking, as the authors have pointed out “tobacco sales are not financially important for the majority of alcohol-licensed tobacco retailers”, so it is a win-win situation for preventing initiation of cigarette smoking by adolescents as alcohol vendors will have no incentive to bypass regulations by selling tobacco products to those who do not qualify as per legal age restrictions. In India, smoking and consumption of alcohol are also social taboos and this particular factor in itself might deter adolescents from buying tobacco products. We feel that limiting sale of tobacco products to alcohol-licensed premises will surely prevent initiation of cigarette by adolescents.
References:
1. Barua MP, Mishra V, Kumar S. Reducing adolescent smoking in India. Lancet Glob Health. 2017 Mar;5(3): e266. doi: 10.1016/S2214-109X(17)30036-0. PubMed PMID: 28193389
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More than 1,000 participants were exposed to IQOS in our clinical studies. The authors of the letter “Possible hepatotoxicity of IQOS" based their analysis on approximatively 10% of the data instead of examining the data as a whole. For example, for the five-day exposure studies in confinement, they stated that the percentage of participants with elevated bilirubin in IQOS arm was more than three times higher than that observed in the smoking abstinence (SA) arm in the European study (8.8% [7 participants] in IQOS arm, 2.6% [1 participant] in SA arm). However, they missed reporting that this percentage was lower in the IQOS arm than in the cigarette smoking (CC) arm in the Japanese study (10% [8 participants] in IQOS arm, 15% [6 participants] in CC arm). They also stated that the mean increase in alanine aminotransferase (ALT) was higher with IQOS than with CC or SA in the Japanese study but did not report that in the European study, the mean increase in ALT was lower in the IQOS arm than in the CC or SA arm.
Similarly, for the 90-day exposure studies in an ambulatory setting, they mentioned that the percentage of participants with increased ALT levels after 60 days of exposure was higher within the IQOS arm (6.3% [5 participants] in IQOS arm, 0% in CC arm, 2.6% [1 participant] in SA arm) in the U.S. study. However they omitted to mention that in the Japanese study, this percentage was lower in IQOS arm compared with CC or SA arms after 3...
NOT PEER REVIEWED
More than 1,000 participants were exposed to IQOS in our clinical studies. The authors of the letter “Possible hepatotoxicity of IQOS" based their analysis on approximatively 10% of the data instead of examining the data as a whole. For example, for the five-day exposure studies in confinement, they stated that the percentage of participants with elevated bilirubin in IQOS arm was more than three times higher than that observed in the smoking abstinence (SA) arm in the European study (8.8% [7 participants] in IQOS arm, 2.6% [1 participant] in SA arm). However, they missed reporting that this percentage was lower in the IQOS arm than in the cigarette smoking (CC) arm in the Japanese study (10% [8 participants] in IQOS arm, 15% [6 participants] in CC arm). They also stated that the mean increase in alanine aminotransferase (ALT) was higher with IQOS than with CC or SA in the Japanese study but did not report that in the European study, the mean increase in ALT was lower in the IQOS arm than in the CC or SA arm.
Similarly, for the 90-day exposure studies in an ambulatory setting, they mentioned that the percentage of participants with increased ALT levels after 60 days of exposure was higher within the IQOS arm (6.3% [5 participants] in IQOS arm, 0% in CC arm, 2.6% [1 participant] in SA arm) in the U.S. study. However they omitted to mention that in the Japanese study, this percentage was lower in IQOS arm compared with CC or SA arms after 30 days of exposure (1.3% [1 participant] in IQOS arm, 4.8% [2 participants] in CC arm, 7.5% [3 participants] in SA arm).
Taken together, the changes reported by the authors concern a small number of participants across all arms and most likely represent normal fluctuations of these parameters.
Finally, the grade 2 ALT increase in IQOS arm that was mentioned in the letter corresponds to a participant with an isolated increase at Day 30, which is explained by the use of concomitant medication. This information was also part of the publicly available information but was not taken into account by the authors.
In conclusion, the data submitted to the FDA as well as the data gathered in the context of our post-market safety surveillance system, based on pharmaceutical industry best practices, show unquestionably that there is no increased risk of developing hepatotoxicity after switching to IQOS.
