Cancer Biomarkers The Role of Structured Data Reporting Ross W. Simpson, MD; Michael A. Berman, MD; Philip R. Foulis, MD, MPH; Dimitrios X. G. Divaris, MBChB, FRCPC; George G. Birdsong, MD; Jaleh Mirza, MD, MPH, CHCQM; Richard Moldwin, MD, PhD; Samantha Spencer, MD; John R. Srigley, MD, FRCPC; Patrick L. Fitzgibbons, MD
Context.—The College of American Pathologists has been producing cancer protocols since 1986 to aid pathologists in the diagnosis and reporting of cancer cases. Many pathologists use the included cancer case summaries as templates for dictation/data entry into the final pathology report. These summaries are now available in a computer-readable format with structured data elements for interoperability, packaged as ‘‘electronic cancer checklists.’’ Most major vendors of anatomic pathology reporting software support this model. Objectives.—To outline the development and advantages of structured electronic cancer reporting using the electronic cancer checklist model, and to describe its
extension to cancer biomarkers and other aspects of cancer reporting. Data Sources.—Peer-reviewed literature and internal records of the College of American Pathologists. Conclusions.—Accurate and usable cancer biomarker data reporting will increasingly depend on initial capture of this information as structured data. This process will support the standardization of data elements and biomarker terminology, enabling the meaningful use of these datasets by pathologists, clinicians, tumor registries, and patients. (Arch Pathol Lab Med. 2015;139:587–593; doi: 10.5858/ arpa.2014-0082-RA)
T
as ‘‘CAP electronic Cancer Checklists’’ (eCCs). Most major anatomic pathology laboratory information system vendors support the eCC model. The rapidly increasing frequency of cancer biomarker testing in the management of patients with cancer has highlighted deficiencies in reporting biomarker results. This review will outline the development of structured electronic reporting using the eCC model, and will describe its extension and relevance to cancer biomarkers and other aspects of cancer reporting.
he College of American Pathologists (CAP) has been producing the CAP Cancer Protocols (CCPs) since 1986 to aid pathologists in the diagnosis and reporting of cancer cases.1 Many pathologists use the cancer case summaries from the CCPs as templates for dictation or data entry into a word processing document,2 but the CCPs are also available in PDF, Microsoft Word (Microsoft Corporation, Redmond, Washington), and computer-readable extensible markup language (XML)3 formats. The XML versions, which contain structured data elements for interoperability, are packaged
Accepted for publication April 28, 2014. Published as an Early Online Release October 2, 2014. From the Department of Pathology, Park Nicollet–Methodist Hospital, St Louis Park, Minnesota (Dr Simpson); the Department of Pathology, Jefferson Regional Medical Center, Jefferson Hills, Pennsylvania (Dr Berman); the University of South Florida Department of Pathology and Cell Biology, James A. Haley Veterans’ Hospital, Tampa (Dr Foulis); the Department of Laboratory Medicine, Grand River Hospital, Kitchener, Ontario, Canada (Dr Divaris); the Department of Pathology, Grady Health System/Emory University School of Medicine, Atlanta, Georgia (Dr Birdsong); Capability & Specialty Advancement, College of American Pathologists, Northfield, Illinois (Drs Mirza, Moldwin, and Spencer); the Laboratory Medicine and Genetics Program, Trillium Health Partners, Mississauga, Ontario, Canada (Dr Srigley); and the Department of Pathology, St Jude Medical Center, Fullerton, California (Dr Fitzgibbons). The authors have no relevant financial interest in the products or companies described in this article. Reprints: Ross W. Simpson, MD, Department of Pathology, Park Nicollet–Methodist Hospital, 6500 Excelsior Blvd, St Louis Park, MN 55440 (e-mail: [email protected]). Arch Pathol Lab Med—Vol 139, May 2015
NARRATIVE VERSUS STRUCTURED DATA REPORTING Clinical laboratory reports typically consist of discrete data elements with structured qualitative or quantitative information, often using standardized laboratory methods, data elements, and units. When discrete data elements are electronically transmitted to external clinical information systems, the transmitted information may be annotated with one or more terminologies such as Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT)4 and Logical Observation Identifiers Names and Codes (LOINC),5 although the consistent application of such codes to structured laboratory data is not yet an interoperable standard. Because the structure of clinical laboratory data tends to be fixed and standardized before the point of data entry, reporting these data elements in a tabular synoptic format is a relatively simple process. The report output may not include all data collected (eg, methodologic details), but clinically relevant data can be easily extracted by computer algorithm and automatically reported in easily readable format (including custom text, result explanations, and test value trends). Cancer Biomarker Structured Reporting—Simpson et al 587
Anatomic pathology reports, by contrast, have traditionally been narrative and recorded as unstructured or partially structured fields of text. Unfortunately, narrative reporting often lacks consistency in organization, content, units, terminology, and completeness.6–8 These structural inconsistencies create difficulties in finding and understanding clinically important data and increase the chance of omitting key data elements and misinterpreting information present in the narrative. This is particularly problematic when clinicians encounter reports from multiple pathology laboratories or when patients receive care at multiple institutions. Narrative reporting has equally negative effects on computer readability; the ability of computers to correctly parse and classify information contained in a narrative report is imperfect even when using advanced natural language processing software designed specifically for anatomic pathology.9,10 Natural language processing–parsed text must always undergo human review, editing, and signoff before release for patient care or research. Ensuring consistency and readability of cancer and biomarker reports requires a reporting solution integrated into the pathologist workflow that supports entry of standardized data directly into a laboratory information system and/or electronic health record system. These systems can produce highly readable synoptic reports and can include computer-based report validation of standardized data elements to reduce or eliminate the chance of omitting required data elements. With the transition from narrative to synoptic reporting for cancer cases, many laboratories have been using modified CCPs or locally developed templates or macros, which may or may not contain all required data elements. This common mode of data entry fits well into the pathologist workflow and can result in organized, highly readable synoptic reports, but generally results in information stored as text in a single large data field. Even when results are entered as discrete data elements, subsequent storage mechanisms usually result in nonstructured text or nonstandard custom data fields in a local computer system. Unfortunately, narrative and nonstandardized data sets are very difficult to reliably aggregate and analyze for laboratory quality assurance, research, or cancer registry surveillance. Such aggregated data also remain relatively unreliable because of changes in information systems. Many of these issues can be eliminated by entering and reporting structured data with standardized electronic templates. CAP eCC HISTORY, DEVELOPMENT, AND ADOPTION Efforts to bring structure to cancer pathology reporting began in the late 1980s and early 1990s1,11,12 with publication of templates that were the precursors of the current CCPs (Table). The primary goal was to improve the care of cancer patients by improving the reporting rate of clinically important data elements. The checklist approach was adopted to help standardize terminology and ensure all relevant data elements are reported. The 66 current CCPs, 3 new cancer biomarker templates,13–16 and 85 eCC templates represent the evolution of the original 1986 CCP model. The CCPs and templates are created and maintained through the ongoing work of the CAP Cancer and Cancer Biomarker Reporting Committees. The CCPs are widely adopted by laboratories and used for accreditation purposes by the American College of Surgeons–Commission on Cancer17 and CAP Laboratory Accreditation Program.18 588 Arch Pathol Lab Med—Vol 139, May 2015
