To conduct stratified analysis of the association between periodontitis exposure and the risk of female breast cancer based on age, comorbidities and level of urbanization.Using claims data taken from the 1997–2013 Taiwanese National Health Insurance Research Database (NHIRD), we identified 60,756 newly-diagnosed female breast cancer patients during the period 2003–2013 from all beneficiaries. We then randomly selected 243,024 women without breast cancer matching (1:4) for age and the year of the index date during 1997–2013 from a one million representative population acting as the control group. A conditional logistic regression analysis was used to examine the association between periodontitis (ICD-9-CM codes 523.3–4) and the risk of breast cancer, shown as an odds ratio (OR) with a 95% confidence interval (CI) after adjustments for the Charlson Comorbidity Index (CCI) and level of urbanization. Subgroup analyses were conducted based on age, CCI and level of urbanization.The mean ± standard deviation age was 53 ± 14 years. After adjusting for potential confounders, the risk of female breast cancer was found to be associated with a history of periodontitis . Such an association was significantly different between patients aged < 65 years  and patients aged ≥ 65 years , as well as between patients where the CCI = 0  and patients with CCI > 0 . The highest level of urbanization was also associated with the risk of breast cancer.This population-based nested case-control study demonstrated that periodontitis was significantly associated with the risk of female breast cancer and such an association was modified by both age and comorbidities. Female breast cancer is one of the most common malignancies among women worldwide . In TaiwPeriodontitis is a chronic oral inflammation condition which is altered by microbiota and the microenvironment . SeveralIn Taiwan, the prevalence of periodontitis also significantly increased from 11.5% to 19.59% during the period 1997 to 2013  analyzedThe study was permitted by the Institutional Review Board (IRB) of Taichung Veterans General Hospital (IRB Number: CE17100B). The requirement for informed consent was waived given that personal information was anonymized.This study was a nationwide, retrospective population-based nested case-control study.The study data included the 1997–2013 administrative data from the Taiwanese NHIRD. The National Health Insurance (NHI) program currently covers over 99% of the Taiwanese population. The data found within the NHIRD includes medication prescription history, ambulatory care services, admission services and traditional medical services. Certain personal data and history data, such as body weight, body height, alcohol use, and smoking habits, are not available in the NHIRD. The National Health Research Institute (NHRI) manages the NHIRD and provides the database to researchers for research purposes after anonymization of personal information is assured. The study used several NHIRD datasets, including enrolment files, inpatient and outpatient 1997–2013 claims files and NHI catastrophic illness files.The NHI registered patients with catastrophic or major diseasese, including cancer and several autoimmune diseases such as systemic lupus erythematosus and rheumatoid arthritis. The NHIRD distributed a package of NHIR catastrophic illness files which include claims of inpatient and outpatient claims and registry details of patients in the catastrophic illness registry. Patients with a catastrophic illness can apply a cartastrophic illness certificate (CIC). The Bureau of NHI (BNHI) validated the accuracy of these catastrophic illness diagnoses in patients who apply CIC by two or more specialists through review of related laboraty data, medical records, pathological data and imaging findings. Patients who meet the diagnositic criteria of a catastrophic illness are issued a CIC and free from co-payment. We utilized the catastrophic illness files in the NHIRD to select newly diagnosed female breast cancer patients and matched patients found during the period 2003 to 2013.In 2000, the NHRI randomly selected and enrolled one million representative individuals from the NHIRD, establishing the Longitudinal Health Insurance Database (LHID2000). Comprehensive information on enrolment and utilization associated this randomly selected cohort are available. We selected a matched non-breast cancer comparison cohort from the population found in the LHID2000. We used LHID2000 claims data from 2003 to 2013 for analysis of the comparison cohort.The flowchart of study subjects inclusion was shown in Patients who had a CIC for breast cancer  were considered female breast cancer patients. Using the 1997–2013 NHIRD, we identified 87,738 newly diagnosed female breast cancer patients from 2003 to 2013. The first date of CIC application was defined as the index date.Using claim data from the 1997–2013 LHID2000, we identified 421,288 females who never had a diagnosis of breast cancer (ICD-9-CM code 174). We matched female breast cancer patients with females without breast cancer at a 1:4 ratio for age and year of the index date and finally included 60,756 female breast cancer patients and 243,.24 matched controls in the study.In Taiwan, beneficiaries of NHI were allowed to receive dental scaling no more than twice per year. Dentists may code gingival or periodontal disease for ambulatory visits of patient who received regular dental scaling. Therefore, in the study, only patients who had at least one outpatient visit before the index date with a diagnosis of acute or chronic periodontitis (ICD-9-CM codes 523.3–4) and concurrently received antibiotic treatment, or periodontal treatment, or scaling more than twice a year by dentists, were identified as patients with periodontitis.2), ratio of elderly individuals aged > 65 years, population ratio of subjects with educational levels of college or above, number of physicians/105 subjects, and population ratio of agricultural workers Reviewers' comments:Reviewer's Responses to Questions  Comments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?  The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: Partly**********  2. Has the statistical analysis been performed appropriately and rigorously?   Reviewer #1: YesReviewer #2: No**********  3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.  The Reviewer #1: YesReviewer #2: No**********  4. Is the manuscript presented in an intelligible fashion and written in standard English?  PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: NoReviewer #2: Yes**********  5. Review Comments to the Author  Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: IntroductionPage 4. Did the prevalence of periodontitis increase because of changes in definitions? This has often been the case in other countries.Page 4. There are many other cohort studies on periodontitis and breast cancer that are not referenced . Also, the Sfreddo et al study referenced is not a cohort study. Please edit the last paragraph of the introduction to reflect this. The discussion (first paragraph) also needs to be revised since the association between periodontal disease and breast cancer risk has previously been reported in Taiwan using the same dataset (PMID: 26280747); please explain the differences/overlap between the two studies in the discussion section.MethodsThis is not a traditional case-control study; based on the selection of all breast cancer cases during a 10-year period and selection of controls from a large cohort database for comparison, this would be better described as a retrospective population-based cohort study.It appears that all incident breast cancer cases identified through the NHIRI between 2003 and 2013 were included in this analysis. It is unclear if the breast cancer cases that are not in the NHRI database would have detailed data on claims for periodontal disease or other co-morbidities and if these were also included. A figure would help between understand the selection process including exclusions that were made and available data available for each step.Statistical analysis – please provide details on how the tests for interactions were conducted.Would it be possible to differentiate different types of breast cancers? E.g. invasive vs non-invasive?Also, given the strong association between urbanization and breast cancer, it would be useful to examine whether the periodontal disease and breast cancer is modified by this variable (this could be added to Table 5).DiscussionThe discussion could be improved. Prior results from existing studies on this topic are not provided . It would also be helpful to point out some limitations in prior studies, and what this study adds to the literature (given that there are over 10 papers on this topic). A better synthesis of the literature is needed.Typos (tables and “CRT” in discussion) and English grammar need to be corrected throughout.Reviewer #2: This study explored the effect of periodontitis on female breast cancer using a population based case control study. The paper is reasonably well written though I have some comments which the authors might consider to improve their study.IntroductionPage 4 final paragraph – "small sample size" is somewhat relative – I would state the sample sizes of these studiesPage 5: "...while Sfreddo et al. [21] found there was a significant association between periodontitis and breast cancer" - Presumably this is a positive association? Please clarify in the textMaterials and methodsPage 7 "Potential confounders included level of urbanization". Presumably this is a city / regional level variable in the dataset?"Sensitivity analyses were conducted based upon age  and CCI" – further elaboration required."We tested the differences in the continuous variables through use of the Student’s t-test and the categorical variables by using the Pearson’s χ2 test" What is the motivation for this and define the specific variables?Logistic regression model – presumably maximum likelihood was used to estimate the model parameters, but it would be good to state this explicitly.There is a strong case for modelling the dose response relationship as a continuous response. Arbitrarily creating categories is statistically inefficient and at worst can be misleading. I would advise modelling each explanatory variable of interest for the dose response as a continuous term. This can easily be achieved in SAS using a spline. A good choice would be a restricted cubic spline with the number of knots selected based on prior knowledge or beliefs (3-5 knots is often sensible – see Harrell F. (2015) Regression Modelling Strategies). The dose response adjusted for covariates can be presented as a smooth curve with confidence intervals. Odds ratios can still be obtained from this curve between specific points of interest. You might also consider modelling the CCI this way. Even if this approach is not adopted, the authors might consider mentioning this as a limitation.Details of the interaction term (later referred to in subsequent sections) in the logistic regression models are missing. This is critical since the primary interest (according to the title of the paper) is effect modification necessitating interaction terms.Perhaps the authors might consider making dataset and SAS code used available as SIResultsPage 9 "After adjusting for age and index date"…this implies that age and index date were covariates in the regression model – this does not appear to be the case according to the statistical analysis section as it stands.It would be nice to have some supportive figures  summarizing the statistical models.DiscussionFirst paragraph talks about several studies one by one – it would be preferable to integrate this as continuous prose and convey the message that your work is supportive of these previous studies."In this study, one important finding is that the risk of breast cancer is modified by both age and comorbidities" - this statement is redundant since it is a repetition of the first sentence of the paragraph.Table 3 – It seems patient is the statistical unit as opposed to an adjustment variable as currently indicated at the foot of the table. Also urban should be "urbanization".