I first encountered CA: A Cancer Journal for Clinicians as a medical student. Back then, the American Cancer Society (ACS) printed hundreds of thousands of copies that were mailed (without any charge) to practicing physicians and dropped off by ACS volunteers at medical schools, with the goals of educating students about cancer and inspiring some of us to pursue careers in cancer-related specialties. I recall appreciating that the Society deemed medical students worthy of their attention. After carrying each issue in the pocket of my short white medical student coat for a few days (back when the journal was printed in a small, digest-sized format), I realized that I was unlikely to get beyond the first few pages anytime soon, so I carefully separated the journal pages and filed the articles in folders labeled by topic, wishing that someday I would be able to read them. (Note—foreshadowing alert). After 2 decades of pathology residency, fellowship, academic pathology practice, and laboratory-based cancer research, this wish came true. A series of fortunate events led me to a staff position at the ACS national office, where one of my roles was reading CA: A Cancer Journal for Clinicians. Every article. At least twice. For more than 20 years. The first message of this editorial is my retirement from the position of Editor. This role has been tremendously fulfilling and enjoyable, but it's time for some new ideas from someone else. By the time you read this I will be almost completely retired from my work with the ACS and looking forward to some other pursuits that, until recently, I haven't had time for. More importantly, this editorial also gives me an opportunity for some reflection about this journal, to thank the people who are responsible for its success, and to introduce the incoming editor, Don Dizon, MD. It would be difficult to name all the distinguished contributors to CA during my tenure as Editor, so I apologize for any truncations in the lists below and for any omissions resulting from lapses in my memory. There are several individuals who have contributed to CA in more than one capacity, and many of them are included below on only one list (the one for which their role seems most significant or most memorable to me). I appreciate them all and extend my utmost gratitude for their expertise and time. CA reaches a heterogeneous audience of clinical and public health professionals to provide information relevant to the entire cancer continuum, from prevention through survivorship and end-of-life care. Content includes educational review articles; ACS guidelines for cancer prevention and early detection; ACS summaries of the most recent data on cancer incidence, mortality, risk factors, and screening prevalence; virtual tumor board discussions; and brief news stories that offer perspectives on recent research. CA has always been free to access and remains free online without subscription. Published since 1950 by the ACS, CA: A Cancer Journal for Clinicians is one of the oldest peer-reviewed journals in oncology and retains the highest impact factor of all journals ranked by the Institute for Scientific Information (now, Clarivate Analytics). Much has changed since that first issue. Younger readers may be shocked to learn that this journal's name CA comes from the term that was used long ago in discussions among clinicians to avoid patients overhearing the word cancer, in the belief that diagnostic disclosure would have a negative impact on the patient's quality of life. In some superficial ways, CA has also changed substantially since my early years as Editor, when manuscripts were submitted via postal mail (not even e-mail) with triplicate copies of the text and photographic prints of graphs and figures to be forwarded to reviewers (also via postal mail). The first online issue of CA was in 2007, and, since 2020, publication has been online only. Nonetheless, the essence of CA has remained remarkably consistent—to provide educational content that advances the ACS goals of reducing cancer incidence and mortality rates and improving quality of life for cancer survivors. The main activity of most journal editors is prioritizing a large number of unsolicited research reports to select a relatively small proportion that will be accepted for publication. In contrast, most CA review articles begin at a meeting of our Associate Editors and Editorial Board members. These experts in various aspects of cancer care and research recommend and discuss topics that they deem most likely to advance the ACS mission and to be relevant to our readers' interests. The success of this journal depends to a great degree on the outstanding expertise, insight, and dedication of our Associate Editors and Editorial Board. It has been an honor to work with these all-stars of the cancer world. I sincerely appreciate Durado Brooks, MD, MPH; Keith Delman, MD; and Charles R. Thomas, Jr., MD, who served the journal as Associate Editors during my term as Editor, and everyone who served on our Editorial Board between 2000 and 2023, including the following list of current Editorial Board members: Gini Fleming, MD; Frederick Greene, MD; Ahmedin Jemal, DVM, PhD; Cathy Meade, PhD, RN; Kevin Oeffinger, MD; Alpa Patel, PhD; Nancy Perrier, MD; Charles R. Thomas, Jr., MD; and Andrew Vickers, PhD. If you look at the CA masthead webpage, you will see an Editor and an Editor-in-Chief. The latter, historically, has generally been the ACS Chief Medical/Scientific Officer (or a similar high-ranking executive position). These leaders are usually too busy with their myriad responsibilities to get involved with decisions regarding most individual articles. However, all Editors-in-Chief during my tenure—Harmon Eyre, MD; Otis W. Brawley, MD; and Arif Kamal, MD, MBA, MHS—made vital contributions to the journal's direction and strategy and, importantly, provided wise advice regarding some challenging editorial situations that I have encountered over the years. My next thank you goes to the authors of CA articles. Writing is much more difficult than editing, and the depth and breadth of CA review articles is not easily or quickly accomplished. Although there are far too many authors of CA reviews for me to thank individually, I sincerely appreciate them taking time from their busy schedules of patient care, research, teaching, and/or administrative work to contribute one or more articles to CA. Moreover, it is my impression that, because time spent writing review articles usually does not provide as much career advancement per hour of effort as research articles do, their willingness to undertake this work reflects genuine dedication to the continuing education of our audience, and I applaud our authors for their commitment and contribution. There are two categories of CA articles that make an especially prominent contribution to CA's identity. The first is the cancer statistics series of articles. Countless scientists have worked on these, but I want to highlight the ACS staff leaders who have directed this endeavor during my editorial tenure: Ahmedin Jemal, DVM, PhD (again); Rebecca L. Siegel, MPH; Elizabeth Ward, PhD; and Michael Thun, MD, MS. Cancer prevention and screening guidelines are the other special category of CA articles. Again, there are far too many staff and volunteer co-authors for me to list comprehensively, but I want to give special thanks to ACS staff who have led guideline teams during my years as Editor: Durado Brooks, MD, MPH (again); Colleen Doyle, MS, RD; Debbie Saslow, PhD; and Robert Smith, PhD. Anyone who has worked in journal editing knows how important managing editors are, and I appreciate the excellence of the outstanding professionals in that role during my tenure as Editor. I especially want to individually thank the current managing editor, Ms. Jin Kim and her immediate predecessor, Ms. Carissa Gilman. Their competence, efficiency, judgment, and organization are unrivaled. I cannot begin to explain how much they helped me and how much I enjoyed working with them. One step higher on the organizational chart, the ACS journal and/or publishing department leaders have also had a tremendously positive impact on CA. Among other contributions, they have the difficult task of reconciling editors' dreams (or delusions) with their organization's business realities. Special thanks to Ms. Esmeralda Galán Buchanan and, before her, Ms. Diane Scott-Lichter and Ms. Emily Pualwan. Our publishers, John Wiley & Sons, Inc. (2008 to present), and Lippincott (2000–2010), have been important partners in distributing our content to our audience, and their ongoing innovation has made our online content delivery more effective and efficient. Finally, this journal would be meaningless without you, our readers. Thank you for your page views and citations that justify our existence. More importantly, thank you for using the information in CA articles to inform your clinical care and your research. Editing CA is not a full-time job. Although this paragraph is a little tangential to the theme of this editorial, I want to allocate a few words to thanking the leaders, mentors, and colleagues who made the remaining percentages of my years with ACS so fulfilling and satisfying. From the ACS department that provides patient information and services, special thanks to Mr. Chuck Westbrook and Ms. Terry Music, and to all of my colleagues who led, guided, and contributed to writing, editing, and distributing the Society's information about all aspects of cancer to patients, their families and friends, and the general public. From the ACS research department, a very sincere thank you to all of my colleagues, and especially to Elizabeth Ward, PhD (again), Susan Gapstur, PhD, and Ahmedin Jemal, DVM, PhD (again), for welcoming me into their research teams, and to Eric Jacobs, PhD, and Stacey Fedewa, MPH, PhD, my most frequent colleagues and mentors in analytic epidemiology and surveillance research, respectively. And finally, as we approach the end of this editorial and the end of my term as CA Editor, I am delighted to introduce the incoming Editor, Don Dizon, MD. Dr. Dizon is a highly respected oncologist who specializes in women's cancers and holds leadership positions at Lifespan Cancer Institute and the Legorreta Cancer Center at Brown University. In addition to his impressive clinical and research background, Dr. Dizon comes to this position with significant editorial expertise, including a 10-year term as Editor-in-Chief of the American Society of Clinical Oncology education book, a peer-reviewed, PubMed-indexed publication. He has the expertise, creativity, and vision that make him the excellent selection as CA's newest Editor. I am certain of CA's future success under Dr. Dizon's leadership alongside the current Editor-in-Chief, Arif Kamal, MD, and look forward to reading future articles online (although maybe not twice) as a reader instead of an Editor. The author made no disclosures.

Background: Research on the relationship of meat, fish, and egg consumption and mortality among prostate cancer survivors is limited. Methods: In the Cancer Prevention Study-II Nutrition Cohort, men diagnosed with nonmetastatic prostate cancer between baseline in 1992/1993 and 2015 were followed for mortality until 2016. Analyses of pre- and postdiagnosis intakes of red and processed meat, poultry, fish, and eggs included 9,286 and 4,882 survivors, respectively. Multivariable-adjusted RRs and 95% confidence intervals (CI) were estimated using Cox proportional hazards models. Results: A total of 4,682 and 2,768 deaths occurred during follow-up in pre- and postdiagnosis analyses, respectively. Both pre- and postdiagnosis intakes of total red and processed meat were positively associated with all-cause mortality (quartile 4 vs. 1: RR = 1.13; 95% CI, 1.03-1.25; P-trend = 0.02; RR = 1.22; 95% CI, 1.07-1.39; P-trend = 0.03, respectively), and both pre- and postdiagnosis poultry intakes were inversely associated with all-cause mortality (quartile 4 vs. 1 RR = 0.90; 95% CI, 0.82-0.98; P-trend = 0.04; RR = 0.84; 95% CI, 0.75-0.95; P-trend = 0.01, respectively). No associations were seen for prostate cancer-specific mortality, except that higher postdiagnosis unprocessed red meat intake was associated with lower risk. Conclusions: Higher red and processed meat, and lower poultry, intakes either before or after prostate cancer diagnosis were associated with higher risk of all-cause mortality. Impact: Our findings provide additional evidence that prostate cancer survivors should follow the nutrition guidelines limiting red and processed meat consumption to improve overall survival. Additional research on the relationship of specific meat types and mortality is needed.