During the past several years, the CAP has worked to create standardized pathology reporting templates that enable individual pathologists and software vendors to capture, store, retrieve, transmit, and analyze diagnostic cancer pathology information. Electronic versions of these templates, the eCCs, are based on consistent structured data representation, which enables simple yet robust computerization of cancer pathology data elements suitable for patient care, cancer registry transmission, and research. Synoptic reports are not the same as ‘‘structured data.’’ Although synoptic reports are formatted for optimum human readability and understanding, they consist of textbased questions and answers (ideally one pair per line) that present problems for computer readability and interoperability. Structured data, by contrast, refers to representation of data elements in a computer-readable data exchange format such as XML. The structured data model used by eCC XML templates assigns a unique identifier (a composite key) to every question and answer choice, template, section, and note listed in the template. Composite keys are used throughout the entire eCC life cycle to transmit the precise identity of each data element and its origin in a specific version of an eCC template. Figure 1 provides short examples of narrative, synoptic, and structured (XML) data reporting. The XML row in this figure illustrates the use of composite keys to precisely identify the structured data derived from the eCC XML data-entry template. Figure 2 shows the life cycle of eCCbased structured data, from CCP creation to the various uses of eCC-generated patient data. Solutions are also being explored for computer representation of synoptic reports that will enable automated and customizable report creation from structured data. The CAP eCC model has been implemented provincewide by Cancer Care Ontario through their multiyear synoptic pathology reporting and change-management project.19–21 The Canadian Partnership Against Cancer is also currently working with several other Canadian provinces to implement population-level electronic synoptic reporting based on the CAP eCC. The Cancer Care Ontario project has shown that there is high acceptability among pathologists and clinicians22 and that data are usable for the secondary needs of tumor registries,20 but there remains room for improvement. For instance, both the Reporting Pathology Protocols project reports23–25 and the Cancer Care Ontario implementation reports22 suggest that pathologists require more time to complete the reporting task. While this may meet quality and data reporting needs, it remains a potential barrier to acceptance. Automated human-readable report generation also could be improved, especially in terms of creating best practice guidelines for report output. Both data entry and report generation have traditionally been supported by laboratory information systems vendors, but the success of implementation has varied, and often significant effort is required to modify the resultant humanreadable report to satisfy local clinical needs. Because the final report remains most important for patient care, the CAP Diagnostic Intelligence in Health Information Technology and Pathology Electronic Reporting committees have initiated work on creating and promoting a standardized data structure within cancer pathology reports. RELEVANCE TO CANCER BIOMARKER REPORTING The lack of report standardization is a growing problem for biomarker testing because of the rapidly increasing Cancer Biomarker Structured Reporting—Simpson et al
CAP eCC History and Milestonesa Year
Milestone
1986–1995 1998–2000 2001–2009
Original CCP model created by CAP1,11,12,31 and ADASP.32–36 32 CCPs published in Reporting on Cancer Specimens: Protocols and Case Summaries.37 RPP projects engage several states to evaluate the use of SNOMED CT coding of the CCPs for cancer registry data transmissions.23–25 General terminology coding with SNOMED CT was found to be unsuitable for cancer reporting. Many SNOMED CT codes are unavailable for rapidly evolving cancer pathology reporting. New CCPs released, adopting AJCC 6th edition staging with SNOMED CT encoding. CCO signs memorandum of understanding with CAP to use CCPs as standard for cancer pathology reporting in Ontario, Canada. Institutions accredited by American College of Surgeons–Commission on Cancer mandate reporting of required data elements included in CCPs.17 First electronic SNOMED CT–encoded version of CCPs in Access (Microsoft Corporation, Redmond, Washington) database. CAP establishes the Pathology Electronic Reporting Taskforce to advance the implementation of CCPs using health information technology. CCO implements eCC-based synoptic reporting in 5 disease sites.21 The CAP eCCs are produced in XML format, and made available to pathologist end users through AP-LIS vendors. Canadian Association of Pathologists adopts CAP CCPs as standard for cancer pathology reporting in Canada. CCO successfully implements population level electronic synoptic reporting in nearly all disease sites based on 2010 CAP eCC standards, which include AJCC 7th edition TNM staging; 97% of labs report using structured data from eCC.20 CAP Laboratory Accreditation Program begins to survey institutions for inclusion of required CCP data elements in AP reports.38 NAACCR Pathology Data Workgroup develops implementation guide to assist with CAP eCC-based transmissions of cancer data to central cancer registries.39 CCO user acceptability data demonstrate high level of acceptance for eCC-derived synoptic reports among clinicians and pathologists.22 CAP forms the multi-organizational Cancer Biomarker Reporting Workgroup, tasked to produce standardized reporting templates for breast, colorectal, and lung cancer biomarkers.40 eCC-based reporting in Ontario is used to improve quality and practice performance.20 The first cancer biomarker templates are produced for breast, colorectal, and lung cancer.13–16 They are available on the www.cap.org/cancerprotocols Web site in Word and PDF format (accessed April 28, 2014). The eCC versions are available through CAP. Launch of CAP eFRM, a software product to aid vendor integration of eCCs into AP-LIS systems or for use as a standalone product. By December 2013, CAP is maintaining current versions of 66 CCPs, 3 cancer biomarker templates, and 85 corresponding eCC templates.
2003 2004 2004 2007 2007 2008–2010 2009 2009 2010–2012 2010 2010 2011 2012 2013 2013 2013 2014
Abbreviations: ADASP, Association of Directors of Anatomic and Surgical Pathology; AJCC, American Joint Committee on Cancer; AP, anatomic pathology; AP-LIS, anatomic pathology laboratory information system; CAP, College of American Pathologists; CCO, Cancer Care Ontario; CCPs, CAP Cancer Protocols; eCC, Electronic Cancer Checklist; CAP eFRM, CAP electronic Forms and Reporting Module; NAACCR, North American Association of Central Cancer Registries; RPP, Reporting Pathology Protocols; SNOMED CT, Systematized Nomenclature of Medicine Clinical Terms. a Based on Amin,41 with modification and updates.
number of important biomarkers and the volume of genomic, proteomic, and epigenetic (eg, gene methylation) data being generated. In part because of a need to improve standardization of reporting and in part because biomarker testing is usually performed independently from the pathologic evaluation of cancer specimens, the biomarker sections (nee ´ ‘‘Ancillary Testing’’) in the CCPs are being removed and placed in separate, enhanced reporting templates. As with the CCPs, these templates will be available in multiple formats, including the eCC XML. As an example, Figure 3 illustrates a Web page rendition of ALK biomarker testing results using the lung cancer biomarker eCC template. The eCC format is ideal for recording most biomarker results and allows interoperability and transmission of results without reentry of data for separate sites and mapping to common terminologies including Human Genome Variation Society (HGVS) nomenclature,26–28 SNOMED CT, and LOINC. Another advantage of the eCC model is that it allows for agile release of a standard electronic reporting system in sync with the rapidly changing reporting requirements and standards for bioArch Pathol Lab Med—Vol 139, May 2015
marker reporting. These new cancer biomarker templates are part of larger CAP initiatives to develop standards in biomarkers, to expand this guidance to biomarker reporting informatics practices, and to promote interoperable, computer-interpretable datasets for cancer care, research, and genetic counseling. FUTURE The use of standardized, structured data elements is foundational for the development of improved reporting and clinical decision support for biomarker results. Clinicians are currently faced with synthesizing data from multiple narrative reports to decide on treatment options. Often these narrative reports are from different laboratories with very different report formats and include variable methodologic details, all of which hinders understanding of important results. For biomarkers that determine a patient’s eligibility for specific drugs, a computer-generated report that presents test results in a tabular form, similar to antibiotic susceptibility testing, may be desirable. This reporting method would allow for display of biomarker test results over time and could also link to other databases, such Cancer Biomarker Structured Reporting—Simpson et al 589
Figure 1. Narrative versus synoptic versus structured reporting of breast biomarker testing (excerpts). The narrative row shows a portion of a dictated biomarker report. The synoptic row satisfies the College of American Pathologists (CAP) synoptic reporting requirements, but is not computer readable. The structured data row shows part of a sample XML report containing a subset of information from the previous rows. The bolded XML text corresponds to the bolded text in the narrative and synoptic rows. The indentation and hierarchy in the XML report reflects the context of the questions and answers in the data entry form. Standardization of the XML reporting format is part of an ongoing multi-organizational effort that includes the CAP. Definitions for the XML structure are as follows. Header, , ?xml version¼‘‘1.0’’ encoding¼‘‘UTF-8’’?., standard header identifying this document’s format as XML. Elements: sr-data, wrapper element for ‘‘structured report data’’ in XML report; question, question derived from the eCC template; answer, selected answer choice derived from the eCC template. Attributes: template-id, identifier for the eCC template class, for example, ‘‘BREAST: Biomarker Reporting Template’’; template-xml-version, the version of the eCC XML template used to generate the report; each template-id may be associated with one or more versions; display-name, default text visible on the data-entry form, derived from the eCC template; ckey, composite key that uniquely identifies each item (eg, questions and answers) in an eCC template; value, text or number entered by user. Abbreviation: HER2, human epidermal growth factor receptor 2.
