...And They Call This "Science"!
The list of all the lung cancer studies by category updated to 2006 on passive smoke, no dangers
|PROLOGUE||The long list of methodological errors in the junk science of passive smoke||The questionnaires of the epidemiological fraud||Downloadable list of all base studies on lung cancer and cardiovascular disease, including financing sources||The list of all the lung cancer studies by category updated to 2006 on passive smoke: no dangers|
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May 31, 2006 - We are glad to introduce our readers to the updated list (May 2006) of the studies on passive smoke and lung cancer. This list includes the separation by categories (i.e.: workplace, spousal); this explains the seemingly doubling of the number of studies which, in reality, are currently slightly over 70. This list should put an end to the diatribe on
passive smoke since it conclusively demonstrates, step by step and in extremely simple language accessible, to all the incredible misrepresentation of evidence used to transform a non-danger into an "epidemic" and into a collective hysteria phenomenon.
We recommend to read the necessary information to better understand the meaning of the tables.
(Skip the information and go to the conditions required for epidemiological validity)
(Skip all and go to the tables)
Incidence of a disease – The frequency at which the disease appears in people.
Relative Risk (RR), Odds Ratio – A ratio between the incidence of diseases in a group of people believed to be exposed to the risk (in our case, passive smoke) and the incidence in a group of people believed not to be exposed to that risk.
|RR=||Frequency of the disease (incidence) that appears in people exposed|
|Frequency of the disease (incidence) that appears in people not exposed|
If the incidence of disease is the same in the exposed and in the non- exposed groups, the ratio is 1 and there is no change in risk. If the incidence of disease is greater in the people exposed, the ratio becomes greater than 1 and the risk has increased. Conversely, the risk is smaller than 1 when the incidence is lower in the exposed people, implying that the exposure protects from the disease.
Confounder, Concomitant Factor – Factors and circumstances that contribute to the occurrence of the disease. As we shall see later, many diseases are multifactorial, meaning that they can be caused by different factors acting by themselves or in concert with others – as opposed to mono- factorial diseases that have one cause, and whose risks can be reliably measured. See the definitions below for further explanation.
Longitudinal or cohort study – Longitudinal or cohort studies identify groups of subjects exposed or not exposed to potentially toxic conditions. Prospective studies identify groups of subjects and follow them over time, often many years. Retrospective studies identify groups of subjects with different incidences of diseases and attempt to reconstruct their past exposures.
Retrospective study: a study based on memories of exposure by the subjects interviewed rather than on direct measurement of exposure. A retrospective study has no way to check the accuracy of memories.
Case-control study - Case-control studies are utilized when it is only feasible to observe differences of postulated toxic exposures in groups of people with or without disease. Case-control studies are necessarily retrospective and their weakness is that they do not measure differences of disease incidence. The incidence is 0% in the controls and 100% in the cases, and therefore such studies infer risks as differentials of exposure, and not as true differentials of incidence. In other words, these studies try to guess the exposure of the subjects to passive smoke - guess based solely on what the subjects say to remember. Then they infer (guess) the risk purely on the basis of the difference of exposure remembered by the subjects during the interview. Finally, the disease that already exists - and that could have been caused by any combination of co-factors - is attributed to passive smoke! The overwhelming majority of the studies on passive smoke is retrospective and case control, and this is the "mountain of evidence" we keep hearing about. It is on this methodological quality that it is said that passive smoke "kills" or "hurts" others - and this is the claimed basis of every single smoking ban in the world.
Hypothesis: A conjecture that must be demonstrated through experimentation.
Statistical significance: a numeric coherence indicating only that the data show either benefit or risk as opposed to both, as it happens for the large majority of the studies on passive smoke. Careful now, don't let them con you: "statistical significance" does not mean that the date are accurate, nor does it mean that the risk/benefit exists, not that it's big. In short, a risk with "statistical significance" (or "statistically significant") does not mean significant risk, as "public health" and antismoking con men activists want us to believe so that we keep on hating smokers.
Confidence Interval: the margin of certainty that mistakes are not made. This interval is 95%. To read the table below, simply remember this easy rule: to have statistical significance the two risk numbers that define the interval must either be both greater than 1 (i.e.: 1.3-4.7), or smaller than 1 (i.e.: 0.6-0.9) to indicate a benefit. If the interval is straddling 1 (i.e.: 0.7-2.3) the study has no statistical significance, that is, it demonstrates nothing.
