Czech Salivary Gland Database

Vojt

ech Jel

ınek

1 a

, Petr Br

uha

1 b

, David Kalfe

2 c

and Pavel Nov

1 d

Department of Computer Science and Engineering, Faculty of Applied Sciences,

University of West Bohemia, Univerzitn

ı 8, Pilsen, Czech Republic

Department of Otorhinolaryngology and Head and Neck Surgery, 1st Faculty of Medicine, University Hospital Motol,

Charles University, V Uvalu 84, Prague 150 06, Czech Republic

vjelinek@students.zcu.cz, {pbruha, novyp}@kiv.zcu.cz, david.kalfert@fnmotol.cz

Keywords:

Salivary Gland Cancer, Clinical Database, Patient Data Management, Data Visualization, Kaplan-Meier

Analysis.

Abstract:

Salivary gland tumors require comprehensive data collection and analysis to support clinical decision-making,

yet existing databases need more focus on speciﬁc tumor-related data and visualization tools. This absence

hinders oncologists’ ability to track patient outcomes effectively and identify potential prognostic indicators.

To address this, we developed the Czech Salivary Gland Database (CSGDB), a specialized clinical application

designed to manage patient data and provide visual analytics. The database includes secure and anonymized

data handling alongside Kaplan-Meier survival analysis for outcome visualization. Deployed at the University

Hospital in Motol, CSGDB empowers healthcare professionals with enhanced tools for tracking and analyzing

patient progress, ultimately contributing valuable data and insights to the ﬁeld of head and neck oncology.

1 INTRODUCTION

Head and neck oncology represents a challenging

ﬁeld within medical research and clinical practice,

given the diverse types of tumors, unique anatomi-

cal features, and complex treatment paths involved.

Among these, salivary gland tumors are relatively

rare yet require specialized care due to their hetero-

geneous nature, potential malignancy, and impact on

critical physiological functions. Currently, effective

diagnosis, treatment, and monitoring of salivary gland

tumors rely on a combination of clinical expertise

and robust, accurate data. However, existing med-

ical databases and general-purpose electronic health

record (EHR) systems must be better suited for man-

aging the detailed, speciﬁc data required for this pa-

tient population.

The challenges associated with these tumors in-

clude tracking long-term outcomes, analyzing treat-

ment effectiveness, and identifying potential prognos-

tic markers—tasks that demand specialized databases

with functionalities tailored to salivary gland oncol-

ogy. Conventional data systems, such as general can-

https://orcid.org/0009-0009-8021-4204

https://orcid.org/0000-0003-4031-8243

https://orcid.org/0000-0003-4369-4113

https://orcid.org/0000-0001-9945-1351

cer registries, often lack ﬁelds for the speciﬁc parame-

ters relevant to these tumors, limiting their usefulness

for clinicians and researchers focused on this area.

Furthermore, these databases frequently do not incor-

porate tools for survival analysis, data visualization,

or detailed cohort tracking, which are essential for un-

derstanding disease progression and informing treat-

ment decisions.

To address these limitations, we developed the

Czech Salivary Gland Database (CSGDB) (Kalfe

et al., 2024), a clinical application to support storing,

managing, and analysis of patient data speciﬁc to sali-

vary gland tumors. CSGDB provides a secure, spe-

cialized platform for capturing detailed clinical and

demographic data, tracking treatment outcomes, and

visualizing survival trends through integrated Kaplan-

Meier analysis. The design of CSGDB not only ad-

dresses the data storage needs but also emphasizes

user accessibility, ensuring that clinicians can efﬁ-

ciently utilize the system within their workﬂows.

This paper presents an overview of CSGDB’s de-

sign, architecture, and functionalities. We also dis-

cuss the implementation and deployment of the sys-

tem at the University Hospital in Motol, highlight-

ing its impact on clinical workﬂow and its potential

contributions to oncology research. CSGDB seeks to

enhance patient care and research capabilities by of-

fering a focused, clinically relevant database, laying

Jelínek, V., Br ˚uha, P., Kalfe

rt, D. and Nový, P.

Czech Salivary Gland Database.

DOI: 10.5220/0013254400003911

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2025) - Volume 2: HEALTHINF, pages 705-711

ISBN: 978-989-758-731-3; ISSN: 2184-4305

705

a foundation for future studies and improved clinical

outcomes in head and neck oncology.

