Closing the diagnostic gap: stopping cancer patients from losing a winnable battle
By Léon Van Wouwe, Clinical Innovation Director, Volv Global
Earlier cancer detection remains one of the most powerful opportunities to improve survival outcomes and reduce treatment burden. Despite major advances in oncology therapies, diagnostic delays continue to prevent many patients from accessing treatment at the stage where it can be most effective. With this perspective, Volv Global’s Clinical Innovation Director Léon Van Wouwe examines why closing the diagnostic gap is critical for modern oncology and what healthcare systems can do to shorten the path from first signal to diagnosis.
Oncology has entered a new era, in which highly specific and targeted therapies are transforming outcomes for many cancers. CAR-T (chimeric antigen receptor T-cell therapy), radioligand therapy (RLT), targeted therapies, and immunotherapies have changed what “treatable” can mean, and what outcomes patients might hope for with some confidence.
But there is a brutal paradox confronting patients, their families and healthcare providers (HCPs) in clinics every day: patients are increasingly at risk of losing a winnable battle against cancer. This isn’t because the science isn’t advancing, nor because there is not an increasingly effective arsenal of highly effective treatment options available, but because still too many people arrive at a diagnosis too late, often after months of diagnostic delay and avoidable missteps. In oncology, time is not just money – it is disease stage, it is treatment intensity, it is whether the window for curative treatment is still open.
Modern therapies can be extraordinary in their effectiveness. And, being more and more specifically targeted, even their side effects profile may not be as daunting as once was. Yet their full benefit is routinely compromised when cancer is detected late, which it frequently is when the pathway to diagnosis is slow, fragmented, or poorly understood.
The global cancer burden remains immense, with ~19.3 million new cases and ~10 million deaths in 2020. Meanwhile, the cancer-drug development pipeline continues to deliver major therapeutic innovation. (1)
But innovation downstream cannot fully compensate for what is being missed upstream. When diagnosis happens at advanced stage, we might trade shorter, less invasive treatment for longer, more toxic regimens. And we can be confronted with dramatically lower odds of long-term survival.
1) Diagnostic work-up delays are common and measured in months.
A large systematic review and meta-analysis across 5.5+ million patients in 68 countries found substantial time intervals from symptom onset to diagnosis and treatment, with wide variation by cancer type; pooled medians for the diagnostic interval were commonly on the order of ~2–3 months in high-income settings (e.g., colorectal cancer ~63 days; haematological cancers ~71 days; prostate cancer ~85 days). (2)
More concerningly, in a 2025 cohort study examining advanced-stage lung cancer and colorectal cancer, missed opportunities for earlier diagnosis were frequent, and the median time from diagnostic signal to workup completion ranged from 1 to 20 months. (3)
2) Late-stage diagnosis is still a population-level reality.
In England, official statistics report that only ~55% of staged cancers were diagnosed at stage 1–2 in 2022 (meaning ~45% were stage 3–4), and there is a clear bias against lower income groups (lower early-stage diagnosis in more deprived groups). (4)
In the US, NCI population data show that for major cancers, late-stage disease remains common. For example ~45% of lung cancer patients present with distant-stage (metastatic) disease at diagnosis and for colon cancer patients, that number is ~23%.
3) Stage and time-to-treatment materially change outcomes, including survival and cost.
US SEER data illustrate how much outcomes are correlated to cancer disease stage at time of diagnosis. For lung cancer, the 5-year relative survival rate is ~65% for localised disease. This number drops steeply, to only ~9% when distant metastases are present. (5)
For colorectal cancer, a similar picture emerges, where 5-year relative survival drops from ~91% in case of localised disease to ~16% for those presenting with distant disease. (6). This trend is confirmed over and over. A BMJ systematic review and meta-analysis found that each four-week delay in cancer treatment (surgery, systemic therapy, or radiotherapy – across several major cancers) was associated with increased mortality. (7)
Costs rise sharply too. A claims-based analysis reported steeper increases in cumulative healthcare costs for patients diagnosed at later stage across multiple cancer types, highlighting the economic as well as clinical value of earlier diagnosis. (8)
Diagnostic delay and misdiagnosis are not merely “awareness issues.” They are predictable outcomes of a complex healthcare pathway with multiple challenges and constraints:
The point here is not to blame healthcare professionals or patients. It is to recognise that this is measurable performance within our healthcare system. And it is something we can improve
Earlier diagnosis is not a slogan. It is operational work done with clinical credibility and real-world constraints in mind. In practice, shortening diagnosis timelines means:
This is the point of alignment for pharma leaders, HCPs, diagnostics stakeholders, and Cancer Patient Organisations (CPOs): the value of even the most advanced therapy does not materialise when patients are diagnosed too late to access it.
At Volv Global, our focus is simple: partner with stakeholders to materially shorten cancer diagnosis timelines, in ways that are clinically credible, operationally realistic, and measurable over time.
We do not believe a single player can fix diagnostic delay alone. But we do believe that better clinical pathway visibility, shared definitions, and collaborative execution can reduce avoidable delay and misdiagnosis – so more patients reach treatment earlier, when outcomes can be dramatically better.
If you’re a pharma leader, HCP, diagnostics strategist, or CPO: let us explore what innovating the pathway for “earlier diagnosis” can look like in your priority cancers and geographies, and how to measure progress without adding burden.
Volv Global combines proprietary machine learning, population-scale real-world evidence, and role-specific insight delivery to make earlier diagnosis operational and actionable. Using our inTrigue methodology, we uncover digital biomarkers, patient clusters, and pathway points where delay and inequity concentrate, and where undiagnosed or fast-progressing patients are most likely to be. These insights enable focused, capacity-aware action across tumour types, regions, and clinical touchpoints, and support earlier diagnosis initiatives that can be scaled responsibly and evaluated with confidence.
We are living through a promising era of oncology innovation. But we will not realise its full promise if we accept late diagnosis and prolonged diagnostic delay as “the way it is.”
Stopping cancer patients from losing a winnable battle means treating earlier diagnosis as a strategic imperative – not an afterthought. The science is moving. Now the system must move with it.
Léon van Wouwe has 20+ years’ global experience in clinical development and operations, uniting data science with pharma and research. He drives cross-functional collaboration to advance innovative treatments.
Photo by chanakon laorob on iStock.
Why is early cancer diagnosis so important?
Early diagnosis often allows patients to receive treatment when the disease is still localised or less advanced, which significantly improves survival rates and reduces treatment complexity.
What causes diagnostic delays in cancer?
Diagnostic delays can result from symptom ambiguity, limited access to diagnostics, fragmented referral pathways, and system-level constraints such as imaging backlogs or follow-up gaps.
How can real-world data improve cancer diagnosis?
Real-world data can help identify patterns across healthcare systems, detect signals earlier, and reveal missed opportunities where patients could have been diagnosed sooner.
What role does technology play in reducing diagnostic gaps?
Advanced analytics and machine learning can analyse population-scale data to uncover diagnostic signals, support clinicians in identifying high-risk patients earlier, and improve healthcare pathway efficiency.
Closing the diagnostic gap has the potential to be one of the most impactful opportunities in modern oncology. While scientific innovation continues to deliver remarkable new therapies, their full potential can only be realised when patients are identified and diagnosed early enough to benefit. By combining clinical insight taken from, real-world data with collaborative healthcare pathways, all of us can move closer to a future where fewer patients lose a winnable battle against cancer.
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