Time is a critical factor in any cancer diagnosis. Data-driven insights, advances in diagnostics and improved access to care are reducing delays between diagnosis and treatment, improving patient outcomes. What do companies, policymakers, and care providers need to do to take advantage of these emerging technologies and accelerate the patient’s path to treatment?
by Kenneth Tan
By 2050, experts predict that cancer can become a manageable chronic disease, like diabetes. Cancer may no longer hold the fear it does today. Oncology experts are using new technologies, artificial intelligence, and machine learning to improve early detection and make diagnostics and treatments more precise.
Time remains a critical factor. Patients can face delays during investigations, as well as from systemic factors like waiting for an operating date or a specialist consultation.1 Studies show that a four-week delay in treatment after diagnosis is associated with poorer patient outcomes, including increased mortality.1 It is critical that we shorten the path between consultation and treatment while providing faster and more accurate diagnosis and treatment plans.
Challenges We Must Overcome to Shape the Future of Oncology
Accelerating the Path From Diagnosis to Therapy to Survivorship
Same-day diagnosis and treatment can become a reality. With the right infrastructure, we will be able to complete accurate diagnostics, provide a personalised treatment plan and begin the treatment within hours of the diagnosis.
The journey from detection to diagnosis is an unnerving experience for patients, where time is of the essence. After a cancer is detected, a multidisciplinary team decides the best approach. Simulations and additional diagnostics may also be needed, and treatment plans adapted further. These steps, though important, can delay the start of treatment.
One way to accelerate this would be to introduce novel delivery treatment techniques and workflows that can expand the utility and adaptability of treatment machines. This would help clinicians attend multiple patients in a shorter timeframe.
Reimagining the role of longitudinal imaging would also benefit the patient journey. The next chapter of longitudinal imaging is understanding how it can impact decision making at every step - right from diagnosis to simulation to response assessment and treatment.
Creating an Integrated, Data-Based Technology Ecosystem
The cancer care ecosystem becomes increasingly complex in the absence of a centralised, networked system. Data shows that one in 10 patients is misdiagnosed because of systemic diagnostic errors.
Roughly half of these patients suffer incorrect treatment.2 Networked care removes the silos between information systems, cancer specialists, and primary care physicians that can lead to these errors.
Integrating machine learning and artificial intelligence will also help convert data and information into actionable insights. New medical journal articles appear at the rate of one every 26 seconds. A doctor would have to read 5,000 articles per day to keep up to date. New systems exist today that can help healthcare professionals access new information and make more informed clinical and operational decisions.
Moving Away From One-Size-Fits-All, Cookie-Cutter Approaches
The complexity of different tumours demands different treatment approaches. The care a patient receives is not always based on the most recent medical information – it is usually determined by the first point of interaction with the health system.
Greater commitment to evidence-based approaches will help patients and healthcare teams deliver the most appropriate form of treatment. Understanding the role played by different therapies is essential to effectively managing the disease.
Improving Access to Care
Last year, the WHO reported that comprehensive cancer treatment is available in more than 90 per cent of high-income countries, but less than 15 per cent of low-income countries.3 Even in developed countries, access to quality care is uneven. Between 50 to 60 per cent of cancer patients require radiation therapy as part of their treatment. However, in low-income countries less than 10 per cent receive it.4 Closing this gap will require investment in rural treatment centres and improving referral pathways for patients.
A Shorter Patient Pathway, With Access at Its Heart, Will Revolutionise Cancer Care
Everyone deserves access to world-class cancer care. Innovation should lead to new products and services that simplify workflows and streamline the patient pathway, building an ecosystem that gives us unprecedented access to data and personalised health. Constructive disruption is needed at every stage in the journey: screening, prevention, imaging, diagnosis, treatment decisions, planning, and survivorship.
We have more data at our fingertips than ever before. Physicians can be empowered to make quicker, informed decisions. Integrating new technologies and treatment approaches will create a world where managing and surviving cancer is much more common. We hope to see a future where tumour types can not only be effectively managed, but even eradicated. By working together towards same-day diagnosis and treatments, we can achieve new victories against cancer.
- Hanna, T. P., King, W. D., Thibodeau, S., Jalink, M., Paulin, G. A., Harvey-Jones, E., ... & Aggarwal, A. (2020). Mortality due to cancer treatment delay: systematic review and meta-analysis. bmj, 371.
- Newman-Toker, D. E., Wang, Z., Zhu, Y., Nassery, N., Tehrani, A. S. S., Schaffer, A. C., ... & Siegal, D. (2021). Rate of diagnostic errors and serious misdiagnosis-related harms for major vascular events, infections, and cancers: toward a national incidence estimate using the “Big Three”. Diagnosis, 8(1), 67-84.
- World Health Organization. (2021, September 21). Cancer. World Health Organization. Retrieved from https://www.who.int/news-room/fact-sheets/detail/cancer.
- Baskar, R., & Itahana, K. (2017). Radiation therapy and cancer control in developing countries: Can we save more lives?. International journal of medical sciences, 14(1), 13.
About the Author
Kenneth Tan is the President of Asia Pacific, Japan and India at Varian, a Siemens Healthineers company that specialises in radiation therapy and oncology informatics software. Kenneth has 20 years of experience in healthcare, driving complex strategic shifts through organisations. He is managing Varian’s strategic growth in Asia Pacific, including integrated innovations in remote diagnosis-planning, machine learning, artificial intelligence, and cloud-based delivery.