Prof. Dragan Trivanović explores how the growing complexity of oncology is reshaping the role of data, technology, and multidisciplinary collaboration in modern cancer care.
As oncology evolves into one of the most scientifically integrated and data-intensive fields, clinicians are facing new challenges in structuring, standardizing, and effectively using clinical information. From biomarker-driven decision-making to the limitations of clinical trials and the realities of everyday practice, the need for better data systems is becoming increasingly urgent.
In this interview, Prof. Trivanović shares his perspective on the importance of standardized data, the broader role of biomarkers, and how simple, well-designed digital tools can support clinicians without adding burden. He also highlights the importance of ensuring that data ultimately serves its primary purpose – improving patient outcomes in real-world oncology care.
The Evolving Oncology Data Landscape
Oncology has become one of the most data-intensive areas in medicine. What are the main reasons behind this transformation?
Oncology has become one of the central points of scientific development. It has ceased to be a separate branch due to the great development of preclinical sciences such as molecular biology, biochemistry, diagnostic and digital sciences such as pathology and radiology, and ultimately the development and application of drugs and medical procedures within clinical pharmacology, oncology, radiotherapy, surgery and numerous multidisciplinary procedures. Oncology integrates theories of the development of living beings, evolution, aging, as well as the processes of continuing life outside our planet. We are witnessing the migration of research into cell growth and control in space missions, which is making oncology a multiplanetary field, which is one of the pillars of the further development of life from single-celled forms of life to complex systems that also incorporate artificial intelligence.
Why is standardization essential in oncology data, particularly from a scientific and clinical perspective?
One of the main laws of science is doubt and questioning, not just the analysis of imposed data. That is why; to more easily compare the results of measurements and actions, we need standardized procedures, which of course also includes standardized data that we can easily compare and analyse.
Documentation Practices and Data Quality
In your experience, what are the main challenges physicians face when documenting oncology cases in daily practice? Can variability in documentation styles between physicians’ impact data usability for research purposes?
One of the main problems in clinical practice today is the lack of trained and certified personnel to perform parts of oncology procedures. If even data collection is difficult or arranged without deep prospective thinking, we additionally burden the system by producing information garbage that has completely lost its meaning.
Biomarkers, Molecular Testing, and Integration
Why are biomarkers so critical in modern oncology, and how should we think about their role beyond molecular testing?
Defining biomarkers is an important segment of how we can treat patients or prevent the development of malignant diseases with a precise approach that fully combines the biological and social characteristics of patients with full information and essential biomarkers that will help us in the prognostic and predictive sense. A good example is the discovery of the Bcr-Abl fusion disorder in the genome and the creation of drugs that are precise. This magic target is something we must strive for in all planned drug research. would point out that biomarkers should be viewed in a much broader sense, because certain characteristics that do not require expensive diagnostic analyses can become excellent biomarkers that meet these requirements.
Clinical Trials and Real-World Data
How do you see the relationship between clinical trials and real-world data evolving in oncology?
Clinical trials are extremely valuable for selecting promising outcomes from experimental research and for generating robust evidence on the efficacy and safety of new therapies. It is not surprising that many investigational drugs do not ultimately meet these criteria. At present, however, there is no better system for drug development, particularly in oncology.
That said, this process is complex, expensive, and often slow, and it remains highly dependent on the financial investment of pharmaceutical companies. It is therefore essential to provide greater support and funding for academic clinical studies, which are primarily conducted by publicly funded scientific institutions.
Another important challenge lies in the inclusion and exclusion criteria used to recruit patients into clinical trials. This raises the question of whether the demonstrated efficacy and safety of drugs apply only to selected patient populations.
For example, in lung cancer, obtaining tumour tissue can be difficult due to the location of the disease, often requiring invasive procedures such as bronchoscopy, which carry risks and potential complications. As a result, many patients in routine practice are treated based on cytological samples, which are less invasive but also less informative.
However, most clinical trials in lung cancer require histological tumour tissue, which is typically available only in patients who have undergone surgery or who have metastases outside the lungs. This raises an important question: do these patients represent a biologically different subgroup compared to those who have not had surgery or do not have accessible metastases? This difference in tumour biology may partly explain why real-world outcomes often diverge from clinical trial results.
A similar issue is the frequent inclusion of patients with ECOG performance status 0 or 1 in clinical trials, whereas real-world populations often include patients with poorer performance status, such as ECOG 1-3.
Standardization and Digital Infrastructure
How can digital health solutions support clinicians without adding administrative burden?
By entering well-structured data into user-friendly databases, the prerequisites for easier data entry and analysis are created. Furthermore, any software work that can replace the work of an oncologist, especially if it does not involve dangerous situations such as making treatment decisions, will significantly improve the quality of treatment outcomes.
Cultural and Institutional Change
Do you believe there is a cultural shift happening among oncologists toward recognizing data as a strategic asset?
It is not easy to answer this question without considering the legal aspects, but we must protect and manage the value of the data we collect and analyse to ensure that patients are the ones who ultimately benefit from it.
The Future of Oncology Data
If you could implement one immediate improvement in your institution to strengthen oncology data quality, what would it be?
This would involve using simple databases to monitor treatment outcomes across different scenarios and, in this way, support the planning of future approaches aimed at improving patient outcomes and enhancing clinician satisfaction.
Prof. Dragan Trivanović, born in 1968, is an Associate Professor, specialist in internal medicine, and subspecialist in medical oncology. He currently serves as Dean of the Faculty of Medicine in Pula, Head of the Department of Oncology and Radiotherapy at the Faculty of Medicine in Rijeka, and Head of the Department of Internal Oncology and Haematology at General Hospital Pula.
He is the author of numerous scientific and professional publications and books, leads clinical trials, and actively promotes the medical profession and science. He also serves as Vice-President of the Croatian Society for Internal Oncology of the Croatian Medical Association.
