Jump to:

Lorillard

A Statistical Review of the Epa Report: Health Effects of Passive Smoking: Assessment of Lung Cancer in Adults and Respiratory Disorders in Children (Epa/600/6-90/00064 - External Review Draft)

Date: Sep 1990
Length: 18 pages
87667159-87667176
Jump To Images
snapshot_lor 87667159-87667176

Fields

Author
Howard, G.
Type
REPT, OTHER REPORT
CHAR, CHART/GRAPH/MAPS
Alias
87667159/87667176
Area
SPEARS,ALEXANDER/EXEC CONF ROOM STORAGE
Site
G65
Named Person
Akiba
Brownson
Buffler
Chan
Cheng
Correa
Fung
Gao
Garf
Garfinkel
Geng
Gillis
Haenszel
Hirayama
Humble
Inoue
Kabat
Koo
Lam
Lee
Mantel
Pershagen
Shimuzu
Sobue
Surgeon General
Svenson
Trichopoulos
Vandenbroucke
Varela
Wells
Wilcoxon
Wu
Recipient (Organization)
RJR, R.J.Reynolds
Date Loaded
12 Feb 1999
Named Organization
Epa, Environmental Protection Agency
Lmat
Monte Carlo
Nrc
Statistical Analysis Center
Litigation
Stmn/Produced
Characteristic
DRFT, DRAFT
EXTR, EXTRA
Master ID
87666576/7485

Related Documents:
UCSF Legacy ID
jtd40e00

Document Images

Text Control

Highlight Text:

OCR Text Alignment:

Image Control

Image Rotation:

Image Size:

