This study examined the quality of life (QOL), measured by the Functional Assessment of Cancer Therapy (FACT) questionnaire, among urban (n = 277) and non-urban (n = 323) breast cancer survivors and women from the general population (n = 1140) in Queensland, Australia.Population-based samples of breast cancer survivors aged < 75 years who were 12 months post-diagnosis and similarly-aged women from the general population were recruited between 2002 and 2007.P < 0.01). Irrespective of residence, breast cancer survivors, on average, reported comparable scores on most QOL scales as their general population peers, although physical well-being was significantly lower among non-urban survivors . Overall, around 20%-33% of survivors experienced lower QOL than peers without the disease. The odds of reporting QOL below normative levels were increased more than two-fold for those who experienced complications following surgery, reported upper-body problems, had higher perceived stress levels and/or a poor perception of handling stress .Age-adjusted QOL among urban and non-urban breast cancer survivors was similar, although QOL related to breast cancer concerns was the weakest domain and was lower among non-urban survivors than their urban counterparts (36.8 versus 40.4, Results can be used to identify subgroups of women at risk of low QOL and to inform components of tailored recovery interventions to optimize QOL for these women following cancer treatment. Breast cancer is a major public health concern, with one in eight women developing the disease before the age of 85 years in developed countries of the world ,2. DespiQOL has been associated with adherence to treatment  and progIn Australia, geographic residence influences stage at diagnosis and type of surgery, with those living in rural areas more likely to have a mastectomy than their urban counterparts  . GeograpResearch that compares QOL between urban and non-urban cancer survivors is lacking, and from those studies that exist, results are inconsistent. Two studies suggest that rural breast cancer survivors fare worse ,18, whilThe Pulling Through Study (PTS) was a longitudinal, population-based study among breast cancer survivors living within 100 kilometers  of the capital city of Brisbane in Queensland, Australia, and diagnosed in 2002 . This stEligible women, diagnosed with unilateral breast cancer at age 74 years or younger, were randomly selected through the Queensland Cancer Registry (target sample). All cancer diagnoses in Queensland are required to be reported to the Registry and therefore these records provide an accurate sampling frame for recruitment. Since breast cancer is mostly a disease of women 50 yrs or older and to ensure adequate numbers were available for specific age group analyses, younger women were over-sampled in the urban arm of the study, while 100% of eligible non-urban women were recruited for all age groups. Following appropriate ethical approval and the requirements of the cancer registry, doctor consent to contact eligible women (provided for 82% of the urban sample and 90% of the non-urban sample) and participant consent was sought. Overall, 277 urban and 323 non-urban women returned completed quuestionnaires at 12 months post-diagnosis .Following ethical approval, the general Queensland population sample was derived from the Queensland Cancer Risk Study (QCRS), a population-based survey conducted in 2004 among English-speaking residents of Queensland, aged 20-75 years, randomly sampled within strata defined by gender, age and geographic region . Further details about the study methods are described elsewhere . BrieflyQOL was measured among women with breast cancer at 12 months post-diagnosis using the Functional Assessment of Cancer Therapy (FACT-G) questionnaire, which is comprised of 27 items rated on a five-point Likert scale  and includes four subscales . Higher scores represent better well-being. Women in the QCRS received the general population FACT instrument (FACT-GP), which is identical to the FACT-G except it excludes six illness-related items inappropriate for the general population ,26. OverDemographic  using SPSS . Analysis of variance tests compared age-adjusted mean QOL scores at 12 months post-diagnosis between urban and non-urban breast cancer survivors. Comparisons between breast cancer survivors and women from the general population involved general linear regression models to obtain QOL scores adjusted for characteristics that differed between the groups .P < 0.05 level (two-tailed) was accepted as statistically significant. Differences of eight or more points in mean FACT-B+4 scores, five or more points in mean FACT-G scores, three or more points on the breast cancer concerns subscale and two or more points for all other subscales between urban and non-urban breast cancer survivors or between women with breast cancer and their general population peers were considered clinically important, as recommended by developers of the FACT [Descriptive results presented in this study have been adjusted for the sampling fraction used to identify younger breast cancer patients from urban areas . The general population comparison group was also weighted by age, based on Australian Bureau of Statistics data, so that results reflect the actual female Queensland resident population  . The conthe FACT . For corAs suggested by Fayers , a new oDemographic and disease characteristics were similar for the women with breast cancer in this study and those in the target sample. The majority of women (75-80%) were diagnosed with infiltrating ductal carcinoma, approximately 60% received complete local excision of their tumour and more than 50% had 10 or more lymph nodes removed. However, participants among urban breast cancer survivors had somewhat smaller tumor size (median tumour size was 14 mm) when compared with the target sample -22. For P < 0.05) difference in body mass index between urban breast cancer survivors and their general population peers, this was attenuated when missing values were omitted from analyses.A comparison of women with or without breast cancer showed significant differences for several demographic and general health characteristics Table . Breast P < 0.01). In contrast, well-being related to breast cancer concerns was lower among non-urban compared to urban survivors by statistical (P < 0.01) and clinical criteria . Scores for emotional, functional and overall (FACT-G) QOL were clinically comparable to their counterparts from the general population despite a statistically significant difference for emotional and functional well-being (P < 0.01).Table lower QOL 12 months following diagnosis than age- (within five years) and residence-matched women without the disease. A further 17.5%-48.5% of women reported similar QOL, while the remainder (19.8%-65.3%) reported clinically better QOL  of reporting reduced QOL, while upper-body function below the median, moderate or higher stress levels and poor perceived handling of stress were each associated with at least four-fold increased odds of reporting reduced QOL .Following adjustment for potential confounding factors, a range of characteristics were associated with breast cancer survivors reporting overall (FACT-G) QOL below normative levels Table , but plaUrban and non-urban breast cancer survivors reported similar levels of QOL 12 months following diagnosis, overall and for subscales. The sole exception was the breast cancer concerns subscale, which showed that non-urban residents fared worse than their urban counterparts. When comparing breast cancer survivors to age- and residence-matched peers, the only detriment to QOL was among non-urban breast cancer survivors who reported statistically and clinically poorer physical well-being. Overall, up to one in three breast cancer survivors reported QOL below the age- and residency-matched general female population. The major independent correlates of reporting overall QOL below that of age-matched women without breast cancer were complications following surgery, poorer upper-body function, higher perceived stress levels, and poor perception of handling stress.Despite the known differences by geographic residence with regards to access to services, availability of treatment and survival outcomes, our results indicate only minor disparities in QOL between urban and non-urban breast cancer survivors 12 months post-diagnosis. The subscale measuring breast cancer-specific concerns yielded the lowest values (based on percent of maximum score) reported by all survivors, but in particular for women living in non-urban areas. Items within this subscale deal with treatment-related symptoms, such as swelling of the arms, pain, shortness of breath, body image and sexuality. These results support existing research which demonstrates that while QOL among breast cancer survivors improves considerably during the first year following completion of treatment, breast cancer treatment-related concerns  may persist -39.It is plausible that non-urban survivors suffer in terms of their breast cancer-specific QOL, more so than urban survivors, as a consequence of inequalities in accessing specialised services. However, study-specific data collection procedures may also have contributed. QOL scores were derived from the third questionnaire for participants in the longitudinal urban breast cancer study, whereas the first (and only) questionnaire was the source of QOL data for non-urban breast cancer participants. Therefore urban survivors may have responded differently to QOL questions over time, not only because their QOL changed, but also because they may have become used to answering questions about QOL and might have over time changed their perception of QOL. This response shift may, in part, explain what appears to be a more positive breast cancer-specific QOL among urban survivors than non-urban survivors. However, the difference in QOL was observed on most but not all subscales, suggesting that response shift played a minor role in our findings.On average, QOL was similar for breast cancer survivors and general population peers, for both urban and non-urban residents, similar to results reported by other authors studying QOL among breast cancer survivors 12 months ,41 or loDespite overall QOL similarities between survivors and their general population peers, up to one-third  of survivors continued to experience lower QOL 12 months following diagnosis of breast cancer. To our knowledge, despite Fayers suggesting advanced analytical procedures using normative scores in 2000 , this isSeveral key design features of this work highlight the strength and importance of the findings. Results were obtained from population-based urban and non-urban breast cancer samples, representative of their respective target populations -22, and Overall, the QOL of breast cancer survivors living in rural and urban areas was similar except for breast cancer related concerns being more dominant in women from rural locations. Among all women about 20%-33% have lower QOL one year past diagnosis compared to age matched women from the general population without breast cancer and thus could benefit from additional support and interventions.ARIA+: Accessibility/Remoteness Index of Australia; CI: Confidence Interval; EORTC: European Organisation for the Research and Treatment of Cancer; FACT: Functional Assessment of Cancer Therapy; FACT-G: Functional Assessment of Cancer Therapy-General; FACT-GP: Functional Assessment of Cancer Therapy-General Population; FACTB+4: Functional Assessment of Cancer Therapy-Breast additional four questions; OR: Odds Ratio; PTS: Pulling Through Study; QOL: Quality of Life; QCRS: Queensland Cancer Risk Study.The authors declare that they have no competing interests.TD carried out data collection and analysis. SH, BN, and MJ supervised TD and contributed to data interpretation and manuscript writing. JA supervised data collection at the Cancer Registry and provided critical input in data collection, analysis and manuscript. All authors read and approved the final manuscript.