**********  6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.  Reviewer #1: NoReviewer #2: Nohttps://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,  9 Jun 2022Reviewer #1: Introduction1.Page 4. Did the prevalence of periodontitis increase because of changes in definitions? This has often been the case in other countries.Response: Thanks for your comment! Yes, the prevalence of periodontitis varied with changes in definitions based on ICD-9-CM codes (Table 1). Therefore, we conducted a sensitivity analysis for the association between periodontitis and breast cancer using various definitions of periodontitis and found consistent results with ORs from 1.10 to 1.12. Also, the non-differential misclassification bias related to periodontitis diagnosis always drives the bias towards the null. Therefore, the magnitude of the association between periodontitis and breast cancer could only be underestimated. We added a description regarding the influence of periodontitis definition on its association with breast cancer in the last paragraph of the Discussion section: ‘Third, although the Bureau of NHI audit had improved coding accuracy, the accuracy of diagnoses based on claims data is still an issue of concern. However, the non-differential misclassification bias related to periodontitis diagnosis always drives the bias towards the null. Therefore, the magnitude of the association between periodontitis and breast cancer could only be underestimated.’2.Page 4. There are many other cohort studies on periodontitis and breast cancer that are not referenced . Also, the Sfreddo et al study referenced is not a cohort study. Please edit the last paragraph of the introduction to reflect this. The discussion (first paragraph) also needs to be revised since the association between periodontal disease and breast cancer risk has previously been reported in Taiwan using the same dataset (PMID: 26280747); please explain the differences/overlap between the two studies in the discussion section.Response: Shao et al [21] demonstrated a meta-analysis study and found periodontal disease may be a risk of female breast cancer. (page 4)A meta-analysis study [21] found a potential association between periodontitis and breast cancer. (page 11)In contrast, we analyzed the association between periodontitis and breast cancer in females, and we also found the important modification effects by age and comorbidities. (page 11)3.MethodsThis is not a traditional case-control study; based on the selection of all breast cancer cases during a 10-year period and selection of controls from a large cohort database for comparison, this would be better described as a retrospective population-based cohort study.Response: Because we retrospectively selected the population of interested based on the outcome  and identified the history of periodontitis exposure before the index date, this study was a retrospective population-based case-control study. (page 5)4.It appears that all incident breast cancer cases identified through the NHIRI between 2003 and 2013 were included in this analysis. It is unclear if the breast cancer cases that are not in the NHRI database would have detailed data on claims for periodontal disease or other co-morbidities and if these were also included. A figure would help between understand the selection process including exclusions that were made and available data available for each step.Response: Taiwan's National Health Insurance (NHI) began in March 1, 1995 and covered 99.9% of Taiwan's residents by 2014. If the female breast cancer cases were not included in the NHRI database, data on claims for periodontal disease or other comorbidities should be unavailable. We added a figure to show the process of study subjects inclusion.5.Statistical analysis – please provide details on how the tests for interactions were conducted.Response: We had provided details on how to test the interaction effects in the statistical method subsection in the Methods section: ‘The significance of modification effect by each covariate on periodontitis exposure-associated female breast cancer risk was examined by calculating the P-value of the coefficient associate with the product of each indicator of the covariate and the indicator of periodontitis using the Wald test.’ (page 9)6.Would it be possible to differentiate different types of breast cancers? E.g. invasive vs non-invasive?Response: Female breast cancer patients were defined as those having a Catastrophic Illness Certificate (CIC) for breast cancer . This criteria only included the invasive breast cancer patients.7.Also, given the strong association between urbanization and breast cancer, it would be useful to examine whether the periodontal disease and breast cancer is modified by this variable (this could be added to Table 5).Response: We have examined the modification effect of urbanization on the association between periodontitis and female breast cancer and added the results to Table 5. 8.DiscussionThe discussion could be improved. Prior results from existing studies on this topic are not provided . It would also be helpful to point out some limitations in prior studies, and what this study adds to the literature (given that there are over 10 papers on this topic). A better synthesis of the literature is needed.Response: Soder et al. [20] selected 3,273 patients aged between 30-40 years and found that chronic periodontitis indicated by missing molars seemed to be associated with breast cancer (odds ratio 2.36). Of note, a meta-analysis study [21] found a periodontal disease significantly increased breast cancer risk . However, the risk of breast cancer development was not significantly increased among patients with periodontal disease and a history of periodontal therapy. Therefore, the author concluded a potential association between periodontitis and breast cancer. Freudenheim et al. [24] analyzed a cohort of 73,737 postmenopausal women and also revealed that periodontitis was associated with the risk of postmenopausal breast cancer . On the contrary, Farhat et al. [25] revealed no association between periodontal disease and overall breast cancer risk . However, in this study, no confounder was analyzed. In contrast, we analyzed the association between periodontitis and breast cancer adjusting for potential confounds, and we also found the important modification effects by age and comorbidities. (page 11)9.Typos (tables and “CRT” in discussion) and English grammar need to be corrected throughout.Response: We corrected it. (page 13)Reviewer #2: This study explored the effect of periodontitis on female breast cancer using a population based case control study. The paper is reasonably well written though I have some comments which the authors might consider to improve their study.10.IntroductionPage 4 final paragraph – "small sample size" is somewhat relative – I would state the sample sizes of these studiesResponse: Soder et al. [20] analyzed 3,273 patients and revealed that severe periodontal disease increased the risk of breast cancer. (page 4)11.Page 5: "...while Sfreddo et al. [21] found there was a significant association between periodontitis and breast cancer" - Presumably this is a positive association? Please clarify in the textResponse: We clarified the results of the meta-analysis study by Sfreddo et al. [21]: ‘ Of note, a meta-analysis study [21] found a periodontal disease significantly increased breast cancer risk. However, the risk of breast cancer development was not significantly increased among patients with periodontal disease and a history of periodontal therapy. Therefore, the author concluded a potential association between periodontitis and breast cancer.’ (page 11)12.Materials and methodsPage 7 "Potential confounders included level of urbanization". Presumably this is a city / regional level variable in the dataset?Response: Thanks for your comment. The variable of level of urbanization is an individual level variable based on individual’s residence region in the dataset.13."Sensitivity analyses were conducted based upon age  and CCI" – further elaboration required.Response: We are sorry that this is a mistake. “Sensitivity” analyses should be replaced with “Subgroup” analyses. Conducted subgroup analyses and examined the modification effects by age group and CCI group on the association between periodontitis exposure and the risk of female breast cancer. We also added a description regarding the statistical method to assess the modification effect in the statistical method subsection in the Methods section: ‘The significance of modification effect by each covariate on periodontitis exposure-associated female breast cancer risk was examined by calculating the P-value of the coefficient associate with the product of each indicator of the covariate and the indicator of periodontitis using the Wald test.’