2 STATE OF THE ART

As described in the introduction, no specialized head

and neck cancer database exists in the Czech Repub-

lic. From our point of view, it should be a comprehen-

sive database focused on head and neck cancers, col-

lecting complete clinicopathological data and subse-

quently used both for scientiﬁc purposes and in every-

day practice. Managing a local database reﬂects the

conditions and possibilities at that particular work-

place (region, state); thus, the collected data’s value

should be higher. In addition to collecting and or-

ganizing data, such a database should contain tools

for analyzing the various parameters being monitored.

Other features include the ability to update the data

for the monitored patients. Currently, most databases

are based more on retrospective data collection, where

patient data is entered on a speciﬁc date (most of-

ten the date the patient is entered into the database)

without subsequent updates. Another advantage of a

local database may be that patients with, e.g., a spe-

ciﬁc histopathological type of tumor can be easily re-

trieved, followed by tracing the actual tumor tissue

in the pathology archives for further, e.g., molecular

analyses.

The absence of such a database in the Czech Re-

public is not only on a national scale but also on the

level of local databases of individual clinical depart-

ments.

The national database for head and neck can-

cer established by The Danish Head and Neck Can-

cer Study Group, DAHANCA, see (Overgaard et al.,

2016), which is unique in the world and is designed

for all head and neck cancers, is the inspiration for the

creation of a local CSGDB with aspirations for future

expansion. Its development from a local to a national

database is also inspiring.

In addition to the DAHANCA database, other

more general databases also contain datasets of head

and neck cancers. Two examples from several such

databases are:

• The International Collaboration on Cancer Re-

porting (ICCR) produces common, internation-

ally validated and evidence-based pathology

datasets for cancer reporting for use through-

out the world through broad collaboration be-

tween Pathology Colleges, Societies and major

cancer organizations internationally, spec. Head

and Neck, see (Thompson et al., 2024), (Seethala

et al., 2018);

• The Surveillance, Epidemiology, and End Results

(SEER) Program of the National Cancer Institute

(NCI), https://seer.cancer.gov/; see (Hankey et al.,

1999), (Friedman and Negoita, 2024).

Common to these databases is that most are pri-

marily focused on histopathological parameters of tu-

mours and are therefore more intended for patholo-

gists, i.e. complete clinicopathological data are miss-

ing.

Since we are currently dealing with large salivary

gland tumors, we designed and implemented a CS-

GDB, which is being created within a clinical depart-

ment with data collection from other clinical depart-

ments using a web form (https://slinnezlazy.cz/).

For an idea of the population and incidence

of head and neck cancers in relation to the cited

DANANCA database as an inspirational model, we

present statistical data for the Czech Republic and

Denmark for the period 2022; the data source is the

International Agency for Research on Cancer, see

(Ferlay et al., 2024), (Bray et al., 2024), Table 1.

Table 1: Overview table of newly diagnosed head and neck

cancers in the Czech Republic and Denmark in 2022.

CZECHIA - 2022

Population 10 736 782

Number of new Cancer 65 676

Cancer Number (%) Rank Cum. risk

Lip, oral, cavity 955 1.45 15 0.54

Oropharynx 582 0.89 21 0.36

Larynx 465 0.71 23 0.28

Salivary glands 151 0.23 27 0.07

Hypopharynx 150 0.23 28 0.10

Nasopharynx 51 0.08 32 0.03

Head & Neck 2 354 3.58

Available from: https://gco.iarc.who.int/media/globocan/

factsheets/populations/203-czechia-fact-sheet.pdf

DENMARK - 2022

Population 5 834 952

Number of new Cancer 48 840

Cancer Number (%) Rank Cum. risk

Lip, oral, cavity 449 0.92 19 0.47

Oropharynx 450 0.92 18 0.52

Larynx 235 0.48 23 0.25

Salivary glands 82 0.17 28 0.08

Hypopharynx 120 0.25 27 0.13

Nasopharynx 21 0.04 32 0.03

Head & Neck 1 357 2.78

Available from: https://gco.iarc.who.int/media/globocan/

factsheets/populations/208-denmark-fact-sheet.pdf

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Front-End

Kaplan-Meier Filter

Kaplan-Meier Chart

Patient

Form

Study

Form

Common

Form

Parts

Patients List

Component

Studies List

Component

Add Patient

Component

Add Study

Component

Kaplan-Meier

Component

Renderer Process Main Process

IPC

Back-End

Database

Encryption

Password

Manager

Patients

Manager

Studies

Manager

Basic DB

Operations

API call

API response

function call

function result

Figure 1: High-level Architecture of the Czech Salivary Gland Database (CSGDB).