PURPOSE To investigate the association of postdiagnosis body mass index (BMI) and weight change with prostate cancer-specific mortality (PCSM), cardiovascular disease-related mortality (CVDM), and all-cause mortality among survivors of nonmetastatic prostate cancer. METHODS Men in the Cancer Prevention Study II Nutrition Cohort diagnosed with nonmetastatic prostate cancer between 1992 and 2013 were followed for mortality through December 2016. Current weight was self-reported on follow-up questionnaires approximately every 2 years. Postdiagnosis BMI was obtained from the first survey completed 1 to < 6 years after diagnosis. Weight change was the difference in weight between the first and second postdiagnosis surveys. Deaths occurring within 4 years of the follow-up were excluded to reduce bias from reverse causation. Analyses of BMI and weight change included 8,330 and 6,942 participants, respectively. RESULTS Postdiagnosis BMI analyses included 3,855 deaths from all causes (PCSM, n = 500; CVDM, n = 1,155). Using Cox proportional hazards models, hazard ratios (HRs) associated with postdiagnosis obesity (BMI >= 30 kg/m(2)) compared with healthy weight (BMI 18.5 to < 25.0 kg/m(2)) were 1.28 for PCSM (95% CI, 0.96 to 1.67), 1.24 for CVDM (95% CI, 1.03 to 1.49), and 1.23 for all-cause mortality (95% CI, 1.11 to 1.35). Weight gain analyses included 2,973 deaths (PCSM, n = 375; CVDM, n = 881). Postdiagnosis weight gain (> 5% of body weight), compared with stable weight (< 3%), was associated with a higher risk of PCSM (HR, 1.65; 95% CI, 1.21 to 2.25) and all-cause mortality (HR, 1.27; 95% CI, 1.12 to 1.45) but not CVDM. CONCLUSION Results suggest that among survivors of nonmetastatic prostate cancer with largely localized disease, postdiagnosis obesity is associated with higher CVDM and all-cause mortality, and possibly higher PCSM, and that postdiagnosis weight gain may be associated with a higher mortality as a result of all causes and prostate cancer.

The American Cancer Society (ACS) publishes the Diet and Physical Activity Guideline to serve as a foundation for its communication, policy, and community strategies and, ultimately, to affect dietary and physical activity patterns among Americans. This guideline is developed by a national panel of experts in cancer research, prevention, epidemiology, public health, and policy, and reflects the most current scientific evidence related to dietary and activity patterns and cancer risk. The ACS guideline focuses on recommendations for individual choices regarding diet and physical activity patterns, but those choices occur within a community context that either facilitates or creates barriers to healthy behaviors. Therefore, this committee presents recommendations for community action to accompany the 4 recommendations for individual choices to reduce cancer risk. These recommendations for community action recognize that a supportive social and physical environment is indispensable if individuals at all levels of society are to have genuine opportunities to choose healthy behaviors. This 2020 ACS guideline is consistent with guidelines from the American Heart Association and the American Diabetes Association for the prevention of coronary heart disease and diabetes as well as for general health promotion, as defined by the 2015 to 2020 Dietary Guidelines for Americans and the 2018 Physical Activity Guidelines for Americans.

Background: Cigarette smoking is causally linked to renal cell carcinoma (RCC). However, associations for individual RCC histologies are not well described. Newly available data on tobacco use from population-based cancer registries allow characterization of associations with individual RCC types. Methods: We analyzed data for 30,282 RCC cases from 8 states that collected tobacco use information for a National Program of Cancer Registry project. We compared the prevalence and adjusted prevalence ratios (aPR) of cigarette smoking (current vs. never, former vs. never) among individuals diagnosed between 2011 and 2016 with clear cell RCC, papillary RCC, chromophobe RCC, renal collecting duct/medullary carcinoma, cyst-associated RCC, and unclassified RCC. Results: Of 30,282 patients with RCC, 50.2% were current or former cigarette smokers. By histology, proportions of current or formers smokers ranged from 38% in patients with chromophobe carcinoma to 61.9% in those with collecting duct/medullary carcinoma. The aPRs (with the most common histology, clear cell RCC, as referent group) for current and former cigarette smoking among chromophobe RCC cases (4.9% of our analytic sample) were 0.58 [95% confidence interval (CI), 0.50–0.67] and 0.88 (95% CI, 0.81–0.95), respectively. Other aPRs were slightly increased (papillary RCC and unclassified RCC, current smoking only), slightly decreased (unclassified RCC, former smoking only), or not significantly different from 1.0 (collecting duct/medullary carcinoma and cyst-associated RCC). Conclusions: Compared with other RCC histologic types, chromophobe RCC has a weaker (if any) association with smoking. Impact: This study shows the value of population-based cancer registries' collection of smoking data, especially for epidemiologic investigation of rare cancers.

BACKGROUND:Given the potential complications of prostate biopsies, it is sometimes reasonable in selected patients to make a non-tissue diagnosis of prostate cancer. Little is known about prevalence and factors associated with non-tissue prostate cancer diagnoses in the United States. METHODS:We identified 40 to 99-year-old prostate cancer patients with prostate specific antigen (PSA) ≥20 ng/ml from the 2010-2015 National Cancer Database. Associations were examined between non-tissue prostate cancer diagnosis and age, race, clinical T (cT) and M (cM) categories, PSA, and Charlson-Deyo Comorbidity Index (CCI) with multivariable analyses. RESULTS:Among 62,635 patients, 6.2% had a non-tissue diagnosis. The proportion of patients with non-tissue diagnoses increased with advanced age (from 0.9% in ages 40-49 to 44.0% in ages 90-99) and disease stage (cT and cM) and higher CCI and PSA level. Demographic and clinical characteristics statistically significantly associated (all P < .001) with non-tissue diagnosis in adjusted analyses were older age (OR = 24.24, 90 to 99 vs. 60 to 69 years), and higher cT (OR = 4.83; T4 vs. T1), cM (OR = 5.25, M1C vs. M0), CCI (OR = 2.07; 3+ vs. 0), and PSA levels (OR = 3.19, >97.9 ng/ml vs.20 to 39 ng/ml), as well as hormonal therapy (OR = 0.51, with vs. without). CONCLUSIONS:Non-tissue diagnosis of prostate cancer, while rare, is not outside normal clinical practice and is strongly associated with advanced patient age, higher clinical stage, multiple comorbidities, and very high PSA levels.