as relevant clinical trials or automated suggestions for other biomarkers. Structured data allows for clinical decision support such that the report displays only eligible drugs, or the report displays a note stating that a test result suggests a patient is not eligible for a specific drug. Using standardized terminology allows these rules to be the same between institutions, even if electronic health record system vendors use different means of implementation. As an example, current CAP guidelines address EGFR and ALK testing for some types of non–small cell lung cancer,13,29 but there are at least 6 additional biomarkers under study,14 some of which are likely to be added to the 590 Arch Pathol Lab Med—Vol 139, May 2015
guidelines. Biomarker results may indicate patient eligibility for treatment with specific drugs or provide evidence that a patient is unlikely to respond to a drug. Figure 4 provides examples of possible ‘‘dashboard’’ report summaries that would link results with targeted therapeutics. These examples are simple, but as the implications of the result are refined over time, the summary could be altered to reflect current knowledge or the availability of new testing. With various molecular alterations indicating increased or decreased likelihood of response, the clinician is currently faced with reading a number of individual reports and interpreting them in aggregate. Standardization of reporting Cancer Biomarker Structured Reporting—Simpson et al
Figure 2. The College of American Pathologists (CAP) Cancer Protocols (CCPs) are developed by the CAP Cancer Committee. Each CCP is reformulated as question/answer structures, entered into the CAP electronic Cancer Checklist (eCC) Template Editor (not shown), and stored in the eCC template database. The eCC files in XML format are produced from this database and delivered to vendors of anatomic pathology/laboratory information system (LIS) software systems. Vendors convert the eCC files into data entry form implementations using their local technologies. In addition, most vendors create eCC-based templates for creating synoptic reports. When pathologists enter data into the eCC-based data-entry forms, the vendor software is able to run validation checks such as assessing whether all CCP-required data elements are recorded. Synoptic reports are developed from the eCC-derived data and delivered to health care providers for patient care. The eCC-structured data is stored in the vendor database, where it can be transmitted in interoperable format to other computer systems. Secondary uses of eCC-based data include cancer registry reporting, quality assurance, biospecimen annotation, research, decision support, and financial reporting. The horizontal arrows involve the exchange of eCC composite keys, preserving the fidelity of the data as part of an eCC template, providing the foundation for interoperable data transmission formats, and enabling the regeneration of eCC datasets in the exact format in which they were recorded. Activity columns that directly impact health care activities are shaded in light blue. Abbreviation: EHR, electronic health record.
results would allow for automation of this task and save time. Reporting results as discrete data would also allow computerized searches for identifying subsets of patients for subsequent research questions, or to find patients that might qualify for new studies or treatments. As an example, searches could be made for lung cancers that are negative for ALK but untested for ROS1, and alert the treating clinician to the availability of this option. If universally adopted, these searches could encompass data generated
Figure 3. College of American Pathologists electronic Cancer Checklist lung cancer biomarker template—anaplastic lymphoma kinase (ALK). Abbreviations: EML4, echinoderm microtubule-associated protein-like 4; KIF5B, kinesin family member 5B; KLC1, kinesin light chain 1; TFG, tropomyosin receptor kinase–fused gene. Arch Pathol Lab Med—Vol 139, May 2015
from multiple labs. This might also allow earlier detection of response trends or complications from a given treatment with a specific combination of biomarker results. This future state of system design would allow for electronic reporting of the discrete tumor and biomarker data for clinical decision support, research, genetic coun-
Figure 4. Examples of tumor biomarker dashboards. Abbreviations: ALK, anaplastic lymphoma kinase; ROS1, ROS proto-oncogene 1, receptor tyrosine kinase. Cancer Biomarker Structured Reporting—Simpson et al 591
seling and screening, and public health needs. This system would allow for more efficient, more accurate, and safer methods of providing data for optimizing patient care, with all of the discrete data transmitted electronically and linked to the original tumor report. In Ontario, Canada, this vision is rapidly advancing, as demonstrated by the Cancer Care Ontario successes with eCC implementation and current plans to implement the eCC biomarker templates across the province. Future challenges include the identity and tracking of related tumor samples over time and integration of testing from different laboratories. Because testing on a given specimen can be performed at different times and in different laboratories, a future standard must address the annotation of results with tumor source, procurement dates, and other biospecimen-specific data.30 The relationship of test results from multiple specimens from the same patient needs to be recorded in a standard format so that this parent-child hierarchical relationship can be analyzed over time. SUMMARY Pathologists are increasingly asked to provide biomarker information for patient care, tumor registries, epidemiologic studies, translational research, and quality improvement activities.20 The eCC model provides a pathway to meet these demands, with efficient and error-free data entry, reporting, and transmission of data elements, and with the ability to produce output that is human readable, efficient to use, and easy to interpret. As the CCPs and eCCs have matured, Ontario pathologists and cancer registries have demonstrated success with large-scale implementations. However, continued improvements are needed. As the field of pathology grows, particularly in the area of biomarkers, structured electronic reporting will become critical to helping physicians provide optimal patient care and will facilitate secondary uses of pathology data. References 1. Hutter RVP. Guidelines for data to be included in consultation reports on breast cancer, bladder cancer, and Hodgkin’s disease. Pathologist. 1986;40:18– 23. 2. Ellis DW. Surgical pathology reporting at the crossroads: beyond synoptic r e p o r t i n g . P a t h o l o g y. 2 0 1 1 ; 4 3 ( 5 ) : 4 0 4 – 4 0 9 . d o i : 1 0 . 1 0 9 7 / PAT. 0b013e32834915e8. 3. Refsnes Data. XML tutorial. http://www.w3schools.com/xml. Accessed February 5, 2014. 4. International Health Terminology and Standards Development Organisation. About SNOMED CT. http://www.ihtsdo.org/snomed-ct/snomed-ct0/. Accessed February 5, 2014. 5. Regenstrief Institute. LOINCt from Regenstrief. http://loinc.org/. Accessed February 5, 2014. 6. Idowu MO, Bekeris LG, Raab S, Ruby SG, Nakhleh RE. Adequacy of surgical pathology reporting of cancer: a College of American Pathologists QProbes study of 86 institutions. Arch Pathol Lab Med. 2010;134(7):969–974. doi: 10.1043/2009-0412-CP.1. 7. Messenger DE, McLeod RS, Kirsch R. What impact has the introduction of a synoptic report for rectal cancer had on reporting outcomes for specialist gastrointestinal and nongastrointestinal pathologists? Arch Pathol Lab Med. 2011; 135(11):1471–1475. doi:10.5858/arpa.2010-0558-OA. 8. Nakhleh RE. What is quality in surgical pathology? J Clin Pathol. 2006; 59(7):669–672. doi:10.1136/jcp.2005.031385. 9. Nguyen A, Lawley M, Hansen D, Colquist S. Structured pathology reporting for cancer from free text: lung cancer case study. Electron J Health Inform. 2011;7(1):e8. 10. Buckley JM, Coopey SB, Sharko J, et al. The feasibility of using natural language processing to extract clinical information from breast pathology reports. J Pathol Inform. 2012;3:23. doi:10.4103/2153–3539.97788. 11. Henson DE, Hutter RV, Farrow G. Practice protocol for the examination of specimens removed from patients with carcinoma of the prostate gland: a publication of the Cancer Committee, College of American Pathologists: task