Page 1: jtd40e00
A STATISTICAL REVIEW OF THE EPA REPORT: HEALTH EFFECTS OF PASSIVE SMOKING: ASSESSMENT OF LUNG CANCER IN ADULTS AND RESPIRATORY DISORDERS IN CHILDREN (EPA/600/6-90/00064 - EXTERNAL REVIEW DRAFT) Prepared for: The R. J. Reynolds Tobacco Company Prepared by: George Howard, Dr. PH Statistical Analysis Center September 1990 R. J. Reynolds Tobacco Company Comments - RJR Appendix A
Page 2: jtd40e00
Introduction The conclusion by EPA that ETS exposure is related to lung cancer is based on a statistical analysis of data presented in Tables 3.5 and 3.6 of the EPA report. That analysis appears to over-interpret the available data and to employ inconsistent statistical methods. For Table 3.5, the postulated association between ETS and lung cancer is evaluated using three statistical methods: (1) a binomial test to examine whether the proportion of "significant" studies is above the 5% which would occur by chance alone, (2) a Wilcoxon test examining whether the "S" statistics (log of the odds ratio divided by its standard error) are significantly above zero, the null hypothesis of no association between ETS and lung cancer, and (3) a Mantel-Haenszel estimate. As performed by EPA, these tests suggest that spousal smoking is statistically associated with lung cancer in the studies contained in Tables 3.5 and 3.6 of the report. This report reexamines five aspects of the EPA's analysis of the epidemiologic data: I. Whether the collective studies reported in Table 3.5 are statistically significant under a Wilcoxon analysis after adjustment for misclassification and publication bias. II. The impact of including in the analysis studies that were omitted by EPA. III. The results of restricting EPA's analysis to: (a) Sex-specific risks, (b) U.S. data only, (c) Asian data, and (d) Studies not reviewed by the Surgeon General or NRC. IV. Whether the epidemiologic data as a whole demonstrate a dose-response relationship. V. Whether the statistics reported in Table 3.6 are internally consistent. A1
Page 3: jtd40e00
L Whether the collective studies reported in Table 3.5 are statistically significant under a Wdcoxon analysis after adjustment for misclassificatian and publication bias. Interpretation of the association identified by EPA's Wilcoxon analysis of the association between ETS exposure and lung cancer depends on, among other things, whether the data examined are free from bias. The effect of misclassification of smoking status and publication bias are both in the direction of increasing the observed relationship of ETS to cancer (overestimating its effect). The EPA report adjusts for the effect of misclassification bias in Chapter 4, by deflating the estimate by a factor of 14% (which is EPA's estimate of the association that would be induced by the expected misclassification). The EPA report totallv discounts publication bias on the basis of reports by Vandenbroucke and Wells, and does not make any quantitative adjustment for that bias source. It should be noted that Vandenbroucke and Wells conclude that publication bias does not account for the total observed difference; they do not conclude that it plays no role at all. As such, the EPA's failure to make an adjustments for publication vias may be viewed as liberal. The EPA should have adjusted for misclassification and publication bias in the analysis of the significance of the association of ETS and cancer in Tables 3.5 and 3.6. If the result is nonsignificant, the analysis in Chapter 4 estimating magnitude of the effect would not be warranted. We will examine the sensitivity of the significance of the ETS/cancer relationship to adjustments for these two biases prior to the analysis of the association. This will be performed in two stages, first adjusting for the effect of misclassification bias, and then examining the effect of publication bias on that adjusted estimate. ~ ~ ~ A2 ~ ~ M C'~ W
Page 4: jtd40e00
Effect of Misclassification Bias on the Wilcoxon Analysis The odds ratios Table I: Analysrs of Odds Ratias Pnsaucd in Tobk 3.5 reported in Table 3.5 are reported in Table I of this report under the column e a in h g OBSER VED ODDS RATIO. Taking the natural log of these odds ratios serves to standardize (normalize) the scale (note: odds STUDY OBSERVED OR LOG OBS OR ADJLOG OR ADJ OR AKIB 1.52 0.41871 0.?8768 133333 BROW 132 0.41871 0.28768 133333 BUFF 0.81 -0.21072 -034175 0.71053 CH.4N 0.75 -0.28768 -0.41871 0.65789 CORR 2.07 0.72755 059652 1.81579 GAO 1.19 0.17395 0.04293 1.04386 GARF 131 0.27003 0.13900 1.14912 GENG 2.16 0.77011 0.63908 1.89474 HUMB 2.34 0.85015 0.71912 2.05263 INOU 0.79 -0.a3 -03~65607s 0.69~298 KOO 1.55 0.43825 030723 135965 LAMT 1.65 050078 036975 1.44737 LAMW 2.01 0.69813 056711 1.76316 LEE 1.03 0.02956 -0.10147 0.90351 PERS 1.28 0.24686 0.11583 1.12281 SVEN 1.26 0.23111 0.10008 1.10526 TRIC 2.13 0.75612 0.62509 1.86842 WU 1.41 0.34359 021256 1.2'i684 ratios of 0.5 and 2.0 imply equal positive and negative association, and taking the log converts these to equal distances from the log of the no effect point of 1.0). The result of this calculation is provided under the column heading LOG OBS ODDS RATIO (i.e., the log of the observed odds ratio). A Wilcoxon signed-rank analysis of the summary log odds ratio (the third column) provides a p-value of 0.0015, the value reported in the EPA report as a measure of the significance of the association between spousal smoking and lung cancer. However, the EPA report concludes that misclassification bias causes an overestimation of the odds ratio by approximately 14% (a 14% increase over the expected 1.00 given no association). For purposes of analysis, this estimate was adopted as the standard. Each of the observed odds ratios was then adjusted to reflect a 14% A3
