The challenge of evaluating annual mammographyscreening for young women with a family history of breastcancer The FH01Management Committee, Steering Committee and Collaborators.
It has been recommended that women aged 40–49 years with a significant family history of breast cancer should be offered annual mammography screening An observa-tional study known as FH01 is evaluating this policy in a cohort of 6000 women at moderately increased risk of breast cancer due to family history. The main aims are to assess the likely impact on breast cancer mortality and cost-effectiveness.
Centre for Epidemiology,Mathematics and Statistics, Measuring these outcomes is challenging in an environment where a randomized trial is not feasible and there is no natural comparison group. In this paper, we present some approaches to estimating effectiveness and the planned analyses. These involve comparison of disease stage and likely consequent breast cancer mortality in the cohort offered screening with that estimated in the absence of screening. The estimation uses observed outcomes in external populations and estimated outcomes forthe hypothetical situation where screening had not taken place.
Management strategies for this last group include surveil-lance that is more intensive and earlier in life than provided Ithasrecentlybeenestimatedfromrandomizedtrialsthat bytheUKNationalBreastScreeningProgramme,possibly invitation to mammography screening in women aged by magnetic resonance imaging (MRI) in certain risk 50–69 years reduces breast cancer mortality by 22% over groups,4 but more likely by mammography.
a period of 12–20 years.1 Evidence such as this led to the Mammographic screening in these younger, moderate- initiation of breast cancer screening programmes in many risk women is an attractive approach, but there is limited European countries and recommendations of regular mam- evidence on whether it would reduce breast cancer mography screening in this age group from worldwide mortality in practice. It does appear that faster growing, health organizations.2 The benefits for women aged 40–49 more aggressive breast tumours tend to be found in women years have not been so well defined and access to breast with a family history diagnosed with breast cancer in their cancer screening in this age group is limited. For example, 40s, and for screening to be effective in this group, it would the UK’s policy of three-yearly invitation to mammography screening covers women aged 50–70 years.
A study was launched in the UK in 2003 to recruit a Public awareness of breast cancer and the discovery of cohort of 10,000 women, later revised to 6000 when certain high-penetrance genes has led to an increase in the number requests for subgroup analyses were withdrawn, aged 40–44 of women seeking advice from their general practitioners years with a moderate family history of breast cancer. This due to a family history of breast cancer. While the number was based on a previous proposal involving a study of of high-risk families with predisposing genes such as BRCA1and BRCA2 or other genetic factors3 is small, there are a 20,000 women.6 This observational study (known as FH01) number of women aged 40–49 years who, although unlikely is recruiting women referred to breast services and clinical to inherit such genes, are at elevated risk due to family genetics departments, who have been recommended to have annual mammography. Women will be observed for a Women referred to breast services or clinical genetics minimum of five years. The main aims of FH01 are to departments can be classified into three groups. Firstly, measure the impact of such an intervention on likely future women whose family history is not sufficiently strong to breast cancer mortality and to evaluate cost-effectiveness.
indicate a substantial elevation of risk of breast cancer Thus, the FH01 study addresses the recent recommendation beyond that of the general population need reassurance but by the UK’s National Institute of Clinical Excellence (NICE) no further intervention. Secondly, women with family history so strong as to lead to a serious suspicion of a ‘All women aged 40–49 years satisfying referral criteria to BRCA1 or BRCA2 mutation may need counselling on the secondary or specialist care should be offered annual subject of genetic testing and possible prophylactic inter- ventions in the event of a positive test. Finally, there is an While it is of key importance to evaluate the impact of intermediate group whose family history is associated with a such a policy, a randomized trial is not feasible for this group substantially increased risk of breast cancer, but is not strong of women both on ethical (lack of equipoise on the basis of a enough to indicate a high probability of a BRCA mutation.
survey of clinicians involved, study length) and practical The FH01 Management Committee, Steering Committee and Collaborators grounds (recruitment problems).6 The FH01 study offers an follow-up after entry. The 106,000 women in the Age Trial opportunity to measure the impact of invitation to annual Cohort are from the general population and do not mammography screening in young women with a moderate necessarily have a family history of breast cancer, but their family history. However, there is no natural comparison age and follow-up period overlap with that of the planned group and so alternatives must be found. Here we describe FH01 cohort. There were 755 interim cancers in this group.7 the comparison groups and strategies available to us and From the estimates of disease progression and screening outline the planned analyses to estimate the predicted effect sensitivity in the Swedish Two-County study, we expect of this policy on breast cancer mortality.
