Clinical trial NCT04142372: Tissue Microarray of Hematological Malignancies
Official title: Tissue Microarray of Hematological Malignancies: Search for Novel Regulators of Disease Pathology Across Disease Entities
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Hematological Malignancies
Keywords: leukemia
lymphoma
biomarker
prognosis
myeloma
myelodysplasia
myeloproliferative disorder
diagnostics
tissue microarray
proteomics
genomics
clinical outcome
biobanking
digitalization
data mining
hematology
oncology
pathology
bioinformatics
real world data
hematological malignancy
survival
treatment response
Lead sponsor: Tampere University Hospital
Sponsor class: OTHER
Collaborators: name: Tampere University
name: University of Eastern Finland
name: Fimlab Oy
name: Helsinki University Central Hospital
First posted: 2019-10-29
Enrollment: 5000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: All patients with new hematological malignancies 1.1.2000- 30.4.2019

Brief summary: The aim of the study is to create new tools for improving management of patients with hematological malignancies by combining extensive clinical data from patients newly diagnosed with hematological malignancies and innovative laboratory analyses made on available tissue samples in regional biobanks from these patients.

Detailed description: Firstly, clinical information is collected on all hematological malignancies diagnosed in our hospital district area retrospectively between the years 2000 and 2019. Clinical outcomes, laboratory results, clinically relevant diagnoses, characteristics defining clinical stage and established prognostic parameters are gathered.

Simultaneously a tissue microarray (TMA) of diagnostic samples is compiled using representative annotated tissue areas. This TMA is used in combination with additional control material to identify prognostic and predictive biomarkers.

A combined microarray dataset of hematological malignancies (Hemap) is utilized to point out genes of possible drug targets, disease specific markers, prognostic markers, or predictive markers.

The clinical datasets and Hemap dataset is ultimately utilized to gain knowledge, new tools for prognostication and diagnostics, and targets for treatment. Artificial intelligence -assisted differential diagnostics will be tested.

Eligibility criteria: Inclusion Criteria:

* hematological malignancy/neoplasm

Exclusion Criteria:

* Non-sufficient data available

Primary outcomes:
measure: Progression-free survival (PFS)
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Overall survival (OS)
timeFrame: From the diagnosis up to the end of the study period (April 2019).
measure: Response to treatment
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Event-free survival (EFS)
timeFrame: From the first line treatment up to the end of the study period (April 2019).
Secondary outcomes:
measure: Sepsis or other life-threatening infection
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Multiple organ failure
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Thrombo-embolism
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Disease transformation
timeFrame: From the diagnosis up to the end of the study period (April 2019).
measure: ICU admission
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Adverse effects
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Secondary malignancy
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Relapse
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Complete remission
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Time to complete remission
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Best response
timeFrame: From the first line treatment up to the end of the study period (April 2019).
measure: Time to best response
timeFrame: From the first line treatment up to the end of the study period (April 2019).
Other outcomes:
Locations:
city: Tampere
country: Finland
facility: Tampere Univerisity Hospital
Study officials:
affiliation: Tampere University
name: Artturi Mäkinen, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: Tampere University
name: Olli Lohi, MD, PhD
role: STUDY_CHAIR
affiliation: University of Eastern Finland
name: Merja Heinäniemi, PhD
role: STUDY_CHAIR
affiliation: Tampere University Hospital
name: Matti Vänskä, MD, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: Tampere University Hospital
name: Tiina Lyly-Yrjänäinen, MD, PhD
role: PRINCIPAL_INVESTIGATOR
References: