This review article combines four disparate observations about Neural Tube Defects (NTDs). They are the worldwide decline in the birth incidence that began prior to prenatal diagnosis; family recurrence risks; the effect of prenatal diagnosis and termination of affected pregnancies; and the effect of folic acid. NTDs are due to many different causes . The incet al [Family studies suggest the recurrence risk for first-degree relatives of affected individuals is approximately 1 in 30. For second-degree relatives (the children of the mother's sisters and brothers) the risk is approximately 1 in 220 . Howeveret al  report tet al [et al [The third aspect, prenatal diagnosis and termination of affected pregnancies, is one that should be discussed with all women in the reproductive age range and, more importantly, with patients who have a family history of an NTD. Folic acid taken orally on a daily basis is shown to lower the occurrence and recurrence of NTDs in their own offspring and in their relatives. The Medical Research Council  was the et al  have recl [et al  demonstrl [et al  and dietl [et al ,18.When recent trends in the birth incidence of NTDs are reported, they focus additionally on the effect that folic acid has on the early second trimester prevalence of affected fetuses. As for the epidemiological studies noted above, these reports include varying types of cases; some report only "spina bifida", others "spina bifida" and anencephaly, and still others mention these two types and encephalocele with or without hydrocephalus. Some studies report only deaths due to complications in these groups of patients as stillborns, or deaths in the neonatal time period; other reports study all affected newborns, and still others cover selective or spontaneously aborted fetuses. Those that include time intervals after the introduction of intrauterine diagnosis and selective termination do not take into consideration the variations in incidence at different gestational ages and at birth, whether stillborn or live . Creasy Our data and this review clearly demonstrate the effects of intrauterine diagnosis and selective termination prior to the recommendation for supplementation and fortification of foodstuffs with folic acid. Because the reason for termination of a pregnancy is not reportable in our state and the USA, we cannot determine the effect of folic acid on the prevalence of myelomeningocele and anencephaly in first and early second trimester fetuses. Studies of the effect of folic acid in reducing the birth incidence in communities with a low incidence, and active prenatal diagnosis associated with termination of affected fetuses, require longer-term studies than published to date. The differences in data discussed above need to be considered if one is to evaluate the effect of prenatal diagnosis and elective termination as well as the effects of fortification or supplementation with folic acid. We recommend that these variables be discussed with women of reproductive age, particularly if they are relatives of a patient with an NTD. Regardless of the uncertainties, we recommend supplementation of the diet of women, beginning three months prior to an anticipated pregnancy. We recommend all women of childbearing age take at least 400 mcg of folic acid daily when they begin sexual activity. Relatives of a patient with an NTD should take 4.0 mg daily, beginning three months prior to conception.The authors declares that he has no competing interests.


Elevated pregnancy estrogen levels are associated with increased risk of developing breast cancer in mothers. We studied whether pregnancy weight gain that has been linked to high circulating estrogen levels, affects a mother's breast cancer risk.Our cohort consisted of women who were pregnant between 1954–1963 in Helsinki, Finland, 2,089 of which were eligible for the study. Pregnancy data were collected from patient records of maternity centers. 123 subsequent breast cancer cases were identified through a record linkage to the Finnish Cancer Registry, and the mean age at diagnosis was 56 years (range 35 – 74). A sample of 979 women  from the cohort was linked to the Hospital Inpatient Registry to obtain information on the women's stay in hospitals.Mothers in the upper tertile of pregnancy weight gain (>15 kg) had a 1.62-fold (95% CI 1.03–2.53) higher breast cancer risk than mothers who gained the recommended amount , after adjusting for mother's age at menarche, age at first birth, age at index pregnancy, parity at the index birth, and body mass index (BMI) before the index pregnancy. In a separate nested case-control study (n = 65 cases and 431 controls), adjustment for BMI at the time of breast cancer diagnosis did not modify the findings.Our study suggests that high pregnancy weight gain increases later breast cancer risk, independently from body weight at the time of diagnosis. Sensitivity of the breast to hormones and environmental exposures varies throughout a woman's life span . During Women whose pregnancy estrogen levels are elevated are at an increased risk of breast cancer. For example, women who took the synthetic estrogen diethylstilbestrol (DES) during pregnancy are at an increased risk of developing breast cancer , as are Adipose tissue aromatizes androgens to estrogens, and thus high body mass index (BMI) is linked to elevated estrogen levels in postmenopausal women . Some stThe study population was a historic cohort of women pregnant between 1954 and 1963 in Helsinki, Finland . The cohort was a sample gathered for a study on hormone exposure, including 2,022 exposed, 2,062 controls and 6 women with unknown hormone exposure status. Information on the cohort was collected from the maternity cards of municipal maternity centers, which are used by most pregnant Finnish women. The hormone-exposed women had been prescribed estrogen or progestin drugs during pregnancy to prevent early abortion or preterm delivery. For each exposed woman, a woman next in the maternity center file who gave birth during the same year and had not been prescribed hormones during pregnancy, was chosen as a control. The cohort has been previously prescribed in detail . There wCancer cases were identified through a record linkage to the national cancer registry until June 2001. Mortality and emigration data were obtained from the population registry until August 2001. The linkage between the cohort and the registries was based on a unique personal identification number.th gestation weeks, the time between the body weight measurements 3–300 days, and delivery between 22–45th gestation weeks. For each mother, the gestation week she gave birth was determined by using the date of estimated timing of delivery. Women who did not fulfill these criteria were excluded  and 15–40th gestation weeks (Line B) for each mother. Weight gain was extrapolated to continue until 40th gestation week for all mothers, although 22.2% of mothers delivered at 39th gestation week or before.Pregnancy weight gain was first calculated as the difference between the first and last visit to maternity center. However, this window varied considerably among included mothers (range 3–295 days). The time-period of calculated weight gain was therefore adjusted by extrapolating a line for each mother to reflect her weight increase during pregnancy. The calculations are described in detail in Additional File th gestation week, the last weight measurement was before 30th gestation week, or information on pre-pregnancy weight, weight at the first or the last visit, or timing of the visits was not available. As indicated above, these subjects were excluded from the analyses.For mothers for whom both Line A  and Line B  were available, total pregnancy weight gain was calculated by adding the extrapolated weight gains from both periods. Thus, total pregnancy weight gain could be extrapolated only for 2,089 women. Cases and controls (66.5% vs 65.0%) did not differ concerning the number of available weight measurements. For the rest of the women, either the first weight measurement was later than 242 vs. 21.8 kg/m2, p < 0.001), older at first birth , had more children during index pregnancy , and were more often exposed to estrogen or progestin drugs . Their children were shorter  and weighed less , suggesting that excluded mothers' pregnancy weight gain might have been lower. It is probable that exclusion of these women had no major effect on the findings.We compared the characteristics of the mothers who were excluded  to the characteristics of the mothers in the final study population for whom total pregnancy weight gain could be determined . The two groups were similar in regard to breast cancer incidence, age at menarche, height and the frequency of visits to a private doctor. However, the excluded mothers were older , heavier  that included all breast cancer cases with data on pregnancy weight gain (n = 123). For each case, we chose seven randomly selected controls (n = 856) who were born in the same year as the case. These 979 women were linked to the Hospital Inpatient Registry to obtain information on the women's stays in hospitals. 117 cases were identified with a hospital visit in average 0.4 months after breast cancer diagnosis , and of these cases information on body weight and height was available for 65 (53% of 123 cases). Among the controls, 699 had been a patient in a hospital at a similar age than their respective cases (maximum difference +/-5 years), and 431 of them had weight and height available in the hospital archives .The breast cancer cases with no information on later body weight did not differ from the cases used for the nested case-control analysis. The controls with no information on later body weight were approximately 1.5 years older at the time of the hospital visit than the controls included to the study (p = 0.027).2-test for proportions. The incidence of breast cancer per 100,000 person years was counted by groups of 5 kg pregnancy weight gain, tertiles of pregnancy weight gain and tertiles of postpartum weight retention. Person years were calculated from the delivery to the diagnosis of breast cancer or other endpoint including death, emigration or end of the study.Statistical significance of possible differences in baseline characteristics of the study population, pregnancy weight gain and postpartum weight loss and weight retention by tertiles of pregnancy weight gain was tested by using analysis of variance for continuous variables and χThe association between pregnancy weight gain and breast cancer risk was further examined using a Cox regression model. Total pregnancy weight gain was included as a categorical covariate (tertiles) in the model. Age at menarche, age at first birth, age at index pregnancy, BMI before pregnancy, and parity (at index birth) were all used as continuous covariates in the model. Postpartum weight retention 51 days after delivery (mean) was later added to the model.The incidence of breast cancer was counted and the Cox regression model was carried out also separately for pre- and postmenopausal breast cancers. Information on the age at menopause was not available. Therefore all women were expected to have menopause at the age of 50 years.In the case-control study, weight and BMI change between pre-pregnancy and at the time of later hospital visit were compared between the tertiles of pregnancy weight gain . A Cox regression model that included later BMI was also used to analyze the data.In the cohort, 123 (5.9%) women developed breast cancer during the mean follow-up of 38.9 years. The mean age at diagnosis was 56.0 years (range 35–74). Background characteristics and index pregnancies are described by tertiles of pregnancy weight gain in Table Weight development during and after pregnancy is presented by tertiles of pregnancy weight gain in Table 2 and the mean total extrapolated weight gain during pregnancy was 13.3 kg (range -5.0–33.1 kg) in our cohort. Average pregnancy weight gain (and range) was 13.1 kg (-3.0–33.1) among primiparas, 13.5 kg (1.9–30.7) among women who gave birth to their second child and 13.2 kg (-5.0–32.4) among women who gave birth to at least their third child. The incidence of breast cancer by 5 kg categories of total pregnancy weight gain is shown in Table The mean BMI before pregnancy was 21.8 kg/m -5.0–32. among woth gestation week, results were similar than in the whole cohort (results not shown).All analyses were initially carried out separately for pre- and postmenopausal breast cancers. The results for postmenopausal women were similar to the results for the whole cohort (results not shown). The incidence of premenopausal breast cancer was too low for statistical analysis and pre- and postmenopausal breast cancers were not separated further in the analyses. When these analyses were restricted to mothers who delivered after 39th gestation weeks) and later pregnancy weight