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AN ONTOLOGY OF THERAPIES
Claudio Eccher - eHealth Research Unit, FBK, Trento
Antonella Ferro - Medical Oncology Unit, S. Chiara
Hospital, Trento
Domenico Pisanelli – Laboratory for Applied Ontology,
CNR, Rome
eHealth 2009– Istanbul, 24th September 2009
BACKGROUND

Medicine is a very complex domain from the point of
view of modeling and representing intended meaning:


different activity domains, scientific granularities, and user
requirements for the same service;
ambiguous terminology (polysemy).
Ontologies are nowadays considered as the basic
infrastructure for achieving semantic interoperability
between information systems.
 Semantic interoperability hinges on shared vocabularies
whose semantics is described by ontologies in an
unambiguous and machine-processable form.

THE ONCOCURE PROJECT

The Oncocure project, started in 2007, aims to:
design, and develop a prescriptive DSS based on breast
cancer protocol encoded in Asbru;
 integrate the DSS with a legacy oncological web-based
EPR in use in the Medical Oncology Unit (MOU) of the
S.Chiara Hospital of Trento (Northern Italy), in order to
provide automatic support at the point of care.


One of the most challenging tasks in building a DSS
and integrating it into the clinical workflow is to
bridge the gap between the EPR and the DSS.

Cancer protocol require temporal and taxonomic
abstractions, especially regarding therapies (e.g.,
anthracyclines in adjuvant).
AIM
Starting from the necessities of unambiguously define
therapy-related concepts in the Oncocure project, we
designed an axiomatic ontology for medical therapies,
focused especially on oncologic therapies.
 Axiomatic ontologies allow the explicit representation
of ontological commitments related to terms to:



Facilitate meaning negotiation among agents;
Clarify and model the negotiation process itself.
WHICH ONTOLOGIES ARE WE TALKING ABOUT?
Formal Ontologies
classes, istances, roles

DOLCE

Rome

Ontology of
therapies
Domain-independent Ontologies
objects, events, processes, parts
Reference Ontologies
medicine, agriculture, law
Domain Ontologies
biomedical instruments,
drugs, oncology therapies
THE NCI THESAURUS

One of the most comprehensive vocabularies in the
cancer domain, defined by its authors as:
“a biomedical vocabulary that provides consistent,
unambiguous codes and definitions for concepts used in
cancer research”
 “exhibits ontology like properties in its construction and
use”

NCIT is available in OWL (over 1.200.000 triples);
 Although a valuable resource as reference
terminology, as regards therapy concepts NCIT is
merely a taxonomy (only IS_A relations) and suffers
of some classification problems.

EXAMPLE OF PROBLEMS WITH NCIT
Adjuvant_Therapy and Neo_Adjuvant_Therapy
(treatments in different care phases) siblings of
Hormone_Therapy and Chemotherapy (different
drug kinds) and of Breast_Cancer_Treatment
(treatment for a specific cancer);
 Dose, Dose_Rate and Dose_Modification direct
subclasses of Treatment_Regimen (is_a relation);
 Protocol_Treatment_Arm (protocol in a clinical trial)
sibling of Second_Line_Treament (treatment given
after the first line failure);
 Palliative_Surgery and Curative_Surgery (goal)
siblings of Ambulatory_Surgical_Procedure (place).

ONTOLOGY DESIGN PRINCIPLES
Created in OWL (DL),
 Based upon the top-level ontology DOLCE.





Endurants are distinguished in physical (resources) and non
Endurants:
entities (information
wholly present
at any time.
physical endurants
entities).
Perdurants:
entities
that extend
time
bycharacterize
accumulating
Qualities: entities
(weight,
color, in
etc.)
that
the
temporal
features ofparts.
the different items.
THE ONTOLOGY DEVELOPED

Medical therapies are represented by the
therapy_description class (information entity).
The enactment of a therapy is a perdurant.
USE OF THE ONTOLOGY

Our axiomatic ontology constitutes a model for
labeling (temporally annotated) EPR data with
higher level abstraction information for:
Modeling guidelines and interfacing automatic DSS with
an EPR: guidelines often requires abstractions related to
therapy history (e.g., Taxanes in adjuvant).
 Enabling automatic data analysis: the identification and
classification of therapies related to specific care
delivery ‘phases’ facilitates visual representation for an
immediate comprehension of the care process.
 Controlling the medical errors: a physician can be
automatically alerted if possible incongruities in data
are found.

AN EXPERIMENT

From the axioms defining the therapy_role_by_phase
subclasses in the ontology we defined the rules to
label oncological therapies in the EPR as neoadjuvant,
adjuvant and metastatic.

Ex: Therapy takes place after surgery, ends before a
progression, is administered to a patient with M0 tumor at
diagnosis  Adjuvant Therapy
Using the rules, we retrieved and labelled the set of
breast cancer hormone and chemo-therapies
administered in three years (2006-2008).
 We compared our results with the therapy roles
registered by the oncologist who planned the
treatment (available since 2006).

RESULTS
961 therapies (474 patients) with valid data (82 MX);
 868 (90.3 %) correctly classified;
 18 not classified (all MX).


93 “incongruities”:
4 adjuvant classified as metastatic (3 M1, 2 MX), 6 as
neoadjuvant (2MX)
 6 neoadjuvant classified as adjuvant (5 M0, 1 MX), 2 as
metastatic (1 M1, 1 M0)
 21 ‘palliative’ (metastatic) classified as adjuvant (1MX),
21 as neoadjuvant (11 M0, 10 MX).
 33 curative classified as metastatic (9 M0, 20 M1, 4 MX)

CONCLUSIONS
The relevant role of ontologies in the design and
implementation of health care information systems
is widely acknowledged.
 Our axiomatic ontology, developed according to
good design principles and based on a foundational
ontology (DOLCE), allows to assign precise
meanings to concepts and remove ambiguities.
 Without an ontological grounding like this the
same information may shift its sense according to
the context and the human agent tacit knowledge.

Thank you for your attention
THE ONTOLOGY DEVELOPED
Medical therapies are represented by the
therapy_description class (information entity). The
enactment of a therapy is a perdurant.
 With the help of an oncologist, therapies were
classified according to their qualities: method (e.g.,
radiant, surgery), involved pathology, role (e.g.,
curative/palliative, primary/non primary), etc.
 To describe a therapy, rather than establishing
IS_A links, we add existential restrictions.
 We can attach several qualities to the same
therapy avoiding the entanglement of multiple
hierarchies.

ONTOLOGY DESIGN PRINCIPLES
Based upon the top-level ontology DOLCE.
 It inherits the basic distinction between
Endurants (entities wholly present at any time )
and Perdurants (entities that extend in time by
accumulating temporal parts).
 Endurants are distinguished between physical
(resources) and non physical entities (information
entities)
 Definition of qualities: entities (pharmacological,
radiant, etc.) that characterize the features of the
different items.