18% of tumours in the FH01 cohort to be node positive. Inthe UK Age Trial, 41% were node positive. We anticipate120 cases in total in FH01. On this basis, a comparison on incidence of node-positive disease between the two cohortswould have power in excess of 95%. We expect a reduction The aim of FH01 is to recruit 6000 women aged 40–44 years, of 53% in incidence of node-positive disease, which would and to offer these women annual mammography over five imply a 32% reduction in mortality, for survival rates by years. Recruitment is scheduled to end in December 2006.
node-positive status in the Two-County trial.8 It is planned At August 2006, there were 5486 recruits. Thus, they will to analyse the data in 2010, by which time the 120 expected still be aged under 50 years at the conclusion of the study, cases will have been amassed to the FH01 cohort.
and any observed benefit of screening will be due to The ‘historical cohort’ refers to 800 breast cancer cases screening activity before age 50. The tumours diagnosed clinically diagnosed in the 1980s in French women aged over the five-year period and their pathological character- 40–49 years with a family history of breast cancer with no istics will provide the major information resource for prior regular mammography. The pathology data on these evaluation. Note that women are eligible whether or not they have undergone previous mammographic surveillance.
To be eligible for the study, they must satisfy the following STATISTICAL ANALYSES AND ESTIMATION OF THE  one first-degree female: breast cancer at age 40 years or When it is not possible to obtain a direct estimate of the quantity of interest using the ideal design (in this case a  one first-degree female: bilateral breast cancer first randomized controlled trial), a good strategy is to derive cancer diagnosed at age 50 years or under; more than one indirect estimate. Accordingly, several  two first- or one first- and one second-degree female: methods of estimating the likely effect on long-term breast both with breast cancer at age 60 years or under (same cancer mortality will be used. If results of the various methods agree, we can be fairly confident of their validity. If  one first- or second-degree female: breast and ovarian there is disagreement among the methods, further model cancer, first cancer diagnosed at age 60 years or under; and method diagnostics will be indicated. All breast cancers  three first- or second-degree female: breast or ovarian diagnosed in the FH01 study period will be followed up for breast cancer death, but since this population will be subject  one first-degree male: breast cancer at any age; to intensive early detection, there will be insufficient  paternal history of a minimum of two second-degree numbers of breast cancer deaths for a precise estimate of relatives (i.e., father’s first-degree relatives) with breast the effect of the screening, even after 10 years. The cancer at or less than age 50 years, or one with breast fundamental question, therefore, is how to estimate the cancer at or less than age 50 years and an ovarian cancer likely effect on future mortality from observations on the (any age), or paternal uncle/grandfather with breast tumours diagnosed during the five years of the study.
These criteria were developed before the NICE guidelines Tumour incidence by size, nodal status and were available. NICE guidelines drew on these but varied from them slightly in their definition of moderate risk. For Table 1 shows the relative risks of node-positive breast high risk (conferring a 20% or more probability of a high- cancer in the randomized trials of mammographic screening risk gene mutation in the family), stronger criteria would be (study versus control group) and the subsequently observed applied. For example, NICE specify at least two relatives, relative risks of breast cancer mortality. It is clear that the one of whom must be first degree, with breast cancer at reduction in advanced stage disease is a powerful predictor average age 50 or earlier as one of the high-risk criteria.
of the reduction in breast cancer mortality at an ecological The major objective of the analysis will be to estimate the level. That this also holds at an individual level is shown in likelihood of death from breast cancer, on the basis of the features of the tumours diagnosed in the FH01 cohort, and It is clear, therefore, that a simple analysis which is in compare this to that which would be expected if the principle predictive of the likely benefit of the surveillance mammographic surveillance had not taken place.
will be the comparison of the incidence of node-positive In the following, ‘FH01 cohort’ refers to the women tumours in the FH01 cohort with that expected in the recruited to the FH01 study with a moderate family history absence of the mammographic surveillance.
of breast cancer. There are two comparison groups availableto us, known as the ‘age trial cohort’ and the ‘historicalcohort’.