gain (15–40th gestation weeks). Early pregnancy weight gain was not associated with breast cancer risk. The impact of later pregnancy weight gain was similar to the impact of total weight gain, but more modest (results not shown).The incidence of breast cancer was calculated separately for early . The results did not either change when adjusted additionally for the year of index birth. The increased breast cancer risk in the highest tertile of pregnancy weight gain was found only for postmenopausal breast cancer . The RR for premenopausal cancer was 1.00 . However, the number of premenopausal breast cancer cases with the information on all variables in the model was too low (n = 25) to yield sufficient power.No statistically significant differences in breast cancer risk were observed between the tertiles of postpartum weight retention, determined approximately 51 days after delivery Table .Later age at menarche was marginally related to a decreased risk of breast cancer . Mother's age at the time of first pregnancy or at the index pregnancy, parity at index birth or BMI before pregnancy were not statistically significantly associated with the risk of breast cancer. The results were similar when height and weight were used as separate variables in the model, instead of BMI.Lower pre-pregnancy BMI was associated with higher weight gain during pregnancy (p < 0.001) and higher postpartum weight retention (p = 0.003), but not with postpartum weight loss. The differences in the incidence of breast cancer were not statistically significant between the pre-pregnancy BMI-categories.Women who gained at least 15 kg weight during pregnancy had a higher BMI at the time of later hospital visit (29 years after pregnancy in average) than women who gained <11 kg weight during pregnancy (p = 0.021) . In the Cox regression model, women's later BMI at the time of diagnoses was not associated with breast cancer risk . Further, results relating to pregnancy weight gain and breast cancer risk were not altered by adding data on later BMI to the model  published their most recent recommendations for pregnancy weight gain in 1990 . The recAn increase in breast cancer risk was seen mostly in women who were diagnosed with this disease after age 50 and thus were postmenopausal. However, the number of premenopausal breast cancers was low in the cohort, and we cannot exclude the possibility that pregnancy weight gain may also increase the risk of premenopausal breast cancer.Data generated in epidemiological studies rarely provide causal relationships. We propose four different mechanisms that may link high pregnancy weight gain to a later increase in breast cancer risk. First, weight retention in women who gained excessive amounts of weight during pregnancy may have persisted into their postmenopausal years. Women prone to postpartum weight retention might also be prone to long-lasting weight gain after pregnancy , and higAnother alternative is that women who gained an excessive amount of weight during pregnancy may have had higher pregnancy hormone and growth factor levels than women who gained within the recommended range, stimulating the growth of existing malignant cells in the breast, leading to development of a detectable tumor. Several studies have shown that markers of high pregnancy estrogen levels increase mother's breast cancer risk ,9-12,16.It is known that high hormone levels increase the proliferation of normal breast cells that then is accompanied by increased genomic instability and accumulation of DNA adducts ,32. ThusFinally, known and unknown causes of breast cancer may have confounded the results. For example, these causative factors might be more common in women who gain excessive amounts of weight during pregnancy or they caused women to gain excessive amounts of weight during pregnancy. A theoretical example is a gene mutation/polymorphism that could both make a woman more prone to gain weight during pregnancy and increases breast cancer risk.Methodological limitations have to be considered when interpreting the results, and they include high rate of exclusion and an exposure to estrogenic drugs during pregnancy. Of the 4,090 women available for the study, 48.9 % were excluded for reasons listed in Figure Some women in our cohort had been exposed to synthetic estrogens during pregnancy to avoid a threatening miscarriage, and this exposure might have affected the results. However, it was the initial reason for obtaining information from pregnant women, and we found no effect of the drug exposure on the incidence of breast cancer. We are not aware of any other cohort that could be used to assess the link between pregnancy weight gain and breast cancer risk, but if such a cohort becomes available, and it is not potentially compromised by high rate of exclusion of subjects or an exposure to drugs during pregnancy, the present results can be either confirmed or nullified. Follow-up of "old" cohorts similar to ours is rarely possible, making our study relatively unique.Another area of potential source for errors is the variability in time period between the weight measurements during pregnancy (range 3–295 days), requiring us to extrapolate the pregnancy weight gain for each woman. This step also has been successfully used in other studies . A furthFinally, in the case-control study that determined the impact of body weight at the time of diagnosis on breast cancer risk, information on this weight was obtained only for 53% of the cases and 50% of the controls. However, the direction of bias rising from exclusion may have diluted the effect, rather than caused it.In conclusion, our findings suggest that excessive pregnancy weight gain increased later risk of developing breast cancer. This association needs to be further confirmed in prospective studies.diethylstilbestrol – DES; body mass index – BMIThe author(s) declare that they have no competing interests.TK: PhD student who collected and put together all the material for the study, managed the data and did statistical analysis, and participated in writing the manuscript.MG: Participated in statistical analysis of the data and writing the manuscript.EH: Collected the original data base of pregnant women and was in charge of linking the data base to cancer registry, participated in statistical analysis planning and writing the manuscript.RL: Generated the idea of testing the hypothesis in the Hemminki data base, and participated in all stages of the study and in writing the manuscript.LH-C: Generated the hypothesis, obtained funding for the study, and was in charge of writing the manuscript.The pre-publication history for this paper can be accessed here:Calculation of line a and line b for each mother.Click here for file


Several family structure-related factors, such as birth order, family size, parental age, and age differences to siblings, have been suggested as risk factors for schizophrenia. We examined how family-structure-related variables modified the risk of schizophrenia in Finnish families with at least one child with schizophrenia born from 1950 to 1976.We used case-sibling design, a variant of the matched case-control design in the analysis. Patients hospitalized for schizophrenia between 1969 and 1996 were identified from the Finnish Hospital Discharge Register, and their families from the Population Register Center. Only families with at least two children  were included in the analysis. Conditional logistic regression with sex, birth cohort, maternal schizophrenia status, and several family-related variables as explanatory variables was used in the case-sibling design. The effect of variables with the same value in each sibship was analyzed using ordinary logistic regression.Having a sibling who was less than five years older , or being the firstborn  predicted an elevated risk, but having siblings who were more than ten years older predicted a lower risk .Several family-structure-related variables were identified as risk factors for schizophrenia. The underlying causative mechanisms are likely to be variable. Several factors relating to family structure have been suggested as risk factors for schizophrenia. They include sibship size, number of older siblings, birth order in the sibship, age difference to older siblings, and age-at-onset, and sex of the affected siblings. These family-related risk factors may provide useful hints about the nature of environmental and genetic risk factors for schizophrenia .In several studies, siblings of female probands have had a higher risk of developing schizophrenia than siblings of male probands in several studies, with the number of cases varying from 123 to 500 . The effThere are mixed results about the effect of birth order on risk. Two studies reported lowest risk for the firstborns ,10, and The number and age of older siblings at the time of birth is hypothesized to be connected to the risk of schizophrenia through infection pressure. In a Swedish register-based study (270 cases), having siblings who were 3–4 years older was associated with increased risk (relative was 2.02) . The DanAll risk factors concerning birth order, family size, number of older or younger siblings, and paternal and maternal age are correlated. For example, the number of older siblings is dependent on both the individual's birth order and family size, which are connected to maternal age. If all these correlated variables are not in the model simultaneously, spurious associations may be found. Therefore, a large, population-based data set that contains a sufficient number of sibships with variable structures is needed to analyze family-related variables. Our aim was to investigate which of these variables were risk factors for schizophrenia in Finland among those who were born between 1950 and 1976.Using the Finnish Hospital Discharge Register of Finland, we obtained information on all hospitalizations with a diagnosis of schizophrenia . The information was sought for all Finns born between 1950 and 1976 for the period between 1969 and 1996. Sibship was defined as a group of individuals having the same mother. Since many of the variables we examined are related to maternal characteristics, we considered it essential that each sibship has the same mother. It should be noticed that generally the mother has a stronger influence on the child than the father especially in early childhood: e.g. mother's womb provides the fetal environment, and after birth the mother has more of a close physical relationship to the child through breast feeding. Siblings and parents of the probands were identified using the data from the Population Register Centre, and their information was then linked back to the Hospital Discharge Register to obtain data on relatives' hospitalizations. Only those who were born between 1950 and 1976 were qualified as probands, but their younger siblings were included in analyses as family members.We assumed our ascertainment was complete, because the two registers used, the Population Register and the Finnish Hospital Discharge Register, are nationwide and accurate . The relAltogether, we identified 17549 sibships with 35481 siblings, of whom 31004 were born between 1950 and 1976. There were 12 siblings in the largest family, and the highest number of cases in one family was six  women. In the 1966 and 1986 Northern Finland birth cohorts, primiparity was a risk factor for having a low birth weight infant and for perinatal mortality . In an eOur results concerning the effect of paternal and maternal age are not comparable to previous studies -18, becaConsistently with a recent meta-analysis , the risOur results showed that the higher was the age-at-onset of the first proband in the family, the lower was the siblings' risk Tables  and 2, wA case-sibling design has some limitations. It can only provide approximate estimates of relative risk. In our analyses only families with two or more siblings were informative, and therefore our results are not applicable to one child families. However, whether matching was taken into account or not did not largely affect the results.Our study was based on a nationwide, representative sample of patients with schizophrenia and their siblings, and our sample size was considerably larger than in any of the previous studies. Register-based information is not as accurate as information based on face-to-face interview, but Finnish registers are quite reliable. The two registers we used, the National Population Register and the National Hospital Discharge Register, are nationwide. The National Hospital Discharge Register covers all public and private hospitals in Finland, and the National Population Register registers all Finnish citizens. However, as information on parents enabling the identification of sibships first appeared in the Population Register only in 1974, sibship data may be more accurate in the younger cohorts. Information in both registers is accurate. Some proportion of siblings of the study population are really half-siblings, but even in this case, the case-sibling design is applicable, because it does not assume that familial aggregation is due to a genetic mechanism. When entries in the National Hospital Discharge Register were compared with data on hospital case notes, the primary diagnosis in the register and hospital case notes was identical in 99 percent of cases for schizophrenia and in 98 percent of cases for all mental disorders -22,37.We investigated concurrently several family-related factors which independently have been suggested to be risk factors for schizophrenia. We were able to verify some of the previous associations, while others were refuted. The risk factors we identified probably have different underlying causative mechanisms. For example, the risk associated with being the firstborn might be explained by increased risk to obstetric complications, while the combination of decreased risk among females but increased risk among siblings of female probands might be explained by genetic factors. The risk factors we identified should be studied further in samples that include more detailed information on possible causative factors, such as infections and obstetric complications.The author(s) declare that they have no competing interests.JH participated in the design of the study, performed the data-analysis and drafted the manuscript. JS participated in the design of the study, and the drafting of the manuscript. JL participated in the design of the study and its coordination. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


