Journal of the National Cancer Institute. Monographs最新文献

{"title":"Perceptions, prevalence, and patterns of cannabis use among cancer patients treated at 12 NCI-Designated Cancer Centers.","authors":"Gary L Ellison, Kathy J Helzlsouer, Sonia M Rosenfield, Yun Kim, Rebecca L Ashare, Anne H Blaes, Jennifer Cullen, Neal Doran, Jon O Ebbert, Kathleen M Egan, Jaimee L Heffner, Richard T Lee, Erin A McClure, Corinne McDaniels-Davidson, Salimah H Meghani, Polly A Newcomb, Shannon Nugent, Nicholas Hernandez-Ortega, Talya Salz, Denise C Vidot, Brooke Worster, Dylan M Zylla","doi":"10.1093/jncimonographs/lgae029","DOIUrl":"10.1093/jncimonographs/lgae029","url":null,"abstract":"<p><strong>Background: </strong>The legal climate for cannabis use has dramatically changed with an increasing number of states passing legislation legalizing access for medical and recreational use. Among cancer patients, cannabis is often used to ameliorate adverse effects of cancer treatment. Data are limited on the extent and type of use among cancer patients during treatment and the perceived benefits and harms. This multicenter survey was conducted to assess the use of cannabis among cancer patients residing in states with varied legal access to cannabis.</p><p><strong>Methods: </strong>A total of 12 NCI-Designated Cancer Centers, across states with varied cannabis-access legal status, conducted surveys with a core questionnaire to assess cannabis use among recently diagnosed cancer patients. Data were collected between September 2021 and August 2023 and pooled across 12 cancer centers. Frequencies and 95% confidence intervals for core survey measures were calculated, and weighted estimates are presented for the 10 sites that drew probability samples.</p><p><strong>Results: </strong>Overall reported cannabis use since cancer diagnosis among survey respondents was 32.9% (weighted), which varied slightly by state legalization status. The most common perceived benefits of use were for pain, sleep, stress and anxiety, and treatment side effects. Reported perceived risks were less common and included inability to drive, difficulty concentrating, lung damage, addiction, and impact on employment. A majority reported feeling comfortable speaking to health-care providers though, overall, only 21.5% reported having done so. Among those who used cannabis since diagnosis, the most common modes were eating in food, smoking, and pills or tinctures, and the most common reasons were for sleep disturbance, followed by pain and stress and anxiety with 60%-68% reporting improved symptoms with use.</p><p><strong>Conclusion: </strong>This geographically diverse survey demonstrates that patients use cannabis regardless of its legal status. Addressing knowledge gaps concerning benefits and harms of cannabis use during cancer treatment is critical to enhance patient-provider communication.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11303851/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141899075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The SEER Program's longstanding commitment to making cancer resources available.","authors":"Patricia K Murphy, Mark E Sellers, Sarah H Bonds, Susan Scott","doi":"10.1093/jncimonographs/lgae028","DOIUrl":"10.1093/jncimonographs/lgae028","url":null,"abstract":"<p><p>The Surveillance, Epidemiology, and End Results (SEER) Program, an authoritative source of cancer statistics in the United States, has been funded by the National Cancer Institute (NCI) since 1973. The goals of SEER include measuring the cancer burden in the United States, making the results available, and supporting cancer research. These goals render products that serve as resources for different audiences, such as cancer registrars, researchers, and the public. Cancer registrars have access to a dedicated tab on the SEER website for questions, assistance with cancer coding, and training and technical resources such as SEER*Rx and SEER Data Management System (SEER*DMS). For researchers, SEER provides access to databases and software such as SEER*Stat and other linked databases such as SEER-Medicare that may offer answers to emerging issues in the field of cancer outcomes, cancer burden, health disparities, healthcare access, diagnosis, and prevention. The public can access cancer materials such as the SEER Cancer Stat Facts sheets, SEER*Explorer, and Did You Know? video series to learn more about cancer. SEER continues to update its resources with and ahead of legislation such as the Plain Writing Act and 21st Century Integrated Digital Experience Act (IDEA) to improve both clarity and user experience. Moving forward, SEER continues to promote awareness of SEER resources, remains accessible and understandable across all audiences, and standardizes how new resources are shared with these groups. The longstanding commitment to making cancer resources available is fundamental to the value of SEER, as evidenced by testimonials from members of various audience types.