The ‘age trial cohort’ refers to the control group of the UK Breast Screening Age Trial. These women, aged 40–41 years We therefore propose in the first instance to compare the at entry into the Age Trial,7 were randomly assigned to the proportion of node-positive tumours in the FH01 with those ‘no invitation to mammography’ arm and have seven years observed in the Age Trial Cohort and the French Historical Table1 Relative risks of breast cancer death and relative risks of node-positive tumours, study versus control groups in the randomized trials of screening for breast cancer Figure 1 Disease model of progression from preclinical to clinical Cohort. Both of these have full pathology data available. We disease and from node-negative to node-positive disease.
shall repeat the comparison for the proportion of invasivetumours larger than 2 cm in maximum diameter, andinvestigate the association of histological grade with any Table 2 Estimated progressive probabilities within one year While a simple comparison of the proportions of advanced tumours is informative and easy to understand, it is prone tolength bias or overdiagnosis. For example, the proportion of node-positive tumours in the FH01 cohort might be artificially reduced by overdiagnosis of node-negativetumours by screening. A second series of analyses will therefore estimate the effect of the mammographic surveil-lance on the absolute incidence of advanced tumours,whether defined by size, node status or a combination ofpathological factors.
interval cancers would have been observed in the tumour We propose several analytical strategies to estimate the population as a whole in the absence of screening (although effect of the surveillance on absolute incidence of advanced this comparison may be subject to length bias if the interval cancers contain more innately aggressive, high-gradetumours than screen-detected). Of the 71 interval cancers,32 (45%) were node positive. Applying this to the total tumour population we estimate that 78 (172 Â 0.45)tumours would have been node positive in the absence of The rates of screen-detected and interval cancers by, for screening, very similar to the estimate derived from the example, node status provide an opportunity to estimate rates of progression from preclinical (i.e., asymptomatic) but In FH01, we shall similarly estimate the effect on node- screen-detectable disease to overt clinical disease, and from positive tumours using both methods.
node-negative to node-positive disease. The process may besummarized as in Figure 1. All women begin with nodetectable disease, some may progress to preclinical node- negative disease with rate l0 and some of these may in turn Suppose we observe 0.8 node-positive tumours per 1000 progress to node-positive (rate l1) or clinical disease (l2).
person-years in the FH01 cohort and 0.6 per 1000 in the Age When a cancer is diagnosed, it is treated and its natural Trial controls. This would give the impression that the progress is not observable thereafter. When the progression screening was actually increasing the rate of advanced rates li have been estimated, they can be used to estimate the cumulative rates of node-positive disease expected inthe absence of screening.
Chen et al.13 present an example of this in the evaluation of the breast screening programme in women aged 40–49 This, however, ignores the fact that the FH01 cohort has a years in Uppsala, Sweden. In Uppsala, screening was offered much higher incidence of breast cancer than the Age Trial to women in this age group every 20 months.
Control Group, as a result of the study family history in the Chen et al. fitted the model shown in Figure 1 to this and FH01 cohort. One way to adjust for this is to divide RRA obtained estimates of the transition rates l above by RRI, the relative risk of breast cancer overall for logical details, see Chen et al.14 These transition rates FH01 compared to Age Trial controls. If, for example, the translated into annual probabilities of progression, as in total incidence of breast cancer in FH01 was four per 1000 Table 2. These progression probabilities can be used to and the total incidence in the Age Trial controls was 1.3 per calculate the predicted numbers of node-positive and node- 1000, we would have a corrected relative risk of node- negative cases in the absence of screening. This would predict 79 node-positive cancers in the Uppsala study population in the absence of screening, compared with the 45 observed. Thus the screening is estimated to havebrought about a 43% reduction in incidence of node- This is a reasonable strategy but may be prone to length bias or its more extreme manifestation, overdiagnosis, in the A simpler approach would be to assume that the FH01 cohort. It amounts to comparing the proportion of proportion of node-positive tumours prevailing in the node-positive cancers in the two cohorts. An alternative is to The FH01 Management Committee, Steering Committee and Collaborators Table 3 Observed cases in the Uppsala screened population and expected cases by lymph node status, with corresponding10-year death rates estimated from the Swedish Two-County Swedish Two-County Study,8 we predict 31 deaths in the Figure 2 Strategy for adjusting comparison of FH01 cohort withAge Trial Cohort for predicted breast cancer risk Uppsala screened population over 10 years. Applying thesame death rates to the expected cases in the absence ofscreening gives a predicted 41 deaths over 10 years. This use the risk factor status of the individuals in the two therefore suggests a 24% mortality reduction as a result of cohorts to predict the overall incidence in each independent the screening in Uppsala in women aged 40–49 years.
