Methods of Cohort Analysis: Appraisal by Application to Asbestos Mining

Liddell, F. D. K.; Jc, McDonald; Thomas, Duncan C.

doi:10.2307/2345280

Cited by 277 publications

(91 citation statements)

References 27 publications

(22 reference statements)

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“…Then and for the lth of combinations of d subjects within that set, and let (7) Then the score test can be expressed as For the special case of a design with D = 1 case and m controls in each matched set, so that n = m + 1, then s i = x i1 and (9) so that (10) This yields the score test (11) …”

Section: Multiply Matched Score Testmentioning

confidence: 99%

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Sample size evaluation for a multiply matched case–control study using the score test from a conditional logistic (discrete Cox PH) regression model

Lachin

2007

Statistics in Medicine

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SummaryThe conditional logistic regression model (Breslow NE. Covariance adjustment of relative-risk estimates in matched studies. Biometrics, 1982; 38:661-672) provides a convenient method for the assessment of qualitative or quantitative covariate effects on risk in a study with matched sets, each containing a possibly different numbers of cases and controls. The conditional logistic likelihood is identical to the stratified Cox proportional hazards model likelihood with an adjustment for ties (Regression models and life-tables (with discussion). J. Roy. Statist. Soc., B, 1972; 34:187-220). This likelihood also applies to a nested case control study with multiply matched cases and controls selected from those at risk at selected event times. Herein the distribution of the score test for the effect of a covariate in the model is used to derive simple equations to describe the power of the test to detect a coefficient θ (log odds ratio or log hazard ratio), or the number of cases (or matched sets) and controls required to provide a desired level of power. Additional expressions are derived for a quantitative covariate as a function of the difference in the assumed mean covariate values among cases and controls, and for a qualitative covariate in terms of the difference in the probabilities of exposure for cases and controls. Examples are presented for a nested case-control study and a multiply matched case-control study.

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Section: Multiply Matched Score Testmentioning

confidence: 99%

“…Liddell, McDonald, Thomas and Cunliffe [11] describe a matched case-control study embedded within a prospective cohort follow-up study. They conducted an analysis using the Miettinen methods.…”

Section: Introductionmentioning

confidence: 99%

Sample size evaluation for a multiply matched case–control study using the score test from a conditional logistic (discrete Cox PH) regression model

Lachin

2007

Statistics in Medicine

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“…In practice, however, such analyses have often proved difficult to interpret (7). In the present case the first variable to be entered would be the direct effect of duration of smoking, which reflects more on the inappropriateness of the choice of primary smoking index than on a true modifying effect of duration.…”

Section: Multivariate Methodsmentioning

confidence: 92%

“…The data used for the following illustration come from a historical cohort study of 10,939 males, comprising a l l who had ever worked for at least a month in the Quebec chrysotile asbestos mining and milling industry and who had been born 1891 through 1920 (7,10). Employers' payroll records were combined with estimates and measurements of past dust concentrations to produce year-by-year exposure estimates for each man.…”

Section: Example -The Quebec Asbestos Mortality Studymentioning

confidence: 99%

“…In all the analyses, the subjects for whom no smoking information was available were excluded (together with their matched referents if the subject was a case). Exposures of the cases were compared with those of their matched referents as evaluated at the same point in time (7), here the death of the case, and exposure-response models were fitted with the use of a matched technique of analysis which allows for multiple referents per case, continuous multiple exposure factors, and arbitrary risk models (16). Different indices of exposure were used in the different sections of the paper, the goid being to explore various ways of incorporating temporal effects.…”

Section: Example -The Quebec Asbestos Mortality Studymentioning

confidence: 99%

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Statistical methods for analyzing effects of temporal patterns of exposure on cancer risks.

Dc¹

1983

Scand J Work Environ Health

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Thiazolidinediones and Cardiovascular Outcomes in Older Patients With Diabetes

Lipscombe¹,

Gomes²,

Lévesque³

et al. 2007

JAMA

304

209

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ARDIOVASCULAR DISEASE IS AN important cause of morbidity and mortality among persons with type 2 diabetes mellitus. 1-3 The thiazolidinediones (TZDs), rosiglitazone and pioglitazone, are oral hypoglycemic agents that have been shown to improve glycemic control and may act to slow the progression of beta cell failure. 4 While improved glycemic control has been linked to better clinical outcomes in diabetes 5-7 and TZDs have been suggested as having potential cardiovascular benefits, 8-11 recent concerns have arisen regarding adverse cardiac effects of these drugs. Use of TZDs is associated with weight gain and edema, 12 and evidence suggests that both rosiglitazone and pioglitazone increase the risk of congestive heart failure (CHF). 8,10,13-19 A recent boxed warning for CHF was added for these agents recommending against the use of TZDs in persons with preexisting CHF. 20 Two meta-analyses have also suggested that rosiglitazone may be associated with an increased risk of acute myocardial infarction (AMI) and death. 18,21 These findings prompted a hearing by a US Food and Drug Administration advisory panel regarding the safety of rosiglitazone; however, the panel voted against removing rosiglitazone from the market because of insufficient data. 22 Most studies to date far have examined adverse cardiovascular outcomes associated with TZDs among clinical trial samples. However, the extent to which these adverse effects apply to real-world populations is less clear. In addition, older persons are traditionally underrepresented in clinical

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Methods of Cohort Analysis: Appraisal by Application to Asbestos Mining

Cited by 277 publications

References 27 publications

Sample size evaluation for a multiply matched case–control study using the score test from a conditional logistic (discrete Cox PH) regression model

Sample size evaluation for a multiply matched case–control study using the score test from a conditional logistic (discrete Cox PH) regression model

Statistical methods for analyzing effects of temporal patterns of exposure on cancer risks.

Thiazolidinediones and Cardiovascular Outcomes in Older Patients With Diabetes

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