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Research Exposure to diagnostic radiation and risk of breast cancer among carriers of BRCA1/2 mutations: retrospective cohort study (GENE-RAD-RISK) BMJ 2012; 345 doi: 10.1136/bmj.e5660 (Published 6 September 2012) Cite this as: BMJ 2012;345:e5660 Breast cancer Epidemiologic studies Screening (oncology) Clinical diagnostic tests Radiology More topics Radiology (diagnostics) Fewer topics Article Related content Article metrics Anouk Pijpe, postdoctoral research fellow1, Nadine Andrieu, senior researcher234, Douglas F Easton, professor5, Ausrele Kesminiene, study coordinator6, Elisabeth Cardis, professor7, Catherine Noguès, oncogeneticist8, Marion Gauthier-Villars, oncogeneticist9, Christine Lasset, oncogeneticist10, Jean-Pierre Fricker, oncogeneticist11, Susan Peock, study coordinator5, Debra Frost, research assistant5, D Gareth Evans, professor12, Rosalind A Eeles, clinical cancer geneticist13, Joan Paterson, clinical geneticist14, Peggy Manders, postdoctoral research fellow115, Christi J van Asperen, clinical geneticist16, Margreet G E M Ausems, clinical geneticist17, Hanne Meijers-Heijboer, clinical geneticist18, Isabelle Thierry-Chef, researcher6, Michael Hauptmann, statistician1, David Goldgar, senior researcher19, Matti A Rookus, senior research fellow1, Flora E van Leeuwen, professor1 on behalf of GENEPSO, EMBRACE, and HEBON1Netherlands Cancer Institute, Department of Epidemiology and Biostatistics, Plesmanlaan 121, 1066 CX Amsterdam, Netherlands2Institut National de la Santé et de la Recherche Médicale, Unité U900, Paris 75248, France 3Institut Curie, Research Centre and Service of Biostatistics, Paris 75248 4Ecole des Mines de Paris, Paris Tech, Fontainebleau 77300, France 5Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge CB1 8RN, UK6International Agency for Research on Cancer, Section of Environment and Radiation, 69372 Lyon 08, France7Centre for Research in Environmental Epidemiology (CREAL), IMIM (Hospital del Mar Research Institute), CIBER Epidemiologica y Salud Pública (CIBERESP), Doctor Aiguader, 88, 08003 Barcelona, Spain8Institut Curie, Hôpital René Huguenin, 92210 Saint-Cloud, Paris9Institut Curie, Service d’Oncogénétique, 75005 Paris10Centre Léon Bérard, 69008 Lyon11Centre Paul Strauss, 67065 Strasbourg, France12Department of Genetic Medicine, St Mary’s Hospital, Manchester M13 9WL, UK13Oncogenetics Team, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, Surrey SM2 5PT, UK14Department of Clinical Genetics, East Anglian Regional Genetics Service, Addenbrookes Hospital, Cambridge CB2 0QQ15Department of Human Genetics, Radboud University Nijmegen Medical Centre, 6525 GA Nijmegen, Netherlands16Department of Clinical Genetics, Leiden University Medical Centre, 2333 ZA Leiden, Netherlands17Department of Medical Genetics, University Medical Centre Utrecht, 3584 CX Utrecht, Netherlands18Department of Clinical Genetics and Human Genetics, VU University Medical Centre, Amsterdam19Department of Dermatology, University of Utah School of Medicine, Salt Lake City, Utah 84132, USACorrespondence to: F E van Leeuwen f.v.leeuwen{at}nki.nlAccepted 10 August 2012AbstractObjective To estimate the risk of breast cancer associated with diagnostic radiation in carriers of BRCA1/2 mutations.Design Retrospective cohort study (GENE-RAD-RISK).Setting Three nationwide studies (GENEPSO, EMBRACE, HEBON) in France, United Kingdom, and the Netherlands,Participants 1993 female carriers of BRCA1/2 mutations recruited in 2006-09.Main outcome measure Risk of breast cancer estimated with a weighted Cox proportional hazards model with a time dependent individually estimated cumulative breast dose, based on nominal estimates of organ dose and frequency of self reported diagnostic procedures. To correct for potential survival bias, the analysis excluded carriers who were diagnosed more than five years before completion of the study questionnaire.Results In carriers of BRCA1/2 mutations any exposure to diagnostic radiation before the age of 30 was associated with an increased risk of breast cancer (hazard ratio 1.90, 95% confidence interval 1.20 to 3.00), with a dose-response pattern. The risks by quarter of estimated cumulative dose <0.0020 Gy, =0.0020-0.0065 Gy, =0.0066-0.0173 Gy, and =0.0174 Gy were 1.63 (0.96 to 2.77), 1.78 (0.88 to 3.58), 1.75 (0.72 to 4.25), and 3.84 (1.67 to 8.79), respectively. Analyses on the different types of diagnostic procedures showed a pattern of increasing risk with increasing number of radiographs before age 20 and before age 30 compared with no exposure. A history of mammography before age 30 was also associated with an increased risk of breast cancer (hazard ratio 1.43, 0.85 to 2.40). Sensitivity analysis showed that this finding was not caused by confounding by indication of family history.Conclusion In this large European study among carriers of BRCA1/2 mutations, exposure to diagnostic radiation before age 30 was associated with an increased risk of breast cancer at dose levels considerably lower than those at which increases have been found in other cohorts exposed to radiation. The results of this study support the use of non-ionising radiation imaging techniques (such as magnetic resonance imaging) as the main tool for surveillance in young women with BRCA1/2 mutations.IntroductionExposure to ionising radiation is an established risk factor for breast cancer in the general population, with exposures in childhood and adolescence conferring a greater risk than exposure in adulthood.1 As BRCA1 and BRCA2 are involved in the repair of DNA double strand breaks,2 3 4 5 6 which can be caused by ionising radiation, it has been hypothesised that carriers of BRCA1/2 mutations might have increased radiosensitivity. Results of the few studies7 8 9 10 conducted so far on diagnostic radiation and risk of breast cancer among carriers have been inconsistent. Explanations for this inconsistency include differences in age at exposure and study limitations such as the investigation of a single type of diagnostic procedure (such as only chest radiography7 8 or only mammography9 10), a retrospective design with potential recall and/or survival bias,7 8 9 10 or sometimes relatively small numbers.8 9 In some countries the screening protocol for BRCA1/2 mutation carriers now recommends the avoidance of mammographic screening before age 30 and advises the use of non-ionising radiation imaging techniques (such as magnetic resonance imaging (MRI)) as the main tool for surveillance at young ages.We report on the BRCA1/2 mutation carrier study arm of the GENE-RAD-RISK project, a large European cohort study designed to examine whether variations in specific DNA repair genes increase the risk of breast cancer associated with radiation. Although the present study has a retrospective design, the association between diagnostic radiation and breast cancer risk in BRCA1/2 mutation carriers is unlikely to be investigated prospectively in the near future. This is because incident case numbers are not expected to increase rapidly because of the increasing uptake of prophylactic surgery among unaffected BRCA1/2 mutation carriers and the relatively short follow-up since DNA testing for BRCA mutations became available (1995), together with the fact that many newly identified carriers were tested because they (already) had breast cancer.MethodsStudy populationThe present study included 1993 women who were tested in a clinical setting (that is, at a clinical genetic centre), identified as carrying a pathogenic BRCA1 or BRCA2 mutation, and aged 18 or older. Women were recruited into the GENE-RAD-RISK cohort study in 2006-09 and were participants in three large ongoing national cohort studies of carriers in France (GENEPSO; n=716 (36%)), the UK (EMBRACE11; n=688 (35%)), and the Netherlands (HEBON12; n=589 (30%)).Each participant completed a standardised questionnaire (response rate 78%; see supplementary table A). Diagnoses of breast cancer were recorded through linkage with national registries or medical records.Exposure to diagnostic radiationParticipants reported their history of exposure to diagnostic radiation in a detailed questionnaire containing indication based questions on lifetime exposure to fluoroscopy, conventional radiography of the chest/shoulders, mammography, computed tomography of the chest/shoulders, and other diagnostic procedures that use ionising radiation (such as bone scans) involving the chest or shoulders. Each section of the questionnaire provided a detailed description of the procedure and its most common indications. For fluoroscopy, radiography, and mammography, we asked about ever/never exposure, age at first exposure, number of exposures before age 20, and at ages 20-29 and 30-39, and age at last exposure. For each of the other exposure types, participants reported the indication, age at exposure, and number of exposures.We estimated the cumulative breast dose as an approximation of breast dose in units of Gy. Nominal estimates of breast dose for fluoroscopy, radiography, mammography, and computed tomography were derived from a literature review of published studies and institutional reports assessing radiation dose delivered to the breast from radiological examinations and expert judgment by ITC, AK, FvL, and AP (table 1?). When possible, we restricted the selected studies and reports to European studies performed on large samples, representative of patients and radiology services. The cumulative breast dose estimate was the sum of the age and calendar specific number of self reported diagnostic procedures multiplied by nominal estimates of breast dose.View this table:View PopupView InlineTable 1 Estimated doses of radiation (in Gy) to breast of diagnostic radiographic procedures by time period Statistical analysisWe used a Cox proportional hazards model to calculate adjusted hazard ratios of breast cancer and 95% confidence intervals, with age (in years) as time scale and cumulative radiation exposure from diagnostic procedures as a time dependent variable lagged by five years to exclude procedures that could have been performed because of a diagnosis of breast cancer and exclusion of radiation dose that probably did not contribute to induction of breast cancer. All analyses were stratified for gene (BRCA1 and BRCA2), birth cohort (<1955, 1955-61, 1962-68, >1968), and country (UK, France, and the Netherlands), and clustered on family. Standard Cox regression leads to biased estimates of the hazard ratio because the women in this study were selected from high risk families qualifying for genetic testing. The disease status might therefore have increased the likelihood of ascertainment leading to an oversampling of affected women. To correct for this potential bias (testing bias), we used the weighted regression approach described by Antoniou et al.13 With this procedure, individuals are weighted according to certain sampling probabilities such that the observed weighted incidence rate agrees with the true incidence rate in a similar but unselected cohort. The value of the weight depends on the age interval in which the person’s follow-up ends—that is, weights were assigned for each mutation and age category based on incidence rates from a population based study.14 Case weights were consistently lower than 1, indicating that cases are oversampled in the study. By the weighted regression approach, hazard ratios are typically shifted away from the null value (=1) at the cost of some power (wider confidence intervals).We defined two types of analytical cohorts: the entire cohort and a subcohort. In the entire cohort analysis, follow-up started at birth and ended at the date of the first diagnosis of breast cancer (n=848), other cancers excluding basal cell carcinoma (n=96), date of bilateral prophylactic mastectomy (n=234), or completion of the questionnaire (n=815), whichever occurred first. There were 78?074 person years of observation. In all retrospective cohort studies that use questionnaire data, affected women who survived until questionnaire completion could fill out the questionnaire only because they have survived. If the exposure under investigation is associated with worse survival, cases without exposure would be more strongly represented, introducing bias to the null. Although little is known about the influence of exposure to ionising radiation, low or high dose, on overall survival and breast cancer specific survival in carriers, there are indications that breast cancer associated with radiation has a distinct, less favourable, gene expression profile.15 To correct for potential survival bias arising from the exclusion of exposed carriers who died from breast cancer long before questionnaire completion, we carried out our main analyses on relatively recent cases—that is, carriers who received diagnosis of a breast cancer or who were censored within the five years before completion of the questionnaire. Follow-up was counted only during this five year period and with a new set of period specific weights. This subcohort analysis contained a total of 1122 participants, 174 of whom had breast cancer. There were 4484 person years of observation. Although based on smaller numbers, we consider the results of the subcohort to be the most valid and have therefore presented these results in the main text. We have presented the results from the entire cohort in supplementary tables and briefly summarise them in the results section.As exposure to diagnostic radiation was reported in decades of age, we assumed that exposures were equally distributed across each decade, taking into account ages at first and last exposure. This resulted in the following categorisation for cumulative number of exposures: 1=0.5-1.4; 2=1.5-2.4; 3-4=2.5-4.4; >4=4.5 or more. The estimate of cumulative breast dose was categorised based on quarters of cumulative dose at age 40.We observed no violation of the proportional hazards assumption by any variable. Tests for trend of number of exposures were conducted by assigning to each individual the median of the number of exposures in each exposure category (rather than the individual’s reported number of exposures) and including this as a continuous variable in an unweighted procedure specific model. Missing values in ever/never exposure (<11%) and covariates (<1%) were coded as an additional category. Among carriers with any exposure to diagnostic radiation, missing values for age at first exposure (<15% for fluoroscopy and radiography and <10% for mammography) and last exposure (<5%) and number of exposures (<21% for fluoroscopy and radiography and <7% for mammography) were imputed by age period, with the mean age and number of exposures of women for whom complete data were available. Linear excess relative risks per Gy were estimated by unweighted conditional logistic regression with SAS code.16 We adjusted the risk estimates for the analyses of cumulative