We decided to investigate, in a group of patients from a geographical area with a low incidence of breast cancer, whether HER-2/neu positive tumours are correlated with established or suspected risk factors for breast cancer and thus to identify distinct subgroups of high risk women.Several researchers have claimed that classification of tumours on the basis of HER-2/neu protein, estrogen and progesterone receptor expression were performed using immunochemistry. Odds ratios and 95% confidence intervals were determined by chi-square test and logistic regression analysis. Case-case odds ratios were calculated in order to measure the risk heterogeneity between HER-2/neu+ and HER-2/neu-tumours. Separate analyses were performed for premenopausal and postmenopausal women and according to estrogen receptor status.This study analysed data from patients who attended the Breast Unit at the University Hospital of Heraklion, Crete, Greece between 1996 and 2002. 384 women with primary invasive breast cancer were compared with 566 screened women who were referred to the Unit and had not developed breast neoplasm by the time the data were analysed. Risk factor data were obtained from each subject by personal interviews using a structured questionnaire. The detection and scoring of the HER-2/neu stratification, an increased breast cancer risk was associated with only four of the factors examined: use of oral contraceptives , use of HRT , an age at first full pregnancy more than 23 years  and body mass index more than 29 kg/m2 . Additionally, a history of abortion or miscarriage  was correlated with a decreased risk of breast cancer. In the case to case comparison only BMI >29 kg/m2 revealed a relative connection that was stronger with positive than with negative HER-2/neu tumours . This may indicate evidence of heterogeneity of a rather significant degree for this factor. In the ER negative group an age at first full pregnancy >23 years and a BMI >29 kg/m2 were associated with an increased risk in both HER-2/neu groups, but the association was significantly stronger for the latter factor in the positive HER-2/neu tumours .In multivariate analysis without HER-2/neu+ versus HER-2/neu-breast tumours, with the exception of increased BMI. Further innovative studies with larger sample sizes are needed to examine how the status of these potentially modifiable breast cancer risk factors interacts with biological markers such as HER-2/neu oncoprotein.Our study did not confirm that the established or putative hormonal breast cancer risk factors differ regarding their relations with HER-2/ Indeed,survival . In addi lesions . As a regenesis. ,7-9.neu overexpression or amplification may define a subset of breast cancer in which the net effect of a risk factor could be rather more obvious and its impact on breast cancer development more clear [On the other hand, the contribution of even well established breast cancer risk factors to the aetiology of carcinogenesis in the breast remains obscure, ill-defined and tenuous, mostly because of the existence of different pathways for the initiation and the evolution of a breast tumour . In ordere clear ,7,8.neu overexpression could indicate either that a HER-2/neu alteration is the way that this risk factor evolves into the carcinogenesis or that there is a parallel interaction between them that leads to breast tumour initiation and development. Since the data in the literature supporting the above hypothesis are few and conflicting, we decided to investigate, in a group of patients from a geographical area with a low incidence of breast cancer, whether HER-2/neu positive tumours are correlated with established or suspected risk factors for breast cancer and thus to identify distinct subgroups of high risk women.Thus, a close correlation of a risk factor with HER-2/This study analysed data derived from the database of the Breast Unit of the Department of Surgical Oncology at the University General Hospital of Heraklion on the island of Crete, Greece. The study considered all women who were consecutively diagnosed with primary, invasive breast cancer in our unit from 1996 to 2002. Subjects of other races, ethnicity, with residence outside Crete or diagnosed with DCIS or LCIS were excluded. Finally, 384 women, all originating from the island of Crete, were eligible for analysis.An age-stratified random sample of 566 women was used as a control group, derived from the Breast Unit's database of screened patients who had not developed breast cancer after a median follow up period of 40 months (range 12–92 months). Personal interviews were conducted with each woman during her first visit (both patients and controls) by a consultant or a senior resident. The interview followed a structured questionnaire, which did not change during the study period. Anthropometric measures were also made during the first visit.Women were classified as postmenopausal if their menstrual cycles had ended naturally at least 12 months before the interview or from surgery or radiation therapy at any age. Those who reported not having menstrual cycles for the last 10 months were considered as perimenopausal and were combined with premenopausal women for the purpose of our analysis.2 vs. BMI>29 kg/m2, median value for the study population) and radiation history of the chest (yes/no).The following variables were analysed for all patients and controls: residence , age at interview (≤ 50 and >50 years), age at menarche (≤ 12 and >12 years old), age at first full birth (<23 vs. ≥ 23 years old), parity , lactation (yes/no), use of medications to suppress lactation (yes/no), abortions and miscarriages (yes/no), age at menopause for postmenopausal women (≤ 50 and >50 years old), use of HRT for more than 2 months (yes/no), use of oral contraceptives for more than 2 months (yes/no), family history of breast cancer in a first degree relative (yes/no), history of benign breast disease (yes/no), obesity on the day of the interview  and in 377 (98.17%) of the 384 interviewed cases for the immunohistochemical detection of HER-2/Immunohistochemistry with the monoclonal antibody CB11 , at a dilution of 1/50 with incubation period of 60 min, was performed using the OPTIMAX automated system with the Super Sensitive Link-Label Detection System RTU Multilink AP/Fast Red, QA200OXE , following antigen retrieval by microwave pre-treatment at 500 Watts for 3 × 5 min in citrate buffer . Sections from breast cancer of known positivity were used as positive controls. Negative controls were processed by omitting the primary antibody and substituting non-immune serum. Scoring was based on the criteria recommended by DAKO A/S for the HercepTest . Only meThree (3) μm-thick sections taken on negatively-charged (SuperFrostPlus) slides were dewaxed in xylene, and rehydrated through graded alcohols. Following antigen retrieval by microwave pre-treatment at 500 W for 3 × 5 min in citrate buffer , estrogen receptor (ERa) and progesterone receptor (PR) expression was detected by immunohistochemistry using the same automated system and detection kit as above, and primary monoclonal antibodies to ERa (DAKO M7047) and PR (Biogenex code # MU 328-UC) at dilutions of 1/50 and 1/20, respectively, with incubation time 60', at room temperature. Positive and negative controls were processed as above. Positive nuclei counting was performed at a final magnification of 400× . After scanning at a final magnification of 100× for locating the areas with highest density of ER+ or PR+ carcinoma cell nuclei (hot spots), a 40X/¥/0.17 WD 0.65 objective lens was used for cell counting. All carcinoma cells in three hot spots per immunostained slide were evaluated by two pathologists working simultaneously, though independently, and the mean of the two independent counts was considered the final counting value for each field and hot spot. The ratio of the ER+ or PR+ carcinoma cell nuclei was recorded separately for each of the hot spots. The final immunoreactivity index (score) was calculated as the mean percentage of ER+ or PR+ carcinoma cell nuclei in the three hot spots. Specimens were interpreted as positive for ER or PR if at least 10% of the cells demonstrated nuclear staining of any intensity of reactivity, from 1+ to 3+. Staining intensity was graded as negative (0), weak (1+), intermediate (2+) or strong (3+), and reported separately. A mean value of intensity was assigned for specimens in which the staining intensity varied from field to field, and/or from hot spot to hot spot.2) test. A p value <0.05 was defined as significant. The potential association between breast cancers stratified by HER-2/neu status and well known predisposing factors was further investigated by using a stepwise logistic regression analysis (backward LR), testing the independent effect of breast cancer risk factors (independent variables) on breast cancer (dependent variable) for all women and also separately for premenopausal and postmenopausal females. In addition, we undertook further stratification with estrogen receptor status by using the same multivariate logistic regression model. These patient-controls odds ratios helped us to detect the pattern of heterogeneity and to explore plausible aetiological correlations between patient subgroups. Additionally, case-case odds ratios were calculated in order to measure the risk heterogeneity between HER-2/neu+ and HER-2/neu-tumours. It seems that the departure of the OR from unity can reveal the degree of heterogeneity between these subgroups [Odds ratios (OR) and 95% CI , as approximators of relative risk, were calculated to measure the association of the groups of breast cancer and the risk factors, using the chi-square , use of HRT , an age at first full pregnancy more than 23 years  and body mass index more than 29 kg/m2 . Additionally, a history of abortion or miscarriage  was correlated with a decreased risk of breast cancer. However, the number of oral contraceptive and HRT users was too small for reliable estimates of risk.Risk factor distributions in breast cancer patients and matched controls are presented in table neu protein overexpression. HER-2/neu positive tumours were not related with menopausal state, age at interview, tumour size, grade and stage, nodal and estrogen receptor status, but there was a modest positive association between HER-2/neu and progesterone negative tumours.Tumour characteristics of breast cancer patients are shown in table premenopausal group of women, an increased risk for HER-2/neu-tumours was observed for those women who reported an age at first full pregnancy ≥ 23 years , a BMI>29 kg/m2, first degree family history  or use of oral contraceptives , while an age at menarche less than 12 years was the only factor which slightly increased the risk in premenopausal HER-2/neu+ patients . Abortion played a less protective role (p = 0.068) for HER-2/neu-breast cancer in premenopausal than in postmenopausal women (p = 0.038). However, the intercase comparison in the premenopausal subgroup showed an evidence of heterogeneity only for the HER-2/neu+ women who had ever had an abortion , while use of oral contraceptives  and a positive first degree family history  showed a stronger association for HER-2/neu negative tumours.Subgroups of women