(page 9)14."We tested the differences in the continuous variables through use of the Student’s t-test and the categorical variables by using the Pearson’s χ2 test" What is the motivation for this and define the specific variables?Response: We intended to compare the continuous variables and categorical variables between cases and controls. To clarify our motivation of this and define the specific variables, we revised our description as: ‘We compared continuous variables including age and CCI using the Student’s t-test and the categorical variables including variables related to periodontitis history and level of urbanization by using the Pearson’s chi-square test between cases and controls.’15.Logistic regression model – presumably maximum likelihood was used to estimate the model parameters, but it would be good to state this explicitly.Response: We revised the description regarding statistical analysis in the statistical analysis subsection in the Methods section as:’ A multivariable conditional logistic regression with maximum likelihood estimation was used to examine the association between periodontitis exposure and the risk of breast cancer development after adjustment for potential confounders shown as adjusted odds ratio (aOR) with 95% confidence interval (CI).’ 16.There is a strong case for modelling the dose response relationship as a continuous response. Arbitrarily creating categories is statistically inefficient and at worst can be misleading. I would advise modelling each explanatory variable of interest for the dose response as a continuous term. This can easily be achieved in SAS using a spline. A good choice would be a restricted cubic spline with the number of knots selected based on prior knowledge or beliefs (3-5 knots is often sensible – see Harrell F. (2015) Regression Modelling Strategies). The dose response adjusted for covariates can be presented as a smooth curve with confidence intervals. Odds ratios can still be obtained from this curve between specific points of interest. You might also consider modelling the CCI this way. Even if this approach is not adopted, the authors might consider mentioning this as a limitation.Response: We have modelled the dose response relationship of age and CCI for the interaction with periodontitis as a continuous response and showed the results in supplementary figure 1 & 3.17.Details of the interaction term (later referred to in subsequent sections) in the logistic regression models are missing. This is critical since the primary interest (according to the title of the paper) is effect modification necessitating interaction terms.Response: Details of the interaction term was described in the Statistical analysis subsection in the Methods section: ‘The significance of modification effect by each covariate on periodontitis exposure-associated female breast cancer risk was examined by calculating the P-value of the coefficient associate with the product of each indicator of the covariate and the indicator of periodontitis using the Wald test.’ (page 9)18.Perhaps the authors might consider making dataset and SAS code used available as SIResponse: Thank you for your comment. We have provided our dataset and SAS code in the supplementary files.19.ResultsPage 9 "After adjusting for age and index date"…this implies that age and index date were covariates in the regression model – this does not appear to be the case according to the statistical analysis section as it stands.Response: We are sorry to make a wrong description. Actually, age and year of the index date are matching variables, not adjustment variables. We corrected this description as: ‘After adjusting for CCI and level of urbanization, periodontitis was significantly associated with the risk of female breast cancer .’ (page 9)‘20.It would be nice to have some supportive figures  summarizing the statistical models.Response: Thank you for your suggestion. We have conducted partial effect plots to summarize the statistical models and showed them in the supplementary files. (page 10)21.DiscussionFirst paragraph talks about several studies one by one – it would be preferable to integrate this as continuous prose and convey the message that your work is supportive of these previous studies.Response: We had revised our first paragraph of the Discussion section: ‘This is the first nationwide, population-based case control study which assessed the association between a history of periodontitis and the risk of female breast cancer development in Asia, and we have demonstrated a significant association of female breast cancer with periodontitis. The results remained robust in patients aged <65 years or ≥65 years and patients with a CCI = 0. Consistent with our finding, Soder et al. [20] selected 3,273 patients aged between 30-40 years and found that chronic periodontitis indicated by missing molars seemed to be associated with breast cancer. Of note, a meta-analysis study [21] found a periodontal disease significantly increased breast cancer risk. However, the risk of breast cancer development was not significantly increased among patients with periodontal disease and a history of periodontal therapy. Therefore, the author concluded a potential association between periodontitis and breast cancer. Freudenheim et al. [24] analyzed a cohort of 73,737 postmenopausal women and also revealed that periodontitis was associated with the risk of postmenopausal breast cancer. On the contrary, Farhat et al. [25] revealed no association between periodontal disease and overall breast cancer risk . However, in this study, no confounder was analyzed. In contrast, we analyzed the association between periodontitis and breast cancer adjusting for potential confounds, and we also found the important modification effects by age and comorbidities.’ (page 11)22."In this study, one important finding is that the risk of breast cancer is modified by both age and comorbidities" - this statement is redundant since it is a repetition of the first sentence of the paragraph.Response: We deleted this statement. (page 11)23.Table 3 – It seems patient is the statistical unit as opposed to an adjustment variable as currently indicated at the foot of the table. Also urban should be "urbanization".Response: We corrected it. (Table 3)Attachmentresponse to reviewers 20220609.docxSubmitted filename: Click here for additional data file. 4 Jul 2022
 PONE-D-22-02756R1

 Effect Modification by Age and Comorbidities on the Association Between Periodontitis and Female Breast Cancer: A Population-based Case-control Study

 PLOS ONEDear Dr. Chen,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.Please submit your revised manuscript by Aug 18 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at
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For instructions see: We look forward to receiving your revised manuscript.Kind regards,Antonis ValachisAcademic EditorPLOS ONEJournal Requirements:Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.Additional Editor Comments:Although the authors have adequately respond to several of the reviewers' comments, there are some issues that need to be clarified before the manuscript be accepted for publication. Please, read the additional comments from the reviewers carefully and address all the remaining issues.[Note: HTML markup is below. Please do not edit.]Reviewers' comments:Reviewer's Responses to Questions  Comments to the Author  1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: (No Response)Reviewer #2: All comments have been addressed**********   2. Is the manuscript technically sound, and do the data support the conclusions?  The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: Yes**********   3. Has the statistical analysis been performed appropriately and rigorously?   Reviewer #1: YesReviewer #2: Yes**********   4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.  The Reviewer #1: NoReviewer #2: Yes**********   5. Is the manuscript presented in an intelligible fashion and written in standard English?  PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********   6. Review Comments to the Author  Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: The authors have not addressed the comment on how their study was different from the previous study published on periodontal disease and cancer using the same Taiwan database  "A population-based study on the associations between chronic periodontitis and the risk of cancer" Shiu-Dong Chung et al.Since breast cancer is a female cancer, stating that they studied females (vs both sexes) makes little sense as obviously prior studies on breast cancer risk were in women only. Please mention this study in the Introduction and this study should not be referred to as the "first" case-control on periodontal disease that is population based (as it is not).This is not a retrospective case-control study. Retrospective case-control studies are studies that recruit cancer patients and ask about their past exposures; the exposure here is measured prior to the development of the disease. So, this is a retrospective cohort study, because the cohort exists and the analysis is conducted on a sample of the cohort retrospectively. Alternatively, you can call it a nested case-control study, which is nested in a cohort population.Figure 1 – can you clarify what is meant by “unsured amount” given that half of the population is excluded for this reason (+ missing data) can you justify whether this was a reasonable exclusion and whether it might have caused some selection bias ?Table 5. The title needs to be modified to clearly describe that the ORs presented are for the comparison of periodontal disease vs no periodontal disease stratified on age, CCI and urbanization. Many readers will misinterpret these results otherwise.I don’t think the figures add any value, especially the ones that are based on categorial comparisons.Please edit the abstract for grammar "assess that periodontitis" change to "assess whether periodontitis"Reviewer #2: I enjoyed re-reviewing this interesting study and was pleased that the authors considered many of my suggestions. I only have two minor comments:-Response to Reviewers - Reviewer #2: Point 12. The authors responded that "The variable of level of urbanization is an individual level variable based on individual’s residence region in the dataset." I believe this should be termed an ecological level variable since it describes properties of the region, and not each person.Perhaps a very slight re-wording will suffice.-The conclusion section looks a little peculiar with just one sentence. I would add a few more sentences or integrate into the discussion depending on the requirements of the journal.Overall this is now essentially ready for publication and will be a valuable contribution to the literature.**********   7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.  Reviewer #1: NoReviewer #2: No**********https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.