With this information we can now examine what a study needs to have real epidemiological validity.
Conditions required for epidemiological validity
1. A study must warrant that its numerical representations of individual lifetime PS exposure recalls are true measures of actual exposures.
2. A study must warrant that an exposure recall bias affects cases and control groups, and exposed and non-exposed groups at the same rate.
3. A study must warrant that subject selection and misclassification biases affect cases and control groups, and exposed and non-exposed groups at the same rate.
4. A study must warrant that known causal confounders affect cases and control groups, and exposed and non-exposed groups at the same rate.
5. A study must warrant the accuracy of pathological and diagnostic records.
6. The results from different studies addressing the same subject must be consistently reproducible.
7. In any study, the statistical margin of error of reported risks should reach no less than the 95% level of significance.
8. If the above criteria are met, the results of a study should also be consistent with Hill’s criteria of causality.
9. Meta-analysis summations shall not be credible unless performed on the basis of all available studies, which studies also must be of homogeneous design and conduct, and must have met the above criteria of validity.
The conditions satisfied by the studies on passive smoke
For sake of brevity and clarity we focus here on the epidemiologic studies of PS and lung cancer, which their sponsors claim to represent the best and strongest evidence of the risks of PS exposure. On this basis, a consideration of the reliability of claims for other conditions allegedly linked with PS exposure would be subordinate to the considerations for lung cancer.
The credibility of the criteria above is self-evident and accepted by epidemiology. It is also easy to understand, and comprehensible to all who are interested in the verification of evidence on the basis of facts. On such basis we challenge anybody to disagree on what follows, which we state it applies to any study and any meta-analysis on passive smoke so far.
1. It is incontrovertible that no extant study can warrant that the numerical representation of individual lifetime PS exposure recalls is a reliable measure of actual exposures.
2. It is incontrovertible that no extant study can warrant that PS exposure recall bias affects cases and control groups, and exposed and non-exposed groups at the same rate.
3. It is incontrovertible that no extant study can warrant that subject selection and misclassification biases (and other biases) affect cases and control groups, and exposed and non-exposed groups at the same rate.
4. It is incontrovertible that no extant study can warrant that known causal confounders affect cases and control groups, and exposed and non-exposed groups at the same rate.
5. It is incontrovertible that no extant study has warranted the accuracy of pathological and diagnostic records.
6. It is incontrovertible that results from different studies addressing the same subject have been grossly inconsistent and not reliably reproducible.
7. It is incontrovertible that only for a random minority of studies has the numerical margin of error of reported risks been at or below the 95% confidence level of statistical significance.
8. It is incontrovertible that no study of PS has met Hill’s criteria of causality.
9. It is incontrovertible that no meta-analysis summation of PS studies has been performed on the basis of all available studies, of studies that are of homogeneous design and conduct, and of studies that have met the above criteria of validity.
A detailed consideration of each signle study on PS and lung cancer would make this report not accessible to non-specialized persons. However, upon request we commit to supply a detailed analysis of any of the studies listed below with respect to what stated above.
That notwithstanding, the points on coherence and statistical significance can be presented and understood immediately with the simple list of the studies and their reported risks. Summary pie charts are also supplied after the list.
We remind the reader that statistical significance concerns only the numerical context of a study, and it refers only to the numeric error field of a particular study. No statistical manipulation can improve the quality of the base data - hence if the data are not reliable and corrupt, each statistical estimate deriving from them is equally unreliable and corrupt.
For example, no statistical manoeuvre can improve the lack of reliability that comes from the memory recall of the people examined in a given study. It follows that a study with a risk elevation that has statistical significance gives no assurance that the risk elevation is credible. On the other hand, a study without statistical significance - that is, showing a risk and a benefit at the same time - is doubly unreliable: First because of the unreliability of the base data, and second because the margin of error is not acceptable. At any rate, the largest studies have a statistical advantage since the size of the error is inversely proportional to the number of the subjects examined by one particular study.
As general table, here are all the studies available to date concerning the exposure to PS and lung cancer, classified in three categories:
SPOUSAL STUDIES - On non smokers living with smoking spouses.
