Factor V Leiden and Venous Thrombosis Case Study
Summaries and Questions & Answers

Investigators at Leiden University Hospital in the Netherlands were first to identify the factor V G1691A variant, which has since become known as factor V Leiden (FVL).  In several Swedish and Dutch populations, the prevalence of FVL was 2-7%, or about 10-fold higher than all previously identified genetic risk factors for thrombosis combined.  The prevalence of activated protein C resistance was 20%-60% in selected groups of patients with venous thrombosis, depending on selection criteria.

In 1994, Vandenbroucke et al. conducted a case-control study to examine whether FVL might be a causative factor in venous thrombosis occurring as an uncommon but serious complication of oral contraceptive (OC) use.  Cases were women aged 15-49 years who experienced a first episode of venous thrombosis during 1988-1993 and who did not have cancer.  They were enrolled 6-19 months after the acute event from clinics that monitor nearly all anticoagulation therapy in three well-defined geographic areas in the Netherlands.  Controls were women in the same age group who were friends or acquaintances of cases or partners of other clinic patients.   Current OC use was defined as use within 30 days before the thrombosis event (cases) or index date (controls).  Women who were postmenopausal or who had been pregnant within the prior 30 days were excluded.  The results are summarized in the following table.

Factor V genotype and current oral contraceptive (OC) use among women with venous thrombosis and controls*

 *Adapted from Vandenbroucke et al., 1994.
^HG=normal allele, A=factor V Leiden (FVL) allele. 

Question 1: What was the prevalence of the FVL genotype (at least one A allele) among controls?  Among cases?

Your answer:

Because there were no homozygotes among controls, the investigators combined data for the G/A and A/A genotypes.  They calculated the following relative risks of venous thrombosis (estimated as odds ratios):

• 7.9 (95% CI 3.2-19.4) for FVL
• 7.0 (95% CI 2.1-23.5) for FVL among OC nonusers
• 3.8 (95% CI 2.4-  6.0) for OC use. 

The investigators also reported the results of a stratified analysis to examine the effect of OC use according to FVL genotype.

 *Adapted from Vandenbroucke et al., 1994. 
 ^† “+” denotes G/A or A/A genotype; “-” denotes G/G. 

They concluded that the relative risk of thrombosis in OC users was similar regardless of FVL genotype and not different from the overall relative risk associated with OC use-that is, 5.0 » 3.7 » 3.8.

Question 2: Do you agree that the relative risk of venous thrombosis in OC users was similar regardless of factor V genotype?

Your answer:

The investigators reasoned that, because FVL did not appear to modify the effect of OC use on risk of venous thrombosis, a reasonable estimate of the joint effect was:  OR_FVL x OR_{OC use} » 7 x 4 » 30.  The odds ratio calculated from the data, comparing women who had FVL and used OCs with those who had neither risk factor, was 34.7 (95% CI 7.8 – 154). 

Another way to present these data is in a “two-by-four table.”[i]  This format lends itself to calculating measures of association for genetic and environmental exposures and the joint exposure, consistently using persons with neither exposure as the reference group. 

  *adapted from Botto and Khoury, 2001  
  ^† “+” denotes G/A or A/A genotype; “-” denotes G/G.

The two-by-four table is also convenient for assessing gene-environment interaction.  Two common statistical models of interaction are:

1.      additive, where ORge = ORg + ORe – 1, and

2.      multiplicative, where ORge = ORg x ORe

where g denotes genotype and e denotes the environmental factor.  Inequality in either statement may be interpreted as statistical evidence of interaction. 

Of course, biologic models of interaction can be more complicated, depending on the number of genetic loci involved, the dose of the environmental exposure, and the interplay of their effects at the molecular level.

Question 3: What evidence do these data provide for or against interaction between FVL and OC use in venous thrombosis?

Your answer:

The case-only study[ii] is a nontraditional study design that has been suggested for evaluating gene-environment interaction where only case data are available (e.g., from a case series or registry), or where sample sizes are too small for stratified analysis.  Under a multiplicative model of interaction where genotype and exposure are independent in the population,

OR _case-only   = OR_ge / ( OR_e x OR_g) = 1 

where OR _case-only  measures the association between the genotype and the exposure among cases.  A departure from unity indicates the presence of gene-environment interaction. 

We can analyze the case data from the study by Vandenbroucke et al. in the manner of a case-only study by constructing a two-by-two table:

   * “+” denotes G/A or A/A genotype; “-” denotes G/G.

Question 4: How does the result of this case-only analysis compare with results of the case-control analysis?

Your answer:

From their analysis, Vandenbroucke et al. concluded that “the combined effect of these risk factors seems close to a multiplication of the separate relative risks.  In terms of absolute effect, however, this means that the risk of venous thrombosis among women who use OCs is much greater when they carry the factor V Leiden mutation.”

The investigators estimated the incidence (absolute risk) of first venous thrombosis using data from the Leiden clinic, which had a geographic source population of 109,824 women aged 15-49 years (according to census data).  In all, 117 cases of venous thrombosis occurred in this geographic area during the 5 years of the study.  Thus, the estimated incidence of venous thrombosis among 15- to 49-year-old women was:

                        117 / (109,824  x 5) = 2.1 per 10,000 person-years 

The 155 cases from all three areas were assumed to have arisen from 

                            155 / 2.1 / 10,000 » 740,000 person-years 

Total person-years were apportioned to the four exposure groups according to the distribution of exposures among controls.  The results served as approximate denominators for calculating incidence.  For example, women without FVL who did not use OCs accounted for 59% of the control group and 

   0.59 x 740,000 = 437,870 person-years.

Question 5: What biases could be introduced by using this approach to estimate person-years at risk for calculating incidence ?

Your answer:

 *adapted from Vandenbroucke et al., 1994 
  ^†G=normal allele, A=FVL allele  

Question 6: What is the risk difference associated with OC use in women without FVL?  In women with FVL?

Your answer:

Clearly, a woman who uses OCs is at much higher risk for venous thrombosis if she has FVL, raising the question whether women should be screened for FVL before taking OCs.   The investigators addressed this issue in a second article. 

Vandenbroucke JP, van der Meer FJM, Helmerhorst FM, Rosendaal FR.  Factor V Leiden: should we screen OC users and pregnant women?  BMJ 1996;313:1127-1130.

The authors considered the “worst case” outcome, death from pulmonary embolism.  A U.S. study estimated that the case fatality rate for venous thrombosis was 2% in persons aged <40 years. 

Estimated population incidence of pulmonary embolism in women aged 15-49 years with FVL:  

• 5.7 x 0.02 / 10,000 py = 0.11 / 10,000 py in OC non-users

• 28.5 x 0.02 / 10,000 py = 0.57 / 10,000 py in OC users

Question 7: How many women with FVL would have to avoid OCs to prevent one death from pulmonary embolism?  How many women would have to be screened to find this many women with FVL?

Your answer:

The authors concluded that about 400,000 women would have to be screened-and 20,000 carriers of FVL would have to avoid OCs-to prevent one death from pulmonary embolism each year.

Question 8: What are other potential costs and benefits to consider when deciding whether to screen young women for FVL to prevent venous thrombosis?

Your answer:

The authors discussed several issues that introduce uncertainty in this kind of analysis:  imperfect estimates of  FVL prevalence and incidence of venous thrombosis, issues related to screening test performance, costs associated with alternative forms of contraception, and morbidity costs associated with venous thrombosis (including risks associated with anticoagulant therapy). 

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