592 Arch Pathol Lab Med—Vol 139, May 2015
force on the examination of specimens removed from patients with prostate cancer. Arch Pathol Lab Med. 1994;118(8):779–783. 12. Henson DE, Hutter RV, Sobin LH, Bowman HE. Protocol for the examination of specimens removed from patients with colorectal carcinoma: basis for checklists: Cancer Committee, College of American Pathologists: task force for protocols on the examination of specimens from patients with colorectal cancer. Arch Pathol Lab Med. 1994;118(2):122–125. 13. Cagle PT, Sholl LM, Lindeman NI, et al. Template for reporting results of biomarker testing of specimens from patients with non–small cell carcinoma of the lung. Arch Pathol Lab Med. 2014;138(2):171–174. doi:10.5858/arpa. 2013-0232-CP. 14. Cagle PT, Allen TC, Olsen RJ. Lung cancer biomarkers: present status and future developments. Arch Pathol Lab Med. 2013;137(9):1191–1198. doi:10. 5858/arpa.2013-0319-CR. 15. Bartley AN, Hamilton SR, Alsabeh R, et al. Template for reporting results of biomarker testing of specimens from patients with carcinoma of the colon and rectum. Arch Pathol Lab Med. 2014;138(2):166–170. doi:10.5858/arpa. 2013-0231-CP. 16. Fitzgibbons PL, Dillon DA, Alsabeh R, et al. Template for reporting results of biomarker testing of specimens from patients with carcinoma of the breast [published online ahead of print November 15, 2013]. Arch Pathol Lab Med. 2014;138(5):595–601. doi:10.5858/arpa.2013-0566-CP. 17. Amin MB. Key issues in reporting common cancer specimen findings using the College of American Pathologists cancer protocols. Arch Pathol Lab Med. 2006;130(3):284–286. doi:10.1043/1543–2165(2006)130[284:KIIRCC]2.0. CO;2. 18. Allen TC, Hammond MEH, Robboy SJ. Quality and the College of American Pathologists. Arch Pathol Lab Med. 2011;135(11):1441. doi:10.5858/ arpa.2011-0287-SA. 19. Nofech-Mozes S. Synoptic reporting on breast cancer biomarkers: a novel quality improvement module. Can J Pathol. 2011;3(4):11–15. 20. Srigley J, Lankshear S, Brierley J, et al. Closing the quality loop: facilitating improvement in oncology practice through timely access to clinical performance indicators. J Oncol Pract. 2013;9(5):e255–e261. doi:10.1200/JOP.2012.000818. 21. Srigley JR, McGowan T, Maclean A, et al. Standardized synoptic cancer pathology reporting: a population-based approach. J Surg Oncol. 2009;99(8): 517–524. doi:10.1002/jso.21282. 22. Lankshear S, Srigley J, McGowan T, Yurcan M, Sawka C. Standardized synoptic cancer pathology reports—so what and who cares?: a population-based satisfaction survey of 970 pathologists, surgeons, and oncologists. Arch Pathol Lab Med. 2013;137(11):1599–1602. doi:10.5858/arpa.2012-0656-OA. 23. Report on the Reporting Pathology Protocols for Colon and Rectum Cancers Project. Atlanta, GA: Department of Health and Human Services (HHS), Centers for Disease Control and Prevention (CDC), National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP); 2005:1–124. 24. Hassell L, Aldinger W, Moody C, et al. Electronic capture and communication of synoptic cancer data elements from pathology reports: results of the Reporting Pathology Protocols 2 (RPP2) project. J Regist Manag. 2009; 36(4):117–124; quiz 163–165. 25. Hassell LA, Parwani AV, Weiss L, Jones MA, Ye J. Challenges and opportunities in the adoption of College of American Pathologists checklists in electronic format: perspectives and experience of Reporting Pathology Protocols Project (RPP2) participant laboratories. Arch Pathol Lab Med. 2010;134(8):1152– 1159. doi:10.1043/2009-0386-OA.1. 26. Human Genome Variation Society. Nomenclature for the description of sequence variants. http://www.hgvs.org/mutnomen/. Accessed February 6, 2014. 27. Taschner PEM, den Dunnen JT. Describing structural changes by extending HGVS sequence variation nomenclature. Hum Mutat. 2011;32(5):507–511. doi: 10.1002/humu.21427. 28. Den Dunnen JT, Antonarakis SE. Mutation nomenclature extensions and suggestions to describe complex mutations: a discussion. Hum Mutat. 2000; 15(1):7–12. doi:10.1002/(SICI)1098-1004(200001)15:1,7::AID-HUMU4.3.0. CO;2-N. 29. Lindeman NI, Cagle PT, Beasley MB, et al. Molecular testing guideline for selection of lung cancer patients for EGFR and ALK tyrosine kinase inhibitors: guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology. Arch Pathol Lab Med. 2013;137(6):828–860. doi:10.5858/arpa.2012-0720-OA. 30. Robb JA, Gulley ML, Fitzgibbons PL, et al. A call to standardize preanalytic data elements for biospecimens. Arch Pathol Lab Med. 2014;138(4):526–537. 31. Scully RE, Henson DE, Nielsen ML, Ruby SG. Practice protocol for the examination of specimens removed from patients with ovarian tumors: a basis for checklists: Cancer Committee, College of American Pathologists: task force on the examination of specimens removed from patients with ovarian tumors. Arch Pathol Lab Med. 1995;119(11):1012–1022. 32. Simpson PR, Tschang TP. ADASP recommendations: consultations in surgical pathology: Association of Directors of Anatomic and Surgical Pathology. Hum Pathol. 1993;24(12):1382. 33. Immediate management of mammographically detected breast lesions: Association of Directors of Anatomic and Surgical Pathology. Am J Surg Pathol. 1993;17(8):850–851. 34. Recommendations of the Association of Directors of Anatomic and Surgical Pathology, part II: consultations in surgical pathology. Hum Pathol. 1993;24(7):691–692.
Cancer Biomarker Structured Reporting—Simpson et al
35. Recommendations on quality control and quality assurance in surgical pathology and autopsy pathology: the Association of Directors of Anatomic and Surgical Pathology. Mod Pathol. 1992;5(5):567–568. 36. Recommendations on quality control and quality assurance in anatomic pathology: Association of Directors of Anatomic and Surgical Pathology. Am J Surg Pathol. 1991;15(10):1007–1009. 37. Compton CC, Henson DE, Hammond EH, Schramm JB, eds. Reporting on Cancer Specimens: Protocols and Case Summaries. Northfield, IL: College of American Pathologists; 1998. 38. College of American Pathologists. CAP cancer protocols frequently asked questions. http://www.cap.org/apps//cap.portal?_nfpb¼true&cntvwrPtlt_ actionOverride¼%2Fportlets%2FcontentViewer%2Fshow&_windowLabel¼
Arch Pathol Lab Med—Vol 139, May 2015
cntvwrPtlt&cntvwrPtlt%7BactionForm.contentReference%7D¼committees%2 Fcancer%2Fcancer_protocols%2Fprotocols_intro.html&_state¼maximized& _pageLabel¼cntvwr. Accessed February 6, 2014. 39. Klein WT, Havener LA, eds. Standards for Cancer Registries Volume V: Pathology Laboratory Electronic Reporting, Version 4.0. Springfield, IL: North American Association of Central Cancer Registries; 2011:1–310. 40. Fitzgibbons PL, Lazar AJ, Spencer S. Introducing new College of American Pathologists reporting templates for cancer biomarkers. Arch Pathol Lab Med. 2014;138(2):157–158. doi:10.5858/arpa.2013-0233-ED. 41. Amin MB. The 2009 version of the cancer protocols of the College of American Pathologists. Arch Pathol Lab Med. 2010;134(3):326–330. doi:10. 1043/1543-2165-134.3.326.