 While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,  9 Jul 2022Reviewer #1: 1.The authors have not addressed the comment on how their study was different from the previous study published on periodontal disease and cancer using the same Taiwan database  "A population-based study on the associations between chronic periodontitis and the risk of cancer" Shiu-Dong Chung et al.Response: Chung et al [20] observed an increased risk of a number of cancers among chronic periodontitis patients, and the adjusted hazard ratio was 1.23 for breast cancer. (page 4)2.Since breast cancer is a female cancer, stating that they studied females (vs both sexes) makes little sense as obviously prior studies on breast cancer risk were in women only. Please mention this study in the Introduction and this study should not be referred to as the "first" case-control on periodontal disease that is population based (as it is not).Response: We deleted ‘’first’’. (page 11)3.This is not a retrospective case-control study. Retrospective case-control studies are studies that recruit cancer patients and ask about their past exposures; the exposure here is measured prior to the development of the disease. So, this is a retrospective cohort study, because the cohort exists and the analysis is conducted on a sample of the cohort retrospectively. Alternatively, you can call it a nested case-control study, which is nested in a cohort population.Response: We rewrite as ‘’nested case-control study’’. 4.Figure 1 – can you clarify what is meant by “unsured amount” given that half of the population is excluded for this reason (+ missing data) can you justify whether this was a reasonable exclusion and whether it might have caused some selection bias ?Response: We are sorry to make a mistake here. Actually, we only excluded patients with missing data of residence region (a confounding factor in this study). Also, in 906,287 individuals from the 1997-2013 Longitudinal Health Insurance Database, we excluded excluded 458,873 men first and then excluded anther 26,126 women who had missing data of residence region. We have revised Figure 1. 5.Table 5. The title needs to be modified to clearly describe that the ORs presented are for the comparison of periodontal disease vs no periodontal disease stratified on age, CCI and urbanization. Many readers will misinterpret these results otherwise.Response: We have revised the tile as ‘Stratified Analysis of the Association Between Periodontitis and Female Breast Cancer Based on Age, Comorbidities and Level of Urbanization: A Population-based Nested Case-control Study.’6.I don’t think the figures add any value, especially the ones that are based on categorial comparisons.Response: Thank you for your suggestion. The other reviewer requested us to plot these figures based on both categorical and continuous comparisons. However, we have put them in the supplemental materials.7.Please edit the abstract for grammar "assess that periodontitis" change to "assess whether periodontitis"Response: We revised the sentence as: ‘ To conduct stratified analysis of the association between periodontitis exposure and the risk of female breast cancer based on age, comorbidities and level of urbanization.’ (page 2)Reviewer #2: I enjoyed re-reviewing this interesting study and was pleased that the authors considered many of my suggestions. I only have two minor comments:8.Response to Reviewers - Reviewer #2: Point 12. The authors responded that "The variable of level of urbanization is an individual level variable based on individual’s residence region in the dataset." I believe this should be termed an ecological level variable since it describes properties of the region, and not each person.Perhaps a very slight re-wording will suffice.Response: Thank you for your suggestion. We added a description regarding the variable of level of urbanization ‘The variable level of urbanization is an ecological level variable since it describes properties of the region.’ (page 8)9.The conclusion section looks a little peculiar with just one sentence. I would add a few more sentences or integrate into the discussion depending on the requirements of the journal.Response: We revised the conclusion section and integrated it into the Discussion section as: ‘In conclusion, this population-based nested case-control study revealed periodontitis exposure is significantly associated with the risk of breast cancer. We also found this association is modified by both age and comorbidities. Further studies are warranted to clarify the mechanisms.’(page 15)Attachmentresponse to reviewers.docxSubmitted filename: Click here for additional data file. 12 Jul 2022Stratified Analysis of the Association Between Periodontitis and Female Breast Cancer Based on Age, Comorbidities and Level of Urbanization: A Population-based Nested Case-control StudyPONE-D-22-02756R2Dear Dr Chen,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. 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For more information, please contact Kind regards,Antonis ValachisAcademic EditorPLOS ONE 14 Jul 2022PONE-D-22-02756R2 Stratified Analysis of the Association Between Periodontitis and Female Breast Cancer Based on Age, Comorbidities and Level of Urbanization: A Population-based Nested Case-control Study Dear Dr. Chen:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. 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Approximately 80% of breast cancers are estrogen receptor-positive (ER+), and 68–80% of those occur in premenopausal or perimenopausal women. Since the introduction of tamoxifen for adjuvant endocrine therapy in women with non-metastatic ER+ breast cancer, subsequent trials have demonstrated an oncologic benefit with the addition of ovarian function suppression (OFS) to adjuvant endocrine therapy. Subsequently, therapies to either suppress or ablate ovarian function may be included in the treatment plan for patients that remain premenopausal or perimenopausal after upfront or adjuvant chemotherapy and primary surgery. One strategy for OFS, bilateral salpingo-oophorectomy (BSO), has lasting implications, and the routine recommendation for this strategy warrants a critical analysis in this population. The following is a narrative review of the utility of ovarian suppression or ablation  in the context of adjuvant endocrine therapy, including selective estrogen receptor modulators (SERMs) and aromatase inhibitors (AIs). The long-term sequelae of bilateral oophorectomy include cardiovascular and bone density morbidity along with sexual dysfunction, negatively impacting overall quality of life. As gynecologists are the providers consulted to perform bilateral oophorectomies in this population, careful consideration of each patient’s oncologic prognosis, cardiovascular risk, and psychosocial factors should be included in the preoperative assessment to assist in shared decision-making and prevent the lifelong adverse effects that may result from overtreatment. Approximately eighty percent of breast cancers diagnosed in premenopausal women are estrogen receptor-positive (ER+) ,2,3. ThePremenopausal breast cancer is associated with distinctive risk factors, tumor characteristics, and clinical outcomes that oftentimes warrant additional therapy . There ip = 0.009). However, women deemed “low-risk” and thus not requiring adjuvant chemotherapy in this trial still did extremely well on tamoxifen alone, with an overall survival of 98.8% [A 2007 meta-analysis demonstrated a reduction in recurrence in women with ER+ breast cancer when an ovarian function suppressor (OFS) was combined with tamoxifen . A more The publication of this and subsequent trials demonstrating the benefit of OFS when added to adjuvant endocrine therapy has led to the addition of suppression or ablation of ovarian function for most women with premenopausal breast cancer. As such, medical oncologists may refer these patients to gynecologists for consideration of BSO, a single operation, instead of monthly or tri-monthly injections of a GnRH agonist to achieve suppression, especially in cases of continued menstruation after primary treatment .BSO is associated with long-term adverse effects in both premenopausal and postmenopausal populations. These risks include cardiovascular disease, stroke, accelerated bone density loss, and mood disorders ,12,13,14Long-term survival continues to improve with the addition of adjuvant CDK 4/6 inhibitors to high-risk premenopausal patients with ER+ breast cancer; however, long-term sequelae of permanent ovarian ablation will vary from patient to patient . As a reAn electronic search was conducted to identify relevant publications in PubMed since the year 2000. The following (MESH) terms were used and combined: oophorectomy, salpingo-oophorectomy, breast cancer, breast neoplasms, endocrine therapy, premenopausal breast cancer, adverse effects, quality of life, cardiovascular effects, and bone density. Eligibility was assessed by FK and PJ, and discrepancies were resolved through discussion. Publications evaluating cancer-related outcomes of BSO after a diagnosis of ER+ premenopausal breast cancer and publications evaluating long-term effects of BSO regardless of cancer history were included. Specifically, we searched studies that provided a comparison of overall survival (OS) or disease-free survival (DFS) between individuals who received BSO and those in a control group. Regarding long-term effects, we focused on studies that provided adequate measurements of risk in individuals who received BSO compared to those in a control group. We also sought data examining cost and quality of life. Publications were considered for review if they were randomized controlled trials (RCTs), cohort studies, retrospective studies, reviews, and cost analyses. Publications were excluded if they: (1) were not in English; (2) evaluated BSO surgical technique only; (3) did not use BSO as the primary independent variable; (4) were case reports; (5) were non-clinical ; or (6) included only women undergoing prophylactic surgery for HBOC syndrome.Our initial search yielded 446 publications, 417 of which were excluded after full-text screening, leaving 30 for inclusion in this review . The incAdditional studies report similar or slightly improved outcomes with the addition of OFS to endocrine therapy, alongside high rates of adverse effects.Tamoxifen, a SERM, is