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This study has some important findings that could, if replicated, guide FDA decision making on applications from manufacturers to make modified risk tobacco product claims. However, while it does not detract from the study’s findings, the article does not accurately describe the standards FDA must apply when evaluating those applications. The abstract inaccurately suggests that tobacco products in the U.S. may make reduced-risk or reduced-exposure claims so long as they are not misleading, and does not mention that any explicit or implicit reduced-exposure or reduced-risk claims may not be legally made without first submitting an application to FDA and receiving a permissive order, which considers various other factors, as well.
The introduction of the paper does a bit better, accurately stating that the Tobacco Control Act requires prior review by FDA before making lower-exposure or lower-risk claims. But it then suggests that manufacturers can receive that permission if they either demonstrate that the product lowers harm or risk compared with other tobacco products or if they demonstrate that the product is free of or contains reduced levels of harmful chemicals and the related claims don’t mislead consumers to believe that the reduced-exposure means lower risk. While that description is accurate as far as it goes, it leaves off the enormously important requirement, in both cases, that a manufacturer’s application for permission to...
NOT PEER REVIEWED
This study has some important findings that could, if replicated, guide FDA decision making on applications from manufacturers to make modified risk tobacco product claims. However, while it does not detract from the study’s findings, the article does not accurately describe the standards FDA must apply when evaluating those applications. The abstract inaccurately suggests that tobacco products in the U.S. may make reduced-risk or reduced-exposure claims so long as they are not misleading, and does not mention that any explicit or implicit reduced-exposure or reduced-risk claims may not be legally made without first submitting an application to FDA and receiving a permissive order, which considers various other factors, as well.
The introduction of the paper does a bit better, accurately stating that the Tobacco Control Act requires prior review by FDA before making lower-exposure or lower-risk claims. But it then suggests that manufacturers can receive that permission if they either demonstrate that the product lowers harm or risk compared with other tobacco products or if they demonstrate that the product is free of or contains reduced levels of harmful chemicals and the related claims don’t mislead consumers to believe that the reduced-exposure means lower risk. While that description is accurate as far as it goes, it leaves off the enormously important requirement, in both cases, that a manufacturer’s application for permission to make a modified-risk claim must also show that the proposed claim will benefit the health of the population as a whole (taking into consideration impacts of the product and its marketing with the modified-risk claim on implementation, cessation, relapse, etc.).
This study’s findings could have been presented even more powerfully if the article had also discussed their relevance to FDA’s consideration of how reduced-risk or reduced-exposure claims would impact the public health based on the claims likely influence on youth and adult consumer behaviors.
The "serious criticism" that Mr. Bates refers to is from him (on another website).
In order for the FDA to issue an order allowing Philip Morris International to market IQOS in the United States as a reduced risk tobacco product, the law required that, among other things, FDA "determines that the applicant [PMI] has demonstrated that such product [IQOS], as it is actually used by consumers will significantly reduce harm and the risk of tobacco- related disease to individual tobacco users."
That is why PMI provided the information of biomarkers of potential harm to the FDA. and how they compare to values observed in smokers. My paper shows that, using PMI's own data, IQOS will not significantly reduce risk to consumers compared with cigarettes.
Bates ignores this reality and instead talks about biomarkers of exposure, which is a different question.
NOT PEER REVIEWED The main problem with the claim of equivalence between smoking and switching to iQOS is that some biomarkers of potential harm change over a much longer timeframe than the 90-day duration of the trials. Biomarkers of potential harm can reflect years of accumulated physical changes arising from smoking and only improve slowly after smoking cessation. The trial did, of course, pick up very substantial reductions in biomarkers of exposure, which would, over time, emerge as reductions in biomarkers of potential harm.
This would have been apparent and obvious to readers if the paper had also shown the results for the third arm of the trial, smoking abstinence. The biomarkers of potential harm for smoking abstinence and for switching to iQOS are quite similar in this trial. This is a curious omission. Furthermore, biomarkers of exposure turned quite similar for both switching to iQOS and smoking abstinence - both are greatly reduced, which is an encouraging finding about the iQOS product.
It is unlikely that anyone would argue against smoking abstinence on the basis of the biomarkers of potential harm in the original PMI study. However, the author has selectively used the iQOS data from these trials without the context of the smoking abstinence data to oppose the Modified Tobacco Product Application that PMI made to the U.S. FDA - the author's attempt to block this reduced-risk product from entering the US market. ...