Sirvs never’ or ‘current vs never’ could account for such possible time-dependent or genetic associations is unclear. The possibility of an association between cigarette smoking and breast cancer risk among certain groups of women should not be ruled out based solely on the Collaborative Group's analyses.The conclusion of the Collaborative Group on Hormonal Factors in Breast Cancer  that cig


The reasons for elevated breast cancer rates in the upper Cape Cod area of Massachusetts remain unknown despite several epidemiological studies that investigated possible environmental risk factors. Data from two of these population-based case-control studies provide geocoded residential histories and information on confounders, creating an invaluable dataset for spatial-temporal analysis of participants' residency over five decades.The combination of statistical modeling and mapping is a powerful tool for visualizing disease risk in a spatial-temporal analysis. Advances in geographic information systems (GIS) enable spatial analytic techniques in public health studies previously not feasible. Generalized additive models (GAMs) are an effective approach for modeling spatial and temporal distributions of data, combining a number of desirable features including smoothing of geographical location, residency duration, or calendar years; the ability to estimate odds ratios (ORs) while adjusting for confounders; selection of optimum degree of smoothing (span size); hypothesis testing; and use of standard software.We conducted a spatial-temporal analysis of breast cancer case-control data using GAMs and GIS to determine the association between participants' residential history during 1947–1993 and the risk of breast cancer diagnosis during 1983–1993. We considered geographic location alone in a two-dimensional space-only analysis. Calendar year, represented by the earliest year a participant lived in the study area, and residency duration in the study area were modeled individually in one-dimensional time-only analyses, and together in a two-dimensional time-only analysis. We also analyzed space and time together by applying a two-dimensional GAM for location to datasets of overlapping calendar years. The resulting series of maps created a movie which allowed us to visualize changes in magnitude, geographic size, and location of elevated breast cancer risk for the 40 years of residential history that was smoothed over space and time.The space-only analysis showed statistically significant increased areas of breast cancer risk in the northern part of upper Cape Cod and decreased areas of breast cancer risk in the southern part . There was also a significant association between breast cancer risk and calendar year , with earlier calendar years resulting in higher risk. The results of the one-dimensional analysis of residency duration and the two-dimensional analysis of calendar year and duration showed that the risk of breast cancer increased with increasing residency duration, but results were not statistically significant. When we considered space and time together, the maps showed a large area of statistically significant elevated risk for breast cancer near the Massachusetts Military Reservation . This increased risk began with residences in the late 1940s and remained consistent in size and location through the late 1950s.Spatial-temporal analysis of the breast cancer data may help identify new exposure hypotheses that warrant future epidemiologic investigations with detailed exposure models. Our methods allow us to visualize breast cancer risk, adjust for known confounders including age at diagnosis or index year, family history of breast cancer, parity and age at first live- or stillbirth, and test for the statistical significance of location and time. Despite the advantages of GAMs, analyses are for exploratory purposes and there are still methodological issues that warrant further research. This paper illustrates that GAM methods are a suitable alternative to widely-used cluster detection methods and may be preferable when residential histories from existing epidemiological studies are available. Surveillance of routinely collected data for unusual clusters of disease in space and time is a topic of general importance. Many epidemiologists resist community pressures to conduct cluster investigations believing they rarely provide conclusive information regarding the etiology of the disease. This is because cluster investigations often combine unrelated diseases; contain too few cases to be meaningful; have "gerrymandered" boundaries; and examine only cases without taking into account differences in population density . Even stCommunity concern over elevated cancer rates in upper Cape Cod, Massachusetts, USA Figure  promptedWe combined data from two of these existing population-based case-control studies of breast cancer in upper Cape Cod ,10 to inAn import consideration in spatial-temporal analyses is how to define time. Many space-time cluster analyses examine location at time of disease diagnosis . For a dAlthough latency is a more relevant time measure for breast cancer than diagnosis year, it does not address timing in relation to exposure occurrence. For example, in a 20-year latency analysis, two participants who moved into the same neighborhood in 1970 would not both be in the analysis if one was diagnosed in 1983 (13-year latency) and the other was diagnosed in 1993 (23-year latency). If an environmental exposure occurred in 1970, then a fixed latency analysis may not predict the correct breast cancer risk. Calendar years of residency are important because the magnitude of exposure can vary over time, and past rather than current exposures may be more relevant for breast cancer etiology. Residency duration is also relevant to etiologic exposures assuming duration of exposure is related to duration of residency. A participant who lived at a residence near the source of an environmental contaminant for five years but moved before the contamination occurred would be unexposed, while someone who lived in the same residence for five years after the contamination occurred would be exposed. Likewise, a person who lived at an exposed residence for 5 years may have a different disease outcome than someone who lived there for 35 years. Our present work measures time both in calendar years of residency and residency duration.In this paper, we examine breast cancer risk with a space-only analysis where time is not considered, a time-only analysis where space is not considered, and a spatial-temporal analysis that allows both time and space to vary. We used continuous residential histories so participants who moved away from the study area and later returned were excluded. We report global statistics for disease clustering and visualize breast cancer risk using GIS.We investigated the association between residential history since 1947 and risk of breast cancer during 1983–1993 using data from two population-based case-control studies ,10. TherThe space-only analysis included all eligible addresses  in the residential history. The optimal span for the adjusted space-only GAM was 95%. The model was adjusted for the time period of case ascertainment , age at diagnosis or index year, year of diagnosis or index year, vital status at interview, family history of breast cancer, personal history of breast cancer (before diagnosis or index year), parity and age at first live- or stillbirth, history of radiation exposure, and race. The large span size indicates the data are close to planar, but the plane was tilted with increased odds ratios (ORs) in the north of the study area and decreased ORs in the south Figure . PredictCombining data from two population-based case-control studies resulted in a residential history that spanned 47 years  and adjusted for the time period of case ascertainment , age at diagnosis or index year, year of diagnosis or index year, vital status at interview, family history of breast cancer, personal history of breast cancer (before diagnosis or index year), parity and age at first live- or stillbirth, history of radiation exposure, and race.We first analyzed time using a one-dimensional smooth of the participants' residency durations in the study area. Residency durations, calculated as the difference between diagnosis/index year and earliest year in the study area, ranged from 1 to 47 years. The earliest year was either the year a participant moved to upper Cape Cod or 1947 for participants already living there. Half of the participants had residency durations of less than 15 years. Another 18% of the participants (n = 297) had durations over 35 years. The majority of these participants (n = 254) were already living in the study area in 1947, the beginning of the residential history.The optimal span for the univariate smooth term in the residency duration model was 95% of the data. Figure We next examined time using a one-dimensional smooth of calendar year. We examined the earliest calendar year a participant lived in the study area rather than diagnosis year because it is potentially more relevant for breast cancer etiology. Because the case ascertainment periods for the first and second studies were 1983–1986 and 1987–1993, respectively, only participants of the second study had the opportunity to move to the study area during the early 1990s. This accounts for the sharp drop in the number of participants moving to the study area between the mid 1980s and the early 1990s. The median move year was 1976.The optimal span for the univariate smooth term in the calendar year model was 25% of the data. Figure Figure We predicted the adjusted breast cancer odds ratios for every valid combination of earliest calendar year and residency duration. The optimal span for the bivariate smooth term was 95% of the data. Figure We used GAMs and GIS to create a movie of continuous space-time animation for breast cancer risk during 1983–1993 based on the location and calendar years participants lived in upper Cape Cod. The model included a bivariate smooth of longitude and latitude similar to that of the space-only analysis, but the data were divided into overlapping datasets of 11-year time spans to smooth over time. The 11-year span size was chosen because the optimal span for the temporal analysis of calendar year was 25% of the data. The analysis started with years 1947–1957 representing the first frame of the movie (which corresponds to year 1947 on the movie timeline) and moved a year at a time until 1983–1993 (year 1983 on the movie timeline), for a total of 37 map frames. The span size for the smooth of longitude and latitude was 20%. This was the optimal span for the first 11-year dataset and was used for all the datasets. This ensures that the differences in maps are not due to differences in the span size.Although residency duration was not explicitly included as a model term in this analysis, the longer a participant's duration, the more datasets to which the participant contributed. For example, a participant that moved to the study area in 1948 was included in all datasets. Consequently, participants with longer residency durations contributed more to the overall spatial-temporal analysis.. It is important to emphasize that the movie visualizes the risk of being diagnosed with breast cancer during 1983–1993 that is associated with the location of participant residences in upper Cape Cod during historical time periods. It does not show the incidence of breast cancer during the historical periods.The spatial-temporal analyses