an integral component of the adjuvant treatment of premenopausal ER+ breast cancer treatment, and is recommended by the NCCN Clinical Guidelines in Oncology and the 2014 American Society of Clinical Oncology (ASCO) Clinical Practice Guidelines based on level 1 evidence ,20,21. Sp = 0.56) or OS  [The Adjuvant Breast Cancer (ABC) Ovarian Ablation or Suppression Trial included 2144 participants with perimenopausal or premenopausal breast cancer, all of whom received tamoxifen with or without chemotherapy and who were randomized to receive either OFS with tamoxifen or tamoxifen alone. At 5.9 years, there was no significant difference in the OFS vs. non-OFS arms in relapse-free survival  .p = 0.0003 and p = 0.0002, respectively) [In a sample of 709 premenopausal women with breast cancer, a 2008 phase III randomized trial found that seven-year DFS and OS were significantly improved after receipt of BSO plus tamoxifen compared to those of the control group (ctively) . Notablyp = 0.004) [The 2014 phase III Eastern Cooperative Oncology Group (ECOG 3193) trial randomized 345 women with node-negative ER+ breast cancer to either tamoxifen alone or tamoxifen and OFS, where none of the enrolled patients received chemotherapy. There was no significant difference in the 5-year rates of DFS or OS between the arms. Notably, grade 3 toxicities were twice as high in patients who received OFS  .p = 0.009) [The combined analysis of the randomized Tamoxifen and Exemestane Trial (TEXT) and the Suppression of Ovarian Function Trial (SOFT) sought to determine the benefit of the addition of OFS to either tamoxifen or exemestane, an aromatase inhibitor, in premenopausal women with early-stage ER+ breast cancer. The 8-year results from SOFT found a disease-free survival (DFS) of 78.9% with tamoxifen alone, 83.2% with tamoxifen plus OFS, and 85.9% with exemestane plus OFS (p = 0.033) [The 2020 ASTRRA trial was a randomized phase III study allocating 1483 premenopausal women with ER+ breast cancer to either five years of tamoxifen alone or five years of tamoxifen with OFS for two years. Most patients received OFS through a monthly injection of a gonadotropin-releasing hormone (GnRH) agonist. The five-year DFS was significantly greater in the group that received an additional two years of OFS  . However= 0.033) . There wOverall, the addition of OFS confers a greater DFS and OS in many of these studies. While these studies did not directly compare BSO to non-surgical methods of OFS, the statistically significant differences in DFS in these studies were achieved largely by non-surgical methods of OFS. Therefore, the irreversibility of BSO and its associated risks may not afford an additional oncologic benefit, especially in high-risk women who are likely to receive chemotherapy or CDK 4/6 inhibitors in the neoadjuvant or adjuvant setting ,27.Many scholarly reviews also offer perspectives regarding the value added by OFS. In a review of OFS combined with various adjuvant endocrine therapy modalities, Jain et al. determined that the benefits of OFS plus tamoxifen are best achieved among higher-risk populations, defined as women under 40 years with higher grade and stage, lymph-node-positive disease, among other factors . Citing While OFS shows gains in DFS when added to tamoxifen in younger patients with more advanced disease who may not be candidates for chemotherapy, the benefits of surgical OFS in average-risk women in resource-rich settings are less likely, and need to be evaluated on a case-by-case basis.Aromatase inhibitors (AIs) have become a standard of care for the adjuvant endocrine treatment of most postmenopausal women with early-stage ER+ breast cancer. Although the use of aromatase inhibitors alone is generally contraindicated in premenopausal women due to the stimulation of estrogen production in functioning ovaries, the combination of OFS with an AI in premenopausal women is a potential strategy for adjuvant therapy for high-risk women.There are very few studies that directly compare OFS and ovarian ablation through surgery or radiation when combined with an aromatase inhibitor. In the landmark MONARCH-E trial, high-risk patients with ER+/Her2- breast cancer were randomized to receive either adjuvant endocrine therapy alone or adjuvant endocrine therapy with the CDK 4/6 inhibitor abemaciclib. “High-risk” was defined as having four or more positive axillary lymph nodes on surgical pathology or one to three positive nodes with any of the following: tumor size ≥ 5 cm, grade 3, or high ki-67 (>20%). Endocrine therapy included AI+/-OFS and tamoxifen +/-OFS, depending on the patient’s menopausal status. Approximately 45% of the patients were premenopausal, but only half received OFS. The addition of the CDK 4/6 inhibitor abemaciclib to endocrine therapy resulted in a 25% reduction in the risk of an invasive event over a median follow-up period of 15.5 months. This risk reduction was even greater (37%) in patients who were premenopausal at the time of randomization. Comparative DFS analyses between therapy strategies, such as tamoxifen alone vs. endocrine therapy with OFS, in the premenopausal subgroup have not been reported.However, any benefit to one strategy over another is tempered by the benefit afforded with the addition of the CDK 4/6 inhibitor . As suchp = 0.245). Most patients in both arms achieved a clinical response after six months, and there was a significantly higher proportion of patients in the BSO group compared to the GnRH group  [In a retrospective analysis of 66 premenopausal women with recurrent or metastatic breast cancer, BSO plus AI treatment did not result in a significantly higher progression-free survival when compared to patients who received OFS with a GnRH antagonist plus an AI  . Interesp < 0.001) [Several studies have noted an association between early BSO and an increased risk of cardiovascular death, which is the leading cause of death in women living in the United States ,31,32. I< 0.001) ,34. Thou< 0.001) ,35,36. T< 0.001) . A revieGiven that estrogens and androgens inhibit bone resorption, the decline in estrogen from natural menopause or BSO has significant implications for bone health. A phase II randomized controlled trial of 80 women with breast cancer not on aromatase inhibitors but with a history of BSO demonstrated a mean reduction in bone mineral density of 8.5% in the lumbar spine and 5.7% in the hips over 18 months, which translates to an increased risk of fracture .Additionally, a prospective study of 270 Asian women previously treated with BSO for premenopausal breast cancer found a reduction in bone mineral density of 4.7% in the lumbar spine . Taken tp < 0.05, two-sided) [The effects of BSO have the potential to impact overall quality of life in several aspects, including vasomotor symptoms. BSO is an independent predictor of vasomotor symptoms in postmenopausal women treated for breast cancer , and was the most prominent quality-of-life symptom reported among women under the age of 35 years in the TEXT/SOFT trials . In a coo-sided) . BSO, asIn the Nurses’ Health Study, an ongoing prospective cohort study of over 15,000 women, BSO at any age for any indication was associated with an increased risk of death from all causes  . This elWhile our analysis illustrates either modest or no improvement in survival associated with OFS in patients with ER+ premenopausal breast cancer, additional retrospective analyses are necessary to elucidate the prognosis and sequelae associated with BSO exclusively. There is an ongoing clinical trial (NCT02440230) that aims to assess the safety of OFS with anastrozole compared to that of OFS with exemestane in Chinese premenopausal breast cancer patients. However, there is no treatment arm that does not receive OFS, and like in SOFT/TEXT trials, the method of OFS includes a mix of goserelin, a LHRH agonist, ovarian irradiation, and BSO.A 2016 review by Love et al. concluded that BSO with tamoxifen is an effective therapy for ER+ premenopausal breast cancer, particularly in resource-limited settings, as one-third of annual new cases of breast cancer globally are now hormone receptor-positive tumors in premenopausal women from low- and middle-income countries . As suchAdditionally, BSO is associated with an increased risk of cardiovascular death, especially amongst women with a family history of CVD. Furthermore, BSO increases the risk of osteoporotic fracture and impacts sexual function. Thus, the role of BSO for adjuvant permanent ovarian ablation in premenopausal women with ER+ breast cancer, considering the long-term sequelae, should involve a thoughtful multidisciplinary discussion between providers along with patient-shared decision-making.The value added to endocrine therapy by BSO has also been examined under an economic lens. In a cost–benefit simulation model, tamoxifen alone was associated with the highest life expectancy gain (18 years) at the lowest cost (USD 1566) . Adding The challenge in determining the isolated potential benefit from BSO as an OFS strategy is that in large landmark trials that provide rich data, BSO and medical OFS are often analyzed together, making it difficult to ascertain differences between these subsets of OFS. Furthermore, only a handful of studies have directly examined ovarian suppression or ablation against BSO in the context of breast neoplasms, as both methods have been shown to be effective in suppressing ovarian function ,52. TherA recurring theme in many of the studies included in this review is the conclusion that BSO is best reserved for individuals with high-risk disease. However, “high-risk” can be a subjective determination based on the variety of different criteria used in these studies, including node status, grade and stage, and the age of the patient. Additionally, the conclusions made in the landmark trials we have discussed are based on relatively small samples of participants. In SOFT, only 8% of the patients undergoing OFS received BSO, making the results of this trial difficult to generalize when considering BSO specifically.Premenopausal women diagnosed with ER+ breast cancer represent a cohort with unique challenges apart from coping with the stress of a diagnosis. Long-term survival in women living with breast cancer is steadily increasing due to improvements in early diagnosis and advances in cancer treatments and surveillance . Despite