WORKPLACE STUDIES - On non smokers working in places where smoking is permitted
CHILDHOOD STUDIES - On non smokers exposed to PS during childhood and adolescence.
|COLOR CODE AND NOTATIONS:
NR = No Risk. Reported by the researchers as no correlation, that is, RR=1.00. See bibliographical references at the end of the page
|Studies and Authors||Year||Nation||Sex||Number of lung cancers||Relative Risk |
1.18=18% risk elevation)
|95% Confidence Interval|
|Garfinkel et al. 1 (SG)||81||United States||F||153||1.18||0.90-1.54|
|Chan et al. SG||82||Hong Kong||F||84||0.8||0.43-1.3|
|Correa et al. (SG)||83||United States||F||22||2.07||0.81-5.25|
|Correa et al.(SG)||83||United States||M||8||1.97||0.38-10.32|
|Trichopouls et al. (SG)||83||Greece||F||77||2.08||1.20-3.59|
|Buffler et al.||84||United States||F||41||0.8||0.34-1.9|
|Buffler et al.||84||United States||M||11||0.51||0.14-1.79|
|Hirayama et al. (SG)||84||Japan||F||200||1.6||1.00-2.4|
|Hirayama et al. SG||84||Japan||M||64||2.24||1.19-4.22|
|Kabat et al. 1(SG)||84||United States||F||24||0.79||0.25-2.45|
|Kabat et al. 1(SG)||84||United States||M||12||NR||0.2-5.07|
|Garfinkel et al. 2(SG)||85||United States||F||134||1.23||0.81-1.87|
|Lam W. et al.||85||Hong Kong||F||60||2.01||1.09-3.72|
|Wu et al. (SG)||85||United States||F||29||1.4||0.4-4.2|
|Akiba et al. (SG)||86||Japan||F||94||1.5||0.9-2.8|
|Akiba et al. (SG)||86||Japan||M||428||1.8||0.4-7.0|
|Lee et al. (SG)||86||United Kingdom||F||41||1.00||0.37-2.71|
|Lee et al. (SG)||86||United Kingdom||M||22||1.3||0.38-4.39|
|Bownson et al. 1||87||United States||F||19||1.68||0.39-6.9|
|Gao et al.||87||China||F||246||1.19||0.82-1.73|
|Humble et al.||87||United States||F||20||2.2||0.80-6.6|
|Humble et al.||87||United States||M||8||4.82||0.63-36.56|
|Koo et al.||87||Hong Kong||F||86||1.64||0.87-3.09|
|Lam T et al.||87||Hong Kong||F||199||1.65||1.16-2.35|
|Pershagen et al. (SG) .||87||Sweden||F||70||1.2||0.7-2.1|
|Butler et al||88||United States||F||8||2.2||0.48-8.56|
|Geng et al.||88||China||F||54||2.16||1.08-4.29|
|Inoue et al.||88||Japan||F||22||2.25||0.8-8.8|
|Shimizu et al.||88||Japan||F||90||1.08||0.64-1.82|
|Choi et al.||89||Korea||F||75||1.63||0.92-2.87|
|Choi et al.||89||Korea||M||13||2.73||0.49-15.21|
|Hole et al.||89||Scotland||F||6||1.89||0.22-16.12|
|Hole et al.||89||Scotland||M||13||3.52||0.32-38.65|
|Svensson et al.||89||Sweden||F||34||1.26||0.57-2.81|
|Janerick et al.||90||United States||F&M||191||0.93||0.55-1.57|
|Kalandidi et al.||90||Greece||F||90||2.11||1.09-4.08|
|Sobue et al.||90||Japan||F||144||1.13||0.78-1.63|
|Liu Z et al.||91||China||F||54||0.77||0.30-1.96|
|Brownson et al. 2 ^||92||United States||F||431||NR||0.80-1.2|
|Stockwell et al. ^||92||United States||F||62||1.6||0.80-3.0|
|Liu Q et al. ^||93||China||F||38||1.66||0.73-3.78|
|Wu et al.||93||China||F||75||1.09||0.64-1.85|
|Fontham et al. ^||94||United States||F||651||1.29||1.04-1.60|
|Zaridze et al.||94||Russia||F||162||1.66||1.12-2.46|
|Du et al.||95-96a||China||F||69||1.19||0.66-2.16|
