PURPOSE:To determine the incidence of all-cause and cancer mortality (CM) in association with immunosuppression. DESIGN:Retrospective cohort study at ocular inflammatory disease (OID) subspecialty centers. We harvested exposure and covariate data retrospectively from clinic inception (earliest in 1979) through 2010 inclusive. Then we ascertained overall and cancer-specific mortalities by National Death Index linkage. We constructed separate Cox models to evaluate overall and CM for each class of immunosuppressant and for each individual immunosuppressant compared with person-time unexposed to any immunosuppression. PARTICIPANTS:Patients with noninfectious OID, excluding those with human immunodeficiency infection or preexisting cancer. METHODS:Tumor necrosis factor (TNF) inhibitors (mostly infliximab, adalimumab, and etanercept); antimetabolites (methotrexate, mycophenolate mofetil, azathioprine); calcineurin inhibitors (cyclosporine); and alkylating agents (cyclophosphamide) were given when clinically indicated in this noninterventional cohort study. MAIN OUTCOME MEASURES:Overall mortality and CM. RESULTS:Over 187 151 person-years (median follow-up 10.0 years), during which 15 938 patients were at risk for mortality, we observed 1970 deaths, 435 due to cancer. Both patients unexposed to immunosuppressants (standardized mortality ratio [SMR] = 0.95, 95% confidence interval [CI], 0.90-1.01) and those exposed to immunosuppressants but free of systemic inflammatory diseases (SIDs) (SMR = 1.04, 95% CI, 0.95-1.14) had similar mortality risk to the US population. Comparing patients exposed to TNF inhibitors, antimetabolites, calcineurin inhibitors, and alkylating agents with patients not exposed to any of these, we found that overall mortality (adjusted hazard ratio [aHR] = 0.88, 0.89, 0.90, 1.11) and CM (aHR = 1.25, 0.89, 0.86, 1.23) were not significantly increased. These results were stable in sensitivity analyses whether excluding or including patients with SID, across 0-, 3-, or 5-year lags and across quartiles of immunosuppressant dose and duration. CONCLUSIONS:Our results, in a cohort where the indication for treatment was proven unassociated with mortality risk, found that commonly used immunosuppressants-especially the antimetabolites methotrexate, mycophenolate mofetil, and azathioprine; the TNF inhibitors adalimumab and infliximab, and cyclosporine-were not associated with increased overall and CM over a median cohort follow-up of 10.0 years. These results suggest the safety of these agents with respect to overall and CM for patients treated with immunosuppression for a wide range of inflammatory diseases. FINANCIAL DISCLOSURE(S):Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Supplementary material and methods: supplementary information on data collection, statistical analyses, and presentation of results in the figures.

Supplementary Figure Legends for Figures S1-S15.

Supplementary tables and figures showing study and assay characteristics, correlations between analytes, and the relationships of the analytes with prostate cancer risk overall, by study and study design, and subdivided by clinical and other characteristics.

Supplementary Tables 1-3 from Pancreatic Cancer Risk and ABO Blood Group Alleles: Results from the Pancreatic Cancer Cohort Consortium

This file contains Supplementary Tables 1-3. Supplementary Table 1 gives the distribution of prostate cancer cases by subtype included in the pooled Analyses of fruit, vegetable, and mature bean consumption and prostate cancer risk. Supplementary Table 2 gives the results of analyses using all main exposures modeled continuously. Supplementary Table 3 provides information on funding information for all cohort studies included in the pooled analysis.

Supplementary Table S1 provides details on each of the participating studies, including recruitment period, fasting status at blood collection and storage temperature of blood specimens, number of matched controls per case, and the matching criteria employed in each study. Supplementary Table S2 shows the blood sample fraction available, the assays used for androgen measurement, and laboratory coefficients of variation. Supplementary Table S3 includes the geometric means of hormone concentrations by cohort after log2 transformation and standardization. Supplementary Table S4 provides the case characteristics for each of the participating cohorts. Supplementary Table S4 shows the odds ratios (ORs) and 95% confidence intervals (95% CIs) for quintiles of androgen concentrations and overall invasive EOC and serous invasive EOC. Supplementary Figure S1 is a forest plot showing the odds ratios (ORs) and 95% confidence intervals (95% CIs) for a doubling of androgen concentration and Type I EOC in a sensitivity analysis restricted to EOC cases with grade data.