3 SYSTEM DESIGN AND

ARCHITECTURE

3.1 Overall Design Goals

The Czech Salivary Gland Database (CSGDB) design

focuses on three main objectives: clinical usability,

data security, and scalability. These priorities ensure

the system functions effectively in a fast-paced clini-

cal environment while adhering to strict data protec-

tion standards. CSGDB features a modular architec-

ture that allows for future expansions, enabling the

implementation of additional functionalities or sys-

tem integrations without disrupting core operations.

The primary design objectives for CSGDB are

to facilitate comprehensive data entry for patient

records, support straightforward data retrieval and

analysis, and ensure compliance with legal require-

ments for patient data security, such as GDPR stan-

dards. The system utilizes a modern technology stack

that includes ElectronJS for cross-platform applica-

tion development, ReactJS for creating a responsive

and intuitive user interface, SQLite as the primary

database for reliable data storage and portability, and

NodeJS as the backend framework. This combina-

tion ensures that CSGDB is lightweight and high-

performing, providing clinicians with an efﬁcient and

fast system. It is easily deployable on various oper-

ating systems used in healthcare facilities, further en-

hancing its usability.

The interface design enhances clinical usability by

prioritizing ease of navigation and efﬁcient data en-

try, allowing clinicians to input and access patient in-

formation quickly. The layout minimizes cognitive

load, featuring customizable ﬁelds tailored to salivary

gland tumors. These ﬁelds capture essential clinical

and demographic details in an organized manner. This

level of customization promotes consistency in data

collection, which is beneﬁcial for tracking patients

over time and analyzing outcomes.

Data security is paramount in CSGDB, given the

sensitive nature of patient records. The system in-

corporates encryption mechanisms, access control,

and anonymization protocols to protect patient iden-

tities and ensure that only authorized personnel can

access or modify data. This approach safeguards

privacy and supports data sharing for research pur-

poses, where anonymized patient data can drive in-

sights while maintaining conﬁdentiality.

Lastly, scalability is a key design consideration,

allowing CSGDB to grow alongside advancements in

clinical informatics and data management. The sys-

tem’s architecture and technology choices support ef-

ﬁciently handling an increasing volume of data. Fu-

ture enhancements, such as machine learning mod-

els for predictive analysis, can be implemented with

minimal changes to the existing infrastructure. This

ﬂexibility ensures that CSGDB remains a valuable

resource for both clinical practice and research over

time.

3.2 Architecture Overview

CSGDB is designed as a client-server (Oluwatosin,

2014) application (see Figure 1), providing a clear

separation between data management on the server

side and user interaction on the client side. The server

Czech Salivary Gland Database

707

manages data storage and processing, while the client

provides healthcare professionals with intuitive ac-

cess to the system’s functionalities through a user-

friendly interface.

As illustrated in Figure 1, the CSGDB system ar-

chitecture is built around a relational database back-

end that handles both structured medical data (e.g.,

patient demographics, tumor classiﬁcations) and un-

structured notes (e.g., clinician observations). This

database forms the core of the application, ensuring

reliable and secure data storage. An API layer facili-

tates communication between the database and client

applications, providing seamless access to data.

We designed the client side to provide a re-

sponsive, cross-platform user experience that func-

tions smoothly across different operating systems.

The client-side application is structured around sev-

eral key components to address the diverse needs

of healthcare professionals. These include the pa-

tients list component, which displays a searchable and

sortable list of patients; the studies list component,

which organizes studies and their associated patient

data for efﬁcient navigation; the add patient com-

ponent, allowing users to add new patient records

seamlessly; the add study component, facilitating the

creation of new studies with relevant patient associ-

ations; and the Kaplan-Meier component, enabling

clinicians to generate survival curves for advanced

data analysis.

On the server side, the back-end processes incom-

ing requests, manages interactions with the database,

and handles the application’s core business logic. One

of the most essential modules in the back-end is the

encryption module, which is responsible for encrypt-

ing all the sensitive patient data.

Communication between the front-end and back-

end is achieved with the Inter-Process Communica-

tion module. Its purpose is to process user requests

from the front-end, then call appropriate functions on

the back-end and provide a response with the result of

the desired operation.

In addition to the core client-server architecture,

the system’s modular structure supports robust scala-

bility. Future enhancements, such as adding predic-

tive analytics or extending data processing capabili-

ties, can be seamlessly integrated. The clear separa-

tion of responsibilities within the architecture ensures

the secure handling of sensitive patient data.

3.3 Data Security and Anonymization

Data security within CSGDB is implemented through

robust encryption, access control, and anonymization

protocols. All sensitive patient data are encrypted

upon entry and stored securely in the database, en-

suring protection against unauthorized access. To

further safeguard patient privacy, pseudonymization

techniques are applied so that direct identiﬁers are

separated from clinical information, minimizing the

risk of re-identiﬁcation. Access control is managed

through two-factor authentication, allowing only au-

thorized users to view or edit speciﬁc data. These

measures collectively ensure a high data security and

privacy standard, enabling secure handling of sensi-

tive medical information in clinical and research set-

tings.

4 KEY FUNCTIONALITIES OF

CSGDB

CSGDB includes several key functionalities designed

to streamline the data management process for clini-

cians and researchers, enabling better data utilization

and visualization in clinical decision-making.

Figure 2: Screenshot of Czech Salivary Gland Database

User Interface (Brierley et al., 2017).

4.1 User Interface and Experience

Our main goal for the CSGDB user interface was to

make it straightforward for clinical staff to access. We

devised a simple design that included two main com-

ponents to accomplish this. The main menu is on the

program window’s left side, allowing users to access

the application’s core capabilities immediately. The

corresponding view for the chosen menu option is dis-

played in the center of the application’s windows (see

Figure 2). This layout enables users to navigate be-

tween each functionality easily.

4.2 Updating Patient Records

Updating patient records is essential for medical pro-

fessionals. Currently, most databases rely on retro-

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708

spective data collection, meaning that patient infor-

mation is recorded on a speciﬁc date—typically the

date the patient is entered into the system—without

any subsequent updates. Our application addresses

this limitation by enabling the editing of patient

records with a streamlined, user-friendly process.

The update begins when the user opens the pa-

tient’s list component, displaying all patient records.

The user can then locate the speciﬁc patient they wish

to edit using search and ﬁltering functionalities. Once

the desired patient is identiﬁed, a single click on the

edit button enables editing mode. In this mode, the

user can modify the patient’s details.

The interface provides two options upon complet-

ing the edits. If the user is satisﬁed with the changes,

they can click the save button, which commits the up-

dated data to the database. Alternatively, if the user

decides to discard the changes, they can click the undo

button, which reverts the record to its previous state.

4.3 Application Security

Because clinical data is one of the most sensitive

pieces of information about anyone’s life, it is nec-

essary to secure it properly. Our application en-

crypts all sensitive information about patients with

AES encryption (Daemen, 1999), (Rijmen and Dae-

men, 2001). To log in to the application, the user

must provide his password simultaneously with the

encryption key; otherwise, access to the application is

not granted.

4.4 Data Filtration

The ability to ﬁlter patients based on deﬁned factors is

critical for effectively utilizing clinical datasets. Cur-

rently, the application supports ﬁltration based on pa-

rameters such as the type of impacted salivary gland,

the therapy administered, and the histopathological

classiﬁcation. The system’s modular design facili-

tates the addition of new ﬁltering criteria based on

user requirements or emerging research needs.

Figure 3: Filtration menu.

The ﬁltration menu, accessible within the patient’s

list component and illustrated in Figure 3, allows

users to conﬁgure and apply ﬁlters based on vari-

ous criteria. Users can also reset all applied ﬁlters

to their default state. These functionalities enhance

the system’s ﬂexibility, supporting targeted data anal-

ysis, which proves especially valuable in clinical and

research contexts.

4.5 Visualization and Analytics

Figure 4: Generated Kaplan-Meier curve.

The application offers users a tool to generate Kaplan-

Meir (Kaplan and Meier, 1958) curves. Currently,

there are two possible curve variations. The ﬁrst rep-

resents survival probability, while the second depicts

recurrence likelihood.

Patients for the curve dataset are chosen based on

their histopathological type. Multiple Kaplan-Meier

curves can be displayed in the same chart, allowing

quick visual data comparisons between patients with

certain histology classiﬁcations. (Goel et al., 2010)

Figure 4 shows the Kaplan-Meier survival curves

for patients across three histopathological groups

listed at the top of the graph. The X-axis represents

time in years, and the Y-axis indicates the probability

of survival.

4.6 Data Back-Up and Import/Export

The CSGDB offers robust tools for managing data

integrity and interoperability. Users can perform

database back-ups, a critical feature given the ex-

tended timeframes often required for comprehensive

data collection. These back-ups are securely stored

and encrypted, ensuring that sensitive data remains

protected even in unexpected damage to the user’s

machine. Each back-up ﬁle can be restored within

the application by providing the correct password and

encryption key, ensuring only authorized users can

access the data. While the application does not cur-

Czech Salivary Gland Database

709

rently include tools for advanced statistical analysis, it

enables data exchange through an import/export fea-

ture. Users can export patient and study data into Ex-

cel ﬁles, allowing for detailed statistical processing

in external software. This functionality ensures clin-

icians and researchers can leverage specialized ana-

lytical tools without compromising data security or

usability.

Understanding the sensitive nature of patient

data, the application provides an export option that

anonymizes all personal patient data. This feature is

particularly useful when medical professionals share

their research data, ensuring patient privacy is always

protected.

It is also possible to import the Excel ﬁle with data

into CSGDB, which enables sharing of the collected

data between application instances.

5 IMPLEMENTATION AND

DEPLOYMENT

study

id int NOT NULL

study_name TEXT NOT NULL

study_type INT NOT NULL

is_in_study

id INT NOT NULL

FK1

id_study INT NOT NULL

FK2

id_patient INT NOT NULL

patient_type INT NOT NULL

password

id INT NOT NULL

password TEXT

encryption_enabled TINYINT

submandibular_patient

id INT NOT NULL

form_type INT NOT NULL

name TEXT

surname TEXT

// other basic information

...

// gland specific information

...

parotid_patient

id INT NOT NULL

form_type INT NOT NULL

name TEXT

surname TEXT

// other basic information

...

// gland specific information

...

sublingual_patient

id INT NOT NULL

form_type INT NOT NULL

name TEXT

surname TEXT

// other basic information

...

// gland specific information

...

Figure 5: ERA Model of CSGDB.

The CSGDB prioritizes reliability and scalability,

leveraging a modern tech stack to ensure secure, ef-

ﬁcient, and compliant operations within a clinical en-

vironment.

5.1 Technology Stack and Data Model

The CSGDB is built on a modern technology stack

that provides secure, scalable, and efﬁcient data man-

agement. It employs an SQLite relational database

for data storage, ensuring reliability and ﬂexibility in

handling clinical data. The backend is implemented

using a Node.js-based API, while the front-end inter-

face is developed with ReactJS, providing a respon-

sive and user-friendly experience.

The underlying database schema is structured

to meet the speciﬁc needs of salivary gland tumor

data management. Figure 5 illustrates the Entity-

Relationship-Attribute (ERA) model of the database,

which comprises six tables, one for each gland that

may be affected by a tumor. Each study can include n

patients, and each patient can participate in n studies,

reﬂecting the complex relationships inherent in clini-

cal datasets.

Additionally, the database includes a password

table to store hashed passwords and encryption-

related metadata. Users can enable or disable encryp-

tion during the application’s initial setup. This feature

supports testing with ﬁctitious data while maintaining

security for actual clinical data.

5.2 Deployment Context

CSGDB was deployed at the University Hospital in

Motol as a pilot program. This setting allowed for

real-world testing and validation of the system’s us-

ability and performance.

6 CONCLUSIONS

The Czech Salivary Gland Database (CSGDB) is a

signiﬁcant contribution to clinical data management

and oncological research. By addressing challenges

such as secure storage, real-time updates, and data

visualization, the platform provides a structured ap-

proach to managing data related to salivary gland tu-

mors. The tailored design of CSGDB facilitates clin-

ical decision-making and research, bridging a critical

gap in the availability of domain-speciﬁc information

systems.

The development of CSGDB involved integrating

advanced technological components, including AES

encryption for data security, modular architecture for

extensibility, and tools for visualizing survival out-

comes. Its deployment in a clinical setting demon-

strates the system’s applicability and reliability un-

der real-world conditions. These achievements un-

derscore the value of combining technological inno-

vation with domain-speciﬁc requirements in develop-

ing medical information systems.

Future work will focus on extending the database

to encompass additional rare tumor types, thereby in-

creasing its applicability to a broader range of onco-

logical studies. The planned integration of predictive

analytics and large language models will further en-

hance the system’s capacity to provide insights, con-

tributing to advancements in personalized medicine.

These directions align with the broader objectives

of improving patient outcomes and facilitating high-

quality research in head and neck oncology.

This work exempliﬁes the role of targeted

databases in advancing clinical research and practice,

HEALTHINF 2025 - 18th International Conference on Health Informatics

710

offering a model for future systems to address speciﬁc

challenges in medical data management and analysis.

ACKNOWLEDGEMENTS

This work was supported by Grant No. SGS-2022-

016 Advanced methods of data processing and analy-

sis.

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