stratified by menopausal status were further analysed by a multivariate stepwise logistic regression model adjusted for the remaining variables table . In the all women and the postmenopausal groups of patients due to the large sample size. Patients with an age of menarche ≤ 12 years , first degree family history , use of HRT  or OC  were at increased risk of developing HER-2/neu-breast cancer only, although the significance of the latter two factors was of little value due to the limited sample size. On the other hand, an age at first full pregnancy ≥ 23 years and a BMI greater than 29 kg/m2 increased breast cancer risk independently of HER-2/neu status, while a history of abortion decreased risk in the same way. In the case to case comparison only BMI >29 kg/m2 revealed a relative stronger connection with positive than with negative HER-2/neu tumours  and this may indicate an evidence of heterogeneity of a rather significant degree for this factor. The stronger association between an age at menarche ≤ 12 years, use of HRT and negative as opposed to positive HER-2/neu status did not reach statistical significance .The results of logistic regression were identical for neu positivity and obesity already shown in the analysis so far. In more detail, although BMI >29 kg/m2 elevated risk for both ER negative and positive tumours independently of HER-2/neu status, the association was significantly stronger for positive HER-2/neu tumours in the ER negative group . Additionally, in the same group an age at first full pregnancy >23 years revealed an increase of risk in both HER-2/neu groups, while first degree family history , age at menopause >50 years  and birth of 1–2 children  elevated risk for HER-2/neu negative tumours only. In the ER+ group of women the direct comparison between cases revealed no associations with any factor at all, while abortion showed a protective pattern against breast cancer which expressed estrogen receptors independently of HER-2/neu status.A different stratification pattern of our study's population is presented in table neu oncoprotein. In fact, increased BMI elevated risk in both groups, but the comparison between HER-2/neu+ and HER-2/neu- tumours revealed a much stronger association with HER-2/neu+ breast cancers.This epidemiological study, conducted in a low incidence Mediterranean population,  found thneu status can help discriminate aetiologically distinct subgroups of breast cancer cases, and none of them has identified the effect of increased BMI with HER-2/neu positive tumours [Very few studies have examined the possibility whether HER-2/ tumours ,5,7-9.neu+ tumours with an early age at first full pregnancy, we found a strong elevated risk with a late age regardless of HER-2/neu protein expression [neu+ breast cancers, while we also found this inverse association but independently of HER-2/neu status [neu+ tumours only in the premenopausal group of women. Early contraceptive use has been positively associated with HER-2/neu+ breast cancer in two studies [neu negative tumours. However, because the number of oral contraceptive (and HRT) users in this study was small, this subgroup analysis was hindered by decreased power to detect associations of any magnitude. The slightly protective effect of parity found in the age-adjusted analysis was diminished after logistic regression and did not reveal any association with HER-2/neu status, in contrast with previous findings [neu positive tumours in one study while other investigators reported opposite results [More specifically, in contrast with other investigators who have shown an elevated risk for HER-2/pression . Previouu status . Interes studies ,8, but ofindings . Breastf results ,9. Althoneu status. This inconsistency may reflect differences in study design, populations, and laboratory methodology. In this study we used immunochemistry  to assess the HER-2/neu protein overexpression, which is highly correlated with gene amplification according to previous reports [neu protein overexpression found here was within the limits reported elsewhere [Our findings have similarities and differences with respect to previous reports that examined the associations of breast risk factors with HER-2/ reports . Also, tlsewhere ,5-9.neu protein overexpression and most of the hormone-related breast cancer risk factors does not completely agree with several hypotheses which have maintained that combined estrogen and HER-2/neu activation is closely involved in the same pathway in breast cancer carcinogenesis [This lack of relationship between HER-2/ogenesis ,18.neu positive tumours in our study was high body mass index, which is an established risk factor that has an estrogen-mediated oncogenic effect on the mammary gland. More specifically, obesity is associated with higher breast cancer risk among postmenopausal women through greater lifetime exposure to higher levels of estrogens produced in adipose tissue and lower SHBG production [neu gene [neu receptor, and so promote carcinogenesis through common means [The only hormone-related factor that was found to be related with HER-2/oduction ,20. Highneu gene ,21. Accoon means ,17,18.neu-positivity and lack of hormone receptor expression in breast tumours [neu positive tumours were weakly related with the absence of estrogen receptors, although this was not statistically significant .Numerous epidemiological and experimental studies have shown the strong relationship between HER-2/ tumours ,18,22. IThe interview was conducted during the subjects' first visit to the unit and before clinical examination or any other intervention took place. This constitutes an advantage, because there was no chance that the subjects (both cases and controls) would be influenced by the diagnosis and might therefore falsely inflate the relative risk. Thus, the likelihood of recall bias is not high, improving the comparability of several covariates in both groups, and the selection bias is lessened since all subjects had taken the same route through the Breast Unit's standard routine procedures.neu status subgroup. Some caution regarding our findings is related to the size of the study group. In the analyses stratified by HER-2/neu and menopausal or ER status numbers are quite small and for some risk estimates the confidence intervals are wide and the estimates of risk unstable.Since each case group was compared with the same control group, any selection bias would be expected to have a similar effect on the estimates in the tumour subgroups. Thus, it is extremely unlikely that recall bias issues would apply only to those cases in a specific HER-2/neu+ versus HER-2/neu-breast tumours, with the exception of increased BMI. Further innovative studies with larger sample sizes are needed to examine how the status of these potentially modifiable breast cancer risk factors interacts with biological markers such as HER-2/neu oncoprotein. Their findings will provide us with greater insight into breast cancer aetiology and will help us identify any association that would help discriminate subgroups of women at higher risk.In conclusion, our study did not confirm that the established or putative hormonal breast cancer risk factors differ regarding their relations with HER-2/EGFR: epidermal growth factor receptor, HRT: hormonereplacement therapy, BMI: body mass index, SHBG: sex hormone-binding protein, ER: estrogen receptor, PR: progesterone receptor, OC: oral contraceptives.The author(s) declare that they have no competing interests.NT conceived the study, participated in its design and drafted the manuscript.ES participated in the design of the study, assisted in writing and reviewed the final article.EfS and KM scheduled and performed the laboratory analysis.NA performed the statistical analyses.VG and DDT participated in the design and coordination of the study and reviewed the final article.All authors have read, discussed and approved the manuscript.The pre-publication history for this paper can be accessed here:


It is believed that the development of gastric cancer (GC) before the age of 50 has a hereditary basis. Blood group A and history of gastric cancer in first-degree relatives have been shown to be risk factors for GC.In this case-control study, we enrolled patients with GC who were diagnosed before the age of 50. Patients who were diagnosed as having GC were selected. A total of 534 cases were found; of these, 44 diagnosed before the age of 50 were included in the case group. For the control group, 22 males and 22 females were randomly selected from the remaining subjects, who had diagnoses of GC after the age of 50. All the surviving patients and family members of the dead patients were interviewed about the history of cancer in the family and the age at which other family members developed cancer. The blood group of each subject was also obtained.forty-four cases under 50 years old (mean age: 36.2 years) and forty-four controls (mean age: 67.1 years) were enrolled in the study. At the time of the study, 59.1% of the study group and 50% of the control group were alive . In the study group, 68.1%, 13.6%, 13.6% and 4.5% had blood groups O, A, B and AB, respectively. In the control group the corresponding figures were 27.7%, 63.6%, 6.8% and 4.5%. First or second-degree relatives with cancer, including gastric (the most frequent), breast, lung, gynecological and hematological malignancies, were noted in 54.5% of the cases and 11.4% of the controls (p < 0.01). Family histories of cancer were accepted as valid provided that they were based on valid medical documents.It seems that the development of GC before the age of 50 is likely to be accompanied by familial susceptibility. Interestingly, our study showed a significant correlation between blood group O and the development of gastric cancer under the age of 50. Gastric cancer is the second most common cause of cancer-related death in the world . Its incThe reduced incidence of gastric cancer in western countries reflects a decrease in cancers arising in the distal stomach (body and antrum). In contrast, the incidence of cancer in the proximal stomach and esophagogastric junction has steadily increased, at a rate exceeding that of any other cancer except melanoma and lung cancer -13. In aIn general, familial genetic mechanisms do not play as important a role in gastric cancer as they do in e.g. colorectal cancer. Nonetheless, in some regions, a family history of gastric cancer may be a risk factor for the disease, although this might reflect environmental factors shared by members of a family . Rate coIn a review about genetic predisposition to gastric cancer, Bevan and Houlston 1999) concluded that several genes may be associated with increased risk [99 concluMany studies have addressed the correlation between ABO antigens and the development of gastric cancer, but most of these have indicated a correlation between sporadic cases of gastric cancer and blood group A. This association further supports the role of genetic factors in the development of gastric cancer . Blood tThe study was designed as a case-control study. We set up an active surveillance to identify patients with gastric cancer. Patients' records in the department of pathology in the main private referral facility in Tehran were scrutinized for gastric cancer cases between 1999 and 2003. Patients are referred here from all regions of the country and from different ethnic backgrounds and they are operated upon in the same hospital, so all the operation and pathology reports were available simultaneously. All the pathology reports were prepared and diagnosed by the same pathologists. The cases were selected from patients who were diagnosed with gastric cancer before the age of fifty. The sex-matched controls were randomly selected and enrolled from patients who were diagnosed over the age of fifty. All the patients and their family were interviewed regarding the history of gastric or other types of cancer over three generations, and the blood groups of affected members were ascertained. Family histories of cancer were accepted as valid provided that they were based on valid medical documents. The transfusion records of the operation were also used to identify the patients' blood groups.Statistical analysis was performed using the SPSS Statistical Package (version 10.0). The quantitative variables were expressed as means (minimum-maximum) when appropriate. A chi-square test was performed to ascertain the overall effect of blood group on the development of gastric cancer before the age of 50. All statistical tests were two-sided and differences at the 0.01 level were considered statistically significant.At the beginning of the study, 44 cases  under 50 years old and 44 sex-matched controls  were enrolled. Table This case control study demonstrates that hereditary factors, especially familial history of cancer and possession of blood group O, are