Many cancer survivors use complementary and alternative health methods (CAM). Because we are unaware of high-level evidence supporting CAM for preventing cancer recurrence, we studied post-treatment survivors who use CAM to assess (1) the percentage who included preventing recurrence as a motive for using CAM, (2) characteristics of survivors who use CAM intended to prevent recurrence, and (3) CAM domains associated with use for recurrence prevention. We studied participants in the American Cancer Society’s Study of Cancer Survivors-I (nationwide study of adult survivors) who used CAM (excluding osteopathy, yoga, tai chi, or qi gong users, as well as anyone whose only reported CAM was prayer/meditation). Multivariable logistic regression was used to examine associations of independent variables with CAM use for recurrence prevention. Among 1220 survivors using CAM, 14.8% reported recurrence prevention as a reason for CAM use (although only 0.4% indicated this was their only reason). The following were independently associated with odds of CAM use to prevent recurrence: not being married/in a marriage-like relationship (OR = 1.53, 95% confidence interval [CI] 1.05–2.23), using mind–body (OR = 1.65, 95% CI 1.08–2.51) or biologically based (OR = 4.11, 95% CI 1.96–8.59) CAM and clinically relevant fear of recurrence (OR = 1.96, 95% CI 1.38–2.78). Approximately 1/7 of survivors who use CAM have unrealistic expectations about CAM reducing recurrence risk. This expectation is strongly associated with the use of biologically based CAM. Patient education should support informed decisions and realistic expectations regarding any complementary/integrative or mainstream/conventional clinical intervention.

Abstract Background: Machine learning (ML) methods are becoming more feasible for use in clinical and epidemiologic research of breast cancer, particularly when characterizing histopathology. Compared to supervised ML methods, unsupervised approaches represent an opportunity to distinguish features heretofore unknown. The purpose of this study was to use unsupervised deep learning methods to identify histopathological features in diagnostic breast cancer hematoxylin and eosin (H&E) slides that are associated with clinical characteristics and patient outcomes. Methods: One H&E slide was scanned (Leica Biosystems Aperio Versa scanner) at 20x magnification for each of 1,716 women diagnosed with breast cancer from the Cancer Prevention Study-II Nutrition Cohort. In the pre-processing phase, the scanned images underwent color normalization, artifact detection, and tiling. We then used an un-pretrained VGG16 autoencoder with data augmentation for feature learning and extraction from tiles. These features were two-tiered clustered using the K-means algorithm. Each tile was assigned the cluster with the highest probability. The tiles were reassembled into whole slide images. For each slide, the proportion of tiles in each cluster was calculated. We will associate clusters with clinical features and 5- and 10-year breast cancer-specific survival using multivariable logistic and Cox proportional hazards regression models, respectively. Results: Mean age at baseline enrollment (1992-1993) and breast cancer diagnosis for the cases was 60.6 years (SD=6.0) and 71.5 years (SD=7.0), respectively. The majority of cancer diagnoses occurred after 1999 (79%) and 81% of women included were diagnosed invasive breast cancer. The final pipeline for the full set of images is currently being built. Preliminary runs at the 1x magnification level with 100 cases (N=21,472 tiles) have shown clustering based on macro-level features such as adipose, stromal and epithelial content. Second-tier clustering (clustering within clusters) shows further delineation of groups within clusters of interest (i.e. epithelial-cell rich regions). The final output with all 1,716 slides will be based on analysis at the 5x magnification level. Discussion: We expect that some histopathological features identified by ML models will be associated with conventional pathology features, clinical features, and breast cancer-specific survival. Utilization of ML methods for analyzing histology slides provides additional data that can be integrated into epidemiological studies. Future directions include analyzing images at higher magnifications (10x or 20x) and assessing the association between ML histopathological characteristics and breast cancer risk factors and incorporating these characteristics into prognostic models. Citation Format: Samantha Puvanesarajah, James M. Hodge, Jacob L. Evans, William Seo, Michelle Yi, Michelle M. Fritz, Mary Macheski-Preston, Ted Gansler, Susan M. Gapstur, Mia M. Gaudet. Unsupervised deep-learning to identify histopathological features among breast cancers in the Cancer Prevention Study-II Nutrition Cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2417.