breast dose for parity and menopausal status. We adjusted analyses of radiography and mammography for age at menarche, parity, and menopausal status. Other potential confounding factors, including age at first full term pregnancy and breast feeding, did not change the log(hazard ratio) estimates by more than 10% and were omitted from final models. We examined effect modification by country, BRCA1 versus BRCA2, birth cohort, and attained age. Two sided P<0.05 was considered significant. Analyses were performed with Stata/SE 11.0 (StataCorp).ResultsIn the entire cohort, 43% (n=848) of carriers had received a diagnosis of breast cancer (table 2?; of these 89% (n=755) were confirmed by medical records or linkage with national registries. There was no difference between cases and unaffected carriers in age at diagnosis of breast cancer and age at censoring (mean 39.5 (SD 7.4) and 39.7 (SD 7.4) for cases and unaffected carriers respectively; P=0.601). Women with breast cancer, however, were older at questionnaire completion (49.7 (SD 8.6) v 42.1 (SD 10.5), P<0.001). In general, there were no differences in characteristics between the entire cohort and the subcohort, though the carriers in the subcohort were on average younger at questionnaire completion than those in the entire cohort (41.1 (SD 9.7) v 50.7 (SD 8.8), P<0.001).View this table:View PopupView InlineTable 2 Characteristics of entire cohort (n=1993) of BRCA1/2 mutation carriers and subcohort (n=1122) of relatively recent cases. Figures are numbers* (percentage) of participantsRadiography was the most common diagnostic procedure; 48% (n=919) of carriers reported ever having had a radiograph while 33% (n=649) had ever had a mammogram (table 3?). The median numbers of procedures before age 40 were 2.5 for radiography and 2.4 for mammography. The mean age at first mammogram was 29.5 (SD 5.8). Only a small proportion (<5%) of carriers were ever exposed occupationally, during pregnancy or during breast feeding, to computed tomography or other diagnostic radiation procedures (table 3). None of the carriers had received radiotherapy before the end of follow-up because cancers other than breast cancer were censored. The mean estimated cumulative breast dose from fluoroscopy, radiography, mammography, and computed tomography combined was 0.0140 Gy and ranged from 0.0005 to 0.6130 Gy (interquartile range 0.0020-0.0174 Gy).View this table:View PopupView InlineTable 3 Exposure to diagnostic radiation in entire cohort (n=1993) and subcohort (n=1122). Figures are numbers* (percentage) of participantsTable 4 shows the results of the analyses on cumulative breast dose and risk of breast cancer ?. When compared with no exposure, any exposure before age 30 was associated with an increased risk (hazard ratio 1.90, 95% confidence interval 1.20 to 3.00). We also observed a pattern of increasing risk with increasing dose; for a cumulative dose estimate of more than 0.0174 Gy we observed an almost fourfold increased risk of breast cancer (3.84, 1.67 to 8.79). A similar increased risk was observed for exposure before age 20 even after a lower dose of more than 0.0066 Gy (3.16, 1.19 to 8.39). There was no evidence of an increased risk of breast cancer associated with exposure at ages 30-39. The unweighted excess relative risks per Gy for exposures before ages 40 and 30 were 14.76 (P=0.138) and 29.81 (P=0.100).View this table:View PopupView InlineTable 4 Analyses of estimated cumulative breast dose of diagnostic radiation and risk of breast cancer for subcohort (n=1122) of BRCA1/2 mutation carriersIn the analysis of specific diagnostic procedures we observed a trend of increasing risk of breast cancer with increasing number of radiographs before age 20 (P=0.041 for trend) and a non-significantly increased risk of breast cancer after more than two fluoroscopies before age 20 (hazard ratio 2.01, 95% confidence interval 0.71 to 5.71, P=0.102 for trend) compared with no exposure (table 5 ?). Furthermore, there was a non-significantly increased risk of breast cancer after exposure to mammography before age 30 (1.43, 0.85 to 2.40, P=0.040 for trend). We observed an almost twofold risk increase for exposure to more than four radiographs before age 30 (1.83, 0.84 to 4.00, P=0.012 for trend) and for more than four radiographs at ages 30-39 (2.04, 0.85 to 4.90, P=0.101 for trend; data not shown), though this latter category included only six cases. We found no other associations between exposure at ages 30-39 and risk of breast cancer.View this table:View PopupView InlineTable 5 Analyses on different types of diagnostic procedures by age period and risk of breast cancer for subcohort of 1122 BRCA1/2 mutation carriersThe risk estimates presented in tables 4 and 5 were not materially affected by inclusion of the estimates for each age period (that is, <20, 20-29, and 30-39 years) in the same model or by adjustment for occupational exposure. The results of the procedure specific analyses did not change when we included different exposure types in one model. The results did not differ by country (data not shown). Use of a two or 10 year time lag did not materially affect the results (data not shown).A strong family history of breast cancer could be an indication for mammographic screening at a young age. We investigated this potential bias away from the null by a subgroup analysis of the cumulative breast dose in carriers who never had a mammogram before age 30 (table 6?). This resulted in a similar association compared with the complete model (table 4).View this table:View PopupView InlineTable 6 Analyses of estimated cumulative breast dose of diagnostic radiation before age 30 and risk of breast cancer for BRCA1/2 mutation carriers who had never undergone mammographyWe investigated whether there was a difference in the association between exposure to diagnostic radiation and risk of breast cancer for BRCA1 and BRCA2 carriers. Among BRCA1 carriers, any exposure before age 30 was associated with an increased risk (hazard ratio 2.83, 95% confidence interval 1.59 to 5.04) and the following pattern of dose-response emerged: risks for cumulative dose estimates of <0.0020 Gy, =0.0020-0.0065 Gy, =0.0066-0.0173 Gy, and =0.0174 Gy were 2.46 (1.27 to 4.77), 2.45 (1.02 to 5.90), 2.72 (0.99 to 7.44), and 5.00 (1.96 to 12.74), respectively. For BRCA2 carriers we did not observe an association in the subcohort, but this analysis was limited because of the small number of cases. The P value for interaction between gene and ever versus never exposure before age 30 was 0.631. We also evaluated risk associated with exposure before the age of 30 by attained age below and above the median of 40 to examine the effect of time since exposure. We observed a non-significant higher risk for the younger attained age group compared with the older age group (1.87 (1.13 to 3.10) v 1.64 (1.00 to 2.68), respectively). We observed no effect modification by birth cohort (P>0.05 for interaction; data not shown).In the entire cohort, a history of any exposure before age 30 was also associated with a significantly increased risk (hazard 1.39, 1.12 to 1.73) but no dose-response emerged (supplementary table B). The association with exposure before age 20 was similar (1.37, 1.11 to 1.68), with some indication of a dose-response. There was no evidence of an increased risk of breast cancer associated with exposure at ages 30-39. The unweighted excess relative risks per Gy for exposures before