found a large area of elevated breast cancer risk during 1983–1993 corresponding to historical residences in the center of the study area near the Massachusetts Military Reservation from 1947 to 1956. Odds ratios for these ten maps (1947–1956) ranged from 0.25 to 2.5, and global p-values ranged from 0.01 to 0.05, indicating a statistically significant association between residential histories during 1947–1956 and breast cancer risk during 1983–1993. A smaller area of elevated breast cancer risk during 1983–1993 was also seen corresponding to residences in the northeast region of upper Cape Cod during the 1960s, but the global p-values for maps of these years were not statistically significant. Figure Space-time maps allow for disease-pattern analysis of cases and controls using historical residences . The GAMKulldorff's space-time SaTScan method detects cancer clusters of specified shape and provides center coordinates and relative risk measure for the mostly likely cluster . SaTScanKwan et al. use an interesting three dimensional geovisualization method to display movement across time and space . This meAlthough GAMs have many advantages, a number of issues remain. The GAM analysis uses one constant optimal smoothing span for space and another for time. While this ensures that mapped results are unaffected by the degree of smoothing, we ideally would use smoothing spans determined to be optimal in a combined time-space framework. Further work is needed to resolve this methodological issue. GAMs may also exhibit edge effects, which are biased behavior at the edges of the data . As muchWe identified areas with significantly increased or decreased risk using pointwise hypothesis tests. By making these multiple comparisons, we increase the likelihood of finding significant hot or cold spots by chance alone. Although we make no adjustment for multiplicity, we only conducted pointwise tests if the global deviance test indicated that the map was unlikely to be flat. The location of significant hot and cold spots should be considered exploratory.There are also limitations implicit in using epidemiological data for secondary analysis. There are sparse data for the earlier calendar years of the temporal datasets, which affect the power of our clustering tests. To date, our spatial-temporal analysis methods also do not directly consider duration of time living at a residence, an important component to exposure. We are currently exploring additional GAM methods for simultaneously smoothing calendar year, duration, and location .Spatial-temporal analysis of the breast cancer data may help identify new exposure hypotheses that warrant future epidemiologic investigations with detailed exposure models. We performed a spatial-temporal analysis of breast cancer risk during 1983–1993 that combined statistical and visualization tools to examine time and place of participants' residences as proxies for unknown environmental exposures. Our results indicated only slight increases in breast cancer risk when we considered location or time alone while controlling for known risk factors. However, when we considered the combined effects of both space and calendar year of residency, we observed a strong statistically significant association between breast cancer risk and living near the Massachusetts Military Reservation from 1947 to 1956 . These results suggest that further analyses be conducted to explore the reason for this geographic association. If the association is not a result of residual confounding or bias, then activities on the Military Reservation during that time window should be investigated to provide insight into possible exposure routes . The current analyses illustrate the usefulness of GAMs and GIS to visualize cancer risk, adjust for known confounders, and test for the statistical significance of location and time. Our method is particularly useful residential histories are available.We investigated the association between residential history and breast cancer in upper Cape Cod, Massachusetts (USA) using data from two population-based case-control studies ,6. PartiThe Massachusetts Cancer Registry was used to identify incident cases of breast cancer. Cases were diagnosed from 1983–1986 for the first study and 1987–1993 for the second study. Participants were restricted to permanent residents of the upper Cape Cod region with complete residential histories. Table Controls were chosen to represent the underlying population that gave rise to the cases in a manner that was not spatially biased, that is, permanent residents of the study area during the case ascertainment period. Because many cases were elderly or deceased at diagnosis, three different sources of controls were used: (1) random digit dialing to identify living controls less than 65 years of age; (2) Centers for Medicare and Medicaid Services  to identify living controls 65 years of age or older; and (3) death certificates to identify controls who had died from 1983 onward. See Aschengrau et al.  for a deControls were frequency matched to cases on age and vital status. "Index years" were randomly assigned to controls in a distribution similar to that of diagnosis years for cases. We used index years to estimate length and time of environmental exposure for controls in a fashion comparable to that of cases. Controls that moved to the study area after the assigned index year were excluded from the analyses. In the first study, there were 526 controls with index year between 1983 and 1986 who contributed 762 upper Cape Cod residences between 1943 and 1986. In the second study, there were 445 controls with index year between 1987 and 1993 who contributed 704 upper Cape Cod residences between 1947 and 1993  and linked to the participant's interview data. Geocoding was done without knowledge of case/control status, and the final data were checked for accuracy.We used generalized additive models (GAMs) to examine breast cancer risk for 1983–1993 in (1) a spatial analysis of residence location that did not consider time, (2) a temporal analysis of calendar year and residency duration that did not consider space, and (3) an analysis that combined both space and time. Given the dependency of etiologically meaningful exposure on both duration and calendar year, we analyzed these two measures of time both individually and in a combined analysis. All analyses were adjusted for the time period of case ascertainment , age at diagnosis or index year, year of diagnosis or index year, vital status at interview, family history of breast cancer, personal history of breast cancer (before diagnosis or index year), parity and age at first live- or stillbirth, history of radiation exposure, and race. Other covariates including education and usual adult body mass index (BMI) were examined but did not change the appearance of the maps. Women with missing covariate data or non-continuous residency in the study area were excluded from the analysis.1) or bivariate smooth SWe estimated local disease odds using GAMs, a form of non-parametric/semi-parametric regression with the ability to analyze binary outcome data while adjusting for covariates . We use z is a vector of covariates, and γ is a vector of parameters. Univariate smooths were used in the individual models for earliest year lived in the study area and residency duration; bivariate smooths were used in the analyses for space (longitude (x1) and latitude (x2)) and calendar year/duration (earliest year (x1) and duration (x2)). We used a loess smooth which adapts to changes in data density [where the left-hand side is the log of the disease odds, S is the univariate or bivariate smooth term,  density . The amo density . We deteGAMs also provide a framework for hypothesis testing. We first tested the null hypothesis that case status does not depend on the smooth term using the difference of the deviances of model (1) with and without the smooth term. We estimated the distribution of the global statistic under the null hypothesis using a permutation test. We condition on the number of cases and controls, preserving the relationship between case/control status and covariates, and randomly assign individuals to locations. We carry out 999 permutations of location in addition to the original. For each permutation, we run the GAM using the optimal span of the original data and compute the deviance statistic. We divide the rank of the observed value by 1000 to obtain a p-value. We used a p-value cut off of 0.05 as a screening tool for possibly meaningful associations. We discuss results as "significant" if the associated p-values are less than 0.05, but acknowledge that some results may be due to chance.If the global deviance test indicates that the map is unlikely to be flat, we next want to locate areas of the map that exhibit unusually high or low disease odds. We examine pointwise departures from the null hypothesis of a flat surface using permutation tests. We obtained a distribution of the log odds at every point using the same set of permutations we used for calculating the global statistics. We defined areas of significantly decreased odds ("cold spots") to include all points that ranked in the lower 2.5% of the pointwise permutation distributions and areas of elevated odds ("hot spots") to include all points that ranked in the upper 2.5% of the pointwise permutation distributions. See Webster et al.  for a deIn addition to hypothesis testing, we computed variability bands – a nonparametric relative of confidence intervals – to examine the precision of the point estimates for the models with a univariate smooth. We bootstrapped by resampling our data 1000 times, recomputing the log odds at each point on the grid . We consIn the one-dimensional time-only analyses, we constructed two separate univariate smooth models to examine the association between breast cancer risk during 1983–1993 and (1) earliest year lived in the study area or (2) residency duration. In the two-dimensional time-only analysis examining earliest calendar year and duration, we created a grid using all possible pairs of earliest year lived in the study area (1947–1993) and duration (1–47). Duration was calculated by subtracting the earliest year from the diagnosis or index year. We used a bivariate smooth to estimate the adjusted log odds at each cell on the grid.In the space-only analysis, we created a rectangular grid covering the study area using the minimum and maximum longitude and latitude coordinates from the original data set as its dimensions. We clipped grid points lying outside the outline map of the study area or in areas where people cannot live . We used the spatial model to estimate the adjusted log odds at each grid point on the study area map.Results from the generalized additive models were exported from S-plus  into ArcWe analyzed the data in fixed-year time spans to study combined space-time effects of location and calendar years on breast cancer risk during 1983–1993. By dividing the data into datasets of overlapping time spans, we essentially smoothed over time. We used the optimal bandwidth from the smooth term in the one-dimensional calendar year analysis (earliest year a participant lived in the study area) to determine the time span for the data subsets. For each data subset, a spatially-smoothed map was created using methods similar to those in our space-only analysis, i.e., where the smooth term in the GAM is the coordinates for location and the span size is the same. We used the optimal span for the smooth term of location in the GAM for the first dataset in the models for the other data subsets to ensure that any differences observed in the maps were not due to differences in the span size. The combination of time spans and GAMs resulted in the simultaneous smoothing of space and calendar year.These maps depict the risk of being diagnosed with breast cancer during 1983–1993 according to the location of participant residences in upper Cape Cod during historical time periods. They do not show the incidence of breast cancer during the historical periods. The maps were used to create a movie showing how breast cancer risk during 1983–1993 varied as historical residences changed over space and time. Maps were saved as image files and used to create a storyboard in Windows Movie Maker . Each maAIC: Akaike's Information Criterion; GAM: generalized additive model; GIS: geographical information systems; ORs: odds ratiosThe authors declare that they have no competing interests.VV conducted the spatial-temporal analyses, drafted the manuscript, and provide analytical and editorial support. TW collaborated on all analytical and editorial decisions. JW provided statistical support and consulted on analytical and editorial issues. AA provided the data and assisted in epidemiologic analysis and editing. All authors read and approved the final manuscript.Spatial-temporal analysis of breast cancer risk during 1983–1993. A movie that shows changing patterns of breast cancer risk during 1983–1993 based on participants' historical residenceClick here for file