associated with the development of gastric cancer under the age of fifty. To our knowledge, this may be the first study showing a correlation between blood group O and the development of gastric cancer in a specific category of patients.Risk factors for gastric cancers have been explored in a number of previous studies, including genetic factors such as blood group. Haenszel et al. suggested an association between gastric cancer and blood type A, supporting the view that genetic factors have a role in the development of gastric cancer . Our stuIn our study, approximately 54% of the case group had a familial history of cancer compared to 11% of the control group. This seems compatible with the findings of a population-based case-control study of stomach cancer in Warsaw, Poland. Here, the investigators interviewed 464 cases and 480 controls to evaluate the role of family history and other risk factors. A greater than threefold increase in risk was associated with a history of gastric cancer in a first degree relative (OR = 3.5), but no excess risk was seen for other forms of cancer. The risk associated with familial occurrence was not significantly modified by gender, age or ABO blood type, and did not vary with Lauren histological classification24. Despite the relatively large sample size in the Polish study, younger patients were not evaluated as a separate category. This may explain the difference between their results and ours. Furthermore, they defined "positive family history" as having a first-degree relative with gastric cancer. In contrast, we considered all types of malignancy in first and second-degree relatives; though the familial incidence of other (non-GI) malignancies in our study may reflect their higher frequency in the community rather than any genetic risk factor. The Polish study did not confirm previous results on the correlation between blood group A and gastric cancer. Moreover, another study by Parsonnet et al on 90 cases and 89 controls showed no association between ABO blood group and malignancy . In a muMatching the geographical origins of the cases and controls could have improved the power of our study by excluding ethnic factors from the study population. However, this is very difficult to achieve in such studies because there is a high rate of combinations between races in the country. In addition, the sample size was too small for such effects to be excluded. However, there were no significance differences between the two groups in respect of the origins of the subjects.In conclusion, our results show that familial history of cancer, and hereditary factors including blood group, have a role in the development of gastric cancer in young patients. The role of environmental factors may be more important in older patients and can be considered in future studies.The authors declare that they have no competing interest.MY designed and assisted in the conduction of the study, analyzing of the data and draft the manuscript.NR, FS, RB and YJ assisted in the conducting and designing the study and interview with the study cases as well as drafting manuscript.AM and MA assisted in analyzing of the study and conducting interviews.AA and MH reviewed and approved the pathology reports of the patients and case collecting.RM supervised the study scientifically and executively and assisted in drafting the manuscript.All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


It has been shown in our previous work that breast asymmetry is related to several of the known risk factors for breast cancer, and that patients with diagnosed breast cancer have more breast volume asymmetry, as measured from mammograms, than age-matched healthy women.In the present study, we compared the breast asymmetry of women who were free of breast disease at time of mammography, but who had subsequently developed breast cancer, with that of age-matched healthy controls who had remained disease-free to time of the present study. The study group consisted of 252 asymptomatic women who had normal mammography, but went on to develop breast cancer. The control group were 252 age-matched healthy controls whose mammograms were also normal and who remained free of cancer during the study period. Breast volume was calculated from the cranio-caudal mammograms for each group, and the relationships between asymmetry, established risk factors and the presence or absence of breast cancer were explored.The group who went on to develop breast cancer had higher breast asymmetry than controls  1.10, 2.04; relative asymmetry 1.09, CI 1.01, 1.18), increased incidence of family history of breast cancer, lower age at menarche, later menopause, later first pregnancies and a higher frequency of high risk breast parenchyma types. Conditional logistic regression analysis showed that breast asymmetry, height, family history of breast cancer, age at menarche, parenchyma type and menopausal status were significant independent predictors of breast cancer. When age at menopause was included in the model for the subgroup of post-menopausal women, absolute breast fluctuating asymmetry (FA) and relative breast FA remained significant effects.Breast asymmetry was greater in healthy women who later developed breast cancer than in women who did not. Humans, in common with most other vertebrates, show bilateral symmetry in paired morphological traits such as ear size, digit length and breast volume. Perfect symmetry may be disturbed by a number of intrinsic and extrinsic factors, including the secretion of hormones such as oestrogen ,2. The sFA in such traits as ear size and digit length is related to health measures including body mass index (BMI) in young women and men . HoweverBreast cancer is the most common malignancy among women in Western society, with incidence rates continuing their upward trend, increasing by 70% cent since 1971, and by 15% in the 10 years to 2000 in England. It is the most common cause of cancer death in women . There aBreast volume FA, as measured from mammograms, is related to several of the known risk factors for breast cancer ,2, and pThis was a retrospective study on women who had mammography during the period 1979 to 1986. The original study collected detailed breast cancer risk factor data from a total of 12,942 women self-referred to the Liverpool Breast Screening Unit between 1979 and 1986, the aim being to establish whether mammographic parenchymal patterns were associated with hypothesised risk factors for breast cancer ,27. The Breast volume (ml) was calculated from cranio-caudal mammograms of the 252 patients who had subsequently developed breast cancer, and 252 age-matched controls, as breast FA increases with age .The method employed for breast volume calculation from the mammograms was that used by Katariya and colleagues  and Hoe 2hπ rwhere r was half the breast width and h the breast height. FA of breast volume was calculated by subtracting the right volume measure from that of the left (L - R).FAs from linear measurements of mammograms have been shown to correlate significantly with FAs calculated from direct measurements of the breasts . SubjectMammograms had been rated for increasing density of breast parenchyma tissue by a single reporting radiologist using the classification of Wolfe  where: NThe data were analysed using the SPSS v.13 and Stata v.8.2 statistical packages . Using two conditional logistic regression models (for absolute breast FA and relative breast FA) the crude and adjusted relative odds of breast cancer were estimated for each breast FA variable and other known potential risk factors and confounders, together with 95% confidence intervals (95% CI). For the purposes of this analysis, because a 1 ml change in breast volume FA is very small, the results for breast volume FA are presented as the change in relative odds for a 100 ml change in breast volume FA. In addition, given the strong effect of age at menopause on breast cancer risk, this was controlled for in additional models containing only post-menopausal women. The effect of age at first pregnancy was modelled using another set of conditional logistic regression models for the subset of women who had ever been pregnant, and again age at menopause was controlled for in an additional analysis including only post-menopausal, ever pregnant women. A case-control stratum was excluded from the analysis if the information for either the cases or controls was not known for the variable in question. The variables were entered together into the multivariable regressions, and then factors that did not contribute significantly after consideration of other potential cofactors were removed from the model only if they were found not to influence the FA associations. The models containing all risk factors are presented and only minor changes to the parameter estimates in the main findings resulted if insignificant terms were removed.The mean age at diagnosis of breast cancer was 55.20 . The mean interval between mammography and presentation of the tumour was 6.44 years . There were 120 right sided tumours, 119 left sided tumours, 6 cases of bilateral disease and 7 where the side was not recorded.r1) of FAs calculated from mammograms were calculated on a random sub-set of 20 mammograms from the study and showed highly significant r1 values . Ideal FA shows a normal distribution with a parametric mean at zero [g1 and kurtosis g2) [Repeatabilities   and deviosis g2) ,33. The The characteristics of the cases and controls are detailed in Table The difference in breast asymmetry between left- and right-sided tumour groups was not significant. For those women who developed left-sided tumours, the right breast was larger at the time of mammography in 57 cases, and the left larger in 57 cases. For those who developed right sided tumours, there were 53 larger right breasts and 64 larger left. The mean BMI was similar for the cancer group and the controls, as was mean breast volume.Many of the risk factors for breast cancer are interrelated, so the cancer group and controls were entered into a conditional logistic regression analysis, firstly with independent variables absolute breast FA, family history, mean breast volume, BMI, height, age at menarche, number of pregnancies, menopausal status and parenchyma type and secondly with relative breast FA in place of absolute FA. Right breast parenchyma type was used in these analyses as there was little difference between the left and right parenchyma types. The regression results are shown in Table n = 51), breast asymmetry had a significant inverse relationship with time from mammogram to diagnosis .Table These findings are the first evidence that breast asymmetry is higher in healthy women who are free of breast disease but subsequently go on to develop breast cancer than in women who remain disease-free in the same period. Both absolute and relative breast volume asymmetries were higher in the group that went on to develop cancer than in the control group. This is consistent with our previous findings that women with already diagnosed breast cancer had higher breast FAs than healthy women . The resOf the other breast cancer risk factors examined, family history, age at menarche and parenchyma type showed significant differences between the two groups. The cancer group had lower menarchal age than the controls, and a higher frequency (75% of the cancer group compared to 64% of controls) of high risk parenchymal patterns (P2 and DY). The probability that a woman will develop breast cancer is dependent in part on the type and duration of oestrogen exposure, which in turn relates to many of the known risk factors for the disease. Many studies have sought to establish the importance of parenchymal patterns as a predictor of breast cancer. The majority have shown an increased risk associated with increased breast density patterns ,34-39. TFA is a measure of one component of fitness, namely, the developmental stability of an individual. Stable development is difficult to maintain if an individual has harmful mutations, or if normally bilaterally symmetrical structures undergo rapid periods of growth ,43. The In this study, we found that breast asymmetry was greater in the healthy women who subsequently developed breast cancer than those who remained disease free. Asymmetrical breasts could prove to be reliable indicators of future breast disease in women and this factor should be considered in a woman's risk profile.BMI = body mass index; FA = fluctuating asymmetry; IQR = inter-quartile range.The authors declare that they have no competing interests.DS carried out the data collection and drafted the manuscript. DS and JTM both participated in the design of the study and undertook the asymmetry measurements. DS, JTM and GL performed the statistical analysis. JTM and GL helped to draft and edit the manuscript. All authors read and approved the final manuscript.