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300012/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Virtual Pooled Registry-Cancer Linkage System: an improved method for ascertaining cancer diagnoses.","authors":"Dennis Deapen, Castine Clerkin, William Howe, Don Green, Christopher J Johnson, Betsy A Kohler, Annelie M Landgren, Anca Preda, Joanne Elena, Lynne Penberthy","doi":"10.1093/jncimonographs/lgae005","DOIUrl":"10.1093/jncimonographs/lgae005","url":null,"abstract":"<p><strong>Background: </strong>The National Cancer Institute funds many large cohort studies that rely on self-reported cancer data requiring medical record validation. This is labor intensive, costly, and prone to underreporting or misreporting of cancer and disparity-related differential response. US population-based central cancer registries identify incident cancer within their catchment area, yielding all malignant neoplasms and benign brain and central nervous system tumors with standardized data fields. This manuscript describes the development, implementation, and features of a system to facilitate linkage between cohort studies and cancer registries and the release of cancer registry data for matched cohort participants.</p><p><strong>Methods: </strong>The Virtual Pooled Registry-Cancer Linkage System (VPR-CLS) provides an online system to link cohorts with multiple state cancer registries by 1) securely transmitting a study file to registries, 2) providing an optimized linkage algorithm to generate preliminary match counts, and 3) providing a streamlined process and templated forms for submitting and tracking data requests for cohort participants who matched with registries.</p><p><strong>Results: </strong>In 2022, the VPR-CLS launched with 45 registries, covering 95% of the US state populations and Puerto Rico. Registries have linked with 15 studies having 14 273-10.9 million participants. Except in 1 study, linkage sensitivity ranged from 87.0% to 99.9%. Numerous registries have adopted the VPR-CLS templated institutional review board-registry application (n = 39), templated data use agreement (n = 25), and central institutional review board (n = 16).</p><p><strong>Conclusions: </strong>The VPR-CLS markedly improves ascertainment of cancer outcomes and is the preferred approach for determination of outcomes from cohort studies, postmarketing surveillance, and clinical trials.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300027/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141895008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"History of the Surveillance, Epidemiology, and End Results (SEER) Program.","authors":"Steve Friedman, Serban Negoita","doi":"10.1093/jncimonographs/lgae033","DOIUrl":"10.1093/jncimonographs/lgae033","url":null,"abstract":"<p><p>The Surveillance, Epidemiology, and End Results (SEER) Program established in 1973 was the first laboratory for experimenting with new methods for cancer data collection and translating the data into population-based cancer statistics. The SEER Program staff have been instrumental in the development of the International Classification of Disease-Oncology and successfully implemented the routine collection of anatomic and prognostic cancer stage at diagnosis. Currently the program consists of 21 central registries that generate cancer statistics covering more than 48% of the US population and an additional 10 research support registries contributing to certain research projects, such as the National Childhood Cancer Registry. In parallel with the geographical expansion, the program built an architecture of methods and tools for population-based cancer statistics, with SEER*Explorer as the most recent online tool for descriptive statistics. In addition, SEER releases annual updates for a comprehensive data product line, which includes SEER*Stat databases with an annual caseload of more than 800 000 incident cases. Furthermore, the program developed a full suite of analytical applications for population-based cancer statistics that include Joinpoint (regression-based trend analysis), DevCan (risk of diagnosis and death), CanSurv (survival models), and ComPrev and PrejPrev (cancer prevalence), among others. The future of the SEER Program is closely aligned to the overall goals of the \"war on cancer.