P for trend <0.001). Among subjects without gallstones, BMI was also positively associated with gall bladder cancer risk. Regardless of BMI levels, increasing WHR was associated with an excess risk of gall bladder cancer risk, with those having a high BMI (⩾25) and a high WHR (>0.90) having the highest risk of gall bladder cancer , relative to those with a low BMI and WHR. We found no clear risk patterns for cancers of the bile duct and ampulla of Vater. These results suggest that both overall and abdominal obesity, including obesity in early adulthood, are associated with an increased risk of gall bladder cancer. The increasing prevalence of obesity and cholesterol stones in Shanghai seems at least partly responsible for the rising incidence of gall bladder cancer in Shanghai.Though obesity is an established risk factor for gall bladder cancer, its role in cancers of the extrahepatic bile ducts and ampulla of Vater is less clear, as also is the role of abdominal obesity. In a population-based case–control study of biliary tract cancer in Shanghai, China, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for biliary tract cancer in relation to anthropometric measures, including body mass index (BMI) at various ages and waist-to-hip ratio (WHR), adjusting for age, sex, and education. The study included 627 patients with biliary tract cancer  and 959 healthy subjects randomly selected from the population. A higher BMI at all ages, including early adulthood (ages 20–29 years), and a greater WHR were associated with an increased risk of gall bladder cancer. A high usual adult BMI (⩾25) was associated with a 1.6-fold risk of gall bladder cancer (95% CI 1.2–2.1,  Biliary tract cancers, which include cancers of the gall bladder, extrahepatic bile duct, and ampulla of Vater, are rare but highly fatal , both usual (adult) and at various time points in life, and waist-to-hip ratio (WHR).The study protocol was approved by the Institutional Review Boards of the US National Cancer Institute (NCI) and the Shanghai Cancer Institute (SCI). Details of the study have been reported elsewhere , 2007d. In-person interviews were conducted using a structured questionnaire to elicit information on potential risk factors, including demographic characteristics, cigarette and alcohol use, medical history, diet, and family history of cancer. All interviews were tape-recorded and reviewed to verify that these data were recorded accurately and to ensure that each interview was conducted properly. In addition, 5% of the study subjects were randomly selected and re-interviewed, with a concordance rate of over 90% on responses to key questions across the two interviews. Of those eligible, 627 cancer patients and 959 population control subjects agreed to participate and provided written informed consent at enrollment, a response rate of over 90% for cases and 82% for controls. Among participating controls, 85% also consented to abdominal ultrasound screening for gallstone detection. Individuals were defined as having biliary stones if they had previously undergone cholecystectomy or had gallstones.At the interview, subjects were asked for their adult height, current weight; usual weight 5 years before interview, usual weight during specific age decades , maximum adult weight , age at and duration of maximum weight, main area of weight gain on the body, and history of adult weight cycling (⩾7 kg gain or loss). Physical measurements of standing height, weight, and waist and hip circumference were also taken at the interview. Each measure was taken two times. When the difference between the two measurements exceeded predetermined tolerance limits , an additional measurement was taken. Final measurements for height, weight, and waist and hip circumference were determined by averaging the two closest values.2), was used to assess overall obesity. Self-reported data were used to calculate BMI at specific age periods and maximum adult BMI, respectively. The change in BMI over time, defined as the difference in BMI between age intervals , was also computed. Subjects were classified into the BMI categories established by the World Health Organization (WHO) for Asian populations, with the BMI category of 18.5–22.9 kg/m2, defined as ‘normal’ and used as the reference group , whereas patients with bile duct or ampullary cancer were compared with all control subjects. Additional covariates, including cigarette smoking, alcohol use, and history of diabetes and hypertension, were evaluated as potential confounding variables but were not included in the final models, as they did not appreciably change the risk estimates. Sex-specific analyses were performed to evaluate differences between men and women in risk associated with body size. Tests for linear trend in risks of cancer were conducted when appropriate, with anthropometric variables evaluated on a continuous scale. All tests were two-sided, with P<0.05 defined as statistically significant.Unconditional logistic regression was used to calculate odds ratios and 95% confidence intervals for each cancer subsite associated with BMI and other anthropometric measures, adjusting for age, sex, and education. Gall bladder cancer patients were compared with controls without a history of cholecystectomy (P for trend=0.01) or among subjects without gallstones  (data not shown). Although larger waist circumference was only slightly associated with an increased risk of gall bladder cancer, a high WHR (>0.897) was associated with a 4.7-fold risk . There was no clear association with cancers of the extrahepatic bile duct or ampulla of Vater. Timing and duration of maximum adult weight, primary location of weight gain, and weight cycling did not appear to be related to risk for stones or cancer (data not shown), although too few subjects reported a history of weight cycling for reliable assessment.In this population-based study, WHR and BMI at all ages, including early adulthood, were associated with an increased risk of gall bladder cancer. These results suggest that both overall and abdominal obesity play an important role in the aetiology of gall bladder cancer. It seems likely that the increasing prevalence of obesity and cholesterol stones in Shanghai is at least partly responsible for the rising incidence of gall bladder cancer in Shanghai. These findings for gall bladder cancer are consistent with those of previous studies .Despite the fact that our study is the largest population-based study to date, we found no clear association between obesity and cancer of the bile duct or ampulla of Vater, possibly because of their small numbers. Of the five available studies assessing bile duct cancer risk specifically (2) in the Shanghai population is 25% but it is only 4.1% if the conventional cutoffs (BMI >30 kg/m2) are used. It should be noted that although median BMI in our population is low (22.9 kg/m2), the prevalence of abdominal obesity (WHR>0.9) is quite high (50%).In this report, we used the WHO-recommended BMI cutoffs for Asians, as they have been shown to have different body composition and bone density  and there is a good correlation between reported BMI and measured WHR, suggesting that misclassification by BMI is minimal. The validity of recalling weight for each decade in adulthood is likely to be lower than that of current weight. However, in our study correlations between reported weights in various decades of life were high (>0.8) and misclassification, if any, is likely to be non-differential in cases and controls.The validity of our results hinges largely on the validity of self-reported BMI, which appeared to be quite good, given the fact that, among our population controls, self-reported current weight correlated well with measured weight (Several strengths of the study should be noted. Selection bias was minimal because of population-based design with high case ascertainment and high participation rates. Misclassification of cases was minimal, given the nearly complete confirmation of case status, achieved by comprehensive pathology and clinical review. As the largest study to date, we were able to investigate the role of obesity by anatomic subsite.One major limitation of our study is the potential disease effect on the reporting and measurement of body size. As cancer can cause wasting and weight loss, cases might be expected to have lower body weight than controls. However, we found that cases actually had a higher BMI than controls, suggesting that the weight, especially usual adult weight, in our cases had not been greatly affected by cancer. We cannot generalize our results to western populations, because of the large differences in prevalence of obesity and the fact that we were unable to evaluate the effect of BMIs greater than 30, as only 4% of the controls had a BMI that large.In summary, this population-based study in Shanghai confirmed that overall obesity is an important risk factor for gall bladder cancer and found that obesity in early adulthood and abdominal obesity are also relevant. Given the epidemic of obesity worldwide and the substantial burden of gallstones in most populations, a strategy to slow down the rising obesity trend and to minimize the burden of gallstones and biliary cancer would be important to develop.


In a cohort of women aged 40-64 at entry, 12 h urine samples were obtained at the beginning of a follow-up period of up to 15 years in which incident cases of lung cancer were registered as well as deaths from lung cancer. In this cohort a nested case-control study (n = 397) was carried out by measuring urinary cotinine. The method for quantitation of cotinine was sensitive enough to study lung cancer risk not only in active smokers but also in passive smokers. The results seem to indicate that cotinine estimations in single 12 h samples of urine are enough to predict lung cancer risk. Relative risk rose with increasing levels of nicotine intake already in the range associated with passive smoking. The smoking-related risk of adenocarcinoma was much less than that of other lung carcinomas.