Page 5: jtd40e00
nI misclassification bias. This is done by subtracting log(1.14) = 0.131 from each of the values in the second column, resulting in the ADJ LOG ODDS RATIO (column 4 of the Table) estimates. The exponential of this value can be taken to provide the ADJUSTED ODDS RATIO (column 5), which represents the odds ratio after adjustment for the misclassification basis. A Wilcoxon analysis of the fifth column provides a p-value of 0.02, which while significant, represents a more marginal association of ETS and lung cancer (a 2/100 chance that the observed association happened by chance alone). The EPA's determination that misclassification bias spuriously elevates the observed odds ratios by 14% is only one possible assumption. Different assumptions regarding the relevant parameters would produce different estimates of the significance after adjustment. In order to examine the Probability at Various Levels of Misclassification Adjustment 0.25 ~ 0.20 ~ 0.05 TcOM 3.5 0.00 1.00 1.05 1.10 1.15 1.20 1.25 1.30 Odds Rotio Cut Point Figner 1: Wdcoxon probabiliry of 6TSkanca association as a fwcrion of the sizc of adjustmciu fa.,nfsclassifrcati«a bial< sensitivity of the observed association of ETS and lung cancer to the assumed misclassification value for adjustment, a similar analysis was conducted for misclassification effect values ranging from 1.00 (no adjustment) to 130, with results provided in Figure 1. A4
Page 6: jtd40e00
For adjustments above 1.24 the association between ETS and cancer becomes statistically nonsignificant. Table II provides a similar analysis for the odds ratios provided in Table 3.6 of the EPA report. Again, a Wilcoxon analysis of the LOG ODDS RATIO, as performed in the report, is significant (p = 0.014), the analysis of the log odds ratio (ADJ LOG RATIO) is only marginally significant (p = 0.04). The sensitivity of T°blr fL A"°h'su of Odds Ratias Presaucd in TabJe 3.6 the observed association between ETS and lung cancer to variations in the of assumption of the level the odds ratio attributable to misclassification bias is STUDY OBSERVED OR LOG OBS OR ADJ LOG OR ADJ OR BROW 1.68 0.51879 038777 1.47368 GAO 1.70 053063 039960 1.49123 GARF 1.70 0.53063 039960 1.49123 HUMB 1.20 0.18232 0.05129 1.05263 INOU 3.09 1.12817 0.99714 2.71053 KOO 1.19 0.17395 0.04293 1.04386 LAMW 1.00 0.00000 -0.13103 0.87719 LEE 2.40 0.87547 0.74444 210526 PERS 1.90 0.64185 051083 1.66667 VARE 0.94 -0.06188 -0.19290 0.82456 WU 1.20 0.18232 0.05129 1.05263 provided in Figure 2. This shows that for adjustments above an odds ratio of 1.20 for misclassification bias the association becomes statistically insignificant. Effect of adjustment for publication bias Because statistically nonsignificant studies and/or studies providing no basis for rejecting the null hypothesis are difficult to publish, meta analyses of the published literature are biased towards overestimating an effect. The magnitude of the size of the overestimation is a function of: (1) the number of "unreported" studies, and (2) the size of and the results of the studies. That is, the more studies which are not reported, and/or the A5
Page 7: jtd40e00
I more nonsignificant the nonreported studies are, the more likely meta analysis is to overestimate the size of the association. In this section, the effect of: (1) the number of unincluded papers, and (2) the size of the effect in these papers which were not included is examined. This Probability at Various Levels of Misclassification Adjustment 0.25 1 0.20 ; ~ , 1.00 1.05 1.10 1.15 1.20 Odds Ratio Cut Point 1.25 1.30 Figure 2: af'~Icoxon p-value of ETSICancer effect as a function of the size of adjusrmau for misclaunccation bias will be considered after the above adjustment for misclassification of 1.14 in the EPA report) as discussed from one to five unreported studies on the analysis of Table 3.5 is examined. The vertical axis shows the Wilcoxon p-value and the horizontal the significance of the unreported studies. Each of the lines represents the relationship of the p-value for a specific number of in the previous section. bias (assuming the value Probability After Adding Additional Nonsignificant Studies TobN 3.5 0.40 - 0.30 -i ~ 0 0.20 1J _ - 1 oddt O ` _ _ 2 . addt. 0- 3 oddt. ______ 4 oddt. 0.10 - •-____-_-_. _•.~..~ - 5 oddt. '- ~_ ----- - - - 0 00 . 0.70 0.79 0.88 0.97 1.06 1.15 Odds Ratio Cut Point Figure 3: Effect of publicadon biar on Table 3.S A6 In Figure 3 the effect of I
Page 8: jtd40e00