ages 40 and 30 were 3.90 (P=0.121) and 5.54 (P=0.107). In the analysis of specific diagnostic procedures we found no significant associations between specific procedures and risk of breast cancer (supplementary table C). Based on only a few cases, exposure to computed tomography before age 30 seemed to be associated with increased risk of breast cancer (2.36, 0.71 to 7.88).DiscussionPrincipal findingsIn this large European study, exposure to diagnostic radiation before age 30 was associated with an increased risk of breast cancer in BRCA1/2 mutations, at dose levels considerably lower than those at which increases have been found in other cohorts exposed to radiation. We estimated the cumulative breast dose from various exposures to diagnostic radiation and observed increases in risk for exposure before age 30, even for a relatively low dose category (that is, below 0.0066 Gy0. No association with risk of breast cancer was apparent for exposure at ages 30-39.Comparison with other studiesTwo previous studies among women with BRCA1/2 mutations who had undergone mammography observed no association with risk of breast cancer.9 10 This could be because of the relatively high age at first mammogram, which was on average 35, while in our study it was 29.5 (SD 5.8) years. We observed a 1.4-fold increased risk of breast cancer after mammography before age 30 with a (non-significant) pattern of dose-response (table 5). We were concerned that this latter association might be attributed to confounding by indication—that is, self selection for early mammography in carriers with a strong family history of breast cancer. This was not the case as the association between cumulative breast dose and risk of breast cancer remained after we excluded carriers who had had mammography (table 6). Confounding by indication on the other diagnostic procedures is highly unlikely.Two other studies have reported an association between self reported exposure to chest radiography and risk of breast cancer in BRCA carriers.7 8 Risks were particularly high among those exposed before age 20. Some of our participants (21%) were also included in one of these previous studies, the IBCCS.7 In their subcohort, the IBCCS reported a 1.8-fold increased risk while we observed a 1.4-fold non-significantly increased risk (hazard ratio 1.38, 95% confidence interval 0.87 to 2.20; data not shown) for exposure to radiography. This difference could be explained by the fact that we excluded radiographs received after age 40 and less than five years before diagnosis while the IBCCS had included all lifetime radiographs, including those after diagnosis of breast cancer. Exclusion of the overlapping group did not materially affect our results.We hypothesised that BRCA carriers could have increased radiosensitivity because of impaired DNA repair mechanisms. We observed increased risks of breast cancer among BRCA1/2 mutation carriers at dose levels considerably lower than those at which increases have been found in other cohorts exposed to radiation. A pooled analysis of eight cohorts exposed to radiation estimated a relative risk of about 2.0 at a dose of 1 Gy, assuming an age at exposure of 25 years.17 Nowadays, the dose estimate to the breast from a two view mammogram is in the order of 4 mGy. Even in women who reported undergoing a large number of mammograms, the total radiation dose to the breast is unlikely to exceed 20 mGy. This corresponds to a predicted relative risk of less than 1.02 based on the Preston model, which is substantially less than the risk estimates we observed.In the general population, a minimal induction time for breast cancer of 10 to 15 years after exposure to radiation is generally accepted, with relative risks decreasing as a function of attained age after reaching a peak, usually between the age of 30 and 40.17 18 As we hypothesised that BRCA carriers could have increased radiosensitivity because of impaired DNA repair mechanisms, we used a five year time lag in our analyses. Analyses with a two or 10 year time lag showed similar results (data not shown). Analyses stratified by attained age (=40 v >40) showed no significant effect modification. In line with published literature19 we observed a slightly stronger risk for the younger attained age group. It is possible that we did not see a strong effect of attained age because of limited variation in attained age in our study population. Alternatively, it could be that the attained age/time since exposure effect in BRCA1/2 carriers differs from that in the general population.Strengths and limitationsSeveral strengths and weaknesses of our study should be considered in the interpretation of these results. The strengths of our study include the sample size and the detailed information on all diagnostic procedures that used ionising radiation in different age periods. While previous studies7 8 9 10 were based only on mammography or radiography, we also investigated types of diagnostic exposures other than mammography and radiography in carriers and calculated one estimate of total radiation dose. The weighted cohort approach was used to overcome testing bias. The changes of the hazard ratios from the weighting (see supplementary tables C and D) were relatively small and in the expected direction, so the weights seem to meet their purpose of taking away some testing bias. The weighting procedure does not have any impact on the interpretation of the results. The retrospective nature of our study, however, might have caused recall bias. We relied on self reports rather than review of medical records because of the difficulties in accessing medical records with regard to the various diagnostic procedures. These took place for many different indications and many occurred in the distant past. Two methodological studies in the Dutch cohort (test-retest reliability20 and validity21 of self reported diagnostic radiation) showed that the extent of the observed misclassification was small and mainly non-differential by disease status, consistent with other studies.22 23 24 25 In the validation study, for example, the proportion agreement and ? for ever/never having had a mammogram before age 30 was >90% and >0.80, respectively, and this was not different between cases and unaffected carriers (P=0.237).21 Therefore, recall bias seems unlikely in our study and the observed non-differential misclassification might have biased our results towards unity. Non-differential misclassification could also have occurred because exposure before age 10 is unlikely to have been recalled by women. Also, exposure before age 20 is more difficult to recall than exposure at higher and thus more recent ages. Therefore, in our study, exposure before age 20 could have been prone to more non-differential misclassification than exposure at ages 20-29. This might explain the similar relative risks observed for both age groups, in contrast with what was observed in radiation exposed cohorts that did not rely on self reports.1 17 Furthermore, our follow-up might not have been long enough to detect an association between radiation exposure at ages 30-40 and risk of breast cancer.The calculation of the cumulative dose estimate was based on several assumptions. Firstly, we did not use indication specific dose estimates for fluoroscopy and radiography. Most (>95%) fluoroscopies before age 20, however, were chest fluoroscopies for tuberculosis screening and originated from the Dutch cohort (where