TLRs) and nucleosome-binding oligomerization domain (NOD) genes are integral to the recognition of pathogens and are highly polymorphic. For these reasons, the aim of the study was to assess the frequency of polymorphic variants in TLR and NOD genes in an Australian endometrial cancer population.Endometrial cancer is the most common gynaecological malignancy in women of developed countries. Many risk factors implicated in endometrial cancer trigger inflammatory events; therefore, alterations in immune response may predispose an individual to disease. Toll-like receptors , NOD2 , TLR2 (rs5743708), TLR4 (rs4986790) and TLR9 .Ten polymorphisms were genotyped in 191 endometrial cancer cases and 291 controls using real-time PCR: TLR9 polymorphisms, rs5743836 and rs187084, were protective for endometrial cancer risk: OR 0.11, 95% CI (0.03-0.44), p = 0.002. This result remained highly significant after adjustment for endometrial cancer risk factors and Bonferroni correction for multiple testing. There were no other associations observed for the other polymorphisms in TLR2, TLR4, NOD1 and NOD2.Haplotype analysis revealed that the combination of the variant alleles of the two TLR9 transcriptional activity compared to the 'T' allele, therefore, higher TLR9 activity may be related to efficient removal of microbial pathogens within the endometrium. Clearly, the association of these TLR9 polymorphisms and endometrial cancer risk must be further examined in an independent population. The results point towards the importance of examining immune response in endometrial tumourigenesis to understand new pathways that may be implicated in disease.The variant 'C' allele of rs5743836 causes greater  Extenl cancer . This hyl cancer . Supportl cancer -7. Many l cancer , therefoThe maintenance of the immune response is important for the recognition and subsequent response to a wide range of microbial pathogens . To deteTLRs, TLR2, TLR4 and TLR9 are highly polymorphic and represent interesting targets to elucidate their role in endometrial cancer development [TLR2 recognises PAMPs from a wide range of pathogens; TLR4 is involved in the recognition of bacterial lipopolysaccharide (LPS) and TLR9 recognises unmethylated CpG motifs present in bacterial DNA and intracellular antigens [NOD1 and NOD2 are involved in the recognition of many bacterial pathogens and their activation signals the transcription of many pro-inflammatory genes following NF-κB activation [NOD1 and NOD2, have been associated with Crohn's disease and other inflammatory disorders [The TLR family consists of 10 membrane-bound proteins that respond to microbes in the extracellular matrix . Polymorelopment . TLR2 reantigens ,14. Furttivation . Geneticisorders .NOD1 , NOD2 , TLR2 (rs5743708), TLR4 (rs4986790) and TLR9 (rs5743836 and rs187084) to determine whether there was any association with endometrial cancer risk in an age and sex matched Caucasian population.The aim of this study was to examine 10 polymorphisms in The study population has been previously described -17. ThisThe final analysis included 191 endometrial cancer patients. Data on reproductive and environmental risk factors including ethnicity, body mass index (BMI), diabetes, high blood pressure (HBP), age of diagnosis of endometrial cancer, age of menarche, age of menopause, other personal cancer history, family cancer history (Family history of cancer was defined as cancer in the index patient plus one or more 1st or 2nd degree relatives diagnosed with cancer), parity, breastfeeding, oral contraceptive use, chemotherapy, radiotherapy, hormone therapy (HT), smoking and alcohol use was collected using self reported questionnaires. Information regarding recurrence, stage, grade and histology of endometrial cancer was collected from their medical records.The control population consisted of 291 women that were recruited between the years 2004 and 2005 for the Hunter Community Study. This study aims to identify genetic and environmental factors associated with ageing in a cohort of individuals obtained from the Hunter region, Newcastle, New South Wales, Australia. Any control that had a prior diagnosis of either breast or endometrial cancer was excluded from the study. Controls were matched to cases by sex and age.All participants provided informed written consent prior to participation in this study. Ethics approval was obtained from the Human Research Ethics Committee, University of Newcastle, New South Wales, Australia (H-050-0605) and the Hunter Area Research Ethics Committee, Hunter New England Health Service, Newcastle, New South Wales, Australia (05/03/09/3.14).Genomic DNA was extracted from 10 ml EDTA blood using the "salting-out" method .NOD1 polymorphisms ; three NOD2 polymorphisms , one TLR2 polymorphism (rs5743708), one TLR4 polymorphism (rs4986790) and two TLR9 polymorphisms (rs5743836 and rs187084) was performed on an ABI PRISM® 7500 Real-Time PCR System , using primers and probes from the Assay-by-Design service (Applied Biosystems). The primer and probe sequences are available upon request. The assay was performed under universal conditions as previously described . The genotyping results were confirmed by a second laboratory research assistant and 5% of the samples were re-genotyped with 100% concordance. Any sample where a genotype could not be accurately assessed was re-genotyped. The overall call rates were 100%.Genotyping of three http://hydra.usc.edu/GxE). The calculations performed showed that the number of cases and controls (ratio 1:1.52) in our cohort was large enough to detect a significant, p < 0.05, 2-fold increased risk (OR >2.0), with 80% power, assuming a dominant genetic model, with a minor allele frequency of 6.5%. Therefore, our study has a large enough sample size to statistically demonstrate that significant OR values over 2.0 or below 0.5 provide a statistically robust result.Power calculations were performed using Quanto . To determine differences in genotype frequencies and environmental and reproductive risk factors between the cases and controls, chi-squared (χ2) statistics, odds ratios (ORs) and 95% confidence intervals (CI) were calculated using unconditional logistic regression. Multivariate unconditional logistic regression was performed to determine if any risk factors altered the significance of the genotype frequency results. The risk factors taken into account were: BMI (<25 kg/m2 and ≥25 kg/m2), diabetes (yes/no), HBP (yes/no), HT (yes/no), personal history of cancer (yes/no), smoking (ever/never) and alcohol consumption (ever/never). Other risk factors such as age of menopause were not included in the analysis since this information was not available for the controls.For each polymorphism, Hardy-Weinberg Equilibrium (HWE) was calculated in the control group to check for compliance using the Institute for Human Genetics, statistics website, 2) analysis and ORs and 95% CI were calculated using unconditional logistic regression. To avoid chance findings due to multiple testing of the 10 polymorphisms and 16 environmental/reproductive risk factors, Bonferroni correction was used and the significance levels was lowered to p = 0.005 (p = 0.05/10) for the 10 polymorphisms and p = 0.003 (p = 0.05/16) for the 16 environmental factors.The genotype frequencies of all polymorphisms were compared in the case group stratified for the environmental and reproductive risk factors by using chi-squared , Intercooled STATA 8.2  and SPSS Version 15 .Cases and controls were different with respect to potential endometrial cancer risk factors, including HBP, diabetes, HT, alcohol consumption, personal history of any cancer, personal history of ovarian cancer, cervical cancer and other cancers as previously described -17.NOD1, NOD2, TLR2, TLR4 and TLR9 among the cases and controls did not deviate from HWE. The three NOD1 polymorphisms were in high LD . In addition, the NOD2 polymorphisms were in high LD  however rs2066844 and rs2066845 were not in LD (D' = 0.2). None of the TLR polymorphisms were in high LD. Three TLR combinations were in partial LD: TLR2 rs5743708 + TLR4 rs4986790, D' = 0.61; TLR2 rs5743708 + TLR9 rs187084, D' = 0.57; and TLR4 rs4986790 + TLR9 rs187084, D' = 0.57.The distributions of the genotypes of all ten polymorphisms in NOD1, NOD2, TLR2, TLR4 and TLR9 , p = 0.025. After Bonferroni correction for multiple testing, this result was no longer significant . Haplotype analysis revealed that the combination of the variant alleles for TLR9 rs187084 and rs5743836 were associated with a significant decreased risk of endometrial cancer; TT vs CC: OR 0.11, 95% CI (0.03-0.44), p = 0.002  in comparison to those with the wild-type genotype (62 years): Log-Rank p = 0.028; Wilcoxon, p = 0.054; and Tarone-Ware, p = 0.039. However, after stratifying the results for the environmental/reproductive risk factors using Cox regression, the results showed a similar trend but were no longer statistically significant, p = 0.061.Kaplan-Meier survival analysis and T-tests were used to evaluate the influence of the This analysis focused on all of the polymorphisms in the cases stratified for known environmental/reproductive confounders. After the results were adjusted using Bonferroni correction, no significant results were observed.TLRs and NOD genes in inflammatory disorders and oncogenesis [TLRs and NOD genes  were associated with risk of developing endometrial cancer. These polymorphisms were chosen as they have been previously related to a number of inflammatory diseases.Recent attention has been given to the role of ogenesis  as theseogenesis . For theTLR9 polymorphisms, rs5743836  and rs187084  combined, are associated with a decreased risk of endometrial cancer. Even though the CC subgroup harboured a small number of patients (2 cases and 21 controls), the association observed remained highly significant following adjustment for endometrial cancer risk factors and Bonferroni correction for multiple testing, indicating a true effect. These results must be interpreted with caution due to the group sizes and confirmed in an independent and larger cohort. No other associations were observed for the variants in the TLR2, TLR4, NOD1 or NOD2.In the current study, we showed that the variant alleles of the TLR9 belongs to the family of nucleic acid recognition TLRs, specifically identifying DNA-containing unmethylated CpG motifs in bacteria [TLR9 leads to an increase in NF-κB transcriptional activation, allowing maturation of dendritic cells and release of proinflammatory cytokines [TLR9 polymorphisms, rs5743836 and rs187084, located in the promoter region, alter the functional ability of TLR9 [et al. (2009), showed that following either TNFα or lipopolysaccharide (LPS) stimulation, TLR9 activity, for the rs5743836 polymorphism, was greater for the C allele vector compared to the T allele vector using luciferase reporter constructs [TLR9 rs187084 polymorphism needs to be performed.bacteria . Activatytokines . It has  of TLR9 . The varnstructs . In addiTLR9 rs5743836 polymorphism was transcribed more efficiently than the C allele, indicating greater activity of the T allele rather than the C allele [et al. (2009), assessing basal levels may not be appropriate when studying a disease that may be influenced by exposure to bacterial pathogens. The results of our study are however similar to those observed by Novak and colleagues. They showed that the T allele was associated with an increased risk of atopic eczema (AE) whereas the C allele was observed as protective for AE. Furthermore, a study by Lazarus et al. (2003) revealed that the C allele was associated with asthma [Under basal conditions, another group reported that the T allele of C allele , but as h asthma . ClearlyTLR9 rs5743836 and rs187084 appears to be protective for endometrial cancer and that the high activity C allele of rs5743836 may allow a better response to pathogenic microbes that present in the endometrium. This statement must be interpreted with caution as the biological mechanisms underlying altered immune response in individuals harbouring these polymorphic variants must be further interrogated. The results presented in this study highlight that alterations in immune response genes may vary an individual's susceptibility to develop endometrial cancer. Further studies examining genes involved in the immune response pathway are warranted and have the potential to identify new biological mechanisms involved in endometrial cancer.The combination of the variant C alleles of The authors declare that they have no competing interests.KAA designed and executed the study. KAA provided significant insight into the interpretation of the data and wrote the manuscript. AP and GO supplied case samples and clinical information. MM supplied control samples and clinical information. IS contributed to the design of the study. JA supplied control samples and clinical information, and assisted with statistical analysis. RJS designed the study, provided the concept and corrected the manuscript. All authors have read and approved the final version of the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/10/382/prepub