Investigating body shapes may offer novel insights into the role of adiposity and body size in breast cancer development. We derived three distinct body shapes from combinations of height, weight, body mass index (BMI), waist and hip circumference, and waist-to-hip ratio (WHR) by a principal component analysis. We then used genetic variants linked to these body shapes and investigated associations with breast cancer risk. A body shape characterizing general adiposity was associated with a lower breast cancer risk, however this is likely because the genetic variants predicting this body shape reflect body fatness during childhood and adolescence rather than during later adulthood. A body shape characterizing tall women with a low WHR was weakly associated with a higher breast cancer risk. A body shape characterizing tall women with a large WHR was not associated with breast cancer risk. These findings can spur wider application in cancer research and possibly risk stratification.p-value = 0.016). PC2  was weakly positively associated with overall BC risk , but with a confidence interval including the null. PC3  was not associated with overall BC risk. Some of these associations differed by BC sub-types. For instance, PC2 was positively associated with a risk of luminal A BC sub-type . To clarify the inverse association of PC1 with breast cancer risk, future studies should examine independent risk associations of this body shape during childhood/adolescence and adulthood.Observational and genetic studies have linked different anthropometric traits to breast cancer (BC) risk, with inconsistent results. We aimed to investigate the association between body shape defined by a principal component (PC) analysis of anthropometric traits  and overall BC risk and by tumor sub-type . We performed two-sample Mendelian randomization analyses to assess the association between 188 genetic variants robustly linked to the first three PCs and BC ). PC1  was inversely associated with overall BC risk (0.89 per 1 SD [95% CI: 0.81–0.98];  Breast cancer is the most frequently diagnosed cancer in women worldwide (2.26 million new cases in 2020) and is the leading cause of cancer mortality in women  . MammogrEstablished risk factors for female breast cancer include age, family history, alcohol consumption, ionizing radiation exposure, reproductive factors, such as early menarche, late menopause, late age at first pregnancy, low parity, and elevated levels of both endogenous and exogenous estrogen .There is inconsistent evidence from prospective observational and genetic studies linking body fatness, mostly assessed by body mass index (BMI), to breast cancer incidence ,7. MostlWhile a correlation between different anthropometric variables exists, individuals with similar values in one trait  may differ considerably for others  resulting in different body shapes. A promising approach to capture the complexity of body shape phenotypes is to combine multiple traits. In 2016, a principal component analysis (PCA) was performed on six anthropometric traits , and WHR) to define body shape . Each prMendelian randomization (MR) analysis uses genetic variants as instrumental variables (IVs) to strengthen the causal inference in exposure–outcome associations in the absence of pleiotropic effects . This methodology can overcome some of the limitations of conventional approaches, such as reverse causation and unmeasured confounding, provided that the key assumptions of MR are not violated .In this study, a two-sample MR analysis was conducted to investigate the potential causal associations between three body shape phenotypes, as derived in Ried et al. , and theRied et al. performed a PCA of six anthropometric traits  obtaining three body shape phenotypes . Each PCRied et al. also reported a fourth body shape (PC4) characterizing individuals with high BMI and weight with low WC and HC  and vice versa . Althougp < 5 × 10−8) of 200 loci , some of them not previously associated with single anthropometric traits ; p-value = 0.016)  and of overall directional pleiotropy   (PC1 was inversely associated with breast cancer risk (IVW= 0.016) . There w< 0.001) . Neverth< 0.001) . The lea< 0.001) . This ge< 0.001)  were ide< 0.001) .random-effects OR = 1.05 [95% CI: 0.98–1.12]; p-value = 0.135) , but directional pleiotropy was not detected (PC2 was weakly positively associated with the risk of breast cancer (IVW= 0.135) , but thedetected . Accordidetected . Howeverdetected . The weidetected .random-effects OR = 1.04 [95% CI: 0.89–1.21]; p-value = 0.619) , but without the presence of overall directional pleiotropy (There was no evidence of an association between PC3 and breast cancer risk (IVW= 0.619) . We obseeiotropy . The seneiotropy .random-effects OR = 0.81 [95% CI: 0.67–0.99]; p-value = 0.043) and triple negative sub-types     . Neverth< 0.001) . Sensiti< 0.001) . MR-PRES< 0.001) .Comparab = 0.02)  with the= 0.256) .random-effects OR = 0.75 [95% CI: 0.53–1.08]; p-value = 0.122)  (2GX~0%) similar to the overall breast cancer analysis (PC3 was suggestively inversely associated with the risk of the HER2+ sub-type breast cancer (IVW= 0.122) , in cont8–1.44]) . The senanalysis .We performed a large-scale MR analysis to estimate potential causal associations between three distinct body shape phenotypes and the risk of overall breast cancer and five breast cancer tumor sub-types. A body shape capturing general adiposity (PC1) was inversely associated with the risk of overall breast cancer. The inverse association was stronger for ER− subtypes as compared to ER+ sub-types. A body shape contrasting tall women with a low WHR to short women with a large WHR (PC2) was weakly positively associated with overall breast cancer risk and most sub-types. There was no evidence of an association between PC3, a body shape characterizing tall women with a large WHR, and the risk of overall breast cancer. There was suggestive evidence that PC3 was differentially associated with breast cancer sub-types .General adiposity has been traditionally assessed using BMI, and in the absence of MR studies using PC1, BMI is an indicator that is closest to the PC1 body shape in our study. Previous MR analyses showed an inverse association between BMI and pre- and post-menopausal breast cancer risk ,31,32,33This difference could be due to the specificity of PC1, which captures a body shape that goes beyond BMI. PC1 could thus be complementary to, and potentially more specific than, BMI in characterizing general adiposity. This assertion is supported by the finding that two novel loci for PC1 were identified by Ried et al. that were not identified before in larger GWAS analyses for BMI, WHRadjBMI, and height . In compIn contrast to the MR results, observational studies have shown that a high BMI throughout adulthood is convincingly associated with a higher risk of post-menopausal breast cancer ,34. ObseIn post-menopausal women, adipose tissue converts adrenal androgens into estrogen by the aromatase enzyme . The preOur findings concerning PC2  are in line with the observational analysis of a previous publication of our group, where PC2 was positively associated with pre- and post-menopausal breast cancer with risk increments of 8–10% per 1 SD increase . Our obsRegarding breast cancer sub-types, only PC2 showed a positive association with the luminal A (ER+/PR+) tumor subtype. The results of other sub-types showed a confidence interval including the null. Zhang et al. reported a positive association between height and all hormone receptor-positive (ER+/PR+) sub-type breast cancers and no relationship for hormone receptor-negative (ER−/PR−) sub-types . The lacMechanistically, breast tissue in taller women is thought to be exposed to higher levels of insulin, growth hormone and IGF-I, and thus may have undergone more cell divisions contributing to a greater potential for error during DNA replication . Animal For body shape PC3, indicating body height combined with small HC and large WHR, we found little evidence for an association with breast cancer risk and sub-types, congruent with observational results from our group . HoweverIn this study we employed different MR approaches: IVW-based, Egger regression, and median-based methods. IVW methods are generally more powerful compared to the other methods implemented but they do not account for directional  pleiotropy. MR-Egger accounts for heterogeneity due to pleiotropy and detects directional pleiotropy. The median-based method is more robust to overall pleiotropy as it allows up to 50% of invalid instruments  .Although we checked for associations between our genetic variants and confounders, a violation of the second assumption of the MR approach cannot be entirely excluded due to the potential presence of unknown confounding factors. Other limitations include that our study may be slightly biased due to uncontrolled confounding from family effects, such as assortative mating, dynastic effects, and population structure . We miniThis MR analysis provides evidence of an inverse association between a body shape that reflects general adiposity and the risk of overall breast cancer among women of European decent. The strength of association differed across sub-types of breast cancer suggesting a stronger inverse association for ER− sub-types as compared to ER+ sub-types. The most likely explanation for these inverse associations with overall breast cancer and sub-types is that the genetic instruments for this body shape indicate general adiposity during childhood/adolescence rather than during later adulthood. To test this assertion in future studies, genetic instruments for body shape during both childhood/adolescence and adulthood (age 30+ years) should be identified and their independent risk associations with breast cancer compared in a multivariable MR framework.Furthermore, we found a weak positive association between a body shape characterizing tall women with a low WHR and overall breast cancer risk and most sub-types. This is in line with previous evidence on height and breast cancer. Our findings add to this evidence base by ruling out confounding by WHR.A body shape characterizing tall women with a large WHR was not associated with breast cancer risk.The current study provides complementary evidence to observational studies to interrogate multiple anthropometric measurements in relation to breast cancer risk.


