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Record W4247381534 · doi:10.5858/133.8.1197

The 7th Edition AJCC Staging System for Eye Cancer: An International Language for Ophthalmic Oncology

2009· article· en· W4247381534 on OpenAlexaboutno aff
Paul T. Finger

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCancer stagingCancerMedical physicsOncologyPathologyInternal medicine

Abstract

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The Ophthalmic Oncology Task Force1 has significantly changed the American Joint Committee on Cancer (AJCC) staging system for eye cancer. The 7th edition incorporates more clinically relevant, site-specific staging systems for primary cancers of the eyelids, eye, and orbit.2 All chapters now include detailed clinical and pathology guidelines for data acquisition and tissue processing, while collecting evidence-based biomarkers and prospective data points.In 2004, pairs of clinical and pathology specialists were assigned to review each of the 6th edition AJCC chapters for their clinical, pathology, and research utility. Each pair was charged with creating a new, evidence-based medical foundation for its staging systems. They were required to seek biomarkers (known risk factors) and up to 6 data points for evaluation as potential “future” biomarkers. Their initial drafts were reviewed by a second clinician and pathologist team of reviewers. Their comments and suggestions were discussed during periodic subcommittee teleconferences and face-to-face meetings. Then, each section was subjected to review by multiple additional specialists. During this 4-year process, the Ophthalmic Oncology Task Force grew to include 45 eye cancer specialists from 10 countries (including 3 official International Union Against Cancer [UICC; L'Union Internationale Contre le Cancer] representatives) who worked together to define a comprehensive, anatomically based TNM (tumor-node-metastasis)–based staging system for eye cancer. This peer-review system allowed for an evaluation, synthesis, and consensus for clinical practice parameters and pathology techniques and review.The following AJCC chapters are reviewed in 3 different papers published in this joint issue for ophthalmic pathology between the Archives of Pathology & Laboratory Medicine and the Archives of Ophthalmology.The evolution of the eyelid carcinoma staging system was particularly complex. From a clinical perspective, Ainbinder et al were expected to design a staging system that could be used by ophthalmologists, head and neck surgeons, Mohs surgeons, dermatologists, radiation oncologists, and pathologists. The authors were further challenged to describe site-specific implications of invasion of the eye, orbit, sinuses, and brain. This staging system now covers 58 histologic profiles, and includes new nodal and pathology-based biomarkers and unique multispecialty-based data points.2In contrast to eyelid tumors, lacrimal gland carcinomas are rare. In this issue, Drs Jack Rootman and Valerie A. White explain how independent multicenter studies and reviews of epithelial lacrimal tumor diagnosis pathology and treatment were used to shape the lacrimal gland carcinoma staging system.34 They brought this section into line with that used for the more diverse salivary gland neoplasias, while preserving the site-specific aspects of this more occult location. They emphasized the need for a uniform approach to pathologic analysis and classification. The biomarkers Ki-67 and NM23 were added as well as 6 pathology-related prospective data points.2Ocular adnexal lymphoma was revolutionary because it did not exist in the 6th edition. We thought it unreasonable to exclude the most common orbital malignancy from site-specific staging. We needed to know how site-specific factors (location, laterality, histopathology) affected local and systemic prognosis. This site-specific staging system was created by Coupland and colleagues,5 who were uniquely qualified for this task. As you will read, the clinical extent of disease of the ocular adnexal lymphomas was not adequately described by the Ann Arbor staging system. The 7th edition AJCC staging system for ocular adnexal lymphoma continues histologic subtyping according to the World Health Organization (WHO) lymphoma classification and will allow for a more precise description of disease extent and biomarker identification.The committee's aim was to make a useful TNM-based classification system for clinical care (for local and systemic risk assessment), research, and pathology. Each chapter was edited to conform to what is used throughout medicine, for other