Cancer Biomarker Structured Reporting—Simpson et al 593
Copyright of Archives of Pathology & Laboratory Medicine is the property of College of American Pathologists and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
Context.—The College of American Pathologists has been producing cancer protocols since 1986 to aid pathologists in the diagnosis and reporting of cancer cases. Many pathologists use the included cancer case summaries as templates for dictation/data entry into the final pathology report. These summaries are now available in a computer-readable format with structured data elements for interoperability, packaged as ‘‘electronic cancer checklists.’’ Most major vendors of anatomic pathology reporting software support this model. Objectives.—To outline the development and advantages of structured electronic cancer reporting using the electronic cancer checklist model, and to describe its
extension to cancer biomarkers and other aspects of cancer reporting. Data Sources.—Peer-reviewed literature and internal records of the College of American Pathologists. Conclusions.—Accurate and usable cancer biomarker data reporting will increasingly depend on initial capture of this information as structured data. This process will support the standardization of data elements and biomarker terminology, enabling the meaningful use of these datasets by pathologists, clinicians, tumor registries, and patients. (Arch Pathol Lab Med. 2015;139:587–593; doi: 10.5858/ arpa.2014-0082-RA)
T
as ‘‘CAP electronic Cancer Checklists’’ (eCCs). Most major anatomic pathology laboratory information system vendors support the eCC model. The rapidly increasing frequency of cancer biomarker testing in the management of patients with cancer has highlighted deficiencies in reporting biomarker results. This review will outline the development of structured electronic reporting using the eCC model, and will describe its extension and relevance to cancer biomarkers and other aspects of cancer reporting.
he College of American Pathologists (CAP) has been producing the CAP Cancer Protocols (CCPs) since 1986 to aid pathologists in the diagnosis and reporting of cancer cases.1 Many pathologists use the cancer case summaries from the CCPs as templates for dictation or data entry into a word processing document,2 but the CCPs are also available in PDF, Microsoft Word (Microsoft Corporation, Redmond, Washington), and computer-readable extensible markup language (XML)3 formats. The XML versions, which contain structured data elements for interoperability, are packaged
Accepted for publication April 28, 2014. Published as an Early Online Release October 2, 2014. From the Department of Pathology, Park Nicollet–Methodist Hospital, St Louis Park, Minnesota (Dr Simpson); the Department of Pathology, Jefferson Regional Medical Center, Jefferson Hills, Pennsylvania (Dr Berman); the University of South Florida Department of Pathology and Cell Biology, James A. Haley Veterans’ Hospital, Tampa (Dr Foulis); the Department of Laboratory Medicine, Grand River Hospital, Kitchener, Ontario, Canada (Dr Divaris); the Department of Pathology, Grady Health System/Emory University School of Medicine, Atlanta, Georgia (Dr Birdsong); Capability & Specialty Advancement, College of American Pathologists, Northfield, Illinois (Drs Mirza, Moldwin, and Spencer); the Laboratory Medicine and Genetics Program, Trillium Health Partners, Mississauga, Ontario, Canada (Dr Srigley); and the Department of Pathology, St Jude Medical Center, Fullerton, California (Dr Fitzgibbons). The authors have no relevant financial interest in the products or companies described in this article. Reprints: Ross W. Simpson, MD, Department of Pathology, Park Nicollet–Methodist Hospital, 6500 Excelsior Blvd, St Louis Park, MN 55440 (e-mail: [email protected]). Arch Pathol Lab Med—Vol 139, May 2015
NARRATIVE VERSUS STRUCTURED DATA REPORTING Clinical laboratory reports typically consist of discrete data elements with structured qualitative or quantitative information, often using standardized laboratory methods, data elements, and units. When discrete data elements are electronically transmitted to external clinical information systems, the transmitted information may be annotated with one or more terminologies such as Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT)4 and Logical Observation Identifiers Names and Codes (LOINC),5 although the consistent application of such codes to structured laboratory data is not yet an interoperable standard. Because the structure of clinical laboratory data tends to be fixed and standardized before the point of data entry, reporting these data elements in a tabular synoptic format is a relatively simple process. The report output may not include all data collected (eg, methodologic details), but clinically relevant data can be easily extracted by computer algorithm and automatically reported in easily readable format (including custom text, result explanations, and test value trends). Cancer Biomarker Structured Reporting—Simpson et al 587
Anatomic pathology reports, by contrast, have traditionally been narrative and recorded as unstructured or partially structured fields of text. Unfortunately, narrative reporting often lacks consistency in organization, content, units, terminology, and completeness.6–8 These structural inconsistencies create difficulties in finding and understanding clinically important data and increase the chance of omitting key data elements and misinterpreting information present in the narrative. This is particularly problematic when clinicians encounter reports from multiple pathology laboratories or when patients receive care at multiple institutions. Narrative reporting has equally negative effects on computer readability; the ability of computers to correctly parse and classify information contained in a narrative report is imperfect even when using advanced natural language processing software designed specifically for anatomic pathology.9,10 Natural language processing–parsed text must always undergo human review, editing, and signoff before release for patient care or research. Ensuring consistency and readability of cancer and biomarker reports requires a reporting solution integrated into the pathologist workflow that supports entry of standardized data directly into a laboratory information system and/or electronic health record system. These systems can produce highly readable synoptic reports and can include computer-based report validation of standardized data elements to reduce or eliminate the chance of omitting required data elements. With the transition from narrative to synoptic reporting for cancer cases, many laboratories have been using modified CCPs or locally developed templates or macros, which may or may not contain all required data elements. This common mode of data entry fits well into the pathologist workflow and can result in organized, highly readable synoptic reports, but generally results in information stored as text in a single large data field. Even when results are entered as discrete data elements, subsequent storage mechanisms usually result in nonstructured text or nonstandard custom data fields in a local computer system. Unfortunately, narrative and nonstandardized data sets are very difficult to reliably aggregate and analyze for laboratory quality assurance, research, or cancer registry surveillance. Such aggregated data also remain relatively unreliable because of changes in information systems. Many of these issues can be eliminated by entering and reporting structured data with standardized electronic templates. CAP eCC HISTORY, DEVELOPMENT, AND ADOPTION Efforts to bring structure to cancer pathology reporting began in the late 1980s and early 1990s1,11,12 with publication of templates that were the precursors of the current CCPs (Table). The primary goal was to improve the care of cancer patients by improving the reporting rate of clinically important data elements. The checklist approach was adopted to help standardize terminology and ensure all relevant data elements are reported. The 66 current CCPs, 3 new cancer biomarker templates,13–16 and 85 eCC templates represent the evolution of the original 1986 CCP model. The CCPs and templates are created and maintained through the ongoing work of the CAP Cancer and Cancer Biomarker Reporting Committees. The CCPs are widely adopted by laboratories and used for accreditation purposes by the American College of Surgeons–Commission on Cancer17 and CAP Laboratory Accreditation Program.18 588 Arch Pathol Lab Med—Vol 139, May 2015