of screening. This would give an estimate of RRI which was In our analysis, we will use multivariate prediction of not affected by length bias or overdiagnosis. We have mortality using size, node status and histological grade.8 The developed a method and computer programme for predict- ing individual risk of breast cancer from family history and We shall also estimate the benefit, if any, by external other risk factor data.15 The programme has been validated comparison with the Age Trial Cohort and the Histological Cohort. As with the comparison of incidence of node- The problem with this strategy is that the Age Trial positive tumours, we shall adjust for the different under- Control Group have not previously been contacted and are lying incidences in the two groups using both observed and having no intervention offered them. It might therefore be unethical to raise anxieties about breast cancer by approach-ing them with a view to obtaining the same family history and risk factor data as we have for the FH01 cohort. Instead,we propose to contact a subset of the Age Trial Study Group, Rates of attendance, recall and surgical biopsy who are already being offered annual mammography, and These will be reported and compared with those observed in to ascertain risk factor status in this subgroup. Because of the study groups of the randomized trials and with other the randomization, the risk factor status in the Age Trial service screening programmes.10 Confidence intervals on Study Group will be the same on average as the control these rates will be estimated using the Poisson distribution group. We can therefore impute the risk factor status and approximation, and differences from those expected will be the predicted breast cancer risk in the Age Trial controls. The strategy is illustrated in Figure 2.
However, allowances must be made for the major We will perform both the simple (observed incidence) and distinguishing feature of the FH01 cohort, that it is a the complex (predicted incidence from risk status) proce- volunteer population with an underlying risk higher than dure for comparing the two cohorts. Also, by way of the general population risk due to family history. As sensitivity analysis, we shall repeat the analysis using other described above, this will be done in two ways: (i) using risk prediction algorithms for the adjustment.16 the empirically observed incidence in the FH01 cohort, and(ii) from the strength of the family histories and with other risk factors using the Tyrer–Cuzick and other methods.
As with the comparison of node status, we shall performboth internal estimation of the benefit of the mammo- graphic surveillance and external comparison of predictedmortality in our cohort with the comparison groups.
These will be reported overall and stratified by tumour size, Tumour size, lymph node status and histological grade lymph node status, histological grade and histological type.
have been shown to reliably predict both individual survival As above, cancer detection rates will be compared with and aggregate mortality reductions conferred by screen- those reported in the randomized trials and appropriate ing.10,11 The distribution of these factors, as estimated above adjustments made for underlying differences in incidence.
in ‘Tumour incidence by size, nodal status and histologicalgrade’, will be used to estimate subsequent breast cancer mortality both in the screened FH01 cohort and in the FH01cohort had screening not taken place. These estimates will These will be reported firstly without transformation or then be compared to predict the change in breast cancer rescaling. Thereafter, proportional interval cancer rates will mortality as a result of the surveillance.
be calculated in the FH01 cohort. Proportional interval Table 3 shows the Uppsala breast cancer cases by node cancer rates are the incidence of interval cancer occurring status, and the expected cases in the absence of screening.
after a negative screen, divided by the expected incidence in Applying 10-year death rates to these as observed in the the absence of screening in a group of the same age and risk profile. The faster this ratio approaches unity, the shorter the  quality indicators such as MST, sensitivity, PS, average screening interval needs to be. Incidence in the absence of lead-time and potential overdiagnosis.