similar tumors, tumor registries, and world-wide cancer centers. The 7th edition brings ophthalmic oncology into the mainstream of cancer research.The 7th edition AJCC Staging System provides clinically useful definitions of tumor size, location, and metastatic disease for almost all eye cancers.2 The use of this common language will allow us to compare treatments on equivalently sized and “staged” tumors.6 Use of this staging system will improve participation in clinical trials and compliance with cancer center status.The Ophthalmic Oncology Task Force has undertaken an effort to promote the widespread use of the 7th edition, AJCC Staging System. It either has been or will be presented at all of the major national and international ophthalmologic, ophthalmic pathology, ophthalmic plastic, and ocular oncology subspecialty societies for its diffusion.The peer-reviewed ophthalmology journals Archives of Ophthalmology, American Journal of Ophthalmology, British Journal of Ophthalmology, Ophthalmology, and Ophthalmic Plastic and Reconstructive Surgery have recently added the classification to their instructions for authors. Largely adopted by the College of American Pathologists (CAP), it has been presented for approval by the American Association for Ophthalmic Pathology (AAOP). The 7th edition AJCC classifications have been adopted by the National Cancer Institute–sponsored Cancer Biomedical Informatics Grid (caBIG) initiative (http://cabig.nci.nih.gov/).Participants in the 7th edition AJCC ophthalmic oncology classification effort included core members of the AJCC and the UICC. These are large, broadly supported organizations. For example, the AJCC is supported by the American Cancer Society, American College of Radiology, American College of Surgeons (ACS), College of American Pathologists (CAP), United States National Cancer Institute (NCI), Centers for Disease Control and Prevention (CDC), American Society of Clinical Oncology (ASCO), American College of Physicians, American Society for Therapeutic Radiology (ASTRO), caBIG, American Head and Neck Society, American Society of Colon and Rectal Surgery, American Urological Association, National Cancer Institute of Canada (NCI-Canada), National Cancer Registrars Association (NCRA), National Comprehensive Cancer Network, North American Association of Central Cancer Registries, Society of Gynecologic Oncology, Society of Surgical Oncology, Society of Urologic Oncology, and the UICC.The UICC complements the AJCC by reaching additional cancer-related organizations in 103 countries including 27 in Africa, 74 in the Asia/Pacific region, 91 in Europe, 41 in Latin America/the Caribbean, 20 in the Middle East, and 40 in North America in addition to 5 purely international associations.The AJCC-UICC Ophthalmic Oncology Task Force demonstrated how 45 eye cancer specialists can work together to create a common language.6 As part of the AJCC, and in affiliation with the UICC, the 7th edition staging systems will be used by tumor registries and clinical cancer centers around the world.The members of the 7th Edition, AJCC-UICC Ophthalmic Oncology Task Force include Col Darryl J. Ainbinder, MD; Daniel M. Albert, MD, MS; James O. Armitage, MD; James J. Augsburger, MD; Nikolas E. Bechrakis, MD; Maj John H. Boden, MD; Patricia Chévez-Barrios, MD; Sarah E. Coupland, MBBS, PhD, FRCPath; Bertil Damato, MD, PhD; Laurence Desjardins, MD; Ralph C. Eagle, MD; Deepak P. Edward, MD; Bita Esmaeli, MD; Paul T. Finger, MD (Chair); James C. Fleming, MD; Brenda L. Gallie, MD; Dan S. Gombos, MD; Jean-Daniel Grange, MD; Hans E. Grossniklaus, MD, MBA; Barrett G. Haik, MD; Col John B. Halligan, MD; J. William Harbour, MD; George J. Harocopos, MD; Leonard M. Holbach, MD; John L. Hungerford, MD; Martine J. Jager, MD, PhD; Zeynel A. Karcioglu, MD; Tero Kivela, MD; Emma Kujala, MD; Ashwin C. Mallipatna, MBBS; Col Robert A Mazzoli, MD; Hugh McGowan, MD; Tatyana Milman, MD; A. Linn Murphree, MD; Tim G. Murray, MD, MBA; Jack Rootman, MD, FRCS; Didi de Wolff-Rouendaal, MD, PhD; Andrew P. Schachat, MD; Stefan Seregard, MD; E. Rand Simpson, MD; Arun D. Singh, MD; Valerie A. White, MD, MHSc; Matthew W. Wilson, MD; Christian W. Wittekind, MD; Guopei Yu, MD, MPH.This work is supported by the American College of Surgeons, the American Joint Committee on Cancer (AJCC), the International Union Against Cancer (UICC), Springer, and The EyeCare Foundation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.372
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations70
Published2009
Admission routes1
Has abstractyes

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