P=0.046), and between dense patterns and number of deliveries (P=0.04). Among women with nondense breast patterns, the non-Chinese had lower risk than the Chinese with an odds ratio (OR) of 0.47 , whereas in those with dense patterns, the non-Chinese had considerably higher risks . Alternatively expressed, the increased risk with dense patterns was only observed in the non-Chinese . Among parous women, the protective effect of three or more deliveries was only observed in those with dense breast patterns . Suggestive but nonsignificant interactions with dense patterns were observed for ever having delivered, age at first delivery, breast feeding and body mass index. The results are consistent with dense breast patterns as a marker for hormonal modification of breast cancer risk.The question of interactions between breast density and other breast cancer risk factors is of interest, since it bears upon the use of density as a marker for changes in breast cancer risk. We studied breast parenchymal patterns and 13 other potential risk factors for breast cancer in 172 breast cancer cases and 338 age-matched controls in Singapore. Dense breast patterns were defined as having Tabar parenchymal pattern IV or V. We found significant interactions between dense patterns and ethnic group ( In recent years, there has been increasing interest in breast density as a risk factor for breast cancer, as a potential marker for changes in the breast and as a criterion for inclusion in prevention trials (The last phenomenon is of particular interest. Increased density (i.e. high-risk pattern) is associated with preparations such as hormone replacement therapy, which increases exposure to oestrogens (vice versa). For example, if the protective effect of an early first birth was only manifested in those who showed a corresponding reduction in breast density, this would be further evidence of density as a marker of progression towards breast cancer and would give further support to investigating its potential as an early indictor of the effectiveness of chemoprevention. We therefore propose to investigate interactions between dense breast patterns and other risk factors within the Singapore case–control study.In a previous paper reporting on dense breast patterns and breast cancer risk in a case–control study in Singapore, we noted a significant effect on risk of the dense Tabar IV pattern  cases and 338 (97%) controls. The results of interaction analyses are shown in P=0.04), and of the effect of racial group (P=0.046). Among parous women, the reduction in risk with large numbers of children is only seen in those with dense patterns. Among women with dense patterns, a strong increased risk for non-Chinese women was apparent, but for women with nondense patterns, the Chinese women had significantly higher risk than the non-Chinese. This can be expressed in terms of the increased risk with dense patterns: among non-Chinese women there were very few women with dense patterns, but there was a substantial increase in risk associated with these, with an OR of 13.99 ; no such increase in risk with dense patterns was observed among Chinese women.The results of the interaction tests indicate that there is significant heterogeneity between dense and nondense patterns, of the effect of number of deliveries on breast cancer risk , for which the increased risk with dense patterns was observed only for those with high BMI .The analysis above was prompted by the results of the initial case–control study and should therefore be regarded as hypothesis-generating rather than definitive. It does, however, give rise to some interesting speculations.P=0.009). The interesting and reliable feature of this result is that there was no significant increased risk with dense patterns in Chinese women, despite the relatively high prevalence of such patterns in this group . A possible explanation may be that the high prevalence of dense breast tissue in Chinese women indicates that density in this population reflects body habitus and is not necessarily a feature of a pathological process. In terms of the suggestive heterogeneity of the effect of racial group, this may be a chance effect of the small numbers of women with dense patterns in the non-Chinese racial groups. Whereas substantial numbers of Chinese women had dense patterns (see the appendix), only three cases and one control among the non-Chinese had dense patterns. This difference is highly significant .P=0.1). The increased risk with a late first delivery being confined to those with dense patterns, and the protective effect of breast feeding being confined to nondense are consistent with this, but these interactions are also nonsignificant.The interaction of dense patterns with number of deliveries among parous women is interesting. A similar result was observed by Another nonsignificant but interesting finding is the absence of an increased risk with dense patterns in postmenopausal women. With one exception (The results suggest that further investigation of the interrelationship of breast density, BMI and breast cancer risk is necessary. Although in our study, there was no significant association of BMI with breast cancer risk, high BMI is an established risk factor in postmenopausal women (In conclusion, there are interesting interactions and possible interactions of dense breast patterns with other breast cancer risk factors. The interaction with number of deliveries is consistent with density as a marker of hormonal alteration of breast cancer risk, and therefore for its potential as an early indicator of hormonal prevention, as are the suggestive but nonsignificant interactions with BMI, age at first delivery and breast feeding. Research to further confirm and quantify these interactions is indicated, using percentage density and larger study sizes.


The difference in breast cancer incidence and prognosis between ethnic groups seeks an explanation. We have recently shown that Swedish women are two to three times more likely to be diagnosed with breast cancer compared with Singaporean women. In the present paper, we compare breast cancer survival in the two countries.We compared the survival of 10,287 Singaporean women and 17,090 Swedish women with breast cancer. Relative survival ratios were used to describe the prognosis in the two populations. A Poisson regression model was used to calculate relative risks for different follow-up periods, age groups, time of diagnosis and disease stages.The majority of the Swedish women had local cancer (80%) compared with Singaporean women (51%). The overall 5-year relative survival of the Swedish women appeared better (80%) than that of the Singaporean women (70%). A similar survival pattern was observed, however, between the two countries in a stage-by-stage comparison. Survival improved for all women in Singapore over the two decades, but only in the premenopausal women in Stockholm. In 1980 to 1989, premenopausal Singaporean women had 27% increased risk of death compared with Swedish women, adjusted for stage and year of follow-up, while the postmenopausal women had 48% increased risk. In 1990 to 1999, this risk decreased by 19% and 22% for the premenopausal and postmenopausal Singaporean women compared with the Swedish women.The stage-dependent prognosis was similar for Singaporean women and for Swedish women. Singaporean women, both premenopausal and postmenopausal, had pronounced improvement in prognosis over the calendar periods, probably contributed by marked economic improvement, leading to better medical facilities and management with increased awareness of patients to diagnosis and treatment, as well as improved treatment options. Improvement seen only in the premenopausal women in Stockholm was probably due to improved treatment options. The study of ethnic differences in breast cancer survival is limited except for those between Afro-American women, Asian-American women and Caucasian American women. In the United States, Afro-American women are known to have a worse outcome compared with Caucasian American women. This has been attributed to increased diagnosis of late-stage breast cancers, which could be explained by delayed diagnosis reflecting the socioeconomic status, cultural beliefs, access to healthcare , and theThe ethnic disparity in incidence, mortality and survival is evident in the United States, where breast cancer is predominantly a postmenopausal disease in the Caucasian American population ,9 but a Sweden is relatively homogeneous in ethnic stock, while the Singaporean population is multiracial with a prominent Chinese population (76%), 13% Malays and 7% Indians . Over thThese similarities and differences make the study of breast cancer prognosis important. Such study may highlight biological and nonbiological reasons for any difference in the prognosis between Singapore and Sweden. In this paper, we aim to compare the survival in women diagnosed with breast cancer in Singapore and in Sweden in relation to important clinical prognostic markers for breast cancer. We also studied how the trends in survival patterns of the breast cancer patients relate to the change in incidence and mortality.All cases of invasive breast cancer diagnosed from 1 January 1980 to 31 December 1999 were obtained from the Singapore and Stockholm cancer registries. Patients with a previous malignancy, including contralateral breast cancer, and those diagnosed with breast cancer at autopsy (death certificate only) were excluded from the study. Follow-up was performed until 31 December 2005 by matching with the national death register. The cause of death was coded in accordance with the International Classification of Diseases and Causes of Death ICD9. The ethical committees at the National University of Singapore and Karolinska Institutet accepted the study without any restrictions. This is normal when de-identified material is used.The Singapore Cancer Registry is a population-based registry that was started in 1968. It receives voluntary notifications of incident cancers from all medical practitioners and pathology laboratories, as well as reviews, death certificates and hospital discharges for all patients. Staff of the Registry also reviewed cancer patient hospital discharges and death certificates. The completeness of reporting is high: 96% in the 1970s and close to 100% in the 1990s. The proportion of death-certificate-only notifications was 4.2% for the period 1968 to 1977, 1.0% for 1993 to 1997 and 0.9% for 1998 to 2002 . In totaThe Stockholm Breast Cancer Registry was started in 1977 and receives notification of newly diagnosed cases of breast cancer at all departments of oncology and surgery in Stockholm County, which is inhabited by 1.7 million individuals. There were 17,090 women diagnosed with breast cancer recorded in the calendar period 1980 to 1999. None of them were death-certificate-only diagnoses.The stage of the breast cancer in the Singapore Cancer Registry was classified as localized cancer, regional spread and distant metastases based on the notification forms before 2001. Cancers are staged as local if they are confined entirely to the breast. Regional cancers are those that have extended beyond the limits of the breast directly into surrounding tissues or organs, or into lymph nodes in the region. Distant cancers are those that have spread beyond these locations. No attempt was made to access the extent of localized invasion or the number of regional lymph nodes involved.Stage information in the Stockholm registry was available according to the TMN staging system: tumor stage, lymph node stage and metastatic spread. This information was reclassified, using the Surveillance, Epidemiology and End Results Comparative Staging Guide for Cancer , to be cAge at diagnosis was categorized into six age groups  and the period of diagnosis divided into two 10-year periods (1980 to 1989 and 1990 to 1999) to identify change over time; 1990 was selected because the early 1990s were when the use of tamoxifen became widely accepted and adjuvant treatment was more standardized in Singapore.Descriptive prognostic comparisons between Singaporean women and Swedish women were performed by relative survival analyses. Relative survival ratios were computed by taking the ratio of observed survival to expected survival, accounting for the competing causes of death. The expected survival probabilities were calculated using Ederer II method  derived The incidence rates were calculated using the number of invasive breast cancer cases out of the total female population of each country for each