During the past several years, the CAP has worked to create standardized pathology reporting templates that enable individual pathologists and software vendors to capture, store, retrieve, transmit, and analyze diagnostic cancer pathology information. Electronic versions of these templates, the eCCs, are based on consistent structured data representation, which enables simple yet robust computerization of cancer pathology data elements suitable for patient care, cancer registry transmission, and research. Synoptic reports are not the same as ‘‘structured data.’’ Although synoptic reports are formatted for optimum human readability and understanding, they consist of textbased questions and answers (ideally one pair per line) that present problems for computer readability and interoperability. Structured data, by contrast, refers to representation of data elements in a computer-readable data exchange format such as XML. The structured data model used by eCC XML templates assigns a unique identifier (a composite key) to every question and answer choice, template, section, and note listed in the template. Composite keys are used throughout the entire eCC life cycle to transmit the precise identity of each data element and its origin in a specific version of an eCC template. Figure 1 provides short examples of narrative, synoptic, and structured (XML) data reporting. The XML row in this figure illustrates the use of composite keys to precisely identify the structured data derived from the eCC XML data-entry template. Figure 2 shows the life cycle of eCCbased structured data, from CCP creation to the various uses of eCC-generated patient data. Solutions are also being explored for computer representation of synoptic reports that will enable automated and customizable report creation from structured data. The CAP eCC model has been implemented provincewide by Cancer Care Ontario through their multiyear synoptic pathology reporting and change-management project.19–21 The Canadian Partnership Against Cancer is also currently working with several other Canadian provinces to implement population-level electronic synoptic reporting based on the CAP eCC. The Cancer Care Ontario project has shown that there is high acceptability among pathologists and clinicians22 and that data are usable for the secondary needs of tumor registries,20 but there remains room for improvement. For instance, both the Reporting Pathology Protocols project reports23–25 and the Cancer Care Ontario implementation reports22 suggest that pathologists require more time to complete the reporting task. While this may meet quality and data reporting needs, it remains a potential barrier to acceptance. Automated human-readable report generation also could be improved, especially in terms of creating best practice guidelines for report output. Both data entry and report generation have traditionally been supported by laboratory information systems vendors, but the success of implementation has varied, and often significant effort is required to modify the resultant humanreadable report to satisfy local clinical needs. Because the final report remains most important for patient care, the CAP Diagnostic Intelligence in Health Information Technology and Pathology Electronic Reporting committees have initiated work on creating and promoting a standardized data structure within cancer pathology reports. RELEVANCE TO CANCER BIOMARKER REPORTING The lack of report standardization is a growing problem for biomarker testing because of the rapidly increasing Cancer Biomarker Structured Reporting—Simpson et al
CAP eCC History and Milestonesa Year
Milestone
1986–1995 1998–2000 2001–2009
Original CCP model created by CAP1,11,12,31 and ADASP.32–36 32 CCPs published in Reporting on Cancer Specimens: Protocols and Case Summaries.37 RPP projects engage several states to evaluate the use of SNOMED CT coding of the CCPs for cancer registry data transmissions.23–25 General terminology coding with SNOMED CT was found to be unsuitable for cancer reporting. Many SNOMED CT codes are unavailable for rapidly evolving cancer pathology reporting. New CCPs released, adopting AJCC 6th edition staging with SNOMED CT encoding. CCO signs memorandum of understanding with CAP to use CCPs as standard for cancer pathology reporting in Ontario, Canada. Institutions accredited by American College of Surgeons–Commission on Cancer mandate reporting of required data elements included in CCPs.17 First electronic SNOMED CT–encoded version of CCPs in Access (Microsoft Corporation, Redmond, Washington) database. CAP establishes the Pathology Electronic Reporting Taskforce to advance the implementation of CCPs using health information technology. CCO implements eCC-based synoptic reporting in 5 disease sites.21 The CAP eCCs are produced in XML format, and made available to pathologist end users through AP-LIS vendors. Canadian Association of Pathologists adopts CAP CCPs as standard for cancer pathology reporting in Canada. CCO successfully implements population level electronic synoptic reporting in nearly all disease sites based on 2010 CAP eCC standards, which include AJCC 7th edition TNM staging; 97% of labs report using structured data from eCC.20 CAP Laboratory Accreditation Program begins to survey institutions for inclusion of required CCP data elements in AP reports.38 NAACCR Pathology Data Workgroup develops implementation guide to assist with CAP eCC-based transmissions of cancer data to central cancer registries.39 CCO user acceptability data demonstrate high level of acceptance for eCC-derived synoptic reports among clinicians and pathologists.22 CAP forms the multi-organizational Cancer Biomarker Reporting Workgroup, tasked to produce standardized reporting templates for breast, colorectal, and lung cancer biomarkers.40 eCC-based reporting in Ontario is used to improve quality and practice performance.20 The first cancer biomarker templates are produced for breast, colorectal, and lung cancer.13–16 They are available on the www.cap.org/cancerprotocols Web site in Word and PDF format (accessed April 28, 2014). The eCC versions are available through CAP. Launch of CAP eFRM, a software product to aid vendor integration of eCCs into AP-LIS systems or for use as a standalone product. By December 2013, CAP is maintaining current versions of 66 CCPs, 3 cancer biomarker templates, and 85 corresponding eCC templates.
2003 2004 2004 2007 2007 2008–2010 2009 2009 2010–2012 2010 2010 2011 2012 2013 2013 2013 2014
Abbreviations: ADASP, Association of Directors of Anatomic and Surgical Pathology; AJCC, American Joint Committee on Cancer; AP, anatomic pathology; AP-LIS, anatomic pathology laboratory information system; CAP, College of American Pathologists; CCO, Cancer Care Ontario; CCPs, CAP Cancer Protocols; eCC, Electronic Cancer Checklist; CAP eFRM, CAP electronic Forms and Reporting Module; NAACCR, North American Association of Central Cancer Registries; RPP, Reporting Pathology Protocols; SNOMED CT, Systematized Nomenclature of Medicine Clinical Terms. a Based on Amin,41 with modification and updates.
number of important biomarkers and the volume of genomic, proteomic, and epigenetic (eg, gene methylation) data being generated. In part because of a need to improve standardization of reporting and in part because biomarker testing is usually performed independently from the pathologic evaluation of cancer specimens, the biomarker sections (nee ´ ‘‘Ancillary Testing’’) in the CCPs are being removed and placed in separate, enhanced reporting templates. As with the CCPs, these templates will be available in multiple formats, including the eCC XML. As an example, Figure 3 illustrates a Web page rendition of ALK biomarker testing results using the lung cancer biomarker eCC template. The eCC format is ideal for recording most biomarker results and allows interoperability and transmission of results without reentry of data for separate sites and mapping to common terminologies including Human Genome Variation Society (HGVS) nomenclature,26–28 SNOMED CT, and LOINC. Another advantage of the eCC model is that it allows for agile release of a standard electronic reporting system in sync with the rapidly changing reporting requirements and standards for bioArch Pathol Lab Med—Vol 139, May 2015
marker reporting. These new cancer biomarker templates are part of larger CAP initiatives to develop standards in biomarkers, to expand this guidance to biomarker reporting informatics practices, and to promote interoperable, computer-interpretable datasets for cancer care, research, and genetic counseling. FUTURE The use of standardized, structured data elements is foundational for the development of improved reporting and clinical decision support for biomarker results. Clinicians are currently faced with synthesizing data from multiple narrative reports to decide on treatment options. Often these narrative reports are from different laboratories with very different report formats and include variable methodologic details, all of which hinders understanding of important results. For biomarkers that determine a patient’s eligibility for specific drugs, a computer-generated report that presents test results in a tabular form, similar to antibiotic susceptibility testing, may be desirable. This reporting method would allow for display of biomarker test results over time and could also link to other databases, such Cancer Biomarker Structured Reporting—Simpson et al 589
Figure 1. Narrative versus synoptic versus structured reporting of breast biomarker testing (excerpts). The narrative row shows a portion of a dictated biomarker report. The synoptic row satisfies the College of American Pathologists (CAP) synoptic reporting requirements, but is not computer readable. The structured data row shows part of a sample XML report containing a subset of information from the previous rows. The bolded XML text corresponds to the bolded text in the narrative and synoptic rows. The indentation and hierarchy in the XML report reflects the context of the questions and answers in the data entry form. Standardization of the XML reporting format is part of an ongoing multi-organizational effort that includes the CAP. Definitions for the XML structure are as follows. Header, , ?xml version¼‘‘1.0’’ encoding¼‘‘UTF-8’’?., standard header identifying this document’s format as XML. Elements: sr-data, wrapper element for ‘‘structured report data’’ in XML report; question, question derived from the eCC template; answer, selected answer choice derived from the eCC template. Attributes: template-id, identifier for the eCC template class, for example, ‘‘BREAST: Biomarker Reporting Template’’; template-xml-version, the version of the eCC XML template used to generate the report; each template-id may be associated with one or more versions; display-name, default text visible on the data-entry form, derived from the eCC template; ckey, composite key that uniquely identifies each item (eg, questions and answers) in an eCC template; value, text or number entered by user. Abbreviation: HER2, human epidermal growth factor receptor 2.