The reduced mortality rate from breast carcinoma among women offered screening mammography is demonstrated after 15–20 years of follow-up. However, the assessment of 5-year overall and event-free survival could represent an earlier measure of the efficacy of mammography screening program (MSP).All cases of breast cancer diagnosed in the Province of Modena between years 1996 and 2000 in women aged 50 to 69 years, were identified through the Modena Cancer Registry (MCR). Stage of disease and treatment information were obtained from clinical records. All the events occurring up to June 30, 2003 were retrieved by experienced monitors. Five-year overall and event-free survival were the principal end-points of the study.During a 5-year period, 587 primary breast cancers were detected by the MSP and 471 primary breast cancers were diagnosed out of the MSP. The screen-detected breast cancers were smaller, more likely node negative, with low histological grade, low proliferative activity and positive receptors status. Furthermore, the breast cancer diagnosed through the MSP more frequently received a conservative surgery. The 5-year survival rate was 94% in the screen-detected group, versus 84% in the other group (p = 0.0001). The rate of 5-year event-free survival was 89% and 75% for the MSP participants and not participants, respectively (p = 0.0001).Our data confirm a favourable outcome of screen-detected breast cancers in terms of five-year overall and event-free survival, which reflect the good quality assurance parameters of the MSP. Finally, a cancer registry should be implemented in every area covered by screening programs. Breast cancer is the most common malignancy in women, both in the developed and developing world, with annual incidence rates ranging from 11.8 per 100,000 in eastern China to 86.3 per 100,000 in North America,3. Part In the current study we report the results of an exhaustive review of all breast cancers diagnosed between October 1995 and December 2000 in the Province of Modena, in women 50–69 years of age, assessing the rates of small tumors, the patterns of care and the relapse-free, event-free and 5 years survivals in women exposed to screening and in women diagnosed over the same time-interval out of screening.st December, 1999 to 31st December, 2000, 48,928 women aged 50–69 years participated in the screening mammography, with an adhesion rate of 61.3%. Up to 31st December, 2000, 43,479 women adhered to the program (adhesion rate of 65.9%).In October, a population-based mammography screening program (MSP) began in the Province of Modena, one of the nine provinces of the Emilia-Romagna region . On december 1996, the population of Modena was 613,625, which by the end of 2000 had increased to 632,626, with a density of 235 inhab./sq.km. Out of this population, 80,210 were healthy women, aged 50–69 years. Briefly, all the asymptomatic female residents in the Province of Modena aged 50–69 years were invited to participate in a biannual bilateral two-view screening mammogram, with no direct financial charge to the participant. Women already affected by breast cancer were not invited. From 31in situ breast cancer diagnosed between 1st January, 1996 and 31st December, 2000 who did and did not the MSP. All breast cancer cases were identified as International Classification of Disease (9th revision) rubric 174. For every case, data on histology, staging at presentation (based on the 2003 UICC-TNM classification [All the patients with an age ranging from 50 to 69 years diagnosed with breast cancer in the period 1996–2000 were selected from the Modena Cancer Registry (MCR), which has operated since 1988 and collects all new cases of cancers occurring in residents in the Province of Modena. A cross linkage between data from MSP and MCR allowed the identification of cases with invasive or Overall survival was defined as the time from surgery until death from any cause, and cancer-free survival was defined as the time from surgery until the appearance of the first recurrence of cancer, a second cancer, or death from any cause. Survival was estimated by the Kaplan-Meier method, and any differences in survival were evaluated with a stratified log-rank test.®) was used for all calculations. Differences were considered to be statistically significant when the P value was 0.05 or less. All statistical tests were two-sided.The Statistical Package for Social Sciences , TNM stage (I vs others), chemotherapy (performed or not performed) and hormonal treatment (performed or not performed). Hazard ratios (HR) and 95% exact mid-P confidence intervals (CI) were calculated and the Wald method was used for the significance test.As shown in table andci,s = xi,s - tsts is the mean difference in follow-up time duration between the two groups at stage s, for i from 1 to Nsd and for j from 1 to Nnsd, xi,sd and xj,nsd are durations of follow-up for each woman at each stage in each group and Nsdand Nnsd are the population size of screen and not screen-detected groups. Then, the correct follow-up time  is obtained by subtracting the stage-specific difference from the follow-up time in the screen-detected group.where st January, 1996 and 31st December, 2000, 587 (55%) new breast cancers were detected among women aged 50–69 attending the MSP. The detection rate was 10%0 (428) in the first, 6.5%0 (152) in the second and 7.9%0 (7) in the third round. The recall rate was higher at the first round (8.2%) than in the second (6.4%) and the third round (4.5%). In the same time frame 471 (45%) breast cancers were diagnosed out of the MSP. Out of these cases, 337 had had a carcinoma before they were first invited by the MSP, 56 arose in women excluded by the screening program since they had a mammography in the last year and 78 arose in women that refused to participate in a screening program. Out of 587 screen-detected breast cancers, which also include 34 interval cases developed in women who had participated in the screening program in the past, 482 (82%) were infiltrating and 105 (18%) were in situ carcinomas. Out of the 471 breast cancers non-screen-detected, 429 (91%) were infiltrating and 42 (9%) were in situ carcinomas. The median age at diagnosis was 60 years in both groups. Furthermore the median age at diagnosis in women of 50–69 years in the pre-screening era was 60.5. The age-specific rate of invasive cancers diagnosed each year increased from 304.7 per 100.000 in 1996 to 380.3 per 100.000 in 2000. The age-specific rate of in situ carcinoma diagnosed each year increased from 31.9 per 100.000 in 1996 to 49.7 per 100.000 in 2000. As already reported [Between 1P < 0.0001). The screen-detected tumours were smaller sized, were more likely to be grading I-II, pathologically confirmed node negative disease and low proliferative activity. There was also a significant difference in the percentage in women with positive hormonal status .The clinical pathological factors for the two cohorts are shown in Tab. Concerning the characteristics of interval cancers, they had a mean size of 18 mm, the nodal status and the hormonal receptors were positive in 24% and 70% of cases, respectively, and the proliferative activity was high in 34% of tumours. Finally the tumours was poorly differentiated (GIII) in 45% of cases.The median follow-up was 52 months in both groups, with a 25% of patients followed for more than 66 months. Survival data were evaluated only for invasive cancers, i.e. for 482 patients exposed to screening and 429 in the non-screen exposed group. Six (1%) and thirty-nine (9%) patients were lost at the follow-up in the study and control group, respectively. At time of last follow-up 22 women had died in the screen-detected (20 for breast cancer and 2 for other causes) and 60 in the non-screen-detected group (19 for breast cancer recurrences and 41 for others causes). The overall survival rates in the two groups differed significantly on the basis of the stratified log-rank test. As expected, the majority of deaths occurred in patients with breast cancer non- screen-detected (p < 0.0001).At the time of the present analysis a total of 131 events were registered, including 75 recurrences, 10 second breast cancers, 25 different second malignancies, and 21 deaths not related to breast cancer or its treatment. We observed 48/482 (9.6%) events in the screen-detected group and 83/429 (22.6%) in the non-screen-detected group, with a statistically significant difference (p < 0.0001). A significant difference was also observed in the number of disease recurrences  and of second breast cancers   have been MSP participants. The cancers diagnosed in women within four years of the screening program were histologically more favourable , smaller (13 mm vs 19 mm) and less likely to have spread to axillary lymph nodes compared to breast cancer diagnosed out of the screening over the same time frame.Since the crude breast cancer-specific mortality rate cannot be used for an immediate evaluation of the impact of screening mammography, we have used Event-Free Survival at 5 years as a measure of success of the MSP. We considered as events local or distant recurrence of breast cancer, second breast cancer, second cancer other than breast, and death from any cause. The rate of recurrences and second breast cancers, but not of other second malignancies or deaths, was significantly lower in the screen-detected group. As a consequence we observed a statistically significant and clinically meaningful 14% improvement in the 5-year event-free survival of women diagnosed by the MSP compared with those diagnosed out of the screening (89% vs. 75%). A difference was also observed in the subset of node negative tumors, where the 5-year survival rates are 95% in the screen-detected group and 91% in the non participants to the MSP. These results correlate with data from a recent study performed by Joensuu, in which a 5-year survival rate of 97% was observed in women with node negative tumors . In addiWelch et al.  and BaumOur data clearly show that the major cause for the decreasing breast cancer mortality is the smaller tumour size, associated with the earlier detection by the MSP. Moreover, the chemotherapy was not retained as an independent prognostic factor, confirming that the magnitude of impact of chemotherapy is very likely less relevant compared to the effect of early detection. Despite that, in our series of screen-detected breast cancers, a very high rate of patients were treated with chemotherapy, even if the most used regimen was CMF.Finally, we