Breast Cancer Data FHIR IG Proposal

Breast Cancer Data Logical Models and FHIR® Profiles

Owning work group name

Clinical Interoperability Council

Committee Approval Date:

Pending e-vote (expected week of 3/5)

Contributing or Reviewing Work Groups

Clinical Information Modeling Initiative (CIMI)

FHIR Development Project Insight ID

1363

Scope of coverage

The breast cancer data implementation guide covers oncology-specific data necessary support breast cancer treatment and research, focusing first and foremost on data driving clinical decision-making for medical and surgical oncologists. The implementation guide is expected to incrementally cover a wide variety of clinical domains (e.g. anatomic pathology, radiology), while supporting secondary data use in for clinical research, cancer registry reporting.

The first iteration of this guide is focused on breast cancer staging. Staging information is largely driven by the American Joint Committee on Cancer, which is used in the US; hence, the initial target of the IG is the US Realm.

IG Purpose

The purpose of this implementation guide is to provide detailed clinical models and FHIR Profiles that are required to support reliable and consistent capture and exchange of interoperable medical records in the oncology domain. Applications such as clinical decision support, clinical quality measures, evidence-based and precision medicine all require a standardized specification for computable data elements (aka clinical models). This implementation guide will provide FHIR-based representations of standardized oncology data to support these applications.

Content location

We are in the process of including the content into the HL7 github repository. A superset of the profiles we intend to publish as part of the Breast Cancer FHIR IG can be found at [[1]]. Please note the FHIR IG we intend to publish will contain only oncology related content (SHR namespace: oncology). The first iteration of the IG will be constrained to the domain of breast cancer staging.

A early draft of the oncology profiles can be found in Simplifier at [[2]]. Filter on "oncology" to narrow the search.

Proposed IG realm and code

us/breastcancer

Maintenance Plan

A maintenance plan for this IG is yet to be discussed, as this is the first iteration of the document, which is essentially aimed at documenting requirements for breast cancer data elements.

Short Description

This IG contains a subset of logical models for breast cancer focused on data elements used for breast cancer staging. FHIR profiles are provided as an example physical representation of the logical models. Terminology bindings are preliminary, and in some cases, defined in terms of local codes only.

Long Description

Background

The treatment of breast cancer is driven by several factors influencing the prognosis of each patient. The process of aggregating these factors is called staging. Staging is ultimately represented by a single overall score (0, IA, IB, IIA, IIB, IIIA, IIIB, IIIC, or IV), but many macroscopic, microscopic, and biologic factors go into staging. Note that the goal of the current exercise is not to calculate the overall stage, nor validate consistency among the staging categories, but only to define FHIR profiles to contain staging information.

The American Joint Commission on Cancer 8th Edition Staging Manual (AJCC-8) defines the elements used in staging breast cancer. These include the traditional TNM staging components (anatomic staging), as well as other factors that are known to influence the prognosis of breast cancer patients, including: tumor grade, hormone receptor status (progesterone and estrogen), as well as human epidermal growth factor 2 (HER 2) status.

TNM Staging Elements

There are three staging components:

• T (tumor): defines categories for the primary tumor based on the tumor size.
• N (regional nodes): defines categories for lymph node involvement in the cancer, based on the status of lymph nodes in proximity to the breast.
• M (distant metastases): defines categories for presence or absence of distant metastases.

Each component has a value, referred to as a “category,” whose allowable values are given below.

TNM staging can be done at several points over the patient’s course of care:

• Clinical (c) refers to staging done before tissue samples have been obtained from the tumor. The T, N and M components are prefixed with “c” to denote clinical staging (e.g., cT, cN).
• Pathologic (p) refers applies to staging in patients who had surgery as their initial course of treatment. It includes all data used for clinical staging, data from surgical exploration and resection, and results of pathological examination (gross and microscopic) of the primary carcinoma, regional lymph nodes and metastatic sites. The T, N, and M components are used with the “p” prefix to denote pathologic staging (e.g., pT, pN)
• Post-neoadjuvant (y) refers to staging done after the patient has completed therapy such as chemotherapy, radiation, or hormone therapy. The T and N components are prefixed with “y” denote post-treatment staging without or with surgery (e.g., ycT or ypT).

Conceptually, the staging logical data structure might look something like this:

StageGroup [1..1]: either 0, IA, IB, IIA, IIB, IIIA, IIIB, IIIC, or IV
StageTiming: either clinical (c), pathologic (post-surgical) (p), post-neoadjuvant clinical (yc), or post-neoadjuvant pathologic(yp)
T [1..1]: either TX, Tis (DCIS), Tis (Paget), T1, T1mi, T1a, T1b, T1c, T2, T3, T4, T4a, T4b, T4c, or T4d
N* [1..1]: either cNX, cN0, cN1, cN2, cN2a, cN2b, cN3, cN3a, cN3b, cN3c (for clinical staging) 
or pNX, pN0, pN1, pN1mi, pN1a, pn1b, pN1c, pN2, pN2a, pN2b, pN3 (for pathologic staging)
M [1..1]: either M0 or M1