|Kabat et al. 2 ^||95||United States||F||67||1.08||0.60-1.94|
|Kabat et al. 2 ^||95||United States||M||39||1.6||0.67-3.82|
|Wang et al.||96a||China||F||99||2.5||1.3-5.1|
|Wang et al.||96b||China||F||92||1.11||0.65-1.88|
|Schwartz et al. ^||96||United States||F||175||1.1||0.72-1.68|
|Schwartz et al. ^||96||United States||M||72||1.1||0.60-2.03|
|Sun et al.||96||China||F||230||1.16||0.80-1.69|
|Want SY et al.||96||China||F||82||2.53||1.26-5.10|
|Wang TJ et al.||96||China||F||135||1.11||0.67-1.84|
|Cardenas et al. ^ ^^||97||United States||F||150||1.2||0.80-1.6|
|Cardenas et al. ^ ^^||97||United States||M||97||1.1||0.60-1.8|
|Ko et al. ^ ^^||97||Thailand||F||105||1.3||0.7-2.5|
|Nyberg et al. ^^||97||Sweden||F||89||1.2||0.74-1.94|
|Nyberg et al. ^^||97||Sweden||M||35||1.2||0.57-2.55|
|Jockel et al. ^^||98||Germany||F&M||71||1.12||0.54-2.32|
|Nyberg et al. ^^||98a||Sweden||F||89||1.05||0.6-1.86|
|Nyberg et al. ^^||98a||Sweden||F&M||58||1.17||0.73-1.88|
|Boffetta et al.
|Zaridze et al. ^^||98||Russia||F||189||1.53||1.06-2.21|
|Jee et al. ^^||99||Korea||F||79||1.9||1.0-3.5|
|Rapiti et al. ^^||99||India||F||52||1.2||0.5-2.9|
|Zhong et al. ^^||99||China||F||504||1.1||0.7-1.7|
|Lee et al. ^^||00||Taiwan||F||186||1.2||0.7-2.0|
|Wang et al. ^^||00||China||F&M||200||1.19||0.7-2.0|
|Kreuzer at al. ^^||00/01||Germany||F||234||0.96||0.7-1.33|
|Kreuzer at al. ^^||00/01||Germany||F&M||292||0.99||0.73-1.34|
|Johnson et al. ^^||01||Canada||F||56||1.2||0.5-3.0|
|Nishino et al. ^^||01||Japan||F||23||1.8||0.67-4.6|
|Brennan, Buffler, Reynolds et all||06||USA||F&M||1.18||1.08-1.37|
|de Andrade, Ebbert, Wampfler et al||06||USA||F||===||===|
|Hirayama et all||06||Japan||F&M||1.74||1.19-2.55|
|Studies and Authors||Year||Nation||Sex||RelativeRisk||95% C. I.|
|Kabat et al. 1 ^||84||United States||F||0.70||0.30-1.50|
|Kabat 1 et al. ^||84||United States||M||3.3||1.1-10.4|
|Garfinkel 2 ^||85||United States||F||0.93||0.7-1.2|
|Wu et al. ^||85||United States||F||1.3||0.5-3.3|
|Lee et al. ^||86||United Kingdom||F||0.63||0.17-2.33|
|Lee et al. ^||86||United Kingdom||M||1.61||0.39-6.6|
|Koo et al. ^||87||Hong Kong||F||0.91||0.15-5.37|
|Shimizu et al. ^||88||Japan||F||1.18||0.70-2.01|
|Janerich et al. ^||90||United States||F&M||0.91||0.80-1.04|
|Kalandidi et al. ^||90||Greece||F||1.39||0.80-2.5|
|Wu-Williams et al. ^||90||China||F||1.2||0.90-1.6|
|Brownson et al. 2||92||United States||F||0.79||0.61-1.03|
|Stockwell et al. ^||92||United States||F||NR||NS|
|Fontham et al. ^||94||United States||F||1.39||1.11-1.74|
|Zaridze et al.||94||Russia||F||1.23||0.74-2.06|
|Kabat et al. 2 ^||95||United States||F||1.15||0.62-2.13|
|Kabat et al. 2 ^||95||United States||M||1.02||0.5-2.09|
|Schwartz et al. ^||96||United States||F&M||1.5||1.0-2.2|
|Sun et al.||96||China||F||1.38||0.94-2.04|
|Wang et al.||96a||China||F||2.0||p=0.05|
|Wang et al.||96b||China||F||0.89||0.45-1.77|
|Ko et al. ^ ^^||97||Thailand||F||1.1||0.40-3.0|
|Nyberg et al. ^^||98a||Sweden||F&M||1.61||0.91-2.85|