Abstract Background: Nuclear grade, believed to be established early in carcinogenesis, is an indicator of ductal carcinoma in situ (DCIS) prognosis. Women with high-grade DCIS have a higher risk of local recurrence compared to women with low-grade DCIS. Risk factors for DCIS overall are well-characterized but risk factors by grade are not. Given the prognostic capabilities of grade for DCIS, it is of interest to identify whether risk factors by DCIS grade differ. Methods: Among 75,630 women enrolled in the Cancer Prevention Study-II Nutrition Cohort in 1992-1993, we identified 422 who were diagnosed with low-moderate grade DCIS (i.e. grades 1 or 2) and 355 who were diagnosed with high-grade DCIS (i.e. grade 3) during follow-up through 2013. Beginning in 1997, biennial questionnaires were administered to update exposure status, including screening mammography in the previous two years. For this analysis, these questionnaires were used to partition follow-up time into approximately two-year intervals. Because screening is strongly linked to diagnosis of DCIS, contribution of person-time within a specific interval was conditional on reporting a screening mammogram in the interval prior. Multivariate joint Cox proportional hazards regression models were used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for the associations of known breast cancer risk factors with DCIS overall, and with high-grade and low-grade DCIS individually. Results: Parity (HR=0.70; 95% CI: 0.63-0.78, parous vs. nulliparous), smoking status (HR=0.69; 95% CI: 0.58-0.82, current vs. never smoking) and menopausal status (HR=0.79; 95% CI: 0.73-0.87, natural menopause <50 years vs. natural menopause ≥ 50 years) were inversely associated with risk of DCIS overall. Whereas, positive family history of breast cancer (HR=1.46; 95% CI: 1.36-1.57), personal history of benign breast disease (BBD) (HR=1.73; 95% CI: 1.62-1.85), and current use of combination estrogen and progestin hormone replacement therapy (HR=1.15; 95% CI: 1.04-1.28) were associated with higher risk of DCIS. In analyses stratified on DCIS grade, history of BBD was more strongly associated with higher risk of low-grade (HR=2.21; 95% CI: 1.81-2.70) than with high-grade DCIS (HR=1.29; 95% CI:1.04-1.60) (p for heterogeneity=0.001). Current combination estrogen and progestin hormone replacement therapy use was associated with a higher risk of high-grade DCIS (HR=1.40; 95% CI:1.03-1.90) but not low-grade DCIS (HR=1.02; 95% CI: 0.75-1.40), but the difference by grade was not statistically significant (p=0.5). Conclusions: In this study, which is the first to comprehensively assess risk factors by DCIS grade, the association between personal history of BBD and risk of DCIS appeared to differ by grade. Due to limited power for some risk factor analyses, future studies using larger prospective cohorts or pooled data should be conducted to better identify these associations. Citation Format: Puvanesarajah S, Gapstur SM, Gansler T, Patel AV, Gaudet MM. Risk factors for high-grade and low-grade DCIS in the cancer prevention study-II nutrition cohort [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-08-07.

Accumulating evidence suggests that excess body fatness is associated with an increased risk of aggressive prostate cancer. However, the roles of body mass index (BMI -kg/m2), reported before and after diagnosis, and weight change in long-term prostate cancer survival remain unclear. Prospective data from men diagnosed with non-metastatic prostate cancer between 1992 and 2013 were obtained from the American Cancer Society’s Cancer Prevention Study II Nutrition Cohort. Weight was self-reported on surveys completed at enrollment into the Nutrition Cohort in 1992, in 1997, and every 2 years thereafter. Pre-diagnosis BMI was from the first survey completed >1 year before diagnosis and post-diagnosis BMI from the first survey completed > 2 years after diagnosis to allow for treatment completion. BMI was classified as ideal (18.5-<25), overweight (25-<30), and obese (30+). Weight change was the difference in weight (lbs.) from pre- to post-diagnosis. Follow-up began on the date of diagnosis in pre-diagnosis analyses (n=9,867) and, to reduce the potential for reserve causation, 4-years after the post-diagnosis survey in post-diagnosis analyses (n=6,860). Follow-up ended at death or December 2014, whichever came first. Cox proportional hazard models were used to estimate cause-specific hazard ratios (HR) and 95% confidence intervals (95% CI), adjusted for age, race, education, initial treatment, stage, Gleason score, node involvement, comorbidities, pre-diagnosis BMI (weight change models only), smoking, alcohol, and physical activity. A total of 614 and 330 prostate cancer deaths occurred in the pre- and post-diagnosis cohorts, respectively. The median follow-up time was 10.6 years (interquartile range (IQR) =7.9) and 5.5 years (IQR=6.1) in the pre- and post-diagnosis cohorts, respectively. In pre-diagnosis multivariable models, BMI was not associated with prostate cancer-specific mortality (e.g., Obese vs Ideal: HR=1.09, 95% CI: 0.83, 1.42). In post-diagnosis models, compared to men with an ideal BMI, the hazard of prostate cancer-specific death was similar among overweight men (HR=1.08, 95%CI: 0.84, 1.39) and higher among obese men (HR=1.41, 95% CI: 1.02, 1.97). Compared to men who maintained their weight (± 5 lbs.), the hazard of prostate cancer-specific mortality was higher among men who gained > 10 lbs. (HR=1.33, 95%CI: 0.99, 1.77) or lost > 10 lbs. (HR=1.33, 95%CI: 0.92, 1.92), but was similar among men who gained or lost 5-10 lbs. Our results suggest that post-diagnosis obesity and weight gain may be associated with increased risk of prostate cancer-specific mortality. The suggestion of an inverse association between weight loss and higher prostate cancer-specific mortality in our study should be interpreted with caution as it is unknown whether weight loss occurring was intentional or due to advanced disease. Citation Format: Alyssa N. Troeschel, Eric J. Jacobs, W. Dana Flanders, Victoria L. Stevens, Terryl J. Hartman, Lauren E. McCullough, Ted Gansler, Ying Wang. Pre- and post-diagnosis body mass index, weight change, and prostate cancer-specific mortality among prostate cancer survivors in the US [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-179.