Objective Evaluate the association between cancer incidence and immunosuppressive treatment in patients with ocular inflammatory disease (OID). Methods and analysis We performed a retrospective cohort study of patients from 10 US OID subspecialty practices. Patients with non-infectious OID were included; HIV-infected patients were excluded. Time-dependent exposure to drug classes (ie, antimetabolites, calcineurin inhibitors, alkylating agents, tumour necrosis factor (TNF) inhibitors) and drugs were evaluated. Cancer incidence was ascertained by linkage to 12 state cancer registries from 1996 to 2015. Cancer incidence was analysed using Cox regression survival analysis, using 0-year, 3-year and 5-year lags after immunosuppression began. Results The cancer incidence cohort comprised 10 872 individuals at risk of incident cancer and residing in one of the 12 states covered; 812 primary cancers were identified through cancer incidence tracing with median follow-up time of 10 years. Neither TNF inhibitor, antimetabolite, calcineurin inhibitor nor alkylating agent classes were associated with statistically significant increases in cancer incidence adjusting for covariates. We found statistically significant reduced hazards in the systemic inflammatory disease (SID)-including cohort for adalimumab and chlorambucil, increased hazards for tacrolimus and etanercept in the non-SID cohort and reduced hazards for methotrexate in both. Other immunosuppressive drugs were not associated with overall cancer incidence. Conclusions We found no increased risk of overall or site-specific cancer incidence associated with short-term (non-transplant) therapy with most commonly used immunosuppressive drug classes and many specific drugs. Further research may clarify potentially protective or harmful effects of specific agents that were not consistently associated with reduced or increased cancer incidence. Trial registration number NCT00116090 .

Supplementary methods files describes the participating cohorts, study population, and statistical methods in detail.

PurposeGenetic testing is a tool used in a variety of settings for medical and nonhealth related purposes. The goal of this analysis was to better understand the awareness and use of genetic testing in the United States.MethodsData from the 2020 Health Information National Trends Survey 5 cycle 4 were used to assess the awareness and use of genetic testing by demographic characteristics, personal cancer history, and family cancer history.ResultsOverall, 75% of participants were aware of genetic testing and 19% of participants had genetic testing. Ancestry testing was the most common type of testing that the participants were aware of and had received. Non-Hispanic Asian, Non-Hispanic Black, and Hispanic respondents and participants with incomes less than $20,000 were less likely to be aware of and have received any type of genetic testing than the Non-Hispanic White participants and participants with higher income, respectively. Participants with a family history of cancer were more likely to be aware of cancer genetic testing than those without, and participants with a personal history of cancer were more likely to have had cancer genetic testing.ConclusionIt appears awareness of genetic testing is increasing in the United States, and differences in awareness persist by race/ethnicity and income.

Strategic planning is conducted by many organizations to systematically evaluate and assess their current state, establish or update their mission and/or goals, and identify strategies and activities to achieve the goals. The National Cancer Institute (NCI) Cohort Consortium is a collaborative network of 62 prospective cohort studies and their affiliated investigators that focus on cancer etiology and outcome research. The organization's membership grew markedly from 10 cohort studies at its inception in 2001 to 59 cohort studies at the time of the launch of the Consortium's strategic planning in 2017. This paper describes the strategic planning process that was conducted to establish organizational goals and to develop strategies and activities consistent with the Consortium's mission. The process involved a 2-year iterative approach combining surveys and in-person meetings. The resulting goals focus on communication, career development, research facilitation, scientific gaps, and common scientific challenges. The NCI Cohort Consortium's strategic plan and evaluation of its progress will advance new initiatives in cancer etiology and survivorship research.

The term “big data” refers broadly to large volumes of data, often gathered from several sources, that are then analyzed, for example, for predictive analytics. Combining and mining genetic data from varied sources including clinical genetic testing, for example, electronic health records, what might be termed as “recreational” genetic testing such as ancestry testing, as well as research studies, provide one type of “big data.” Challenges and cautions in analyzing big data include recognizing the lack of systematic collection of the source data, the variety of assay technologies used, the potential variation in classification and interpretation of genetic variants. While advanced technologies such as microarrays and, more recently, next-generation sequencing, that enable testing an individual's DNA for thousands of genes and variants simultaneously are briefly discussed, attention is focused more closely on challenges to analysis of the massive data generated by these genomic technologies. The main theme of this review is to evaluate challenges associated with big data in general and specifically to bring the sophisticated technology of genetic/genomic testing down to the individual level, keeping in mind the human aspect of the data source and considering where the impact of the data will be translated and applied. Considerations in this “humanizing” process include providing adequate counseling and consent for genetic testing in all settings, as well as understanding the strengths and limitations of assays and their interpretation.

