HL7 Europe Common Cancer Model, published by HL7 Europe. This guide is not an authorized publication; it is the continuous build for version 0.1.0 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/hl7-eu/cancer-common/ and changes regularly. See the Directory of published versions

Logical Models

This section describes the European Cancer Common Logical Model, which provides a formal and computable representation of the concepts defined in the European Cancer Common Conceptual Model.

While the Conceptual Model introduces the core concepts and their relationships from a functional perspective, the Logical Model focuses on their structural representation, detailing how each concept is expressed in terms of attributes, data types, cardinalities, constraints, and implementation notes.

For this reason, readers are strongly encouraged to first familiarise themselves with the Conceptual Model, which defines the meaning, scope, and relationships of the concepts described here. The full conceptual description is available at European Cancer Common Conceptual Model.

In this page, the Logical Model is presented at a high‑level overview, with the purpose of supporting navigation and understanding of the model structure rather than replacing the detailed specifications. For each entity, this section provides:

• a short descriptive summary of the entity’s role in the cancer journey,
• a schematic graphical representation illustrating its main attributes and relationships,
• and a direct link to the corresponding Logical Model page, where the full and formal specification is available.

The authoritative definitions of all concepts are maintained in the Glossary. This page does not redefine concepts; instead, it complements the conceptual description with an implementation‑oriented view.

Detailed descriptions of each individual attribute, including clinical meaning, cardinality, data type, terminology bindings, constraints, and notes, are provided in the dedicated Logical Model pages linked from each entity.

For ease of consultation and reuse, especially for readers less familiar with FHIR, a complete representation of the Logical Model is also available in Excel format, offering a tabular view of entities, attributes, descriptions, and notes (Cancer_Common_Logical_Model_20260521.xlsx).

Overview

This section provides an overview of the European Cancer Common Logical Model, highlighting the main entities and their relationships.

The following diagram illustrates the overall structure of the logical model and the dependencies between entities derived from reference relationships. It shows how patient information, cancer condition data, disease evolution, treatments, response assessments, and follow‑up events are connected within the model.

The diagram is intended to support conceptual orientation and navigation. It does not replace the detailed logical definitions of each entity, which are available in the corresponding Logical Model pages.

Logical Models

CancerConditionAtDiagnosis

Represents the cancer condition as it is first diagnosed, capturing the initial tumour characteristics and the diagnostic context that defines the starting point of the cancer journey.

FHIR Logical Model: StructureDefinition-CancerConditionAtDiagnosis.html

CancerStage

Represents the stage at first diagnosis and can be clinical or pathological.
A clinical stage is always expected and is defined based on imaging evidence. A pathological stage may additionally be recorded, when available, and is defined based on surgical evidence.

Different staging or grading classification systems are used in oncology, depending on the tumour type and clinical context.
At the logical model level, this guide does not restrict the set of supported classification systems.

The staging system may be represented in two different ways, depending on whether the classification is composite or single‑value in nature.

For TNM, and other composite staging systems used for most solid tumours, the staging framework is explicitly indicated using the classificationType element, and the stage is represented through multiple stageValue elements (e.g. T, N, and M).

For other staging or grading systems, which are typically represented by a single value (e.g. FIGO stage, Gleason / ISUP Grade Group), the classification is implicitly expressed through the value of stageValue.code, and the classificationType element is typically not populated.

Examples of commonly used classification systems include:

• TNM, widely adopted for most solid tumours;
• Gleason / ISUP Grade Group, used for prostate cancer grading;
• FIGO staging systems, used for gynaecological malignancies;
• other tumour‑specific staging or grading systems used in clinical practice.

These examples are provided for illustration purposes and are not intended to represent an exhaustive or prescriptive list.

The stage information itself is not represented as a single atomic field.
Instead, it is captured through one or more stageValue elements, each expressed as a code / value pair:

• stageValue.code identifies which staging element or classification is being reported
  (e.g. T category, N category, M category, FIGO stage group, Gleason grade group);
• stageValue.value captures the corresponding value
  (e.g. T2, N1, M0, IIIB, Grade Group 4).

This approach supports both:

• single‑value staging systems, where a single stageValue is sufficient;
• composite staging systems, such as TNM, where multiple stageValue elements are used.

For example:

• in a single‑value staging system, such as FIGO or Gleason, the stage is represented by one stageValue, and classificationType is typically omitted;
• in the TNM system, the stage is represented by three stageValue elements, corresponding to T (Tumour), N (Nodes), and M (Metastasis), and classificationType is populated with TNM.

FHIR Logical Model: StructureDefinition-CancerStage.html

Imaging

Represents diagnostic imaging procedures performed to define the diagnosis and the clinical stage.

FHIR Logical Model: StructureDefinition-Imaging.html

CancerPatient

Represents the patient affected by one or more cancer conditionsand acts as the central subject for all clinical events, treatments, disease assessments, and follow‑up information recorded along the cancer journey.

FHIR Logical Model: StructureDefinition-CancerPatient.html

Surgery

Represents a surgical treatment episode delivered to the patient, either as part of the initial treatment strategy or in response to disease progression.

FHIR Logical Model: StructureDefinition-Surgery.html

ActiveSurveillance

Represents a management strategy in which the patient is monitored over time without active treatment, applicable only prior to the occurrence of a documented disease progression.

FHIR Logical Model: StructureDefinition-ActiveSurveillance.html

Radiotherapy

Represents a radiotherapy treatment course delivered to the patient, including intent, timing, and anatomical target, and potentially linked to a specific disease progression event.

FHIR Logical Model: StructureDefinition-Radiotherapy.html

SystemicTreatment

Represents a systemic anti‑cancer treatment episode (e.g. chemotherapy, immunotherapy) delivered to the patient, either at diagnosis or following disease evolution, and characterized by start/end date and possible ongoing indication (e.g., immunotherapy).

FHIR Logical Model: StructureDefinition-SystemicTreatment.html

OverallCancerTreatmentResponse

Represents the overall assessment of how the cancer condition has responded to one or more treatment episodes ((e.g., progression, stable disease, partial/complete remission)) at a specific time point, based on evidence.

FHIR Logical Model: StructureDefinition-OverallCancerTreatmentResponse.html

LastFollowUp

Represents the assessment of the patient’s status at a specific follow‑up visit, including vital status and presence or absence of evidence of disease. Each follow-up visit creates a new instance.

FHIR Logical Model: StructureDefinition-LastFollowUp.html

ClinicalCancerProgression

Represents the evolution of the disease over time, documenting changes in disease status and extent at specific clinical decision points during the cancer journey. Each evaluation creates a new instance.

FHIR Logical Model: StructureDefinition-ClinicalCancerProgression.html