would remark that our study was made possible and facilitated only by the existence of a population-based cancer registry in the area. Through the registry we recognized all new cases of cancers in women aged 50–69 years and achieved information on follow-up status. We consider a cancer registry an important tool for an adequate monitoring of the screening programs.In conclusion, our data show the effectiveness of the MSP in terms of early diagnosis, more favorable behaviour of the tumor and better prognosis, even if only 65% of the age-eligible female were partecipating in this program in 1996–2000. This analysis has pointed out the need and potential value of substantially increasing recruitment to the MSP to 70% or more, as achieved in other geographic areas.The author(s) declare that they have no competing interests.LC participated in the design of the study and drafted the manuscript.VEC acquired the data and performed the statistical analysis.SR participated in the design of the study.VB performed the mammographic screening.RC acquired the mammographic screening data.IR acquired the data of the Modena Cancer Registry.CC participated in the statistical analysis.AF developed the method of eliminating the lead-time and length biases.EG coordinated the Screening Mammography Program in Modena.MF designed the study and revised the final manuscript.All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Women with homozygous polymorphic alleles of catechol-O-methyltransferase (COMT-LL) metabolize 2-hydroxylated estradiol, a suspected anticarcinogenic metabolite of estrogen, at a four-fold lower rate than women with no polymorphic alleles (COMT-HH) or heterozygous women (COMT-HL). We hypothesized that COMT-LL women exposed actively or passively to tobacco smoke would have higher exposure to 2-hydroxylated estradiol than never-active/never passive exposed women, and should therefore have a lower risk of breast cancer than women exposed to tobacco smoke or with higher COMT activity.We used a case-only design to evaluate departure from multiplicative interaction between COMT genotype and smoking status. We identified 502 cases of invasive incident breast cancer and characterized COMT genotype. Information on tobacco use and other potential breast cancer risk factors were obtained by structured interviews.We observed moderate departure from multiplicative interaction for COMT-HL genotype and history of ever-active smoking  and more pronounced departure for women who smoked 40 or more years . We observed considerable departure from multiplicative interaction for COMT-HL genotype and history of ever-passive smoking  or for having lived with a smoker after age 20 .With greater control over potential misclassification errors and a large case-only population, we found evidence to support an interaction between COMT genotype and tobacco smoke exposure in breast cancer etiology. In addition to investigating breast cancer risk factors that influence lifetime exposure to estrogen (nopause) ,2, reseanopause) . It is knopause) . 16α-hydnopause) ,6 whereanopause) -9. Both nopause) -12. Mich [et al.  found th [et al. -17.The 2-hydroxylated catechol estrogen is metabolized by catechol-O-methyltransferase (COMT) into non-genotoxic methyl ethers that are excreted from the body. There are two COMT alleles, the wild-type allele is related to high activity (COMT-H), and the polymorphic allele (COMT-L) in its homozygous form is related to an approximately four-fold lower activity ,19. The This variability in methyltransferase activity related to the polymorphism has prompted research investigating the association between COMT genotype and breast cancer risk. The epidemiologic studies that have examined the association have produced inconsistent results -37. A feFour earlier studies have examined the association between COMT activity and the risk of breast cancer within sub-groups of tobacco exposure ,24,25,28We collected genetic and behavioral information on 502 cases of incident breast cancer arising in five different sites across the United States. We used a case-only design to examine the potential interaction between methylation status – as measured by COMT genotype – and active or passive smoking status among women with breast cancer. We hypothesized that women who have low COMT activity and are exposed to tobacco smoke should have an enriched concentration of 2-hydroxylated catechol estrogen, and should therefore have a lower smoking-related risk of breast cancer than women with high COMT activity. The case-only design is optimal for assessing departure from multiplicative interaction when the genotype and environmental exposure are independent of one another. This investigation is the largest case-only study to date to examine the interaction between COMT genotype and tobacco exposure history as it relates to breast cancer.The cases of female breast cancer included in this analysis were identified as parts of two study populations ,39. The Breast cancer cases were mailed introductory letters in 2001 and 2002. A trained interviewer followed the letter with a telephone call to answer questions and solicit participation. Cases who agreed to participate were sent an enrollment package containing an introductory letter, summary information about the study, a consent form, instructions for submitting a mouthwash sample, a safety-sealed sample of mouthwash, and a wide-mouth sample collection bottle. Participants collected the sample and returned it in a postage-paid box along with their informed consent. Buccal cells were precipitated by centrifugation and stored at -70°C until a batch of 90 samples had been collected. Batches were sent by overnight delivery on dry ice to Qiagen Genomics  for DNA extraction and genotyping.Qiagen genomics applied proprietary Masscode technology to measure Masscode tags, which are low molecular weight compounds linked to the DNA via a photocleavable linker. The tag is cleaved in flow into a mass spectrometer, and a Microsoft Access database converts the raw analytical data into statistically generated genotype calls. The assay has been validated in over one million genotypes. Existing primers were used to characterize COMT genotypes at the codon 158 single nucleotide polymorphism (SNP) in each buccal cell sample. The Qiagen genotyping data characterized each participant as homozygous wild-type, heterozygous, or homozygous polymorphic at the SNP.Cases were interviewed on the telephone by trained interviewers using a structured interview to obtain information on demographic characteristics, history of active and passive exposure to cigarette smoke, and known or suspected risk factors for breast cancer. Cases from the Cape Cod population were interviewed between March 1997 and March 1998. Cases from the second population were interviewed approximately forty months after their date of diagnosis to gather the variables used in this analysis. Most of the exposure information related to early life characteristics and events, so the differential delay between diagnosis and interview should have little impact on the results.We considered a woman a fast methylator if she was homozygous for the COMT-H wild-type allele (COMT-HH), an intermediate methylator if she was a heterozygote , and a slow methylator (COMT-LL) if she was homozygous for the COMT-L polymorphic allele. Women who were COMT-LL were the reference genotype for all analyses.We considered a woman an active smoker if she reported smoking 100 or more cigarettes in her lifetime. We considered a woman a passive smoker if she reported living with someone who was a smoker but was never herself a smoker. For women who reported smoking 100 or more cigarettes in their lifetime or who lived with someone who smoked, information on duration, intensity and timing of exposure to tobacco smoke (active/passive) was also collected. Women who were neither active nor passive smokers were labeled never active/never passive smokers and were the tobacco exposure reference group for all analyses.2). A woman was considered to have a first-degree family history of breast cancer (yes/no) if she reported that her mother, sister(s) or daughter(s) was diagnosed with breast cancer. We defined alcohol use according to the number of drinks a woman reported that she "usually" had before her diagnosis: non-drinker, ≤ one drink/month, few drinks/month, few drinks/week, almost every day, and unknown.In addition to smoking information, we collected information on health and behavioral risk factors including alcohol use, body mass index (BMI), family history of breast cancer, history of benign breast disease, and parity. BMI was calculated as weight divided by the square of height (kg/mWe examined departure from multiplicative interaction for the association between methylation status and exposure to cigarette smoke (gene-environment interaction) among women with breast cancer. We used logistic regression analysis in SAS  to quantify departure from multiplicative interaction. In these analyses, the odds ratios (OR) and 95% confidence intervals (CI) for the association between smoking status and methylation status estimate the departure of the gene and environment joint effect from multiplicative interaction. We examined the associations separately for active and passive smokers. We assessed the interaction between tobacco exposure and COMT genotype separately for high (COMT-HH) and intermediate COMT (COMT-HL) activity as compared to low COMT activity (COMT-LL). Women classified as both COMT-LL and never active/never passive smokers were the reference category for all analyses. We controlled for the potential influence of breast cancer risk factors including age at breast cancer diagnosis, alcohol consumption, BMI, first-degree family history of breast cancer, geographic location , and history of benign breast disease using multiple variable logistic regression. We did not assess the influence of race in the analysis since 97% of the women in our case population were white.We also evaluated departure from multiplicative interaction for variables describing duration, intensity and timing of active and passive smoking exposure. For active smokers, we examined the association between methylation status and the number of packs of cigarettes smoked per day, duration of smoking (in years), age at onset of smoking, and time since quitting. For passive smokers, we examined the duration of passive exposure (in years) and the age at first passive exposure.Among the Cape Cod population, 330 