Abstract Previous prospective studies assessing the relationship between circulating concentrations of vitamin D and prostate cancer risk have shown inconclusive results, particularly for risk of aggressive disease. In this study, we examine the association between prediagnostic concentrations of 25-hydroxyvitamin D [25(OH)D] and 1,25-dihydroxyvitamin D [1,25(OH)2D] and the risk of prostate cancer overall and by tumor characteristics. Principal investigators of 19 prospective studies provided individual participant data on circulating 25(OH)D and 1,25(OH)2D for up to 13,462 men with incident prostate cancer and 20,261 control participants. ORs for prostate cancer by study-specific fifths of season-standardized vitamin D concentration were estimated using multivariable-adjusted conditional logistic regression. 25(OH)D concentration was positively associated with risk for total prostate cancer (multivariable-adjusted OR comparing highest vs. lowest study-specific fifth was 1.22; 95% confidence interval, 1.13–1.31; P trend < 0.001). However, this association varied by disease aggressiveness (Pheterogeneity = 0.014); higher circulating 25(OH)D was associated with a higher risk of nonaggressive disease (OR per 80 percentile increase = 1.24, 1.13–1.36) but not with aggressive disease (defined as stage 4, metastases, or prostate cancer death, 0.95, 0.78–1.15). 1,25(OH)2D concentration was not associated with risk for prostate cancer overall or by tumor characteristics. The absence of an association of vitamin D with aggressive disease does not support the hypothesis that vitamin D deficiency increases prostate cancer risk. Rather, the association of high circulating 25(OH)D concentration with a higher risk of nonaggressive prostate cancer may be influenced by detection bias. Significance: This international collaboration comprises the largest prospective study on blood vitamin D and prostate cancer risk and shows no association with aggressive disease but some evidence of a higher risk of nonaggressive disease.

Animal and experimental data suggest that anti‐Müllerian hormone (AMH) serves as a marker of ovarian reserve and inhibits the growth of ovarian tumors. However, few epidemiologic studies have examined the association between AMH and ovarian cancer risk. We conducted a nested case‐control study of 302 ovarian cancer cases and 336 matched controls from nine cohorts. Prediagnostic blood samples of premenopausal women were assayed for AMH using a picoAMH enzyme‐linked immunosorbent assay. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using multivariable‐adjusted conditional logistic regression. AMH concentration was not associated with overall ovarian cancer risk. The multivariable‐adjusted OR (95% CI), comparing the highest to the lowest quartile of AMH, was 0.99 (0.59–1.67) (P trend : 0.91). The association did not differ by age at blood draw or oral contraceptive use (all P heterogeneity : ≥0.26). There also was no evidence for heterogeneity of risk for tumors defined by histologic developmental pathway, stage, and grade, and by age at diagnosis and time between blood draw and diagnosis (all P heterogeneity : ≥0.39). In conclusion, this analysis of mostly late premenopausal women from nine cohorts does not support the hypothesized inverse association between prediagnostic circulating levels of AMH and risk of ovarian cancer.

Background: In many countries, there are growing numbers of persons living with a prior diagnosis of cancer, due to the aging population and more successful strategies for treatment. There is also growing evidence of the importance of healthful diet and weight management for survivorship, yet many long-term cancer survivors are not successfully following recommendations. Methods: We explored this issue in a mixed methods study with 53 adult survivors of 3 cancers (breast, prostate, and non-Hodgkin’s lymphoma), living in Maryland. Participants provided three 24-hour dietary recalls, and results were used to classify respondents on 2 metrics of healthful eating (the Healthy Eating Index 2010, and a 9-item index based on current dietary recommendations). Recalls were also used to guide in-depth qualitative discussions with participants regarding self-assessment of dietary behaviors, healthful eating, and diet’s importance in cancer prevention and survivorship. Results: Survivors following a more healthful diet were more likely to be female, have greater socioeconomic resources, more years since diagnosis, normal weight, and no smoking history. Qualitative discussions revealed a more nuanced understanding of dietary strategies among healthful eaters, as well as the importance of household members in dietary decision making. Discussion: Most survivors had received little nutrition counseling as part of their cancer care, highlighting the importance of holistic, household-oriented nutrition education for maintaining health among long-term cancer survivors.