screening will be calculated in the two ways described above(i.e. from that observed in the FH01 cohort and that In the above, we had the necessity to summarize and simplify the proposed analyses to some extent. In addition tothe activities described above, there will be separate analysesincluding and excluding DCIS, use of more than one prognostic index to predict future mortality and a variety Programme sensitivity (PS) is the proportion of cancers in of sensitivity analyses investigating departures from the those participating in the screening which are actually detected by screening (as opposed to arising clinically The results of FH01 are expected to inform policy on the between screens). This can be calculated empirically using management of this particular risk group. If a substantial the number of screen-detected and interval cancers observed, benefit is observed, there will be a recommendation to have and using the methods of Launoy et al.17 based on two this annual mammography regime as a national policy for important indicators of potential effectiveness of a screening this group. If negative or only weakly positive results are programme: mean sojourn time (MST) and test sensitivity obtained, it will be necessary to consider other manage- (S). Mean sojourn time is the duration of the preclinical ments strategies, including surveillance by other imaging screen-detectable period (i.e. the window of opportunity for screening to advance the diagnosis). The test sensitivity is the The methods will make use of previously validated probability that a cancer which is in the preclinical detectable predictive modelling on internal and external comparison period will test positive by the screening test. MST and S can groups, together with future observations of the FH01 be estimated using Markov models.14 The average lead time cohort and appropriately chosen comparative cohorts.
achieved is also calculable, since it is the product of the MST While no method is ideal, a variety of methods based and the PS. These methods have been used in the past as part around these key concepts will give a number of estimates, of the evaluation of screening in women at increased familial which can be compared and carefully interpreted. We feel that this clearly planned analysis meets the challenge ofevaluating the policy of invitation to annual mammographyscreening for young women with a family history of breast In screening for breast cancer, it is theoretically possible todiagnose cancers which would never have become clinicallyapparent had screening not taken place (for example, some cases of low-grade ductal carcinoma in situ (DCIS) may fall We thank the women taking part in FH01 and all the staff at into this category). We shall therefore estimate the propor- the participating centres. We thank Jayne Mead for tion of potentially overdiagnosed cases using two ap- proaches based on estimation of incidence. Firstly we willcompare the empirical incidence of breast cancer in the FH01 Management Committee, Steering Committee FH01 cohort with that expected from the family histories using the previously described predictive models.15,16 Drafting subgroup for this paper: Rhian Gabe, Stephen W.
Secondly, we shall use the finding that if there is over- diagnosis or length bias, it tends to occur at the first FH01 Management Committee: Elaine Anderson, Stephen screen.9,14 We propose to compare the observed prevalence Duffy, Ian Ellis, Gareth Evans, Hilary Fielder, Jonathon at first screen with that expected (E) from the MST, S and Gray, Gerald Gui, James Mackay (chair), Douglas Macmil- incidence (I) of breast cancer in the FH01 cohort. The lan, Sue Moss, Richard Sainsbury, Mark Sibbering, Sue expected prevalence, E ¼ S Â MST Â I. Again, we shall derive two estimates of I, one empirical and one theoretical from FH01 Steering Committee: Caroline Boggis, John Burn, Paul family histories. In addition, we shall monitor detection Dillon, Bob Haward, Anthony Howell, Robert Mansel rates of DCIS and invasive cases separately. Finally, we shall (chair), Hazel Marshall Cork, John Robertson, Julietta explicitly estimate the incidence of overdiagnosed cases Patnick, Paul Pharoah, Anne Robinson, Stephen Sutton.