as relevant clinical trials or automated suggestions for other biomarkers. Structured data allows for clinical decision support such that the report displays only eligible drugs, or the report displays a note stating that a test result suggests a patient is not eligible for a specific drug. Using standardized terminology allows these rules to be the same between institutions, even if electronic health record system vendors use different means of implementation. As an example, current CAP guidelines address EGFR and ALK testing for some types of non–small cell lung cancer,13,29 but there are at least 6 additional biomarkers under study,14 some of which are likely to be added to the 590 Arch Pathol Lab Med—Vol 139, May 2015
guidelines. Biomarker results may indicate patient eligibility for treatment with specific drugs or provide evidence that a patient is unlikely to respond to a drug. Figure 4 provides examples of possible ‘‘dashboard’’ report summaries that would link results with targeted therapeutics. These examples are simple, but as the implications of the result are refined over time, the summary could be altered to reflect current knowledge or the availability of new testing. With various molecular alterations indicating increased or decreased likelihood of response, the clinician is currently faced with reading a number of individual reports and interpreting them in aggregate. Standardization of reporting Cancer Biomarker Structured Reporting—Simpson et al
Figure 2. The College of American Pathologists (CAP) Cancer Protocols (CCPs) are developed by the CAP Cancer Committee. Each CCP is reformulated as question/answer structures, entered into the CAP electronic Cancer Checklist (eCC) Template Editor (not shown), and stored in the eCC template database. The eCC files in XML format are produced from this database and delivered to vendors of anatomic pathology/laboratory information system (LIS) software systems. Vendors convert the eCC files into data entry form implementations using their local technologies. In addition, most vendors create eCC-based templates for creating synoptic reports. When pathologists enter data into the eCC-based data-entry forms, the vendor software is able to run validation checks such as assessing whether all CCP-required data elements are recorded. Synoptic reports are developed from the eCC-derived data and delivered to health care providers for patient care. The eCC-structured data is stored in the vendor database, where it can be transmitted in interoperable format to other computer systems. Secondary uses of eCC-based data include cancer registry reporting, quality assurance, biospecimen annotation, research, decision support, and financial reporting. The horizontal arrows involve the exchange of eCC composite keys, preserving the fidelity of the data as part of an eCC template, providing the foundation for interoperable data transmission formats, and enabling the regeneration of eCC datasets in the exact format in which they were recorded. Activity columns that directly impact health care activities are shaded in light blue. Abbreviation: EHR, electronic health record.
results would allow for automation of this task and save time. Reporting results as discrete data would also allow computerized searches for identifying subsets of patients for subsequent research questions, or to find patients that might qualify for new studies or treatments. As an example, searches could be made for lung cancers that are negative for ALK but untested for ROS1, and alert the treating clinician to the availability of this option. If universally adopted, these searches could encompass data generated
Figure 3. College of American Pathologists electronic Cancer Checklist lung cancer biomarker template—anaplastic lymphoma kinase (ALK). Abbreviations: EML4, echinoderm microtubule-associated protein-like 4; KIF5B, kinesin family member 5B; KLC1, kinesin light chain 1; TFG, tropomyosin receptor kinase–fused gene. Arch Pathol Lab Med—Vol 139, May 2015
from multiple labs. This might also allow earlier detection of response trends or complications from a given treatment with a specific combination of biomarker results. This future state of system design would allow for electronic reporting of the discrete tumor and biomarker data for clinical decision support, research, genetic coun-
Figure 4. Examples of tumor biomarker dashboards. Abbreviations: ALK, anaplastic lymphoma kinase; ROS1, ROS proto-oncogene 1, receptor tyrosine kinase. Cancer Biomarker Structured Reporting—Simpson et al 591
seling and screening, and public health needs. This system would allow for more efficient, more accurate, and safer methods of providing data for optimizing patient care, with all of the discrete data transmitted electronically and linked to the original tumor report. In Ontario, Canada, this vision is rapidly advancing, as demonstrated by the Cancer Care Ontario successes with eCC implementation and current plans to implement the eCC biomarker templates across the province. Future challenges include the identity and tracking of related tumor samples over time and integration of testing from different laboratories. Because testing on a given specimen can be performed at different times and in different laboratories, a future standard must address the annotation of results with tumor source, procurement dates, and other biospecimen-specific data.30 The relationship of test results from multiple specimens from the same patient needs to be recorded in a standard format so that this parent-child hierarchical relationship can be analyzed over time. SUMMARY Pathologists are increasingly asked to provide biomarker information for patient care, tumor registries, epidemiologic studies, translational research, and quality improvement activities.20 The eCC model provides a pathway to meet these demands, with efficient and error-free data entry, reporting, and transmission of data elements, and with the ability to produce output that is human readable, efficient to use, and easy to interpret. As the CCPs and eCCs have matured, Ontario pathologists and cancer registries have demonstrated success with large-scale implementations. However, continued improvements are needed. As the field of pathology grows, particularly in the area of biomarkers, structured electronic reporting will become critical to helping physicians provide optimal patient care and will facilitate secondary uses of pathology data. References 1. Hutter RVP. Guidelines for data to be included in consultation reports on breast cancer, bladder cancer, and Hodgkin’s disease. Pathologist. 1986;40:18– 23. 2. Ellis DW. Surgical pathology reporting at the crossroads: beyond synoptic r e p o r t i n g . P a t h o l o g y. 2 0 1 1 ; 4 3 ( 5 ) : 4 0 4 – 4 0 9 . d o i : 1 0 . 1 0 9 7 / PAT. 0b013e32834915e8. 3. Refsnes Data. XML tutorial. http://www.w3schools.com/xml. Accessed February 5, 2014. 4. International Health Terminology and Standards Development Organisation. About SNOMED CT. http://www.ihtsdo.org/snomed-ct/snomed-ct0/. Accessed February 5, 2014. 5. Regenstrief Institute. LOINCt from Regenstrief. http://loinc.org/. Accessed February 5, 2014. 6. Idowu MO, Bekeris LG, Raab S, Ruby SG, Nakhleh RE. Adequacy of surgical pathology reporting of cancer: a College of American Pathologists QProbes study of 86 institutions. Arch Pathol Lab Med. 2010;134(7):969–974. doi: 10.1043/2009-0412-CP.1. 7. Messenger DE, McLeod RS, Kirsch R. What impact has the introduction of a synoptic report for rectal cancer had on reporting outcomes for specialist gastrointestinal and nongastrointestinal pathologists? Arch Pathol Lab Med. 2011; 135(11):1471–1475. doi:10.5858/arpa.2010-0558-OA. 8. Nakhleh RE. What is quality in surgical pathology? J Clin Pathol. 2006; 59(7):669–672. doi:10.1136/jcp.2005.031385. 9. Nguyen A, Lawley M, Hansen D, Colquist S. Structured pathology reporting for cancer from free text: lung cancer case study. Electron J Health Inform. 2011;7(1):e8. 10. Buckley JM, Coopey SB, Sharko J, et al. The feasibility of using natural language processing to extract clinical information from breast pathology reports. J Pathol Inform. 2012;3:23. doi:10.4103/2153–3539.97788. 11. Henson DE, Hutter RV, Farrow G. Practice protocol for the examination of specimens removed from patients with carcinoma of the prostate gland: a publication of the Cancer Committee, College of American Pathologists: task