The Breast JournalVolume 23, Issue 3 p. 377-377 Letter to the Editor Response to Dr. Altundag's Letter to the Editor Lisa Gallicchio PhD, Corresponding Author Lisa Gallicchio PhD lisagallicchio@gmail.com The Prevention and Research Center, Mercy Medical Center, Baltimore, Maryland Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland Department of Epidemiology and Public Health, University of Maryland, Baltimore, Baltimore, MarylandAddress correspondence and reprint requests to: Lisa Gallicchio, PhD, Program Director/Epidemiologist, Epidemiology and Genetics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA, or e-mail: lisagallicchio@gmail.comSearch for more papers by this authorCarla Calhoun MSW, MBA, LGSW, Carla Calhoun MSW, MBA, LGSW The Prevention and Research Center, Mercy Medical Center, Baltimore, MarylandSearch for more papers by this authorDavid Riseberg MD, David Riseberg MD The Prevention and Research Center, Mercy Medical Center, Baltimore, Maryland Hematology & Oncology, Mercy Medical Center, Baltimore, MarylandSearch for more papers by this authorKathy Helzlsouer MD, MHS, Kathy Helzlsouer MD, MHS The Prevention and Research Center, Mercy Medical Center, Baltimore, Maryland Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MarylandSearch for more papers by this author Lisa Gallicchio PhD, Corresponding Author Lisa Gallicchio PhD lisagallicchio@gmail.com The Prevention and Research Center, Mercy Medical Center, Baltimore, Maryland Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland Department of Epidemiology and Public Health, University of Maryland, Baltimore, Baltimore, MarylandAddress correspondence and reprint requests to: Lisa Gallicchio, PhD, Program Director/Epidemiologist, Epidemiology and Genetics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA, or e-mail: lisagallicchio@gmail.comSearch for more papers by this authorCarla Calhoun MSW, MBA, LGSW, Carla Calhoun MSW, MBA, LGSW The Prevention and Research Center, Mercy Medical Center, Baltimore, MarylandSearch for more papers by this authorDavid Riseberg MD, David Riseberg MD The Prevention and Research Center, Mercy Medical Center, Baltimore, Maryland Hematology & Oncology, Mercy Medical Center, Baltimore, MarylandSearch for more papers by this authorKathy Helzlsouer MD, MHS, Kathy Helzlsouer MD, MHS The Prevention and Research Center, Mercy Medical Center, Baltimore, Maryland Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MarylandSearch for more papers by this author First published: 24 February 2017 https://doi.org/10.1111/tbj.12794Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume23, Issue3May/June 2017Pages 377-377 RelatedInformation

Background: The Mullerian ducts are the embryological precursors of the female reproductive tract, including the uterus; anti-Mullerian hormone (AMH) has a key role in the regulation of foetal sexual differentiation. Anti-Mullerian hormone inhibits endometrial tumour growth in experimental models by stimulating apoptosis and cell cycle arrest. To date, there are no prospective epidemiologic data on circulating AMH and endometrial cancer risk.Methods: We investigated this association among women premenopausal at blood collection in a multicohort study including participants from eight studies located in the United States, Europe, and China. We identified 329 endometrial cancer cases and 339 matched controls. AntiMullerian hormone concentrations in blood were quantified using an enzyme-linked immunosorbent assay. Conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CI) across tertiles and for a doubling of AMH concentrations (ORlog2). Subgroup analyses were performed by ages at blood donation and diagnosis, oral contraceptive use, and tumour characteristics.Results: Anti-Mullerian hormone was not associated with the risk of endometrial cancer overall (ORlog(2): 1.07 (0.99-1.17)), or with any of the examined subgroups.Conclusions: Although experimental models implicate AMH in endometrial cancer growth inhibition, our findings do not support a role for circulating AMH in the aetiology of endometrial cancer.

e21619 Background: Hair loss and thinning have been reported by breast cancer patients treated with aromatase inhibitors (AIs); these side effects are documented to be reasons that patients discontinue their AI therapy and have been shown to be associated with a decrease in quality of life. Despite this knowledge, there is a paucity of detailed data on hair changes over the course of AI therapy. The purpose of this study was to examine hair changes and risk factors for hair loss among breast cancer patients initiating aromatase inhibitor therapy and followed for one year. Methods: Data were analyzed from a cohort of 146 breast cancer patients initiating AI therapy and followed over the first year of their AI treatment. At baseline (prior to AI therapy) and at 1-year, a questionnaire was administered that ascertained data on demographics, health behaviors, and symptoms. Detailed hair loss questions, including those pertaining to family history and specific location of hair loss, were added during the study period when study staff noticed that hair loss and thinning were commonly being reported on the symptom checklist after initiation of AI therapy. Multivariable logistic regression analysis was conducted to examine factors related to AI-attributed hair loss. Results: Among the 86 breast cancer patients who completed the detailed hair loss survey at 1-year (mean age = 63y), 43% reported experiencing hair loss after the initiation of AI therapy. The most frequently reported time period of onset of the AI-attributed hair loss was between 3 and 6 months post-AI initiation (43.2%), with 67.6% of patients noting hair loss in the mid-scalp (top of head). Factors significantly associated with AI-related hair loss at 1-year were: hair loss prior to AI therapy, having a BMI > 30 kg/m2(odds ratio (OR) = 6.5), being a current smoker (OR = 7.8), and maternal history of hair loss or hair thinning (OR = 9.1). ORs were similar when patients with prior chemotherapy were excluded. Conclusions: Hair loss is a common side effect of AI therapy that can negatively affect a patient’s quality of life and potentially lead to treatment discontinuation. Treatment options for this AI-related side effect should be explored, especially for patients who are at increased risk.