Digital pathology images potentially contain novel patterns that may be perceived by modern deep learning models, but not humans. Prior unsupervised pattern recognition approaches have been used to reveal prognostically-relevant subtypes of glioblastoma (PMID: 28984190) and breast density segmentation (PMID: 26915120), and may complement supervised machine learning models trained using labeled data. In the Cancer Prevention Study II (CPS-II) cohort (PMID: 12015775), high-resolution, digitized hemotoxylin and eosin diagnostic slides are available for approximately 1,700 breast cancer cases providing an opportunity to perform unsupervised pattern recognition image analysis for epidemiologic breast cancer studies. Given the size of the dataset and complexity of the models, we constructed an end-to-end analytical pipeline, including preprocessing, feature engineering, and clustering, using cloud-based technologies that enable analysis at scale. Prior to training the unsupervised models, we faced issues converting raw images with open-source software. Specifically, OpenSlides could not open the Leica Versa SCN files due to their proprietary format while BioFormats inverted colors. To fix these issues, we altered the BioFormats library to successfully convert the files into a TIFF format. Since this issue likely affects other researchers, we are in discussions to provide the fix under a public license. TIFF formatted images were then denoised through color normalization to reduce hue variance and artifact detection to remove unwanted features such as pathologist annotations. Due to the computational complexity of analyzing the full image, images were padded with white space to ensure divisibility and broken into nine tiles of a predefined size. To further reduce computation time, uninformative tiles were filtered based on a predetermined threshold of artifact and white space composition. The remaining tiles were input to the unsupervised models. We used convolutional autoencoders, specifically a modified VGG-16 model without pretrained weights and a deep embedded clustering algorithm. These models learn representations of the images called ‘feature vectors’ and encode the images’ salient patterns. The final model was chosen based on iterative testing on a subsample of 100 images (N=21,472 tiles) and performance comparison of various VGG-inspired autoencoders. The feature vectors were clustered by K-means to summarize the information in a format suitable for statistical analyses. Our initial results show that the system captures macro-scale tissue patterns at lower magnifications (1x and 5x) and produces clusters that can be integrated into epidemiological studies of breast cancer etiology and prognosis. Citation Format: Jacob L. Evans, William Seo, Mary Macheski-Preston, Michelle Fritz, Samantha Puvanesarajah, James Hodge, Ted Gansler, Susan Gapstur, Mia M. Gaudet, Michelle Yi. A scalable, cloud-based, unsupervised deep learning system for identification, extraction, and summarization of potentially imperceptible patterns in whole-slide images of breast cancer tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1635.

Identifying risk factors for women at high risk of symptom-detected breast cancers that were missed by screening would enable targeting of alternative prevention strategies. To identify breast cancer risk factors by mode of detection, we examined these associations in heavily-screened women from the Cancer Prevention Study (CPS)-II Nutrition Cohort. Among 76,406 women followed for a median of 13.8 years, 2,469 screen-detected and 1,189 symptom-detected breast cancer cases were diagnosed. Multivariable-adjusted associations were estimated using joint Cox proportional hazards regression models with person-time calculated contingent on screening. The mean (standard deviation) age at baseline was 62.0 (6.6) years for non-cases, 61.6 (6.1) for screen-detected cases, and 61.5 (6.2) for symptom-detected cases. Women with symptom-detected tumors were diagnosed at a slightly younger age (mean=69.4) and less likely to be diagnosed with a localized tumor (65.3%), than women with a screen-detected tumor (mean age at diagnosis=70.4 and localized tumors=83.3%). Factors associated with higher risks of symptom detected vs. screen detected breast cancer, included: current combined menopausal hormone use (HR=2.04, 95% CI 1.70 - 2.46 vs. HR=1.43, 95% CI 1.25 - 1.63), current estrogen only menopausal hormone use (HR=1.41, 95% CI 1.15 - 1.72 vs. HR=0.94, 95% CI 0.82 - 1.09), and history of benign breast disease (HR=1.89, 95% CI 1.67 - 2.13 vs. HR=1.49, 95% CI 1.36 - 1.62). The opposite pattern of higher risk of screen detected vs. symptom detected breast cancer was observed for greater adult weight gain (HR=2.32, 95% CI 1.91 - 2.82 vs. HR=1.42, 95% CI 1.10 - 1.84) and alcohol intake (HR=1.39, 95% CI 1.24 - 1.64 vs. HR=1.20, 95% CI 0.92 - 1.58). Our results suggest that understanding risk factors for symptom-detected cancers may help identify women who would benefit from more intensive screening to facilitate early detection. Citation Format: Mia M. Gaudet, Emily Deubler, W. Ryan Diver, Samantha Puvanesarajah, Alpa V. Patel, Ted Gansler, Dana Flanders, Mark Sherman, Susan Gapstur. Breast cancer risk factors by mode of detection among screened women in the Cancer Prevention Study-II [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4211.