time period. The cause of death information was used only to calculate the cause-specific mortality rate, which is the total of breast cancer deaths divided by the total female population of each country. Five-year incidence and mortality rates were reported and were age-standardized to the world standard population . STATA8.Table The overall relative survival for women diagnosed with breast cancer from 1980 to 1999 appeared better for the Swedish cohort, where the Swedish women constantly outperformed the Singaporean women at each year of follow-up Figure .The majority of Swedish patients were diagnosed with a localized cancer while only about one-half of the Singaporean women had localized cancer Table . Over thThe 5-year age-standardized relative survival ratio was used to compare the survival by the period of diagnosis between the two cohorts. In the 1980s the Singaporean women showed an improvement in survival across all stages, most marked in those with regional disease ; a smaller improvement was seen in the Swedish women with the same stage. Singaporean women diagnosed with local cancer and regional cancer had poorer survival than the Swedish women Table .In the 1990s survival among the Singaporean women with localized cancer and regional cancer improved and was comparable with the Swedish women. In addition, these Singaporean women with local cancer showed a marginal survival advantage over the Swedish cohort in the later period.Singaporean women were diagnosed with breast cancer earlier in life than the Swedish women; they were on average 10 years younger. While 52% of the Singaporean women diagnosed with breast cancer were 50 years old or younger, only 25% of the Swedish women were 50 years old or younger Table .P = 0.008), comparison between the two populations was performed stratified by the age and period of diagnosis . In Singapore, the improvement was for all women over the same period .In Stockholm, survival improved only in the premenopausal women over the two decades . In contrast, the increase in incidence in the Swedish women was only modest. The 5-year cause-specific mortality rate was constant in the Singaporean women from 1985 to 1999 Figure . The morSingaporean women diagnosed with breast cancer experienced an overall poorer survival compared with their Swedish counterparts during 1980 to 1999. This poorer survival was confounded by the stage of breast cancer, however, as survival was comparable between the two ethnically different cohorts when stratified by stage. The difference in survival was seen mainly in the regional group in the earlier period, and this converged in the more recent period. Notably, the improvement in survival over the years was marked for the Singaporean women – whereas survival was relatively stable in Stockholm in the postmenopausal women, with improvements only in the premenopausal women.Confounding factors such as registry completeness, stage migration and distribution, diagnostic improvements and lead-time bias have to be considered when analyzing trends in cancer survival. The strengths of our study include the large number of cases, from population-based registries that report high levels of reliability ,25. WomeP < 0.001), and this improved in the last 5 years of the study. This incomplete staging is probably random, however, as the age-standardized survival for the Singaporean women with unknown disease stage was comparable with the overall survival of those with stage information (data not shown). The ethnic distribution between the two groups was not different (P = 0.576), and the age distribution by the period of diagnosis was also similar except for fewer women between 35 and 54 years old being diagnosed in 1985 to 1989 (P = 0.032).Incomplete disease stage information for one-third of women in Singapore is a limitation of the present paper. To our knowledge, every effort has been put in to ensure the completeness of cancer reporting over the years. Clinical staging information, which used to be reported voluntarily, could contribute to the lack of information. There is now a follow-up mechanism by the registry, however, to obtain detailed clinical information from the clinical case notes. The proportion of unknown disease stage was hence worst in the early 1990s, only 52% with complete clinical staging for cases in 1990 to 1994 , an indicator of results of increased mammographic screening. In addition, the improvement in survival in each stage across the periods – including for those with distant metastasis, albeit small (Figure This restructuring coincided with a time trend towards less advanced tumors being diagnosed, where a small but definite increase in women with localized disease and a corresponding decrease in women with regional disease over the study period were observed in Singapore Table . This isl Figure  – would l Figure  suggestsAntiestrogen treatment has been well established since the 1990s. Seventy-seven percent of the Swedish women had tumors that were positive for the ER. This is in contrast to a more recent report of 55% Singaporean women from a local institution , not difUntil the 1970s Singaporean women had a mean fertility rate of approximately five children compared with two children for Swedish women ,30. ThisOther factors such as body mass index, diet, and other behavioral, cultural, environmental, or genetic differences are factors that have been known to affect incidence, but the effect on prognosis is less known , and is As advocated by Dickman and Adami, the trends in survival were interpreted in context with the incidence and mortality rates to evaluate the progress against cancer . As compThe survival of women with breast cancer in each disease stage was comparable between the Singapore and Stockholm cohorts. We hypothesize that better economic status associated with increased awareness of the disease, better access to screening routines or healthcare quality and options, seen in Stockholm and in Singapore only in the later decade, offer the main explanation for the prognostic differences and similarities.ER: estrogen receptor.The authors declare that they have no competing interests.PH and KSC conceived of the study. BKTT and GHL participated in the study design analysis and carried out the statistical analysis. KC, PH and KSC contributed to the epidemiological aspects and participated in the interpretation of data. All authors contributed to the writing of the manuscript, read and approved the final manuscript and gave final approval of the version to be published.


P, trend = 0.47. We also separately examined physical activity at ages 12–18, 19–34, 35–49 and ≥50 years; no significant trends were observed in any age group. These data do not support a role of physical activity in preventing breast cancer. © 2001 Cancer Research Campaignhttp://www.bjcancer.comWe conducted a case–control study of 394 women with breast cancer and 788 control women (91% response) to investigate the association of lifetime physical activity with mainly menopausal breast cancer risk. After controlling for potential confounders, the odds ratios  for increasing quartiles of lifetime physical activity were 1.00 (referent), 0.91 (0.60–1.37), 0.91 (0.60–1.39), and 1.10 (0.73–1.67), respectively;


As predicted, there was a significant decrease in cancer worry for Group 1, but not Group 2. Objective knowledge significantly improved for both Group 1 and Group 2 as expected, but not Group 3. However, there was an unpredicted decline in cancer worry for Group 3. This study supports the value of a scientific and psychosocial information pack in providing up-to-date information related to familial risk of breast cancer for long-term attendees of a familial breast cancer clinic. Further research is warranted to determine how the information pack could be incorporated into the existing clinical service, thus providing these women with the type of ongoing psychosocial support that many familial breast cancer clinics are currently lacking.This study aimed to compare the impact of two versions of a psychoeducational written intervention on cancer worry and objective knowledge of breast cancer risk-related topics in women who had been living with an increased risk of familial breast cancer for several years. Participants were randomised to three conditions: scientific and psychosocial information pack (Group 1), scientific information pack only (Group 2) or standard care control (Group 3). They completed postal questionnaires at baseline ( In recent years, growing numbers of women with a family history of breast cancer have sought genetic risk counselling to gain information about their risk of developing the disease. This increase in public awareness of family history as a risk factor for breast cancer results from scientific advances in understanding cancer genetics and growing media attention to breast cancer. Genetic testing for breast cancer susceptibility was initially expected to be widely available and informative for all women identified as being at increased risk due to family history. However, it is apparent that at present genetic testing is not an option for the majority of these women for whom a mutation in a known breast cancer susceptibility gene has not been identified in an affected relative. In the absence of proven methods to prevent or reduce the risk of breast cancer, the clinical management of these women is focused primarily on breast cancer screening.Large numbers of women under the age of 50 years are currently attending familial breast cancer clinics on a regular basis for clinical surveillance. As these women are faced with multiple chronic uncertainties regarding their personal risk of developing breast cancer and the effectiveness of risk management, the potential for adverse psychosocial effects is clear. However, psychosocial support or educational information out with regular breast cancer screening appointments  are not routinely provided for long-term attendees of many familial breast cancer clinics, including the South East Scotland familial breast cancer clinic in Edinburgh.There is limited psychosocial research in women who have been living with an increased risk of familial breast cancer for at least 2 years . This stA number of different psychological interventions have been evaluated in women with a family history of breast cancer  and objective knowledge of breast cancer risk-related topics (secondary outcome). The subsidiary aims were: to explore the impact of the interventions on breast-cancer-specific distress, general psychological distress and appraisal (i.e. perceived risk and perceived control over developing breast cancer); to evaluate the acceptability of the interventions.Scientific and psychosocial written information will reduce cancer worry to a greater extent than scientific written information alone.Scientific written information will reduce cancer worry to a greater extent than standard care alone .All three groups were assessed at baseline (prior to receiving the information pack) and postintervention (approximately 4 weeks later) by postal questionnaire.Ethical approval for the study was obtained from the local ethics committee. Women who had received breast cancer genetic risk counselling were recruited using a database for South East Scotland held in the Department of Clinical Genetics, Western General Hospital, Edinburgh. Women were included if they were currently enrolled at the Ardmillan Familial Breast Cancer Clinic, had attended the clinic for at least 2 years and had indicated in an earlier questionnaire study  that theThere is a lack of data to suggest what constitutes a clinically significant change on the Cancer Worry Scale (CWS). Therefore, the sample size calculations were based on an effect size of 0.5 which is generally regarded as moderately large , pp 291 The intervention was a psychoeducational written information pack consisting of 10 scientific and psychosocial topics of information related to familial risk of breast cancer , 6. Diagnosis and treatment of breast cancer, 7. Research at the Ardmillan familial breast cancer clinic, 8. Healthy lifestyle, 9. Worry about breast cancer, 10. Sources of information) and three published leaflets to accompany topics 3, 4 and 9 .Two versions of the information pack were evaluated: the scientific and psychosocial information pack  and the scientific information pack . The development and content of the intervention has been described in more detail elsewhere . Objective breast cancer risk was classified as: low (<17% lifetime risk), medium low (17–19%), medium (20–22%), medium high (23–25%) and high (>25%).This six-item scale , 14 items on breast cancer screening (e.g. ‘Mammography: can prevent breast cancer?’) and five items on HRT (e.g. ‘For women with a family history of breast cancer: the effect of using HRT on the risk of breast cancer is not clear?’). Participants were asked to respond ‘true’, ‘false’ or ‘don't know’. The number of correct, incorrect and ‘don't know’ responses were summed separately to produce three total scores all ranging from 0 to 36.This 15-item scale determines levels of intrusive and avoidant thoughts about breast cancer risk in the past week  using a threshold of A single item was used to measure perceived likelihood of developing breast cancer: ‘How likely do you feel it is that you will ever develop breast cancer?’