What is the effect of mammographic breast density notification and information provision on women’s intention to seek supplemental screening and self-reported psychological outcomes?In this randomized clinical trial of 1420 women living in Australian jurisdictions without widespread breast density notification, women who viewed a hypothetical screening mammogram results letter with breast density notification and information were significantly more likely to report intention to seek supplemental screening and feeling anxious, uneasy, confused, and worried about developing cancer.The findings of this trial indicate that more evidence on overall benefits and harms of notification, as well as adequate and equitable service planning and communication strategies, is warranted to inform decisions on widespread breast density notification. Whether the benefits of notifying women about breast density outweigh the potential harms to inform current and future mammogram screening practice remains unknown.To assess the effect of mammographic breast density notification and information provision on women’s intention to seek supplemental screening and psychological outcomes.A 3-arm online randomized clinical trial was conducted from August 10 to 31, 2021. Data analysis was conducted from September 1 to October 20, 2021. Participants included Australian residents identifying as female, aged between 40 and 74 years, with no history of breast cancer who were residing in jurisdictions without existing breast density notification with screening mammograms.Women were randomized to receive 1 of the following hypothetical breast screening test result letters: screening mammogram result letter without breast density messaging (control), screening mammogram result letter with breast density messaging and an existing density information letter taken from a screening service in Australia (intervention 1), and screening mammogram result letter with breast density messaging and a health literacy–sensitive version of the letter adapted for people with lower health literacy (intervention 2).Primary outcomes were intention to seek supplemental screening; feeling anxious , informed, or confused; and having breast cancer worry.P < .001) and feeling anxious , confusion , and worry about breast cancer . There were no statistically significant differences in these outcomes between the 2 intervention groups.A total of 1420 Australian women were randomized and included in the final analysis. The largest group consisted of 603 women aged 60 to 74 years (42.5%). Compared with the control cohort (n = 480), women who received density notification via intervention 1 (n = 470) and intervention 2 (n = 470) reported a significantly higher intention to seek supplemental screening (0.8% vs 15.6% and 14.2%; In this randomized clinical trial, breast density notification and information integrated with screening mammogram results increased women’s intention to seek supplemental screening and made women feel anxious, confused, or worried about breast cancer. These findings have relevance and implications for mammogram screening services and policy makers considering whether and, if so, how best to implement widespread notification of breast density as part of mammography screening.ACTRN12621000253808 This randomized clinical trial evaluates the response to notification of breast density and provision of information for women with increased breast density following screening mammograms. Given this, most Australian women of breast screening age do not receive breast density notification.In Australia, asymptomatic women aged 50 to 74 years are actively invited to participate in free screening mammograms every 2 years, with the free program being open to those aged 40 to 49 years or 75 years and older without invitation.There is currently limited evidence on the outcomes associated with informing women about their breast density. Similarly, there is a lack of research into how attention to HL in written information on breast density might further affect women’s understanding of breast density and their follow-up intentions and behaviors. Therefore, the present study used a randomized design to assess how breast density notification and different formats of information provision affect women’s screening intentions and psychological outcomes using a hypothetical clinical scenario. The findings may provide a foundation to directly inform policy makers and lay the groundwork for subsequent clinical studies into breast density notification and the psychological and behavioral consequences.CONSORT) reporting guideline for randomized clinical trials. The trial protocol and statistical analysis plan are available in This was an online randomized clinical trial and followed the Consolidated Standards of Reporting Trials .23Participants in the WA letter cohort were shown the same generic mammography letter as the controls with an additional notification that the screening mammogram showed their breasts are dense. The wording of this message was adapted from the existing standard mammography letter used in BreastScreen WA public screening services in notifying women of their breast density. Along with this letter, the WA letter group was presented with an information pamphlet on breast density currently used in WA (omitting identifying headers and footers including logos and contact information).24 The letter had a readability level of grade 7.8 on the Microsoft Word Flesch-Kincaid test (with grade ≤8 recommended for average readers).Participants were shown the same mammography results letter as the WA letter group, with a HL-adapted information pamphlet on breast density, which was developed by the research team. Adaptation involved the use of simpler language, removing jargon, reducing sentence length and complexity, and use of the active voice. This process was achieved using the publicly available Sydney Health Literacy Lab Health Literacy Editor.To maximize the likelihood of participants reading the example results letter and the information about breast density, minimum time requirements before being able to proceed roughly based on word length were added to the mammography result letters (30 seconds), WA letter (40 seconds), and the HL-sensitive letter (60 seconds). Copies of the control and intervention materials are provided in the eAppendix of 25 personal and family cancer history,28 and cancer worry.29 Overall well-being in the last 2 weeks of the study was measured using the World Health Organization–5 tool .27 Health literacy was measured using the widely used single-item HL screener.26We used a combination of previously published, validated, and study-specific self-developed questions by the multidisciplinary study team in collecting the baseline and outcome data. Immediately before the intervention, participants completed sociodemographic characteristic questions as presented in 28 and having breast cancer worry.29 Secondary outcomes included intention to speak to a general practitioner (GP); breast density knowledge about increased cancer risk, prevalence, masking effect, and breast density decreasing with age; and cancer risk perception.30 The eAppendix in Primary outcome measures were screening intentions, including intention to seek supplemental screening, feeling anxious , feeling informed or confused after receiving the letter,2 tests. Multinomial logistic regression was used to analyze change in cancer worry from baseline  between groups.The required sample size was 1398, which would have 80% power to detect a moderate effect size (0.25) at an adjusted α value of 0.025 to account for multiple comparisons between either intervention arm and the control arm. Descriptive statistics  of participant sociodemographic and health characteristics, as well as primary and secondary outcome measures, were calculated using SPSS, version 26 software (IBM Corp). Between-group comparisons of categorical variables were analyzed using 2-tailed χ20 the sample was skewed toward higher unemployment, lower household income, and a higher proportion being born in Australia and speaking English as the main language at home. There were 7.5% (n = 106) of the participants who had a personal history of cancer and 15.8% (n = 224) who had a family history of breast cancer, and 73.9% (n = 1050) rated their health as good to excellent. Forty percent (n = 566) of participants completed high school level education or less, with 91.5% (n = 1299) reporting adequate HL.A total of 2265 respondents accessed the online study, with 1420 included in the final analysis  . The samP < .001) and undergo screening mammography more often . There were no significant between-group differences in screening intentions between the 2 intervention groups for supplemental screening  and increased screening frequency   .P < .001). There was no significant difference between the 2 intervention groups    .P = .56). There was no significant difference between the 2 intervention groups .Compared with the control group, a similar proportion of participants in the intervention groups agreed or strongly agreed that the letter made them feel informed to make decisions regarding their breast health . There was no significant difference between the 2 intervention groups .Compared with the control group, a significantly higher proportion of participants in the intervention groups agreed or strongly agreed that the letter made them feel confused about what to do regarding their breast health . There was no significant difference between the 2 intervention groups . Participants in the intervention groups were also more likely to indicate an increase in cancer worry from baseline, compared with the control group. Relative to an outcome of no change, participants were more likely to indicate increased cancer worry if they received the WA letter  or the HL letter , compared with the control group. There was no evidence of a difference between the intervention groups . There was no significant difference between the WA and HL letter intervention groups .Compared with the control participants, significantly higher proportions of participants in the intervention groups reported planning to talk to a GP about the letter . Compared with participants who received the WA letter, a significantly higher proportion of those who received the HL letter correctly answered questions about how common it is for women to have dense breasts  and the increased breast cancer risk . However, a significantly lower proportion of women correctly answered questions related to the masking effect  and density decrease with age .Regarding breast density knowledge, compared with the control group, both the intervention groups had significantly higher proportions of participants correctly answering all 4 questions about breast density . There was no significant difference between the 2 intervention groups .Compared with the control group, significantly higher proportions of participants in the intervention groups reported perceiving their breast cancer risk their lifetime to be above average , provides a new perspective.37 This simulation reported that taking into account the numbers of breast cancers, life-years, quality-adjusted life-years, breast cancer deaths, and overdiagnosis and associated health care costs, it can be cost-effective to offer women with extremely dense breasts magnetic resonance imaging screening at a 4-year interval.37 Other studies found mixed results, with one study concluding ultrasonography after a negative mammography is not cost-effective and the other reporting tomosynthesis plus mammography is cost-effective in women with dense breasts.36 Regardless, our study results can be useful for policy makers in discussion of potential costs associated with notification of breast density, with approximately 15% of women who are notified that they have dense breasts likely to seek supplemental screening, 25% likely to seek additional mammographic screening between routine schedules, and 65% likely to schedule a breast density–related primary care appointment. The widespread notification can also incur out-of-pocket costs for women who are not covered by publicly funded programs or privately insured, or when such services are not adequately covered by public or private health programs. This lack of coverage will have important implications for equity access to care.The long-term health outcomes of breast density notification at a population level remain unclear at this stage, insufficient to allow for detailed cost-effectiveness analysis. Based on limited smaller scale studies, the cost-effectiveness of supplemental screening depends on the modalities used, long-term outcomes used for calculating costs, and characteristics of the target group.38Our work highlights that women are also likely to have heightened feelings of being anxious, confused, or worried about breast cancer risk after being notified that they have dense breasts. An important next step before rolling out widespread notification is to conduct a randomized clinical trial with women who are notified through population-based screening programs in real-life settings to test these outcomes and set up processes to longitudinally evaluate outcomes both quantitatively and qualitatively. This information can assist planning to ensure relevant services are available if density notification is broadly introduced, including additional information and support for both the women and GPs, and a clinical management pathway to progress to supplemental screening. In doing so, the increased rates of false-positive findings with supplemental screening also need to be taken into consideration.40 With an expected increase in GP consultations related to breast density and cancer risk if notification is introduced, it will be crucial to ensure GPs have the knowledge and resources to counsel individuals about breast density and the pros and cons of supplemental screening, including in relation to psychological well-being. Informed and shared decision-making models based on evidence, patient values and goals, and joint decisions may help to reduce worries and other adverse psychological outcomes.42Previous studies have shown that GPs in Australia and primary care practitioners in the US had limited knowledge about breast density, were uncertain about how to manage care for women with dense breasts, and needed support and training.43 In this study, participants in both intervention groups were significantly more likely to have accurate knowledge about breast density than those in the control group. However, we did not find an association between HL-sensitive information and the main outcome measures, such as screening intentions and psychological effects. Although this finding may be explained by the high level of HL among our sample, it also demonstrates an interest in supplemental screening related to breast density information regardless of additional information on both the potential benefits and harms of supplemental screening. Further research in this area that includes samples of people with low HL not recruited online is needed. Previous studies have noted that the degree to which HL interventions may have an influence varies depending on the HL level of the target audience, and the lower the HL level, the larger the possible influence.44 Regardless, at this time HL-tailored information may still be useful in the wider community if breast density notification is introduced, and future research on what format of information achieves the best outcomes is warranted.Outside patient-clinician consultations, written or other materials providing evidence-based and unbiased information available through easily accessible channels can facilitate informed health care decisions.The key strength of this study is the randomization of interventions with participants having similar baseline characteristics across groups. This trial was conducted among screening-aged Australian residents who live in areas with no widespread breast density notification and therefore are unlikely to be biased by prior familiarity with breast density information. To our knowledge, this is the first study to examine the effect of HL-sensitive breast density information on key relevant outcomes.20 there was a high proportion of participants with adequate HL (>90%). This increased level may be explained by the association between higher HL and interest in research participation45 and the online nature of this study. Because this study was hypothetical , women who receive a dense breast notification in real-life settings may respond differently than the participants in our study. Online studies using hypothetical clinical scenarios have been widely used in both psychology and health fields for many years and have been reported to have clinically meaningful findings.46 Randomized clinical trials comparing women with dense breasts who are notified with those who are not notified through population-based screening programs are needed to validate or refute these findings. To minimize the effect of this limitation, our standardized screening mammogram results letters were adapted from currently used letters. The letters, however, may not be suited or directly relevant to other international screening settings owing to differences in health systems, screening policies, and programs.The study has limitations. Despite oversampling for low educational level during the recruitment process and ensuring that 40% of participants had lower educational attainment in line with the national level,In countries outside the US without mandated breast density notification, more evidence on overall benefits and harms of notification, as well as adequate and equitable service planning and communication strategies, are needed to inform future screening policy decisions about density notification. Although research from the US since the legislation of breast density notification provides invaluable insight into what to expect after introducing a mandated notification, other countries should be able to generate local evidence before widespread density notification. The findings of this trial, such as increased demand for services and adverse psychological outcomes associated with notification, have important implications for policy makers in Australia and countries with breast screening programs in considering the outcomes of potential widespread notification of breast density.