*For post-neoadjuvant staging, the N categories are preceded by “y” (e.g. ycNX, ypN1)

Estrogen receptor (ER) status

Estrogen receptor alpha is the predominant estrogen receptor expressed in breast tissue and is overexpressed in around 50% of breast carcinomas. The determination of ER status depends on several observations:

• Nuclear positivity: the percentage of cells that test (stain) positive
• Average staining intensity
• Primary antibody reacting with the ER receptor

A logical data structure for ER status conceptually could look like this:

EstrogenReceptorStatus [1..1]: either positive, indeterminate, or negative
NuclearPositivity [0..1]: percentage
AverageStainingIntensity [0..1]: either None/Negative (0), Weak (1), Moderate (2), or Strong (3)
PrimaryAntibody [0..1]: either SP1, 6F11, or 1D5

Progesterone receptor (PR) status

Progesterone receptor (PR) is expressed in 65% of breast carcinomas. Oncologists use PR status and related details to inform their treatment decision. The determination of PR status depends on several observations:

• Nuclear positivity: the percentage of cells that test (stain) positive
• Average staining intensity
• Primary antibody reacting with the PR receptor

Conceptually, a data structure for PR status could look like this:

ProgesteroneReceptorStatus [1..1]: either positive, indeterminate, or negative
NuclearPositivity [0..1]: percentage
AverageStainingIntensity [0..1]: either None/Negative (0), Weak (1), Moderate (2), or Strong (3)
PrimaryAntibody [0..1]: either IE2, 636, 16, SP2, 1A6, 1294, or 312

Human epidermal growth factor 2 (HER2) status

Human epidermal growth factor receptor 2 (HER2) status can impact the prognosis of breast cancer patients. The determination of HER2 status can be achieved through immunohistochemistry (IHC) or in situ hybridization (ISH). Each method results in a different set of observations used to determine HER2 receptor status:

• HER2 by IHC:
  • Score: 0, 1+, 2+, or 3+. A score of 0 or 1+ translates to a negative HER2 status; a score of 2+ is considered equivocal, and a score of 3+ is considered positive;
  • Percentage of cells with complete staining: 0-100%;
• HER2 by single-probe ISH:
  • Average number of HER2 signals per cell
• HER2 by dual-probe ISH:
  • Average number of HER2 signals per cell
  • Average number of CEP17 signals per cell
  • HER2/CEP17 ratio: ratio of HER2 signals per cell over CEP17 signals per cell

A data structure for HER2 status conceptually could look like:

HER2ReceptorStatus [1..1]: either positive, negative, or indeterminate
Method [0..1]: either ICH, ISH single probe, or ISH dual probe
HER2byIHC [0..1]:
    Score [1..1]: either 0, 1+, 2+, or 3+
    CompleteStaining [0..1]: percentage
HER2byISH [0..1]:
    AverageHER2SignalsPerCell [1..1]: decimal
    AverageCEP17SignalsPerCell [0..1]: decimal
    HER2CEP17Ratio [0..1]: decimal

Tumor Grade

All invasive breast carcinomas should be assigned a histologic grade. The College of American Pathologists (CAP) stipulates the Nottingham combined histologic grade should be used. The grade is determined by assessing morphologic features (tubule formation, nuclear pleomorphism, and mitotic count), and assigning a score of 1 to 3 to each feature. The combined score of the three categories is then divided into categories to produce the overall histologic grade.

Possible data structure for histologic grade:

HistologicGrade: either grade cannot be assessed (GX), low combined histologic grade (G1), intermediate combined histologic grade (G2), 
or high combined histologic grade (G3)
TubuleFormation [0..1]: either 1, 2, or 3
NuclearPleomorphism [0..1]: either 1, 2, or 3
MitoticCount [0..1]: either 1, 2, or 3

Involved parties

This IG is being created through an informal collaboration of wide range of organizations and individual contributors that are part of the Cancer Interoperability Group, which includes representatives from the HSPC, AJCC, NCCN, CiiC, ACS, various health IT vendors, among many others.

Committed organizations include the MITRE Corporation and PenRad.

Expected implementations

MITRE and PenRad.

Content sources

Specifications consulted for the development of this IG include:

• American Joint Committee on Cancer Staging Manual (8th Edition)
• College of American Pathologists Cancer Protocols
• NAACR 2018 Site-Specific Data Items Manual (DRAFT)
• HL7 CDA R2 IG: Reporting to Public Health Cancer Registries from Ambulatory Healthcare Providers
• HL7 CDA R2 IG: Clinical Oncology Treatment Plan and Summary

Example Scenarios

• Capture of staging information by providers in EHR systems
• Transmission of anatomic pathologic reports
• Reporting to cancer registries
• Reporting for clinical trials

IG Relationships

No dependencies identified at present.

Timelines

• For Comment May 2018 Ballot
• For Comment September 2018 Ballot
• STU May 2019 Ballot

When IG Proposal Is Complete

When you have completed your proposal, please send an email to FMGcontact@HL7.org