Abstract Stromal tumor-infiltrating lymphocytes (sTILs) are often prominent in HER2-enriched and triple negative breast cancers and predict a favorable prognosis for these subtypes. Clinical and epidemiological determinants of sTILs have not been defined in large cohorts. Accordingly, we analyzed these associations for 702 eligible, postmenopausal invasive breast cancer cases from the Cancer Prevention Study (CPS)-II Nutrition cohort. CPS-II included 97,786 women who completed baseline and follow-up surveys since 1992. Women with self-reported breast cancer diagnoses were consented for medical record and tumor tissue retrieval. We analyzed pre-diagnostic data from the survey prior to diagnosis on personal history of benign breast disease (BBD), menopausal hormone use, alcohol intake, cigarette smoking status, waist circumference, body mass index, adult weight gain, nonsteroidal anti-inflammatory drugs, and physical activity. One pathologist (TG) evaluated sTILs using whole slide images of H&E stained sections according to recommendations by the International TILs Working Group 2014. sTIL levels were dichotomized: none/minimal (0-10%) and moderate/high (>10%). We compared the sTIL levels by clinical and epidemiologic risk factors using chi-square statistics. Odds ratio (ORs) and 95% confidence intervals (CIs) for the associations of clinical and epidemiologic risk factors with sTILs were estimated with multivariable logistic regression. Mean age at diagnosis was 71.9 years; 44% of cancers were moderate grade, 74% were localized staged and 88% were luminal-like. Cancers with high/moderate sTIL levels (n=614), compared to none/minimal (n=88), were more likely to be high grade (54% vs. 20%; p-value <0.001), node-positive (41% vs. 22%; p-value <0.001), and non-luminal (36% vs. 8%; p-value <0.001). In a model mutually-adjusted for age at diagnosis and clinical factors, all clinical factors were associated with moderate/high sTIL levels: node-positive (OR=2.15, 95% CI 1.28 – 3.58), high grade (OR=3.98, 95% CI 1.88 – 9.06), and non-luminal subtype (OR=3.65, 95% CI 2.00 – 6.59). Age at diagnosis was not associated with sTIL levels (per year: OR=1.01, 95% CI 0.97 – 1.05). Women with BBD were less likely to have moderate/high sTIL levels than minimal/none sTIL levels (38% vs. 54%; age-adjusted OR=0.50, 95% CI 0.31 – 0.79). Ever smokers also were less likely to have moderate/high sTIL levels (38% vs. 49%) with an OR=0.61 (95% 0.38 – 0.97). Other risk factors were not significantly associated with sTIL levels. In this large epidemiologic cohort, non-luminal cancers had more sTILs than luminal cancers. Women with a personal history of BBD and ever cigarette smokers had significant lower levels of sTILs. Our study is among the first to examine pre-diagnostic risk factors in relation to sTILs and provides the impetus for larger, population-based studies with phenotypic characterization of immune cells. Citation Format: Gaudet MM, Mellow MM, Puvanesarajah S, Gapstur SM, Sherman ME, Gansler T. Associations of epidemiologic and clinical features with intensity of immune infiltrates in postmenopausal breast cancer cases from the cancer prevention study-II cohort [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-08-02.

In a screened population, breast cancer-specific mortality is lower for screen-detected versus symptom-detected breast cancers; however, it is unclear whether this association varies by follow-up time and/or tumor characteristics. To further understand the prognostic utility of mode of detection, we examined its association with breast cancer-specific mortality, overall and by follow-up time, estrogen receptor status, tumor size, and grade. In the Cancer Prevention Study-II Nutrition Cohort, 3975 routinely screened women were diagnosed with invasive breast cancer (1992–2015). Among 2686 screen-detected and 1289 symptom-detected breast cancers, 206 and 209 breast cancer deaths, respectively, occurred up to 24 years post diagnosis. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated from Cox proportional hazard regression models. Controlling for prognostic factors, symptom detection was associated with higher risk of breast cancer-specific death up to 5 years after diagnosis (HR≤5years = 1.88, 95% CI 1.21–2.91) this association was attenuated in subsequent follow-up (HR>5years = 1.26, 95% CI 0.98–1.63). Within tumor characteristic strata, there was a 1.3–2.7-fold higher risk of breast cancer death associated with symptom-detected cancers ≤ 5 years of follow-up, although associations were only significant for women with tumors < 2 cm (HR≤5years = 2.42, 95% CI 1.19–4.93) and for women with grade 1 or 2 tumors (HR≤5years = 2.72, 95% CI 1.33–5.57). In subsequent follow-up, associations were closer to the null. Screen detection is a powerful prognostic factor for short-term survival. Among women who survived at least 5 years after breast cancer diagnosis, other clinical factors may be more predictive of breast cancer survival.

Cancer is a devastating disease. It is estimated that 1.7 million Americans will be diagnosed with cancer in 2018 and approximately 610,000 will die of it.1 Cancer does not discriminate. It affects humans of all ages, races, and ethnicities. Although virtually everyone is at risk for developing and dying from cancer, the burden of this disease is not equal. Substantial disparities have been present for years. Bridging these disparities defines a central challenge for our nation's cancer control efforts. Despite a 25-year decline in the cancer mortality rate, cancer is the second leading cause of death in the United States and will surpass cardiovascular disease to become the leading cause of death in the next decade. Review of the progress to date indicates that, although much good has been done, much more good can be done. Since 1991, there has been a 26% decline in the cancer death rate age adjusted to the year 2000 standard population. There are more than 15.5 million cancer survivors in the United States.1 Given the challenge that still exists, it is appropriate to assess where the fields of cancer control and oncology have come from and where they are going, what issues must be dealt with, and what interventions must be implemented if we are to most efficiently control cancer. Over the past 5 decades, there has been an extraordinary investment in cancer research that has led to a greater understanding of the disease. Indeed, cancer is being redefined. We are literally moving from the mid-19th century definition based on histopathology to a 21st century definition of cancer that also includes genomic information. Past investments in basic research are yielding better diagnostic and screening technologies and leading to new approaches to treatment. Molecular biology provides the foundation for new treatments in precision medicine. Decades of immunology research are showing us ways to effectively harness the patient's immune system and encourage it to attack their cancer. At the same time, a better understanding of carcinogenesis is allowing for improved cancer prevention. In the next several issues of CA: A Cancer Journal for Clinicians, the American Cancer Society will publish a series of articles assessing trends in cancer mortality and issues and opportunities in cancer prevention, screening, and treatment. These articles summarize where we have come from, the current state of cancer in the United States, and how more consistent and equitable application of currently available interventions can further reduce the cancer incidence and death rates. When there are sufficient data to make a projection, estimates of the potential effect of cancer control interventions are included. Of course, we must continue to support scientific research and innovation, as the future promises even greater benefit. The foundation of a national cancer control plan to reduce the burden of cancer is a group of initiatives to ensure equal and full access to the combination of preventive and therapeutic measures that are already proven effective. We believe this is a moral imperative. These goals cannot be achieved, however, without recognizing that the roots of health care disparities are deep, reflecting fundamental determinants of health, such as poverty, conscious and unconscious racism, barriers to the availability of healthy foods, a “built environment” that limits opportunities for physical activity, and the lack of systems that ensure access to high-quality health care. Any national cancer control plan must include meaningful efforts to address these determinants of health. The forthcoming series of articles will describe the American Cancer Society's vision for how cancer prevention, screening, diagnosis, and treatment can be transformed to define the most efficient path to lower the cancer burden in the United States; these articles comprise the basis of a national cancer control plan, a blueprint toward the control of cancer and cancer mortality reduction and a mortality reduction goal for the year 2035. It is our hope that this blueprint will be a call to action for patients with cancer, their family members, professional organizations, government agencies, the medical profession, academia, and industry to work together to implement what is known about cancer control and support scientific investigation to further our knowledge.