\" The program aims to release longitudinal treatment data coupled with a comprehensive genomic characterization of cancers with a declared goal of decreasing the cancer burden and disparities across a wide spectrum of diseases and communities.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300016/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning and deep learning tools for the automated capture of cancer surveillance data.","authors":"Elizabeth Hsu, Heidi Hanson, Linda Coyle, Jennifer Stevens, Georgia Tourassi, Lynne Penberthy","doi":"10.1093/jncimonographs/lgae018","DOIUrl":"10.1093/jncimonographs/lgae018","url":null,"abstract":"<p><p>The National Cancer Institute and the Department of Energy strategic partnership applies advanced computing and predictive machine learning and deep learning models to automate the capture of information from unstructured clinical text for inclusion in cancer registries. Applications include extraction of key data elements from pathology reports, determination of whether a pathology or radiology report is related to cancer, extraction of relevant biomarker information, and identification of recurrence. With the growing complexity of cancer diagnosis and treatment, capturing essential information with purely manual methods is increasingly difficult. These new methods for applying advanced computational capabilities to automate data extraction represent an opportunity to close critical information gaps and create a nimble, flexible platform on which new information sources, such as genomics, can be added. This will ultimately provide a deeper understanding of the drivers of cancer and outcomes in the population and increase the timeliness of reporting. These advances will enable better understanding of how real-world patients are treated and the outcomes associated with those treatments in the context of our complex medical and social environment.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-world lessons: combining cancer registry and retail pharmacy data for oral cancer drugs.","authors":"Nadia Howlader, Jennifer L Lund, Lindsey Enewold, Jennifer Stevens, Timothy McNeel, Donna Rivera, Angela Mariotto, Kathleen A Cronin","doi":"10.1093/jncimonographs/lgae023","DOIUrl":"10.1093/jncimonographs/lgae023","url":null,"abstract":"<p><strong>Background: </strong>Recent cancer care advances have introduced new oral therapies, and yet population registries lack detailed treatment data, hampering investigations into therapy uptake, adherence, and outcomes.</p><p><strong>Objective: </strong>This study aimed to assess the representativeness and completeness of linking Surveillance, Epidemiology, and End Results (SEER) cancer registry data with data from two major retail pharmacy chains, collectively covering a large segment of the US market.</p><p><strong>Methods: </strong>A deterministic data linkage between 11 SEER cancer registries and retail pharmacy data (excluding mail order fills) was conducted for individuals diagnosed with selected cancers from 2013 to 2017, with follow-up through 2019. Descriptive characteristics of the linked and unlinked populations were examined. In a selected subcohort of older women (aged ≥65) with first and only primary breast cancer who had Medicare Part D claims for tamoxifen, we further validated the linkage using Medicare Part D event data as the reference standard.</p><p><strong>Results: </strong>Among 758 068 eligible individuals, only 6.4% were linked to CVS/Walgreens data; the linkage percentage varied by age, sex, race, ethnicity, registry, and cancer type. Within the subcohort of 5963 older women with breast cancer and a claim for tamoxifen in Part D data, 25% were identified as tamoxifen users in retail pharmacy data. Out of these 1490 women, 749 (50.3%) had complete longitudinal tamoxifen dispensing information from retail pharmacy data.</p><p><strong>Conclusion: </strong>Retail pharmacy data show promise in identifying oral anticancer treatments, enhancing SEER registry efforts, but they require further validation. We propose an evaluation framework, sharing insights and potential use cases for this resource.