592 Arch Pathol Lab Med—Vol 139, May 2015
force on the examination of specimens removed from patients with prostate cancer. Arch Pathol Lab Med. 1994;118(8):779–783. 12. Henson DE, Hutter RV, Sobin LH, Bowman HE. Protocol for the examination of specimens removed from patients with colorectal carcinoma: basis for checklists: Cancer Committee, College of American Pathologists: task force for protocols on the examination of specimens from patients with colorectal cancer. Arch Pathol Lab Med. 1994;118(2):122–125. 13. Cagle PT, Sholl LM, Lindeman NI, et al. Template for reporting results of biomarker testing of specimens from patients with non–small cell carcinoma of the lung. Arch Pathol Lab Med. 2014;138(2):171–174. doi:10.5858/arpa. 2013-0232-CP. 14. Cagle PT, Allen TC, Olsen RJ. Lung cancer biomarkers: present status and future developments. Arch Pathol Lab Med. 2013;137(9):1191–1198. doi:10. 5858/arpa.2013-0319-CR. 15. Bartley AN, Hamilton SR, Alsabeh R, et al. Template for reporting results of biomarker testing of specimens from patients with carcinoma of the colon and rectum. Arch Pathol Lab Med. 2014;138(2):166–170. doi:10.5858/arpa. 2013-0231-CP. 16. Fitzgibbons PL, Dillon DA, Alsabeh R, et al. Template for reporting results of biomarker testing of specimens from patients with carcinoma of the breast [published online ahead of print November 15, 2013]. Arch Pathol Lab Med. 2014;138(5):595–601. doi:10.5858/arpa.2013-0566-CP. 17. Amin MB. Key issues in reporting common cancer specimen findings using the College of American Pathologists cancer protocols. Arch Pathol Lab Med. 2006;130(3):284–286. doi:10.1043/1543–2165(2006)130[284:KIIRCC]2.0. CO;2. 18. Allen TC, Hammond MEH, Robboy SJ. Quality and the College of American Pathologists. Arch Pathol Lab Med. 2011;135(11):1441. doi:10.5858/ arpa.2011-0287-SA. 19. Nofech-Mozes S. Synoptic reporting on breast cancer biomarkers: a novel quality improvement module. Can J Pathol. 2011;3(4):11–15. 20. Srigley J, Lankshear S, Brierley J, et al. Closing the quality loop: facilitating improvement in oncology practice through timely access to clinical performance indicators. J Oncol Pract. 2013;9(5):e255–e261. doi:10.1200/JOP.2012.000818. 21. Srigley JR, McGowan T, Maclean A, et al. Standardized synoptic cancer pathology reporting: a population-based approach. J Surg Oncol. 2009;99(8): 517–524. doi:10.1002/jso.21282. 22. Lankshear S, Srigley J, McGowan T, Yurcan M, Sawka C. Standardized synoptic cancer pathology reports—so what and who cares?: a population-based satisfaction survey of 970 pathologists, surgeons, and oncologists. Arch Pathol Lab Med. 2013;137(11):1599–1602. doi:10.5858/arpa.2012-0656-OA. 23. Report on the Reporting Pathology Protocols for Colon and Rectum Cancers Project. Atlanta, GA: Department of Health and Human Services (HHS), Centers for Disease Control and Prevention (CDC), National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP); 2005:1–124. 24. Hassell L, Aldinger W, Moody C, et al. Electronic capture and communication of synoptic cancer data elements from pathology reports: results of the Reporting Pathology Protocols 2 (RPP2) project. J Regist Manag. 2009; 36(4):117–124; quiz 163–165. 25. Hassell LA, Parwani AV, Weiss L, Jones MA, Ye J. Challenges and opportunities in the adoption of College of American Pathologists checklists in electronic format: perspectives and experience of Reporting Pathology Protocols Project (RPP2) participant laboratories. Arch Pathol Lab Med. 2010;134(8):1152– 1159. doi:10.1043/2009-0386-OA.1. 26. Human Genome Variation Society. Nomenclature for the description of sequence variants. http://www.hgvs.org/mutnomen/. Accessed February 6, 2014. 27. Taschner PEM, den Dunnen JT. Describing structural changes by extending HGVS sequence variation nomenclature. Hum Mutat. 2011;32(5):507–511. doi: 10.1002/humu.21427. 28. Den Dunnen JT, Antonarakis SE. Mutation nomenclature extensions and suggestions to describe complex mutations: a discussion. Hum Mutat. 2000; 15(1):7–12. doi:10.1002/(SICI)1098-1004(200001)15:1,7::AID-HUMU4.3.0. CO;2-N. 29. Lindeman NI, Cagle PT, Beasley MB, et al. Molecular testing guideline for selection of lung cancer patients for EGFR and ALK tyrosine kinase inhibitors: guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology. Arch Pathol Lab Med. 2013;137(6):828–860. doi:10.5858/arpa.2012-0720-OA. 30. Robb JA, Gulley ML, Fitzgibbons PL, et al. A call to standardize preanalytic data elements for biospecimens. Arch Pathol Lab Med. 2014;138(4):526–537. 31. Scully RE, Henson DE, Nielsen ML, Ruby SG. Practice protocol for the examination of specimens removed from patients with ovarian tumors: a basis for checklists: Cancer Committee, College of American Pathologists: task force on the examination of specimens removed from patients with ovarian tumors. Arch Pathol Lab Med. 1995;119(11):1012–1022. 32. Simpson PR, Tschang TP. ADASP recommendations: consultations in surgical pathology: Association of Directors of Anatomic and Surgical Pathology. Hum Pathol. 1993;24(12):1382. 33. Immediate management of mammographically detected breast lesions: Association of Directors of Anatomic and Surgical Pathology. Am J Surg Pathol. 1993;17(8):850–851. 34. Recommendations of the Association of Directors of Anatomic and Surgical Pathology, part II: consultations in surgical pathology. Hum Pathol. 1993;24(7):691–692.
Cancer Biomarker Structured Reporting—Simpson et al
35. Recommendations on quality control and quality assurance in surgical pathology and autopsy pathology: the Association of Directors of Anatomic and Surgical Pathology. Mod Pathol. 1992;5(5):567–568. 36. Recommendations on quality control and quality assurance in anatomic pathology: Association of Directors of Anatomic and Surgical Pathology. Am J Surg Pathol. 1991;15(10):1007–1009. 37. Compton CC, Henson DE, Hammond EH, Schramm JB, eds. Reporting on Cancer Specimens: Protocols and Case Summaries. Northfield, IL: College of American Pathologists; 1998. 38. College of American Pathologists. CAP cancer protocols frequently asked questions. http://www.cap.org/apps//cap.portal?_nfpb¼true&cntvwrPtlt_ actionOverride¼%2Fportlets%2FcontentViewer%2Fshow&_windowLabel¼
Arch Pathol Lab Med—Vol 139, May 2015
cntvwrPtlt&cntvwrPtlt%7BactionForm.contentReference%7D¼committees%2 Fcancer%2Fcancer_protocols%2Fprotocols_intro.html&_state¼maximized& _pageLabel¼cntvwr. Accessed February 6, 2014. 39. Klein WT, Havener LA, eds. Standards for Cancer Registries Volume V: Pathology Laboratory Electronic Reporting, Version 4.0. Springfield, IL: North American Association of Central Cancer Registries; 2011:1–310. 40. Fitzgibbons PL, Lazar AJ, Spencer S. Introducing new College of American Pathologists reporting templates for cancer biomarkers. Arch Pathol Lab Med. 2014;138(2):157–158. doi:10.5858/arpa.2013-0233-ED. 41. Amin MB. The 2009 version of the cancer protocols of the College of American Pathologists. Arch Pathol Lab Med. 2010;134(3):326–330. doi:10. 1043/1543-2165-134.3.326.
Cancer Biomarker Structured Reporting—Simpson et al 593
Copyright of Archives of Pathology & Laboratory Medicine is the property of College of American Pathologists and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