NOT PEER REVIEWED The main problem with the claim of equivalence between smoking and switching to iQOS is that some biomarkers of potential harm change over a much longer timeframe than the 90-day duration of the trials. Biomarkers of potential harm can reflect years of accumulated physical changes arising from smoking and only improve slowly after smoking cessation. The trial did, of course, pick up very substantial reductions in biomarkers of exposure, which would, over time, emerge as reductions in biomarkers of potential harm.
This would have been apparent and obvious to readers if the paper had also shown the results for the third arm of the trial, smoking abstinence. The biomarkers of potential harm for smoking abstinence and for switching to iQOS are quite similar in this trial. This is a curious omission. Furthermore, biomarkers of exposure turned quite similar for both switching to iQOS and smoking abstinence - both are greatly reduced, which is an encouraging finding about the iQOS product.
It is unlikely that anyone would argue against smoking abstinence on the basis of the biomarkers of potential harm in the original PMI study. However, the author has selectively used the iQOS data from these trials without the context of the smoking abstinence data to oppose the Modified Tobacco Product Application that PMI made to the U.S. FDA - the author's attempt to block this reduced-risk product from entering the US market. https://tobacco.ucsf.edu/pmi’s-own-data-biomarkers-potential-harm-americans-show-iqos-not-detectably-different-conventional-cigs
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We read with interest a recent publication by Li, et. al, entitled Association of smoking and electronic cigarette use with wheezing and related respiratory problems in adults: cross-sectional results from the Population Assessment of Tobacco and Health (PATH) study, wave 2. The primary finding, reported in the abstract, was that risk of wheezing and related respiratory symptoms was significantly increased in current exclusive e-cigarette users compared to never users, with an adjusted odds ratio of 1.67 (1.23, 2.15). We think the report is misleading for several reasons.
First, the main multivariable analysis (Table 2) did not adequately adjust for important confounders that impact wheeze, most importantly, cigarette smoking history. In most analyses of medical outcomes in adults, pack-years of smoking has a strong relation to smoking-related diseases, over-and-above current smoking status. Since three quarters of vapers in the main model were ex-smokers, cigarette smoking history is almost certainly contributing to the size and significance of the main reported finding. Other combustible tobacco use and current marijuana smoking would also be expected to exacerbate cough and wheeze. Our bet is that large numbers of e-cigarette users also use marijuana.
The authors partially addressed smoking history with a secondary analysis (Table 3), in which they stratified by former smoking status. In that analysis, vaping was not significantl...
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A key finding of this paper does not find its way into the abstract namely, "no significant differences in wheezing and related respiratory symptoms was found when comparing current vapers who never smoked with never smokers. " This tends to suggest, unsurprisingly, that it is the prior smoking history that is the critical factor in current wheeze. The paper supports the harm reduction hypothesis for switching to vaping completely from smoking as per the conclusion. But the conclusion also states in the first line, "Vaping was associated with increased risk of wheezing and related respiratory symptoms, " which is incorrect without adding "in current smokers." Vapers who previously smoked have lower risk than those who continue to smoke, including dual users, and those who never smoked have no increased risk.
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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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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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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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In view of the rising prevalence of adolescent smoking worldwide, it makes a lot of sense to strictly limit cigarette sales only to alcohol licensed premises, particularly, in countries where there are minimum age requirements for buying alcohol. In a previous letter (1) to Lancet Global Health we had argued in favor of the same as we believe that restricting sale of cigarettes or other tobacco products will bring about a decrease in consumption by adolescents.
Smoking addictions are usually acquired during adolescence and this usually happens due to an apparently unregulated sale of tobacco products. Regulation is difficult when the number of tobacco selling establishments far exceeds the managing capacity of local administration. In India, adolescents have unrestricted access to tobacco products as small vendors, whose only source of income is by selling tobacco products, tend not to compromise on any business opportunity.
Although there is a positive association between alcohol and smoking, as the authors have pointed out “tobacco sales are not financially important for the majority of alcohol-licensed tobacco retailers”, so it is a win-win situation for preventing initiation of cigarette smoking by adolescents as alcohol vendors will have no incentive to bypass regulations by selling tobacco products to those who do not qualify as per legal age restrictions. In India, smoking and consumption of alcohol are also social taboos and th...
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Show MoreMore than 1,000 participants were exposed to IQOS in our clinical studies. The authors of the letter “Possible hepatotoxicity of IQOS" based their analysis on approximatively 10% of the data instead of examining the data as a whole. For example, for the five-day exposure studies in confinement, they stated that the percentage of participants with elevated bilirubin in IQOS arm was more than three times higher than that observed in the smoking abstinence (SA) arm in the European study (8.8% [7 participants] in IQOS arm, 2.6% [1 participant] in SA arm). However, they missed reporting that this percentage was lower in the IQOS arm than in the cigarette smoking (CC) arm in the Japanese study (10% [8 participants] in IQOS arm, 15% [6 participants] in CC arm). They also stated that the mean increase in alanine aminotransferase (ALT) was higher with IQOS than with CC or SA in the Japanese study but did not report that in the European study, the mean increase in ALT was lower in the IQOS arm than in the CC or SA arm.
Similarly, for the 90-day exposure studies in an ambulatory setting, they mentioned that the percentage of participants with increased ALT levels after 60 days of exposure was higher within the IQOS arm (6.3% [5 participants] in IQOS arm, 0% in CC arm, 2.6% [1 participant] in SA arm) in the U.S. study. However they omitted to mention that in the Japanese study, this percentage was lower in IQOS arm compared with CC or SA arms after 3...
NOT PEER REVIEWED
This study has some important findings that could, if replicated, guide FDA decision making on applications from manufacturers to make modified risk tobacco product claims. However, while it does not detract from the study’s findings, the article does not accurately describe the standards FDA must apply when evaluating those applications. The abstract inaccurately suggests that tobacco products in the U.S. may make reduced-risk or reduced-exposure claims so long as they are not misleading, and does not mention that any explicit or implicit reduced-exposure or reduced-risk claims may not be legally made without first submitting an application to FDA and receiving a permissive order, which considers various other factors, as well.
The introduction of the paper does a bit better, accurately stating that the Tobacco Control Act requires prior review by FDA before making lower-exposure or lower-risk claims. But it then suggests that manufacturers can receive that permission if they either demonstrate that the product lowers harm or risk compared with other tobacco products or if they demonstrate that the product is free of or contains reduced levels of harmful chemicals and the related claims don’t mislead consumers to believe that the reduced-exposure means lower risk. While that description is accurate as far as it goes, it leaves off the enormously important requirement, in both cases, that a manufacturer’s application for permission to...
Show MoreNOT PEER REVIEWED
The "serious criticism" that Mr. Bates refers to is from him (on another website).
In order for the FDA to issue an order allowing Philip Morris International to market IQOS in the United States as a reduced risk tobacco product, the law required that, among other things, FDA "determines that the applicant [PMI] has demonstrated that such product [IQOS], as it is actually used by consumers will significantly reduce harm and the risk of tobacco- related disease to individual tobacco users."
That is why PMI provided the information of biomarkers of potential harm to the FDA. and how they compare to values observed in smokers. My paper shows that, using PMI's own data, IQOS will not significantly reduce risk to consumers compared with cigarettes.
Bates ignores this reality and instead talks about biomarkers of exposure, which is a different question.
NOT PEER REVIEWED The main problem with the claim of equivalence between smoking and switching to iQOS is that some biomarkers of potential harm change over a much longer timeframe than the 90-day duration of the trials. Biomarkers of potential harm can reflect years of accumulated physical changes arising from smoking and only improve slowly after smoking cessation. The trial did, of course, pick up very substantial reductions in biomarkers of exposure, which would, over time, emerge as reductions in biomarkers of potential harm.
Show MoreThis would have been apparent and obvious to readers if the paper had also shown the results for the third arm of the trial, smoking abstinence. The biomarkers of potential harm for smoking abstinence and for switching to iQOS are quite similar in this trial. This is a curious omission. Furthermore, biomarkers of exposure turned quite similar for both switching to iQOS and smoking abstinence - both are greatly reduced, which is an encouraging finding about the iQOS product.
It is unlikely that anyone would argue against smoking abstinence on the basis of the biomarkers of potential harm in the original PMI study. However, the author has selectively used the iQOS data from these trials without the context of the smoking abstinence data to oppose the Modified Tobacco Product Application that PMI made to the U.S. FDA - the author's attempt to block this reduced-risk product from entering the US market.
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