mass population screening for tuberculosis in young people was performed 1940-6026). For radiography before age 20, most (>90%) were chest radiographs for which the dose (0.0005 Gy) differed from the dose of shoulder radiography for exposures before 1974 only (0.0010 Gy).27 Secondly, we dealt with missing values by single stratified mean imputation or by including a separate category. We think that this did not influence our results because the proportion of missing values was not different for cases and unaffected carriers. Moreover, missing values were imputed only if the exposure was known to have occurred in the relevant age period. Thirdly, we assumed that differences in dose estimates between the three European countries would be small as the recent country specific dose estimates for mammography for the UK and the Netherlands were similar. Nevertheless, for all types of diagnostic procedures, large differences might exist between machines and hospitals. Fourthly, the dose estimates for mammography were based on a two view mammogram. The doses used are typical doses for an average woman, but there are large variations depending on several characteristics of patients (such as breast size) and parameters of the equipment. Finally, we assumed the breast dose estimate reflected breast dose, assuming that the estimates reflect absorbed dose to fibroglandular tissue. This might apply only to mammography because those estimates were derived from entrance surface dose to dose to fibroglandular tissue. But we doubt that this is the case for the other diagnostic procedures.The assumptions regarding cumulative dose estimate and the previously discussed non-differential misclassification, together with the small number of cases in some analyses, could have contributed to a lack of consistent dose-response trends. We consider that it is unlikely that there is no true effect because the overall pattern indicates increased risks; hazard ratios are already increased, albeit non-significantly for the lowest dose category, and remain increased for all categories of higher dose.The stronger associations observed in the subcohort compared with the entire cohort are intriguing and suggest survival bias in the entire cohort. Although little is known about the influence of exposure to ionising radiation at low or high doses on overall survival and breast cancer specific survival in carriers, one study showed that radiation associated breast cancer had a distinct, less favourable, gene expression profile.15 Another explanation for the differences between the two analytical cohorts could be more non-differential misclassification in the entire cohort, in which the mean age at questionnaire completion was higher than in the subcohort (50.7 (SD 8.8) and 41.1 (9.7) years, respectively, P<0.001). Older age at questionnaire completion was a significant predictor of the proportion of disagreement in the test-retest reliability study.20 Although based on a smaller number, we consider the results from the subcohort to be the most valid because they are unlikely to be affected by survival bias. A prospective analysis was not possible because the number of incident cases was too small (n=11). Incident case numbers in our study and others studies are not expected to increase rapidly because of the increasing uptake of prophylactic surgery in unaffected carriers and the relatively short follow-up since DNA testing became available (1995), together with the fact that many newly identified carriers were tested because they (already) had breast cancer.Unanswered questions and future researchThe linear non-threshold model is widely accepted to also apply to estimation of risk after low doses and is used in radiation protection.28 29 Linear non-threshold extrapolation, however, might not apply to groups with a genetic susceptibility for increased radiosensitivity. Also, a few studies seem to show some differences in the biological responses to high and low dose radiation.30 Our data are inconsistent with a threshold. The category specific hazard ratios (1.00 (reference), 1.6, 1.8, 1.8, and 3.8 for dose categories <0.002, 0.002-0.0065, 0.0066-0.0173, and =0.0174 Gy, see table 4, exposure before age 30) are already increased, albeit non-significantly, for the lowest dose category and remain increased for all categories of higher dose. When we evaluated curvature by adding quadratic dose to a model with continuous dose, there was some evidence for concavity—that is, downward curvature (P=0.009 for quadratic term). Because there are relatively few cases in the high dose range, this result must be interpreted with caution. The possibility of a dose-response relation other than linear warrants further investigation.To indicate the clinical relevance of our results we calculated the absolute risk of breast cancer for exposure before age 30. Nowadays, the glandular dose of a single two view mammogram is around 4 mGy. This falls into the second dose category (0.0020-0.0065). According to our study results, the hazard of breast cancer associated with a mammogram taken between age 20 and 29 was 1.55 (95% confidence interval 0.76 to 3.17; see table 4). For a 30 year old carrier, the risk of developing breast cancer at age 40 (mean age at diagnosis in our study) is about 9% (assuming a 2:1 ratio of BRCA1 and BRCA2).31 This means that among 100 carriers aged 30, nine will have developed breast cancer by age 40. The absolute number of cases would increase by five ((1.55×9)-9) if all had had one mammogram before age 30. Because of the previously described study limitations and because currently there are no definitive international baseline mutation specific estimates of penetrance for risk of breast cancer among BRCA1/2 mutation carriers, however, this estimate should be interpreted with caution.An interesting finding is the difference we observed in the association between exposure to diagnostic radiation and risk of breast cancer for BRCA1 and BRCA2 carriers. For age specific exposure effects, however, the power in the BRCA2 group was rather low. Future studies should focus on prospective follow-up and examine modifying effects by genotype in larger populations, for exposure to both low and high dose ionising radiation.Conclusions and policy implicationsIn conclusion, in this large European study among BRCA1/2 mutation carriers, exposure to diagnostic radiation before age 30 was associated with an increased risk of breast cancer, at dose levels considerably lower than those at which increases have been found in other cohorts exposed to radiation. The results of this study support the recommendation to use non-ionising radiation imaging techniques (such as MRI) as the main tool for surveillance in young BRCA1/2 mutation carriers.What is already known on this topicEpidemiological studies on the association between diagnostic radiation and risk of breast cancer in BRCA1/2 mutation carriers have inconclusive results, possibly because of limitations such as the investigation of a single type of diagnostic procedure, relatively small numbers and lack of dose estimates, and a retrospective design with potential recall and survival biasWhat this study addsIn BRCA1/2 mutation carriers, exposure to diagnostic radiation before the age of 30 was associated with an increased risk of breast cancer, at dose levels considerably lower than those at which increases have been found in other cohorts exposed to radiationWhile previous studies