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300020/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The SEER Program's evolution: supporting clinically meaningful population-level research.","authors":"Lynne Penberthy, Steven Friedman","doi":"10.1093/jncimonographs/lgae022","DOIUrl":"10.1093/jncimonographs/lgae022","url":null,"abstract":"<p><p>Although the Surveillance, Epidemiology, and End Results (SEER) Program has maintained high standards of quality and completeness, the traditional data captured through population-based cancer surveillance are no longer sufficient to understand the impact of cancer and its outcomes. Therefore, in recent years, the SEER Program has expanded the population it covers and enhanced the types of data that are being collected. Traditionally, surveillance systems collected data characterizing the patient and their cancer at the time of diagnosis, as well as limited information on the initial course of therapy. SEER performs active follow-up on cancer patients from diagnosis until death, ascertaining critical information on mortality and survival over time. With the growth of precision oncology and rapid development and dissemination of new diagnostics and treatments, the limited data that registries have traditionally captured around the time of diagnosis-although useful for characterizing the cancer-are insufficient for understanding why similar patients may have different outcomes. The molecular composition of the tumor and genetic factors such as BRCA status affect the patient's treatment response and outcomes. Capturing and stratifying by these critical risk factors are essential if we are to understand differences in outcomes among patients who may be demographically similar, have the same cancer, be diagnosed at the same stage, and receive the same treatment. In addition to the tumor characteristics, it is essential to understand all the therapies that a patient receives over time, not only for the initial treatment period but also if the cancer recurs or progresses. Capturing this subsequent therapy is critical not only for research but also to help patients understand their risk at the time of therapeutic decision making. This article serves as an introduction and foundation for a JNCI Monograph with specific articles focusing on innovative new methods and processes implemented or under development for the SEER Program. The following sections describe the need to evaluate the SEER Program and provide a summary or introduction of those key enhancements that have been or are in the process of being implemented for SEER.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300003/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"NCI SEER-Linked Virtual Tissue Repository Pilot.","authors":"Pamela Sanchez, Alison L Van Dyke, Valentina I Petkov, Yao Yuan, Sarah Bonds, Connor Valenzuela, Alyssa W Tuan, Radim Moravec, Sean F Altekruse, Aatur D Singhi, Kate M Serdy, Yun Wu, Rosemary D Cress, Jennifer A Doherty, Lloyd Mueller, Brenda Y Hernandez, Charles F Lynch, Thomas C Tucker, Xiao-Cheng Wu, Lynn Matrisian, Lynne Penberthy","doi":"10.1093/jncimonographs/lgae034","DOIUrl":"10.1093/jncimonographs/lgae034","url":null,"abstract":"<p><strong>Background: </strong>The Surveillance, Epidemiology, and End Results (SEER) Program with the National Cancer Institute tested whether population-based cancer registries can serve as honest brokers to acquire tissue and data in the SEER-Linked Virtual Tissue Repository (VTR) Pilot.</p><p><strong>Methods: </strong>We collected formalin-fixed, paraffin-embedded tissue and clinical data from patients with pancreatic ductal adenocarcinoma (PDAC) and breast cancer (BC) for two studies comparing cancer cases with highly unusual survival (≥5 years for PDAC and ≤30 months for BC) to pair-matched controls with usual survival (≤2 years for PDAC and ≥5 years for BC). Success was defined as the ability for registries to acquire tissue and data on cancer cases with highly unusual outcomes.</p><p><strong>Results: </strong>Of 98 PDAC and 103 BC matched cases eligible for tissue collection, sources of attrition for tissue collection were tissue being unavailable, control paired with failed case, second control that was not requested, tumor necrosis ≥20%, and low tumor cellularity. In total, tissue meeting the study criteria was obtained for 70 (71%) PDAC and 74 (72%) BC matched cases. For patients with tissue received, clinical data completeness ranged from 59% for CA-19-9 after treatment to >95% for margin status, whether radiation therapy and chemotherapy were administered, and comorbidities.</p><p><strong>Conclusions: </strong>The VTR Pilot demonstrated the feasibility of using SEER cancer registries as honest brokers to provide tissue and clinical data for secondary use in research. Studies using this program should oversample by 45% to 50% to obtain sufficient sample size and targeted population representation and involve subspecialty matter expert pathologists for tissue selection.