To study the risk of incident breast cancer and subtype-specific breast cancer in relation to excess body weight in a contemporary Swedish prospective cohort study, The Karolinska Mammography Project for Risk Prediction of Breast Cancer, KARMA.A total of 35,412 postmenopausal women attending mammography and included in the KARMA study provided baseline data on body mass index (BMI) and potential confounders. During eight years of follow-up, 822 incident invasive breast cancer cases were identified.2) constituting 34% of the study cohort had an increased risk of incident breast cancer with an adjusted Hazard Ratio (HRadj) 1.19 (95% CI 1.01–1.4). A similar, however, non-significant, association was found for women with obesity (BMI ≥ 30 kg/m2) conferring 13% of the cohort, with a HRadj of 1.19 (95% CI 0.94–1.5). Overweight was associated with risk of node-negative disease , whereas obesity was associated with node-positive disease . Both overweight and obesity were associated with risk of estrogen receptor positive (ER+) disease , and low-grade tumors . Finally, obesity was associated with ER+HER2 negative disease  and similarly luminal A tumors .Women with overweight (BMI ≥ 25–< 30 kg/mOverweight and obesity are associated with an increased risk of developing breast cancer, specifically ER+, low-grade, and for obesity, node-positive, high-risk breast cancer indicating a further need for risk communication and preventive programs. Obesity is classified as a chronic, but preventable disease [According to the World Health Organization (WHO) overweight and obesity has tripled since 1975 worldwide, and in 2016, 1.6 billion adults were classified as overweight , consisting of more than 70,000 women included from 2011 to 2013.The study population consists of 74,877 Swedish women included in the KARMA Cohort  , a studyData on medications were retrieved from the Swedish Prescription Register . Linkage2, normal weight ≥ 18.5–< 25 kg/m2, overweight ≥ 25–< 30 kg/m2, and obesity BMI ≥ 30 kg/m2.Self-reported body mass index (BMI) was accessed through the KARMA-questionnaires and divided and analyzed according to the WHO definition into the following groups: Underweight BMI < 18.5 kg/mData on life-style and reproductive health factors were accessed through the KARMA-questionnaires and included age at menarche, number of pregnancies, parity, age at first childbirth, use of hormonal contraception, hormone replacement therapy, and breast cancer heredity. Life-style factors included smoking and alcohol. Use of co-medications were derived from the Swedish national Prescription Registry including statins (ATC code C10), insulin (ATC code A10A), and metformin (ATC code C10).n = 822) are presented in Table Participants were followed from date of inclusion in the KARMA study until date of breast cancer diagnosis, date of death, or December 31, 2019, whichever came first. Descriptive statistics on baseline characteristics are presented in Table 2 (IQR 22.6–27.7) and 12,029 (34%) of the population was defined as overweight and 4693 (13%) as obese.Detailed information on the baseline characteristics of all 35,412 participants are presented in Table 2 (IQR 22.9–27.7), median tumor size 14.0 mm (IQR 10.0–20.0). At the time of diagnosis, 24.5% were lymph node positive, 0.9% had distant metastases, 78.1% were ER+, 60.0% PR+, 9.9% HER2+, 22.9% with histological grade III, and 38.3% had tumors with high Ki67. Based on immunohistochemical surrogate markers for subtyping, 70.2% were luminal-like (ER+/HER2−) out of which 42.7% were Luminal-A-like and 22.7% Luminal-B-like. Another 7.1% were ER+/HER2+, 2.3% ER−/HER2+, and lastly, 7.3% were diagnosed with TNBC.Table adj 1.19, 95% CI 1.01–1.40). A similar, however, not significant, association was found among obese women .The median follow-up time was 2719 days (7.4 years). Tables adj 1.20, 95% CI 1.00–1.44), and obese women , compared with normal-weight women. Similarly, there was an increased risk of PR+ breast cancer in obese women only , with a similar but not significant association for overweight women. There was also an association with being diagnosed with low-grade tumors in overweight , and obese women . A similar but non-significant association was found for tumors with low Ki67. According to node status, there was an increased risk of node-positive disease in obese women . For overweight women there was instead an increased risk of node-negative disease . No significant association with either overweight or obesity were found for the other prognostic factors, such as tumor size or HER2-status.Table adj 1.37, 95% CI 1.05–1.78, respectively), with a similar but non-significant association in overweight women. There was also an association with risk of low-proliferative Luminal A cancers among obese women (crude HR 1.34 (95% CI 0.97–1.86) and HRadj 1.43 (95% CI 1.02–2.01), respectively). No associations were found for either TNBC, high-proliferative Luminal B tumors, or HER2+ tumors, and either overweight or obesity.Lastly, in Table In this large, contemporary prospective Swedish cohort of postmenopausal women included during modern screening time period (2011–2013), we found an association between overweight and breast cancer risk. Our findings validate previous studies on the association between body weight and risk of breast cancer –7. Here Overweight in postmenopausal women has in previous studies not only been associated with an increased risk of developing breast cancer, especially ER+ breast cancer, but also with a worse prognosis , 22. StuThe mechanisms underlying the increased risks of obese women in developing postmenopausal receptor positive breast cancer are multi-factorial and mainly linked to hormonal pathways . OverweiThe impact of overweight or weight-gain on the risk of developing breast cancer may also vary over a lifetime , 35. A r2 after which the risk of breast cancer did not increase [In our study, we found an association between BMI and breast cancer risk in the overweight group, with a similar but not statistically significant risk among the obese participants. Although many studies find a linear association with the risk of breast cancer increasing with BMI, our results are instead in line with a recent meta-analysis, which found a strong positive but non-linear association between BMI and postmenopausal, receptor positive breast cancer, especially in women who had not used HRT . In thatincrease . The bioIn line with previous publications, we found a positive association between both overweight and obesity and risk of ER+ breast cancer, low-grade breast cancer, and with a significant association between obesity and risk of ER+/HER2− and luminal A tumors , 9, 36. The strengths of the study population are the prospective set-up of a contemporary cohort, representing breast cancer diagnoses of today under the influence of the rising overweight/obesity prevalence with availability of extensive questionnaires with data on BMI and confounders at time of inclusion. The limitations are the relative low number of cases, multiple comparisons, the follow-up of 7.4 years, and the low mean age as the relationship between adiposity and breast cancer risk is more pronounced in older women. With longer follow-up and more cases more pronounced associations would be expected. Lastly, as molecular subtyping was not part of the routine pathological diagnostic procedures at the time of inclusion in the present study, analysis of subtypes relies on immunohistochemical assessments rather than molecular subtyping.In conclusion this study finds overweight and obesity to be associated with an increased risk of developing breast cancer, specifically ER+, low-grade, and for obesity, node-positive, high-risk breast cancer. As overweight is an increasing global health problem and is also one of few modifiable cancer risk factors, with studies finding that weight-loss reduces the risk of breast cancer and may also improve breast cancer outcome, risk communication, and weight-control will remain an important intervention in reducing the incidence and improving the prognosis of postmenopausal breast cancer.