|Zaridze et al. ^^||98||Russia||F||0.88||0.55-1.41|
|Boffetta et al. (WHO)||98||Europe||F&M||1.17||0.94-1.45|
|Zhong et al. ^^||99||China||F||1.7||1.30-2.3|
|Kreuzer et al. ^^||98/00||Germany||F||1.03||0.78-1.36|
|Lee et al. ^^||00||Taiwan||F||1.2||0.50-2.4|
|Johnson et al. ^^||01||Canada||F||1.21
|Studies and Authors||Year||Nation||Sex||RelativeRisk||95% C. I|
|Correa et al. SG||83||United States||F||NR||NS|
|Kabat & Wyn ^||84||United States||F||0.92||0.40-2.08|
|Kabat & Wyn ^||84||United States||M||1.26||0.33-4.83|
|Garfinkel et al. 2 SG||85||United States||F||0.91||0.74-1.12|
|Wu et al. (SG)||85||United States||F||0.6||0.20-1.7|
|Akiba et al. SG||86||Japan||F&M||NR||NS|
|Gao et al. ^||87||China||F||1.1||0.7-1.7|
|Koo et al. ^||87||Hong Kong||F||1.73||0.6-6.4|
|Pershagen et al. ^||87||Sweden||F||NR||0.4-2.3|
|Svensson et al. ^||89||Sweden||F||3.3||0.5-18.8|
|Janerich et al. ^||90||United States||F&M||1.09||0.68-1.73|
|Sobue et al. (^)||90||Japan||F||1.28||0.71-2.31|
|Wu-Will et al. (^)||90||China||F||NR||NS|
|Brownson et al. 2 ^||92||United States||F||0.8||0.60-1.1|
|Stockwell et al. ^||92||United States||F||1.1||0.50-2.6|
|Fontham et al. ^||94||United States||F||0.89||0.72-1.1|
|Zaridze et al.||94||Russia||F||0.98||0.66-1.45|
|Kabat 2 ^||95||United States||M||0.9||0.43-1.89|
|Kabat et al. 2 ^||95||United States||F||1.55||0.95-2.79|
|Sun et al.||96||China||F||2.29||1.56-3.37|
|Wang et al.||96a||China||F||1.91||p=0.01|
|Wang et al.||96||China||F||0.91||0.56-1.49|
|Ko et al. ^ ^^||97||Thailand||F||0.80||0.4-1.6|
|Boffetta et al. (WHO)^^||98||Europe||F&M||0.78||0.64-0.96|
|Jockel et al. ^^||98||Germany||F&M||2.02||0.60-6.75|
|Nyberg et al. ^^||98a||Sweden||F&M||1.02
|Zhong et al. ^^||99||China||F||0.9||0.50-1.9|
|Rapiti et al. ^^||99||India||F||3.99||1.90-8.2|
|Kreuzer et al. ^^||98/00||Germany||F||1.03||0.78-1.36|
|Lee et al. ^^||00||Taiwan||M
|Wang et al. ^^||00||China||F&M||1.52||1.1-2.2|
|Rachtan et al. ^^||01||Poland||F||3.31||1.26-8.69|
|Johnson et al. ^^||01||Canada||F||0.54||0.1-2.7|
|Vineis et al.||05||Europe||F&M||1.42||0.63-3.20|
|Code||Number of spousal studies: 81||Perc.|
|Not statistically significant risk elevation: 57||70.37%|
|Not statistically significant risk reduction (protection): 10||12.34%|
|Statistically significant risk elevation: 13||16.04%|
|Statistically significant risk reduction (protection): 1||1.23%|
|Code||Number of workplace studies: 31||Perc.|
|Not statistically significant risk elevation: 18||58%|
|Not statistically significant risk reduction (protection): 7||22.7%|
|Statistically significant risk elevation: 6||19.3%|
|Statistically significant risk reduction (protection): 0||0%|
|Code||Number of childhood studies: 37||Perc.|
|Not statistically significant risk elevation: 20||55.6%|
|Not statistically significant risk reduction (protection): 10||27.8%|
|Statistically significant risk elevation: 5||13.9%|
|Statistically significant risk reduction (protection): 1||2.7%|