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300006/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Landscape analysis of environmental data sources for linkage with SEER cancer patients database.","authors":"Zaria Tatalovich, Amina Chtourou, Li Zhu, Curt Dellavalle, Heidi A Hanson, Kevin A Henry, Lynne Penberthy","doi":"10.1093/jncimonographs/lgae015","DOIUrl":"10.1093/jncimonographs/lgae015","url":null,"abstract":"<p><p>One of the challenges associated with understanding environmental impacts on cancer risk and outcomes is estimating potential exposures of individuals diagnosed with cancer to adverse environmental conditions over the life course. Historically, this has been partly due to the lack of reliable measures of cancer patients' potential environmental exposures before a cancer diagnosis. The emerging sources of cancer-related spatiotemporal environmental data and residential history information, coupled with novel technologies for data extraction and linkage, present an opportunity to integrate these data into the existing cancer surveillance data infrastructure, thereby facilitating more comprehensive assessment of cancer risk and outcomes. In this paper, we performed a landscape analysis of the available environmental data sources that could be linked to historical residential address information of cancer patients' records collected by the National Cancer Institute's Surveillance, Epidemiology, and End Results Program. The objective is to enable researchers to use these data to assess potential exposures at the time of cancer initiation through the time of diagnosis and even after diagnosis. The paper addresses the challenges associated with data collection and completeness at various spatial and temporal scales, as well as opportunities and directions for future research.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300022/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reporting tumor genomic test results to SEER registries via linkages.","authors":"Valentina I Petkov, Jung S Byun, Kevin C Ward, Nicola C Schussler, Natalie P Archer, Suzanne Bentler, Jennifer A Doherty, Eric B Durbin, Susan T Gershman, Iona Cheng, Tabassum Insaf, Lou Gonsalves, Brenda Y Hernandez, Lori Koch, Lihua Liu, Alain Monnereau, Bozena M Morawski, Stephen M Schwartz, Antoinette Stroup, Charles Wiggins, Xiao-Cheng Wu, Sarah Bonds, Serban Negoita, Lynne Penberthy","doi":"10.1093/jncimonographs/lgae013","DOIUrl":"10.1093/jncimonographs/lgae013","url":null,"abstract":"<p><strong>Background: </strong>Precision medicine has become a mainstay of cancer care in recent years. The National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program has been an authoritative source of cancer statistics and data since 1973. However, tumor genomic information has not been adequately captured in the cancer surveillance data, which impedes population-based research on molecular subtypes. To address this, the SEER Program has developed and implemented a centralized process to link SEER registries' tumor cases with genomic test results that are provided by molecular laboratories to the registries.</p><p><strong>Methods: </strong>Data linkages were carried out following operating procedures for centralized linkages established by the SEER Program. The linkages used Match*Pro, a probabilistic linkage software, and were facilitated by the registries' trusted third party (an honest broker). The SEER registries provide to NCI limited datasets that undergo preliminary evaluation prior to their release to the research community.</p><p><strong>Results: </strong>Recently conducted genomic linkages included OncotypeDX Breast Recurrence Score, OncotypeDX Breast Ductal Carcinoma in Situ, OncotypeDX Genomic Prostate Score, Decipher Prostate Genomic Classifier, DecisionDX Uveal Melanoma, DecisionDX Preferentially Expressed Antigen in Melanoma, DecisionDX Melanoma, and germline tests results in Georgia and California SEER registries.</p><p><strong>Conclusions: </strong>The linkages of cancer cases from SEER registries with genomic test results obtained from molecular laboratories offer an effective approach for data collection in cancer surveillance. By providing de-identified data to the research community, the NCI's SEER Program enables scientists to investigate numerous research inquiries.</p>","PeriodicalId":73988,"journal":{"name":"Journal of the National Cancer Institute. Monographs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300019/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}