unreported studies, ranging from one to five. In addition, there is a horizontal line representing the alpha = 0.05 level. As can be seen, if there are three unreported studies showing no effect (odds ratio of 1.00), the analysis of Table 3.5 would have concluded that there is no effect. Figure 4 shows the effect of publication bias on the Wilcoxon statistic in the analysis of Table 3.6, again after adjustment for misclassification. If there is a single unreported study showing no effect, the analysis would have concluded that there was no ETS/lung- cancer relationship. If there are four unreported studies having odds ratios as great as 1.10 it would still be concluded that there was no relationship between ETS and cancer. Conclusions Misclassification and publication bias both tend to spuriously elevate the overall observed association between spousal smoking and lung cancer. Both biases should be corrected Probability After Adding Additional Nonsignificant Studies ToD4 3.6 - - 1 oddt - - 2 oddt 3 addt- -••°- 4 addl - 5 addl -----,°a , •. ~ I - ~---------------- ---------- -------------- --------• - - - % ---------- --------------- - - -----------------=11 : 0.0 0.70 0.79 0.88 0.97 1.06 1.15 Odds Ratio Cut Point for uantitativel in an meta- ` Q y y Figun I: Effect of mi9dassrfuadm bias on Tabk 3.6 analysis. The relationship between ETS and cancer, as evaluated in Tables 3.5 and 3.6, is at best only marginal after adjustments for misclassification and publication bias. If Table 3.5 is adjusted for an odds ratio of 1.14, and if there are as many as 3 unpublished papers showing no effect, then the A7
Page 9: jtd40e00
relationship between ETS and cancer (as measured by the Wilcoxon statistic) becomes insignificant. In Table 3.6, if a similar adjustment is made for misclassification bias and of there is a single unreported paper showing no effect, then it would be concluded that there was no relationship between ETS and cancer. As such, when one considers (only) misclassification and publication bias the relationship between ETS and cancer appears marginal under the Wilcoxan analysis. If one were also to consider confounders the relationship would appear weaker still. II. The impact of including in the analysis studies that were omitted by EPA. For inclusion in Table 3.5, the EPA required that a study report "raw" frequencies. This restriction was placed to allow the use of Mantel-Haenszel statistic for the estimation of the ETS/lung cancer relationship. This restriction removed a number of studies from consideration. Including these studies could affect the estimated odds ratio or the significance of the relationship. Notably, the study by Varela was omitted, a large case/control study where the overall estimated effect was nonsignificantly protective. Including this study, and other studies omitted from Table 3.5 may modify the estimated odds ratio. An alternative statistical procedure can be adopted to allow for the incorporation of the studies not providing raw data. The data used in this analysis is described in Table III, where the estimated odds ratio, log of odds ratio and the variance of the log-odds ratio are provided. Because the log of the odds ratio is normally distributed (under the central limit A8
Page 10: jtd40e00
Table III: F.arYmnred RR 1ogR1R and vmrwnce ojlogRR theorem), estimation can be performed Variance SOURCE oR LOG OR LOG OR where using weighted general linear models, the weights are the inverse of the variance of the log of the odds ratio. A plot of the weight (inverse of the variance) versus the log odds ratio is rovided in Fi re 5. This fi re clearl P ~' ~ y shows that those studies with a large log risk ratio (and hence, large estimated RR) all have a relatively small weight. Conversely, the three studies with the lar est wei hts {Varela M, Varela F, g g ~ ) () and Garfinkel ('81)}, each with a weight above 60, have estimated logRR very near zero. Two of these three studies were U.S. Studies Brownson (F) 1.52 0.42121 0.48452 Brownson (M) 1.38 031845 121591 Buffler (F) 0.80 -0.21706 0.19265 ButTkr (M) 0.51 -0.68131 0.41394 corna (F) z07 0.72541 0.22671 Correa (M) 1.97 0.68024 0.71162 Garfinkel '85 131 0.27061 0.04429 Garfinkel '81 1.17 0.15700 0.01364 Humble 2.34 0.85043 0.29174 Kabat (F) 0.79 -0.23841 033450 ttabat (M) 1.00 0.00000 0.68571 Varela (F & M) 0.98 -0.98490 0.00691 Wu 1.41 034175 0.23950 European Studies Gillis (F) 1.00 0.00000 0.67176 ~~r(~M) 3.25 1.03 1.17865 0.02632 0.75656 0.21530 Lee (M) 131 0.26706 0.40179 PershaBen 1.27 0.24272 0.07146 Svensson 1.26 0.23361 0.16711 Trichopoulos 2.13 0.75643 0.08950 Acian Studies Akiba (n 1S2 0.41632 0.07883 Akiba (M) 2.10 0.74392 0.51685 Chan & Fung 0.75 -0.28486 0.07826 Gao 1.19 0.17341 0.03656 Geng 2.16 0•76830 0.12303 Hirayama (F) 1.45 037156 0.03304 Hirayama (M) 228 0.82418 0.16086 Inot,e 2.55 0.93609 039771 Koo 1S5 0.43532 0.07762 Lam 1.65 0.49972 0.03264 Lam & Cheng 2.01 0.69857 0.09863 Shimizu 1.08 0.07946 0.07042 Sobue 0.94 -0.06188 0.04857 omitted from the EPA analysis and will have a very heavy weight in the estimated risk ratio. Estimated risk ratios, weighted by the inverse of the variance, and shown for subgroups (as in the previous question), are shown in Table IV. When these three studies are included in the analysis, there is no significant effect between ETS and lung cancer overall or in any subgroup. The Asian studies yield a significantly different summary risk ratio than the U. S. studies (p = 0.0224). A9

Text Control

Highlight Text:

OCR Text Alignment:

Image Control

Image Rotation:

Image Size: