Showing posts with label biomarkers. Show all posts
Showing posts with label biomarkers. Show all posts

Wednesday, February 23, 2022

Different Strokes for Different Smokes: More Evidence That All Quitting Options Are Vital

 

Investigators at the University of Nebraska Medical Center in Omaha and the University of California San Francisco have published an important study in JAMA Network Open on “Exposure to toxicants associated with use and transitions between cigarettes, e-cigarettes, and no tobacco.”

Hongying Dai and colleagues looked at 55 tobacco exposure biomarkers (mostly toxins) in the urine of adult smokers, vapers and dual users in the first wave of the Population Assessment of Tobacco and Health Study.  They compared this data with urine samples from the same participants one year later in Wave 2, when the participants may or may not have changed their tobacco use status.

While Dai and coauthors “found complex patterns and heterogeneous health outcomes associated with transitions between cigarettes and e-cigarettes,” the results can be succinctly summarized.  First, “transitions from dual use or exclusive cigarette use to exclusive e-cigarette use and transitions from any tobacco use to no use” were associated with sharp declines in toxins. Second, “transitions from exclusive e-cigarette use to cigarette use or dual use” were associated with “moderate to large effect” increases in toxin levels.  And third, “transition from exclusive cigarette smoking to dual use of cigarettes and e-cigarettes” didn’t provide any meaningful change in urinary toxins.

The authors found that “only a small percentage of [Wave 1] exclusive cigarette smokers and dual users transitioned to exclusive e-cigarette use at [Wave 2] (1.2%and 5.6%, respectively), which could limit ben

efits in moving combustible cigarette smokers to less hazardous, noncombustible e-cigarettes.”  This is an important statement, because it acknowledges less e-cigarette harm by referencing an FDA press release from 2017 (here).  More importantly, it is followed by a solid explanation for the low transition rate to vapor: “low effectiveness in early generations of e-cigarettes in delivering nicotine [the PATH Waves were in 2013 and 2014, when e-cigarettes were not very effective], lack of knowledge among cigarette users to distinguish harmful effects between dual use and exclusive e-cigarette use, or the effects of negative public health messaging [emphasis added, references omitted].”

All of the above is informative, but the real news from this study is demonstrated in the following table.  It reports levels of cotinine – a breakdown product of nicotine – in the urine of participants, according to the product they used at Wave 1, and one year later at Wave 2.  Cotinine levels are widely used to indicate tobacco use levels.  In general, higher cotinine indicates more tobacco use.  Higher cotinine, especially with cigarette combustion, also means greater exposure to toxins. 

 

 
Urinary Cotinine Levels* at PATH Waves 1 and 2, According to Product Use
Wave 1 Product (n users)Wave 1 CotinineWave 2 Product/Cotinine




NoneCigarettes OnlyE-Cigarettes OnlyDual Use






Cigarettes (247)1585


Cigarettes (1820)2273
2265

Cigarettes (32)1833

713
Cigarettes (257)3068


2522






E-cigarettes (44)162


E-cigarettes (14)502
1942

E-cigarettes (121)727

470
E-cigarettes (31)972


2569






Dual use (42)2136


Dual use (315)2690
2628

Dual use (36)2792

1192
Dual use (252)3179


3374
*in nanograms per milliliter of urine

 

One can readily see that cotinine levels were high in smokers and/or dual users in both waves.  Cotinine levels among e-cigarette users were much lower, confirming that in 2013-14, the products did not deliver nicotine very effectively.

Everyone in the first four rows of the table smoked cigarettes in Wave 1, so one might expect that their cotinine levels in that wave would be the same.  Instead, there were huge differences between them, depending on where the smokers ended up at Wave 2.  The 247 smokers who had a cotinine level of only 158 ng/ml at Wave 1 quit everything at Wave 2 and had negligible cotinine.  The highest Wave 1 cotinine levels were in smokers who continued to smoke at Wave 2, while the smokers who ended up with e-cigarettes went from 1833 ng/ml at Wave 1 to 713 at Wave 2. 

The same is true for the other two categories: The e-cigarette users and dual users at Wave 1 who quit completely at Wave 2 started out with much lower cotinine levels. 

The take-home message is hugely important.  Tobacco users at Wave 1 may have self-selected their Wave 2 product use based on their cotinine status at Wave 1.  This says that those who quit completely, switched to e-cigarettes, or stayed with cigarettes were entirely different groups of smokers, each with distinct nicotine needs.  Because no one can predict how individual smokers will be able to quit, they should be provided access to all quit-smoking options.

 

 

Friday, November 17, 2017

Smoke But No Fire: IQOS Opponent Misrepresents 3-Month Studies to FDA



Stanton Glantz, a University of California, San Francisco professor, this week urged the FDA to “…deny [Philip Morris Intermational’s] application to market IQOS [its heat-not-burn cigarette] as a modified risk tobacco product because PMI’s own data fails to support a modified risk claim in people who are actually using the product.”

Glantz’s declaration is based on his review of lab results from two groups of smokers three months after (1) continuing to smoke or (2) switching to IQOS.  The studies, from Japan and the U.S., were submitted by PMI in its application (available at the FDA website here ).

It is well known that individuals’ lab results do not improve instantly upon smoking cessation.  The PMI submission clearly indicated that many of the subjects’ lab values are not expected to change for 6-12 months or longer after quitting. 
Beyond that, Glantz completely ignored a third PMI study group: smokers who had quit completely for three months. 

In this post I present the comparison that Glantz emphasized – IQOS users versus continuing smokers – but I add an equally important comparison that Glantz ignored – IQOS users versus complete quitters.  Because the U.S. study had too few subjects in the latter group  (n=9) for stable comparisons, I will focus on the Japan study, which involved 70 IQOS users, 41 continuing smokers and 37 complete quitters.  I will also note one omission in Glantz’s comparison.

The comparisons of IQOS and continued smoking in the table below were calculated by PMI and presented in its application.  PMI also calculated differences for IQOS versus quitting, but I could not find them in the material released so far by the FDA.  So those comparisons in the table are from my assessment of point estimates and confidence intervals from the submission.  All differences in the table are described positively with respect to health (e.g. IQOS significantly lower).  “NS” indicates no significant difference between groups for that test.


Comparison of Laboratory Values After 3 Months: IQOS Users Versus Continuing Smokers and Versus Complete Quitters in Japan
Lab MarkerIQOS Versus SmokingIQOS Versus Complete Quitting*



Inflammation

White blood cell countIQOS significantly lower**NS
C-reactive proteinNSNS
Soluble ICAMIQOS significantly lowerNS
FibrinogenNSNS



Oxidative Stress

Prostaglandin F2 alphaIQOS significantly lowerIQOS possibly lower
11-DTX-B2NSQuitting possibly lower



Cholesterol, Triglycerides

High density lipoproteinIQOS significantly higherNS
Low density lipoproteinNSNS
Total cholesterolNSNS
TriglyceridesNSIQOS possibly lower



Blood pressure

SystolicNSNS
SystolicNSNS



Lung function

Forced expiratory vol, 1 sec.NSNS
NS, No significant difference
* My assessment based on point estimates and confidence intervals in submission  
** Omitted by Glantz

The PMI calculations show that IQOS users had four statistically significant favorable comparisons at 3 months compared with smokers.  Other results show no differences.  My assessment of IQOS users versus complete quitters reveals no significant differences for ten lab results.  There were only two possibly significant results favoring IQOS and one favoring complete quitting. 

In summary, the results at three months do not prove anything definitive, which was emphasized in PMI’s application.  These results were not used by PMI to support any positive claims about IQOS; they should not have been used by Professor Glantz to make any counter claims.