Purpose Although information from pathology reports is essential to the care of individuals with cancer and to population-level cancer control, no systematic evidence exists regarding the adequacy of breast pathology reporting in Ethiopia. This study audited pathology reports of mastectomy specimens from patients evaluated at the Tikur Anbessa Specialized Hospital Oncology Center in Addis Ababa, Ethiopia. Methods Mastectomy pathology reports from February 2014 through January 2016 were assessed for gross and microscopic information considered by the Breast Cancer Initiative 2.5 (BCI 2.5; formerly the Breast Health Global Initiative) guideline to be necessary for care of patients with breast cancer stratified according to basic, limited, and enhanced resource settings. Results Fewer than two thirds (61.6%) of the 417 reports we reviewed included all four of the BCI 2.5 basic pathology data elements we could evaluate with available data (tumor category, lymph node category, histologic type, and histologic grade). Only 1.0% of reports included all three pathology data elements recommended for limited resource settings (estrogen receptor status, margin status, and lymphovascular invasion). Several elements were significantly more likely to be noted in reports from nonpublic hospitals than from public hospitals. Although only three of 417 reports included checklists or templates, all three of these reports included all of the basic pathology information, and they all included at least two of the three limited pathology elements not already on the basic list. Conclusion More than one third (38.4%) of mastectomy pathology reports did not meet BCI 2.5 standards for basic resource settings. Quality measurement and improvement programs and capacity-building interventions by national pathology and oncology organizations, collaboration with medical and public health organizations in neighboring countries, adoption of synoptic reporting templates, use of electronic pathology reporting, and histotechnology and histopathology training collaborations with laboratories in high-resource regions are recommended.

This article summarizes cancer mortality trends and disparities based on data from the National Center for Health Statistics. It is the first in a series of articles that will describe the American Cancer Society's vision for how cancer prevention, early detection, and treatment can be transformed to lower the cancer burden in the United States, and sets the stage for a national cancer control plan, or blueprint, for the American Cancer Society goals for reducing cancer mortality by the year 2035. Although steady progress in reducing cancer mortality has been made over the past few decades, it is clear that much more could, and should, be done to save lives through the comprehensive application of currently available evidence-based public health and clinical interventions to all segments of the population. CA Cancer J Clin 2018;000:000-000. © 2018 American Cancer Society.

Purpose: Nonrepresentative biopsy sampling of prostate cancers with a biopsy Gleason score of 8 can adversely influence decisions regarding androgen deprivation in men receiving primary radiation therapy. The frequency of and factors associated with downgrading Gleason 8 biopsies at prostatectomy are not well known. Materials and Methods: We used records from NCDB (National Cancer Database), a hospital based registry in the United States, of 72,556 men with prostate cancer diagnosed from 2010 to 2013, including 5,474 with Gleason 8 biopsies and no other high progression risk criteria according to NCCN (National Comprehensive Cancer Network (R)) Guidelines (R). The prevalence of Gleason 8 downgrading was calculated. Generalized estimating equation multivariable regression models were used to estimate the prevalence ratios and 95% CIs of downgrading by demographic and clinical factors, and evaluate the association of Gleason 8 downgrading with cT (clinical T) to pathological T category up staging. Results: Of 5,474 Gleason 8 biopsies in men lacking other high progression risk criteria 3,263 (60%) were downgraded, changing the progression risk category from high to intermediate. A higher prevalence of Gleason 8 downgrading was significantly and independently associated with decreasing age, African American race, lower cT category, lower prostate specific antigen quartile and certain combinations of primary and secondary Gleason grades (3 thorn 5 greater than 4 thorn 4 greater than 5 thorn 3). Gleason 8 downgrading in cases of cT less than 3 was independently and significantly associated with a lower prevalence of up staging (prevalence ratio = 0.65, 95% CI 0.61-0.69). Conclusions: Downgrading Gleason 8 biopsies is common. Patient evaluation based on Gleason 8 biopsies often results in overestimating progression risk and disease extent, which may lead to overtreatment.

Key Points Distress is very common among individuals living with cancer, and can adversely affect quality of life and decrease adherence to treatment regimens. All individuals diagnosed with cancer should be evaluated for distress and treated according to guideline recommendations. Many individuals with cancer‐related distress remain undiagnosed and untreated. Web‐based psychosocial interventions may provide a valuable option for some patients facing access barriers to face‐to‐face psychological interventions for cancer‐related distress.