were based only on mammography or radiography, this large cohort study used estimates of an individual age specific cumulative breast dose from various diagnostic radiation procedures as a measure of total diagnostic radiation exposure The results support the use of non-ionising radiation imaging techniques (such as MRI) for surveillance in young with BRCA1/2 mutationsNotesCite this as: BMJ 2012;345:e5660FootnotesWe thank Vanessa Tenet, Claude Picard, Irwin Piot, Esther Janssen, Monica Legdeur, Josette van As, and Renée Mulder for their help in data collection, entry, and cleaning; D Richardson and M Schaapveld for their help with the analysis of excess relative risks; M Bleiker and S Muller for their advice on dosimetry issues; Lesley Richardon for assistance in the design and conduct of the Gene-Rad-Risk study; and Dillwyn Williams for his support and advice on the EMBRACE radiation history study.Centres and individuals of the three nationwide studiesGENEPSO (Gene Etude Prospective Sein Ovaire, France)Coordinating Centre, Centre René Hugenin, Saint Cloud: Catherine Noguès, Emmanuelle Fourme, Rosette Lidereau, Denise Stevens; Institut Curie, Paris: Dominique Stoppa-Lyonnet, Marion Gauthier-Villars; Institut Gustave Roussy, Villejuif: Agnès Chompret; Centre René Huguenin, Saint Cloud: Catherine Noguès; Centre Paul Strauss, Strasbourg: Jean-Pierre Fricker; Centre François Baclesse, Caen: Pascaline Berthet; Centre Alexis Vautrin, Vandoeuvre-les-Nancy: Elisabeth Luporsi; Centre Léon Bérard, Lyon: Christine Lasset, Valérie Bonadona; Centres Paul Papin, René Gauducheau, and Catherine de Sienne, Angers, Nantes: Alain Lortholary; Centre Antoine Lacassagne, Nice: Marc Frénay; Hôpital D’Enfants Centre Hospitalier Universitaire, Dijon: Laurence Faivre; Institut Paoli-Calmettes, Marseille: Hagay Sobol, François Eisinger, Laetitia Huiart; Institut Bergonié, Bordeaux: Michel Longy; Institut Jean Godinot, Reims: Tan Dat Nguyen; Institut Claudius Regaud, Toulouse: Laurence Gladieff, Rosine Guimbaud; Centre Hospitalier Georges Renon, Niort: Paul Gesta; Centre Oscar Lambret, Lille: Philippe Vennin, Claude Adenis; Hôpital Charles Nicolle, Centre Henri Becquerel, Rouen: Annie Chevrier, Annick Rossi; Centre Jean Perrin, Clermont-Ferrand: Yves-Jean Bignon; Hôpital Civil, Strasbourg: Jean-Marc Limacher; Centre Eugène Marquis, Rennes: Catherine Dugast; Polyclinique Courlancy, Reims: Liliane Demange; Hôpital de la Timone, Marseille: Hélène Zattara-Cannoni; Clinique Sainte Catherine, Avignon: Hélène Dreyfus; Centre Hospitalier Universitaire Arnaud Villeneuve, Montpellier: Mehrdad Noruzinia; and Centre Hospitalier Régional et Universitaire Dupuytren, Limoges: Laurence Venat-Bouvet.EMBRACE (Epidemiological Study of BRCA1 and BRCA2 mutation carriers, UK)Coordinating Centre, Cambridge: Susan Peock, Margaret Cook, Debra Frost, Clare Oliver; North of Scotland Regional Genetics Service, Aberdeen: Helen Gregory; West Midlands Regional Clinical Genetics Service, Birmingham: Trevor Cole, Lucy Burgess; East Anglian Regional Genetics Service, Cambridge: Joan Paterson; Medical Genetics Services for Wales, Cardiff: Mark Rogers, Lisa Hughes; Peninsula Clinical Genetics Service, Exeter: Carole Brewer; West of Scotland Regional Genetics Service, Glasgow: Rosemarie Davidson, Nicola Bradshaw; South East Thames Regional Genetics Service, London: Louise Izatt, Gabriella Pichert, Caroline Langman; Yorkshire Regional Genetics Service, Leeds: Carol Chu, Julie Miller; Manchester Regional Genetics Service, Manchester: Gareth Evans, Fiona Lalloo, Andrew Shenton; Oxford Regional Genetics Service, Oxford: Lucy Side; Department of Cancer Genetics, Royal Marsden NHS Foundation Trust: Ros Eeles, Elizabeth Bancroft, Elizabeth Page, Elena Castro, Audray Ardern-Jones, Richard Houlston, Nazneen Rahman, Susan Shanley; North Trent Clinical Genetics Service, Sheffield: Jackie Cook, Lauren Baxter; South West Thames Regional Genetics Service, London: Shirley Hodgson, Sheila Goff; and Wessex Clinical Genetics Service, Southampton: Diana Eccles. Gareth Evans and Fiona Lalloo are supported by an NIHR grant to the Biomedical Research Centre, Manchester. The investigators at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust are supported by an NIHR grant to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. Ros Eeles and Elizabeth Bancroft are also supported by Cancer Research UK Grant C5047/A8385.HEBON (Netherlands Collaborative Group on Hereditary Breast Cancer, Netherlands)Coordinating center: Netherlands Cancer Institute, Amsterdam: Senno Verhoef, Anouk Pijpe, Richard Brohet, Frans Hogervorst, Laura van ‘t Veer, Flora van Leeuwen, Matti Rookus; Erasmus Medical Center, Rotterdam: Margriet Collée, Ans van den Ouweland, Mieke Kriege, Mieke Schutte, Maartje Hooning, Caroline Seynaeve; Leiden University Medical Center, Leiden: Rob Tollenaar, Christi van Asperen, Juul Wijnen, Peter Devilee; Radboud University Nijmegen Medical Centre, Nijmegen: Nicoline Hoogerbrugge, Marjolijn Ligtenberg; University Medical Center Utrecht, Utrecht: Margreet Ausems, Rob van der Luijt; Amsterdam Medical Center: Cora Aalfs, Theo van Os; VU University Medical Center, Amsterdam: Hanne Meijers-Heijboer, Hans Gille; University Hospital Maastricht, Maastricht: Encarna Gomez-Garcia, Rien Blok; University Medical Center Groningen, Groningen: Jan Oosterwijk, Annemiek van der Hout; Netherlands Foundation for Detection of Hereditary Tumours, Leiden: Hans Vasen, Inge van Leeuwen.Contributors: AP, NA, DFE, AK, EC, DG, FEvL, and MAR were responsible for study concept and design. AP, DFE, CN, MG-V, CL, J-PF, SP, DF, DGE, RAE, JP, PM, CJvA, MGEMA, HM-H, IT-C, and MAR acquired the data. AP, NA, DFE, AK, MH, FEvL, and MAR analysed and interpreted the data. AP, NA, DFE, AK, FEvL, and MR drafted the manuscript, which was critically revised for important intellectual content by all authors. AP, NA, DFE, AK, MH, FEvL, and MR carried out the statistical analyses. NA, DFE, EC, CN, MAR, and FEvL obtained funding. AP, NA, DFE, AK, EC, CN, SP, PM, MAR, and FEvL supervised the study. All authors commented on and approved the final draft. FEvL is guarantor.Funding: The GENE-RAD-RISK study was supported by grant No 012926 (FI6R) under Euratom Programme; GENEPSO: Fondation de France and Ligue National Contre le Cancer; EMBRACE: Cancer Research UK (grant C1287/A10118 and C1287/A8874); HEBON: Dutch Cancer Society (grants NKI1998-1854, NKI2004-3088, NKI 2007-3756). DFE is a principal research fellow of Cancer Research UK. The sponsors had no role in the design of the study; in the collection, analysis, and interpretation of the data; in the writing of the report; and in the decision to submit the paper for publication.Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: DFE is board member of Genome Canada. RAE receives royalties for the book Genetic Predisposition to Cancer, has received educational grants from Tepnel, Illumina, and Vista Diagnostics and has received honoraria for BRCA-related lectures from MD Anderson and University of Southampton. DG receives royalties from BRCA1 testing.Ethical approval: The study was approved by the medical ethics committees of all participating centres (Commission nationale de l’informatique et des libertés, France; Cambridgeshire 4 Research Ethics Committee; Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam), and all participants provided written informed consent.Data sharing: No additional data available.This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.References?Ronckers CM, Erdmann CA, Land CE. Radiation and breast cancer: a review of current evidence. 