Collaborators: Amir Al-Dabbagh, Elaine Anderson, Riccar- do Audisio, Roger Brookstein, David Brown, Robert Carpenter, Donna Christensen, St John Collier, Julie Cooke,Timothy G Cooke, Richard Cummins, Diana Dalgliesh, In this paper, we have presented methods to assess the Fiona Douglas, Steve Ebbs, Sian Evans, Cathy Farnon, impact of annual invitation to mammography screening for Ferguson J, Nick Gallegos, David George W, Fiona Gilbert, women aged 40–49 years with moderate-high risk due to Gerald Gui, Hansell D, Christopher Hinton, Shirley Hodg- family history. In particular, outcomes of importance son, Tony Howell, Catheryn Hubbard, Sabah Jmor, Alison Lannigan, Claudio Harding Mackean, Douglas Macmillan,Lee Martin, Duncan Matheson, Mary Milne, Dierdre  breast cancer mortality reductions due to the interven- Pallister, Joan Paterson, Oduru Ravisekar, Nicola Roche, tion, differences in tumour features such as size, stage, Linda Rockall, Colin Rogers, Neil Rothnie, Zahida Saad, Richard Sainsbury, Mike Shere, Mark Sibbering, Smith D,  basic features of a screening programme such as rates of Stallard S, Kerstin Stepp-Schuh, Stewart R, William Teh, attendance, recall and biopsy, cancer detection rates, Alastair Thompson, Thompson WO, Philip Turton, Luna interval cancers and investigation of tumour features in Vishwanath, Alison Waghorn, Matthew Wallis, Cilla Wester, The FH01 Management Committee, Steering Committee and Collaborators 10 Organizing Committee and Collaborators FM. Breast-cancer screening with mammography in women aged 40–49 years. Swedish Cancer Society Rhian Gabe, Researcher, Cancer Research UK Centre for Epidemiol- and the Swedish National Board of Health and Welfare. ogy, Mathematics and Statistics, Wolfson Institute of Preventive Medicine, Charterhouse Square, London EC1M 6BQ, UK 11 Balslev I, Axelsson CK, Zedeler K, et al. The nottin Gham Prognostic Index applied to 9,149 patients from the studies of the Danish Breast CancerCooperative Group (DBCG). 12 Chen HH, Duffy SW, Tabar L, et al. Markov chain models for progression of breast cancer. Part 2: prediction of outcomes for different screeningregimes. J Epidemiol Commun Health 1997;2:25–35 13 Chen HH, Thurfjell E, Duffy SW, et al. Evaluation by Markov chain models of a non-randomised breast cancer screening programme in women 2 Duffy SW, Tabar L, Smith RA, et al. Risk of breast cancer and risks with breast cancer: the relationship of histologic type with epidemiology, disease progression and survival. Semin Breast Dis 2;1999:292–300 14 Chen HH, Duffy SW, Tabar L, et al. Markov chain models for progression of 3 Thull DL, Vogel VG. Recognition and management of hereditary breast breast cancer. Part 1: tumour attributes and the preclinical screen- detectable phase. J Epidemiol Commun Health 1997;2:9–23 4 MARIBS Study Group. Screening with magnetic resonance imaging and 15 Tyrer J, Duffy SW, Cuzick J. A breast cancer prediction model incorporat- mammography of a UK population at high familial risk of breast cancer: 16 Amir E, Evans DG, Shenton A, et al. Evaluation of breast cancer risk assessment packages in the family history evaluation and screening 5 IARC. Breast Cancer Screening. Lyon: IARC Press, 2002 6 Mackay J, Rogers C, Fielder H, et al. Development of a protocol for 17 Launoy G, Duffy SW, Prevost TC, et al. Detection of cancer, sensitivity of the evaluation of mammographic surveillance services in women under 50 with test and sensitivity of the screening program. 18 Myles J, Duffy S, Nixon R, et al. Initial results of a study into the effectiveness 7 Moss S, Waller M, Anderson TJ, et al. Randomised controlled trial of of breast cancer screening in a population identified to be at high risk. mammographic screening in women from age 40: predicted mortality 19 Duffy SW, Agbaje O, Tabar L, et al. Estimates of overdiagnosis from two 8 Tabar L, Fagerberg G, Duffy SW, et al. Update of the Swedish two-county trials of mammographic screening for breast cancer. Breast Cancer Res program of mammographic screening for breast cancer. 20 Cuzick J. Aromatase inhibitors in prevention – data from the ATAC 9 Duffy SW, Day NE, Tabar L, et al. Markov models of breast tumor (arimidex, tamoxifen alone or in combination) trial and the design of IBIS-II (the second International Breast Cancer Intervention Study).


Balancing Point Center for Wellness WOMEN’S FERTILITY QUESTIONNAIRE Name: ___________________________________________ Date: _______________________ 1.Basic Information a. Address: ____________________________________________________________________________________________ 2. Menstrual History 3. Gynecologic History a. At what age did you begin your menses? ________a. D

Annex i

Mimpara® (cinacalcet) SUMMARY OF PRODUCT CHARACTERISTICS NAME OF THE MEDICINAL PRODUCT Mimpara® 30 mg film-coated tablets. Mimpara® 60 mg film-coated tablets. Mimpara® 90 mg film-coated tablets. 2. QUALITATIVE AND QUANTITATIVE COMPOSITION Each tablet contains 30 mg cinacalcet (as hydrochloride). Each tablet contains 60 mg cinacalcet (as hydrochloride). Each t

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