. Responses were on a five-point Likert scale (very unlikely/unlikely/likely/very likely/inevitable).A single item was used which has been developed to assess perceived control over developing breast cancer in women at increased risk (‘How much control do you feel you have over whether you develop breast cancer?’)  on the GHQ-12 at either baseline or postintervention (participants having given their consent on recruitment to the study).Potential participants were sent an information sheet and consent form which they were asked to return to indicate whether they were willing to participate in the trial. Women who consented to participate were sent a baseline postal questionnaire and letter notifying them to which of the three groups they had been randomised. Restricted randomisation using the random permuted blocks method (t-tests (two-tailed), Mann–Whitney tests or χ2 tests (two-tailed). Comparisons of the three groups at baseline and postintervention were made using the Kruskal–Wallis test, the χ2 test (two-tailed) or one-way ANOVA. Changes between baseline and postintervention were assessed for each of the three groups (only for women with data at both assessments) by the Wilcoxon matched-pairs signed-rank test or the McNemar test. A number of categorical variables were recoded for the purposes of between- and within-group analysis: breast cancer risk (low or medium low/medium/medium high or high), perceived likelihood of developing breast cancer (unlikely/likely), perceived control over developing breast cancer (no control/some control), marital status (married or living with a partner/not married or living with a partner) and occupation (employed/not employed). The absence of one or more scores on a scale resulted in that total score being classified as missing. Data were analysed on an intention-to-treat basis. A significance level of 0.05 was used throughout. The data were analysed using SPSS for Windows version 10.00 (1999).Descriptive statistics were used to describe participants and to summarise feedback on the information pack. Differences between two groups (e.g. participants and nonparticipants) were analysed with independent samples Figure 1n=163) and nonparticipants (n=45) on any of the sociodemographic or objective breast cancer risk characteristics.Of the 208 women eligible to participate in the trial, 11 refused, two responded too late to be randomised  and 23 did not reply. Of the 172 women who consented to participate, were subsequently randomised and sent the baseline questionnaire, eight  did not return the questionnaire and one woman (randomised to Group 3) was excluded from the analysis because of a protocol violation (she had been discharged from the clinic prior to randomisation and therefore should not have been invited to participate). Therefore, 163 baseline questionnaires were included in the analysis. There were no significant differences between the participants at baseline (n=12) and those who completed both questionnaires (n=151) could not be tested statistically due to the small sample size. The majority of participants in Groups 2 and 3 postintervention requested to be sent the full information pack .In total, 12 women  dropped out of the study between baseline and postintervention (i.e. they did not return the postintervention questionnaire). A total of 151 women (73% of the 208 eligible women) completed both questionnaires. The number of weeks between completing the baseline and postintervention questionnaires ranged from 4.71 to 17.57 . Differences between participants who only completed the baseline questionnaire , had at least one child  and were employed . A total of 53 women (33%) had received schooling until age 16 years only whereas 27 (17%) had attended school/further education/training until age 18 years , 38 (24%) had further education or training after age 18 years and 44 (27%) were university graduates. The majority were estimated to be at medium risk of breast cancer  with 41 (27%) assigned a medium high risk, 15 (10%) medium low, nine (6%) low (these women were likely to soon be discharged from the clinic) and five (3%) high. Current objective breast cancer risk was not assessed for 13 participants, as their clinical case notes could not be located. There were no significant differences between the three groups at baseline on any of the sociodemographic or objective breast cancer risk variables.Participants ranged in age from 28–62 years . They had been attending the Ardmillan Familial Breast Cancer Clinic for 2.75–8.51 years . The majority of participants were married or living with a partner  and 3  only showed a significant decrease in scores on the CWS from baseline to postintervention. Examination of changes in individual items of the CWS for Group 3 indicated that the only item to have improved to a level approaching significance was ‘during the past month, how often have you thought about your own chances of developing cancer?’ (P=0.057).Groups 1 , objective knowledge: total incorrect , objective knowledge: total don't know . In Groups 1 and 2 only, there were significant changes between baseline and postintervention on the objective knowledge total scores. In both groups, there was a significant increase in the total number of correct responses  and a significant decrease in the number of answers participants didn't know . In Group 2 only, there was also a significant decrease in the total number of incorrect responses . Examination of the individual knowledge items revealed persistent misunderstandings in Group 1 where over half of the group postintervention still gave the incorrect response (e.g. ‘The following are designed to reduce the risk of breast cancer developing: mammography?’).There were significant differences between the three groups postintervention on objective knowledge: total correct . For Group 1, there was a significant increase in perceived control from baseline to postintervention (P=0.004). Group 2 experienced a significant decrease in perceived likelihood of developing breast cancer (P=0.039). In Group 3, there was a significant decrease in scores on the intrusion subscale , but no significant changes on avoidance and total Impact of Event Scale scores.There was a significant difference between the three groups postintervention on perceived control . The majority of participants in both groups (60–95%) thought that the information included in every topic was at least ‘a little’ new to them. A total of 45% of women in Group 1 (n=23) and 27% in Group 2 (n=13) had discussed the information in their pack with somebody else . Nine women (18%) in Group 1 and seven (14%) in Group 2 stated that someone else had read their information pack. Only 12 participants (12%) found any of the topics difficult to understand that were most frequently ‘breast cancer genetics’ and ‘genetic testing’. Similarly, only five women (5%) found any of the topics of information upsetting (e.g. ‘diagnosis and treatment of breast cancer’). Participants generally found all of the topics of information and leaflets helpful: 23–45% rated each topic as ‘very much helpful’ and 48–54% rated each leaflet as ‘quite a bit helpful’. The majority of participants reported changing or intending to change certain health behaviours since reading the information pack: greater breast awareness ; healthier lifestyle ; use of techniques to relieve worries about breast cancer . A total of 27% of participants (n=24) thought that they would obtain some of the further reading listed in the information pack. Only one woman in Group 1 (1%) and five women in Group 2 (10%) thought that there was any information not included in the pack that they would have liked to know (e.g. more details on genetic testing and new cancer treatments). A total of 92% of Group 1 (n=44) and 98% of Group 2 (n=48) thought that the information pack covered their need for information and support.In total, 80% of the women in Group 1 and 89% of Group 2 had read all of their information pack. Only two women (both in Group 1) had not read any of their information pack. There were no significant differences between Groups 1 and 2 on when they had last read any of the information pack with most women reading it more than 2 weeks ago  had read any information related to familial risk of breast cancer in the past month (i.e. about breast awareness and genetic testing).This study evaluated the impact of a psychoeducational intervention on cancer worry and knowledge in women living with an increased risk of breast cancer. Compliance with the study was good as the participation rate for completing both questionnaires was 73%.The findings of the study provide evidence to support the first hypothesis. There was a statistically significant decrease in the CWS scores of Group 1 from baseline to postintervention and no corresponding decrease in Group 2. This suggests that the psychosocial topics played a key role in the reduction of cancer worry. However, further research would be needed to identify which specific information made the greatest contribution to this reduction. The results contrast those of a previous study in American women attending breast cancer genetic risk counselling where a written newsletter in addition to counselling was not shown to reduce breast-cancer-specific distress to a greater extent than counselling alone (The results of this study do not support the second hypothesis as there was a significant decrease in CWS scores for Group 3 (the control group), but not for Group 2. This finding may be due to the control group not being contacted about the study for 4 weeks after returning the baseline questionnaire, which meant they may have experienced fewer cues to remind them about breast cancer. Indeed, the only CWS item to have decreased to a level of near statistical significance was the frequency they had thought about their own chances of developing cancer in the past month. Research has described the experiences of women at increased risk of breast cancer concerning increased anxiety prompted by a variety of breast cancer cues  and Group 2 , but remained unchanged in Group 3. Although there was a slight decrease in the number of incorrect responses of Group 1 between baseline and postintervention, it was not found to be statistically significant. As this group was sent more material to read and absorb than Group 2, it is possible that the full information pack was too lengthy to be effectively retained. This is also reflected in the fact that Group 2's knowledge seemed to improve to a greater extent than Group 1. Although Group 1 did not provide any feedback to suggest there was too much information in the pack, a smaller proportion of the women in Group 1 reported reading the whole of the information pack than Group 2. Future research could investigate the effectiveness of written information of varying detail and length to enable the development of an intervention that is of optimal benefit to these women. The persistent misunderstandings of Group 1 where over half of the group still gave the incorrect response postintervention were concerning genetic testing and screening. These findings highlight areas where the information pack could perhaps have provided more emphasis and where future interventions may choose to focus. Persistent errors in understanding of certain issues were reported in British first-time attendees of genetic risk counselling for breast cancer, despite receiving a video about breast cancer genetics and screening  was slightly lower than for those reported in women prior to attending breast cancer genetic risk counselling . A largeThis study supports the value of a psychoeducational written intervention in providing up-to-date information related to familial risk of breast cancer for long-term attendees of a familial breast cancer clinic. The scientific and psychosocial information pack reduced cancer worry and improved knowledge while meeting the subjective needs of these women. Further investigation is warranted to: undertake an economic evaluation of the intervention to determine whether it would be a cost-effective addition to the clinical service; determine how the information pack could be incorporated into the existing clinical service, thus providing these women with the type of ongoing psychosocial support that many familial breast cancer clinics are currently lacking.