of 483 eligible cases agreed to receive a sample collection kit and the remainder refused or were unable to be contacted. Of the 330 who received a kit, 272 returned a sample and 269 samples yielded DNA that could be genotyped. Among the second study population, 372 of 410 eligible cases agreed to receive a sample collection kit and the remainder refused or were unable to be contacted. Of the 372 who received a kit, 321 returned a sample and 233 had samples that yielded DNA that could be genotyped and had the requisite interview data. In both studies, 56% of eligible participants were genotyped and included in the analysis. The proportion of smokers among non-participants was not significantly different than among participants in either study population. The mean age was greater among non-participants than among participants , reflecting greater losses-to-follow-up and refusals among older women. Age was not, however, associated with genotype among the participants. Furthermore, the proportions of participants who were COMT-LL, COMT-HL, COMT-HH, active smokers, and passive smokers did not vary significantly with their site of enrollment. Among the genotyped controls in the Cape Cod study, the odds ratio associating methylation status (homozygotes versus heterozygotes) with exposure to tobacco smoke  equaled 1.10 (p = 0.80). This finding is consistent with earlier studies ,40 in whThere were 502 cases of breast cancer available for analysis. Eighty women 16%) were COMT-LL, 248 (49%) were COMT-HL and 174 (35%) were COMT-HH. Table 6% were CWe observed moderate departure from multiplicative interaction for COMT-HL genotype and history of ever-active smoking  but minimal departure from multiplicative interaction for COMT-HH genotype and history of ever-active smoking  compared to COMT-LL genotype , smoked for 40 or more years , or started smoking before age 22 . The departure from multiplicative interaction was greater than the null for women with COMT-HH genotype when they smoked one or more packs per day  or smoked for 40 or more years .We observed considerable departure from multiplicative interaction for COMT-HL genotype and history of ever-passive smoking  and moderate departure from multiplicative interaction for COMT-HH genotype and history of ever-passive smoking  compared to COMT-LL genotype Table .Estimates for the departure from multiplicative interaction between COMT genotype and the measures of intensity, duration and timing of passive smoking were generally of higher magnitude for COMT-HH activity than COMT-HL activity. The departure from multiplicative interaction was greater than the null for women with COMT-HL genotype who were passively exposed to tobacco smoke for 40 or more years  and who first lived with a smoker after 20 years of age . Similarly, the departure from multiplicative interaction was greater than the null for women with COMT-HH genotype who were passively exposed to tobacco for 40 or more years  and who first lived with a smoker after 20 years of age .O-methyltransferase (COMT) activity and active/passive exposure to cigarette smoke and only the second to remove women passively exposed to tobacco smoke from the reference group, as has been recommended for studies of the relation between tobacco smoke and breast cancer risk [This is the largest case-only study to evaluate the interaction between catechol-cer risk . Our anaThe analyses assessing the departure from multiplicative interaction between the genotypes and intensity, duration or timing of active and passive exposure to cigarette smoke yielded estimates consistent with a promotional role in breast cancer etiology for exposure to tobacco smoke. The relative risk of breast cancer among women with the COMT-HL or COMT-HH genotype who were actively or passively exposed to tobacco smoke for a long duration was higher than expected from the independent effects of the genotype and smoking exposure. These data are consistent with following hypothesis for the interaction between COMT genotype and exposure to tobacco smoke. First, tobacco smoke exposure increases 2-hydroxylation of 17β-estradiol , which let al. [et al. [Only a few studies have assessed potential modification by cigarette smoking on the risk of breast cancer for women with COMT-LL as compared to COMT-HH. Lavigne et al.  found an [et al.  found th [et al. ,28 or paPrevious studies of the association between COMT genotype and breast cancer risk have compared women with one or more copies of the polymorphism to a reference group of women homozygous for the wild-type allele ,24,25,28The genotyping procedures employed in this analysis have superior accuracy compared to PCR-RFLP techniques employed in three of the previous studies ,24,25. COur analysis of interaction using case-only data provides greater control over the impact of potential misclassification errors, because there are only two variables central to the analysis that are susceptible to misclassification – COMT genotype and smoking status. As described above, the impact of misclassification is less predictable in three of the previous case-control analyses. It is therefore possible that previous studies evaluating the interaction of COMT genotype and exposure to tobacco smoke in relation to breast cancer risk may have generated biased estimates of interaction. By using a more accurate genotyping method and by implementing a case-only design, this analysis provides a more valid assessment of departure from multiplicative interaction between COMT genotype and exposure to tobacco smoke in relation to breast cancer.Weighing against this advantage of the case-only design is the limitation that only departure from multiplicativity can be assessed. Many epidemiologists weigh departure from additive interaction more heavily, arguing that the additive scale corresponds better to the biologic meaning of synergistic effects . A furthFinally, these results must be interpreted with the following limitation in mind. Only 56% of eligible cases were available for analysis. Participation was not related to smoking status and although participation was related to age, age was not related genotype. We expect that the selection of participants introduced no substantial bias, although we acknowledge that our study of breast cancer survivors may have influenced the estimates of effect in ways that we are unable to anticipate.This large case-only analysis is only the second to investigate the interaction between COMT genotype and exposure to tobacco smoke as related to breast cancer risk while removing women passively exposed to tobacco smoke from the reference group. The combination of the most complete genotyping data and the large case-only design provided important advantages in this study, whose results suggest potential interaction between COMT genotype and tobacco smoke exposure in breast cancer etiology, perhaps related to the coaction of smoking and genotype on the concentration of 2-hydroxylated catechol estrogen. Weighing against this interpretation is the potential for an unanticipated bias to have arisen by selection of breast cancer survivors from among the incident cases.COMT = catechol-O-methyltransferaseCOMT-HH = homozygous non-polymorphicCOMT-HL = heterozygousCOMT-LL = homozygous polymorphicSNPs = single nucleotide polymorphismsBMI = body mass indexOR = odds ratioCI = confidence intervalaOR = adjusted odds ratio estimate of departure from multiplicativityThe author(s) declare that they have no competing interests.TL conceived of the study, collected genotyping samples, participated in data analysis, and drafted the manuscript. BB conducted data analysis and drafted the manuscript. JW analyzed the genotyping and drafted the manuscript. AA collected interview data from the Cape Cod population and drafted the manuscript. All authors read and approved the final manuscript.


SULT1A1) is involved in the metabolism of procarcinogens such as heterocyclic amines and polycyclic aromatic hydrocarbons, both of which are present in tobacco smoke. We recently reported a differential effect of N-acetyltransferase (NAT) 2 genotype on the association between active and passive smoking and breast cancer. Additional investigation of a common SULT1A1 genetic polymorphism associated with reduced enzyme activity and stability might therefore provide deeper insight into the modification of breast cancer susceptibility.Sulfotransferase 1A1 . Risk for breast cancer with respect to several smoking variables did not differ substantially between carriers of the *2 allele and noncarriers. However, among NAT2 fast acetylators, the odds ratio associated with passive smoking only  was elevated in homozygous carriers of the SULT1A1*1 allele but not in carriers of the SULT1A1*2 allele .The overall risk for breast cancer in women who were carriers of at least one SULT1A1 genotype in itself modifies breast cancer risk associated with smoking in women up to age 50 years. In combination with NAT2 fast acetylator status, however, the SULT1A1*1/*1 genotype might increase breast cancer risk in women exposed to tobacco smoke.We found no evidence that the  Epidemiologic evidence linking cigarette smoking to increased risk for development of breast cancer is mounting . In aN-acetyltransferase (NAT) 2 genotype on the association between active and passive smoking and breast cancer risk ) and another covered by the anchor probe (G654A [Glu218]). Forty-eight such samples were additionally digested with ) and anohe *3 Met3Val and NAT2 gene was also carried out by capillary-based PCR followed by melting curve analysis. The method was described in detail previously quinoline (IQ) and 2-amino-1-methyl-6-phenylimidazo pyridine (PhIP) have been detected in human breast milk indole, another abundant HCA, was strongly enhanced in a Salmonella typhimurium strain expressing SULT1A1 quinoline; NAT = N-acetyltransferase; OR = odds ratio; PCR = polymerase chain reaction; PhIP = 2-amino-1-methyl-6-phenylimidazo pyridine; SULT = sulfotransferase.CI = confidence interval; HCA = heterocyclic aromatic amine; IQ = 2-amino-3-methylimidazo [4,5–The author(s) declare that they have no competing interests.CL performed the statistical analysis and drafted the manuscript. AR was responsible for the genotyping assays, and contributed to study design and manuscript preparation. SK conducted the re-contacting of study participants in 1999 and participated in the statistical analyses. JCC conceived the study and supervised the project. All authors read and approved the final manuscript.