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View larger version:In a new windowDownload as PowerPoint SlideFig 1 Box and whisker plots of distribution of plasma rheumatoid factor levels in 10 year age groups in 9712 participants without rheumatoid arthritis in the Copenhagen City Heart Study Risk of autoimmune rheumatic diseasesRisk of rheumatoid arthritis during the 28 years’ follow-up increased by a factor of 3.3 (95% confidence interval 2.7% to 4.0%) for a doubling of rheumatoid factor level (fig 2?). The risk of the other autoimmune rheumatic diseases Sjögren’s syndrome, systemic lupus erythematosus, and systemic sclerosis showed similar trends for a doubling of rheumatoid factor level, but the number of events for individual diseases were insufficient to reach statistical significance. None of the participants developed polymyositis or dermatomyositis. Sensitivity analyses restricted to participants with complete information on all covariates at baseline showed similar results (supplementary fig 3 in online data supplement).
View larger version:In a new windowDownload as PowerPoint SlideFig 2 Risk of autoimmune rheumatic diseases as a function of doubling of rheumatoid factor level in 9712 participants in the Copenhagen City Heart Study followed for up to 28 years. All hazard ratios were multivariable adjusted (see text for details)Risk of rheumatoid arthritisThe cumulative incidence of rheumatoid arthritis as a function of age for the four categories of baseline level of rheumatoid factor (<25, 25-50, 50.1-100, and >100 IU/mL) is shown in fig 3? as Kaplan-Meier estimates (and in supplementary fig 4 in the data supplement as Fine-Gray estimates). The cumulative incidence of rheumatoid arthritis increased with increasing rheumatoid factor (log rank trend P<0.0001).
View larger version:In a new windowDownload as PowerPoint SlideFig 3 Kaplan-Meier cumulative incidence of rheumatoid arthritis for four categories of baseline level of rheumatoid factor as a function of age in 9712 participants in the Copenhagen City Heart Study followed for up to 28 yearsDuring the full 28 years of follow-up, the multivariable adjusted hazard ratios for rheumatoid arthritis were 3.6 (95% confidence interval 1.7 to 7.3) for rheumatoid factor levels of 25-50 IU/mL, 6.0 (3.4 to 10) for 50.1-100 IU/mL, and 26 (15 to 46) for >100 IU/mL compared with <25 IU/mL (Ptrend<0.0001) (fig 4?, top left panel). During the first 10 years of follow-up, the corresponding hazard ratios were 6.0 (2.1 to 17) for 25-50 IU/mL, 14 (6.7 to 28) for 50.1-100 IU/mL, and 39 (18 to 85) for >100 IU/mL (Ptrend<0.0001) (fig 4?, bottom left panel). Corresponding risk estimates that took account of the competing risk of death were similar (supplementary fig 5, left hand panels, in the data supplement). There was no interaction between sex and rheumatoid factor categories on risk of rheumatoid arthritis.
View larger version:In a new windowDownload as PowerPoint SlideFig 4 Risk of rheumatoid arthritis as a function of rheumatoid factor level in 9712 participants in the Copenhagen City Heart Study by length of follow-up (full 28 years or first 10 years) and number of hospitalisations for rheumatoid arthritis. All hazard ratios were multivariable adjusted (see text for details)In an attempt to exclude patients misclassified with rheumatoid arthritis, we also examined patients with at least two hospitalisations for rheumatoid arthritis at least six weeks apart. This reduced the number of patients with rheumatoid arthritis but strengthened the association between elevated rheumatoid factor and risk of rheumatoid arthritis (fig 4?, right hand panels). These results were also not influenced by competing risk of death (supplementary fig 5, right hand panels). Sensitivity analyses restricted to participants with complete information on covariates at baseline also showed similar results (supplementary fig 6).Absolute 10 year risk of rheumatoid arthritisThe highest absolute 10 year risk of rheumatoid arthritis of 32% was observed for 50-69 year old women who smoked and had rheumatoid factor levels >100 IU/mL (fig 5?, far right middle panel). This means that one out of three of such women will develop rheumatoid arthritis within 10 years from blood sampling. The lowest absolute 10 year risk of rheumatoid arthritis of 0.1% was observed for men =70 years old with rheumatoid factor levels <25 IU/mL irrespective of smoking status (fig 5?, bottom panels far left and inner left).
View larger version:In a new windowDownload as PowerPoint SlideFig 5 Absolute 10 year risk of rheumatoid arthritis in 9712 participants in the Copenhagen City Heart Study as a function of rheumatoid factor level, age, sex, and smoking statusDiscussionThe principal findings in this study of 9712 individuals without rheumatoid arthritis recruited from the general population of Copenhagen are those with elevated levels of rheumatoid factor had up to 26-fold higher long term risk of developing rheumatoid arthritis and up to 32% 10 year absolute risk of developing rheumatoid arthritis. These findings are novel. Importantly, these data do not serve as evidence that rheumatoid factor plays a causal role in the pathogenesis of rheumatoid arthritis.Mechanism and comparison with other studiesDevelopment of rheumatoid arthritis is thought to be an inflammatory process from early arthritis through rheumatoid arthritis and possibly to severe extra-articular rheumatoid arthritis.10 13 22 23 Among patients with early arthritis, only 40% are seropositive for rheumatoid factor, whereas in the final stage of rheumatoid arthritis 80% of patients are seropositive.10 23 A current debate is whether elevated levels of rheumatoid factor, elevated levels of anti-citrullinated protein antibody, variations in the PTPN22 gene, or some combination of these offer the best means of predicting short term (2-3 years) risk of rheumatoid arthritis.8 9 24 25 26 27 28 29 30 31 However, the debate does not include long term risk prediction, simply because good evidence is lacking. Our finding that elevated rheumatoid factor levels are associated with an increased long term (up to 28 years) risk of rheumatoid arthritis provides such data. Unfortunately we do not have information available for elevated anti-citrullinated protein antibody or genetic variations in PTPN22. Our data show that elevated levels of rheumatoid factor can be present many years before the clinical manifestation of arthritis, supported by a few earlier studies.32 33 34Rheumatoid factor levels are believed to increase with age in the general population,1 but we could not confirm this. Although the age of individuals with rheumatoid factor >100 IU/mL was 62 years compared with 58 years for the reference group with rheumatoid factor <25 IU/mL, the corresponding median times to diagnosis of rheumatoid arthritis were seven years and 15 years, indicating that the higher rheumatoid factor level >100 IU/mL group can be explained by a short time to diagnosis rather than by greater age. On direct investigation, we found that rheumatoid factor levels were constant across age groups from 20 years to 100 years old.Tobacco smoking has long been known to play a role in the pathogenesis of rheumatoid arthritis.35 Smoking related alterations to the cytokine balance, stress to the immune system, and modifications of autoantibodies are strongly associated with rheumatoid arthritis.36 37 However, we adjusted extensively for smoking—including daily tobacco use at examination and cumulative tobacco use in pack years at baseline and as time varying covariates at follow-up examinations—so smoking is unlikely as a confounder for our observation of increased long term risk of rheumatoid arthritis in those with elevated rheumatoid factor levels.Strengths and limitations of studyOur study has several strengths. The large study population was homogeneous and representative of the general population, the study population was well characterized, follow-up was more than 28 years, and we had 100% follow-up. Therefore, with a median age of entry to the study above 50 years, the 28 years of follow-up is well beyond the age of 70 years, when the incidence of rheumatoid arthritis peaks.1 Also, because rheumatoid factor concentrations were measured up to 28 years after blood sampling and thus not reported to participants or their doctors, these measurements did not influence ascertainment of rheumatoid arthritis during follow-up. In other words, we here study the natural course from an elevated rheumatoid factor to a clinical diagnosis of rheumatoid arthritis.Potential limitations include selection bias; however, as we enrolled a sample from the general population randomly selected without regard to disease status, selection bias is unlikely as an explanation for our findings. Another potential limitation is the validity of the diagnostic information; however, most of the rheumatoid arthritis diagnoses in the Danish registries were confirmed,38 and random misclassification would tend to bias the results towards the null hypothesis and therefore cannot explain the present results (as illustrated by our sensitivity analysis). Also, as rheumatoid factor enters into the classification of rheumatoid arthritis, individuals with lifelong elevated rheumatoid factor may have a heightened probability of being diagnosed with rheumatoid arthritis. Hospitalisation with a discharge diagnosis of rheumatoid arthritis can happen many years after the first diagnosis of rheumatoid arthritis while a patient is under the care of a rheumatologist or being cared for in some other outpatient setting; thus, those cases identified from a hospital discharge diagnosis may have been classified as not having rheumatoid arthritis when they were simply not hospitalised with it. Similarly, those with rheumatoid arthritis who eventually were hospitalised might have contributed substantially more person years than they should. Likewise important, the patients in this study were presumably at a later or more severe disease stage than patients consulting private rheumatologists; however, this implies that time to diagnosis in the outpatient setting would be shorter and risk estimates correspondingly higher than observed in this study. Given that the categorisation of rheumatoid factor was devised to maximise the relation between rheumatoid factor and rheumatoid arthritis, the risk estimates based on these categories could be exaggerated and need to be replicated in another study. Finally, as we studied only white people, our results may not apply to other races.Implications for clinicians and future workOur finding of a particularly high absolute risk of developing rheumatoid arthritis in women with elevated rheumatoid factor who smoked is yet another reason to promote cessation of smoking among such women. In addition, our finding of high risks of developing rheumatoid arthritis based on elevated levels of rheumatoid factor alone suggests the need for early referral to a rheumatologist or to early arthritis clinics for examination on the basis of a positive rheumatoid factor test—even in the absence of the typical arthritic joint symptoms—because of the better response to therapy the earlier it is initiated in rheumatoid arthritis.The superior specificity of anti-citrullinated protein antibody tests has somewhat diminished interest in rheumatoid factor at time of diagnosis of rheumatoid arthritis, but not necessarily when it comes to prediction of long term risk. Future work should include a comparison of rheumatoid factor and anti-citrullinated protein antibody tests for the long term prediction of development of rheumatoid arthritis. Also, larger studies might be able to confirm or refute that elevated rheumatoid factor is associated with future risk for other autoimmune rheumatic diseases.Finally, our absolute risk estimates could be used for designing a randomised controlled trial studying early intervention in high risk people, by designing the inclusion criteria around patient groups with, say, a =20% elevated 10 year absolute risk of developing rheumatoid arthritis.ConclusionIndividuals in the general population without rheumatoid arthritis but with an elevated plasma level of rheumatoid factor have up to 26-fold greater long term risk of developing rheumatoid arthritis, and up to 32% 10 year absolute risk of rheumatoid arthritis.What is already known on this topicRheumatoid arthritis is an autoimmune disease affecting 0.5-2% of the populationAt present, there is no good clinical available indicator for long term risk of developing rheumatoid arthritisWhat this study addsIndividuals in the general population without rheumatoid arthritis, but with an elevated plasma level of rheumatoid factor have up to 26-fold greater long term risk of developing rheumatoid arthritis, and up to 32% 10 year absolute risk of rheumatoid arthritisThese findings may lead to revision of guidelines for early referral to a rheumatologist and early arthritis clinics based on rheumatoid factor testingNotesCite this as: BMJ 2012;345:e5244FootnotesWe thank staff and participants of the Copenhagen City Heart Study for their contribution.Contributors: SFN and BGN had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. SFN, SEB, and BGN designed the study. PS, SEB, and BGN collected data. SFN performed all statistical analyses. SEB and BGN oversaw statistical analyses and contributed to interpretation of data. SFN wrote the first draft of the paper. SEB, PS, and BGN edited the paper critically, and all authors approved this paper in its final form. SFN and BGN are the guarantors.Funding: This study was funded by Herlev Hospital, Copenhagen University Hospital and the Danish Heart Foundation. The sponsors had no role in the design of the study; collection, analysis, and interpretation of data; writing of the report; or decision to submit the article for publication. The views expressed in this paper are those of the authors and not those of any funding body or others whose support is acknowledged.Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.Ethical approval: The studies were approved by Herlev Hospital, Copenhagen University Hospital, and a Danish ethical committee (the Copenhagen and Frederiksberg committee Nos. KF-100.2039/9 and KF-01-144/01), and were conducted according to the Declaration of Helsinki. Participants provided written informed consent.Data sharing: No additional data available.This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.References?Gaston JSH. Rheumatic diseases, immunological mechanisms and prospects for new therapies. University of Cambridge, 1999.?Neovius M, Simard JF, Askling J. Nationwide prevalence of rheumatoid arthritis and penetration of disease-modifying drugs in Sweden. 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