How Long Do I Have, Doc!

Abstract

Being a graduate of Rawalpindi Medical College and settled as an oncologist in Australia for quite a while, I felt both honoured and humbled when I was requested to write this editorial. I have vivid recollection of my early days as a doctor, when the energy, vigour, and enthusiasm were running through my veins, thinking I could treat all ailments, alleviate the sufferings of humanity, cure disease, and ‘fix everything’. Perhaps, I needed that to drive my ambition to do something bigger, to make a difference, and that journey took me from one pole to another, from academic teaching to acquiring clinical expertise, to research and development and drug discovery, to clinical research and practicing medical oncology.  I also remember that those early years as a doctor, it was never easy to accept ‘defeat’, to encounter failure, to see the complications of disease and treatments, and accept death also as an outcome.  With time came maturity to understand that as a doctor, I have to make the best effort to heal, use my best learnings, knowledge, and skills, and strive to get the best possible outcome for each patient, but also know when not to interfere and when to give up. Death is not a defeat for the doctor; it is a reality that is expected and has to be accepted, after all possible realistic avenues have been exhausted.

Hence, the question, How Long Do I Have Doc!,  that I need to be prepared to answer every day in my practice. I don’t have the crystal ball to look into the future, nor do I have any special powers to make predictions; oncology has indeed taught me the science and the art of prognostication. I have seen oncology being practiced in its very early development phase in Pakistan (as in the 90’s), and then moving to Australia to be a part of state-of-the-art cancer clinics and witness the tremendous advancements in science and continued improvement in outcomes. Just in the last 25 yrs the overall survival for all cancers has improved by 25%.¹  This change is so dramatic that what was then considered a ‘curse’ (lack of effective treatments and relatively short survival in advanced cancers) is now talked about as a manageable and (potentially) curable disease. How, then, does someone prepare to answer the question on prognosis? The Cambridge defines prognosis as a judgment or the act of making a judgment about what is likely to happen in the future. When we apply this to the development of a disease or a disease-related outcome, this translates into a systematic, calculated, and knowledgeable expression statement that makes a clear prediction or estimation of how things will turn out.

In oncology, overall survival (OS) remains the most persuasive and universally acceptable evidence that a treatment works. It is measured as the length of time a patient is alive after a certain diagnosis or treatment. OS is one of the most fundamental and clinically meaningful endpoints used in oncology clinical trials. It remains the benchmark for definitive clinical benefit and is often referred to as the gold standard.  It provides an unambiguous, objective measure of treatment benefit. While OS is ideal, it is also one of the most difficult endpoints to improve in modern oncology. The challenges include longer duration of study timelines, a larger number needed to treat, confounding factors like multiple lines of therapy, crossover design, and many others. There has not been a universal consensus on any other outcome of interest; many surrogate endpoints have successfully been looked at, like progression-free survival (PFS), objective response rate (ORR), quality of life (QoL), etc. Real-world datasets and meta-analyses are performed frequently, which also rely heavily on OS, as this remains one of the strongest and most favoured endpoints looked at by regulators, payers, and clinicians while making treatment-related decisions.

Let’s take an example of Lung Cancer and see what the outlook for stage IV non-small cell lung cancer (NSCLC) was at the turn of the century and compare it with today. In 2000, the expected 5-year relative survival rate typically hovered between 12% and 16%, while median survival (MS) in stage IV was remarkably short, often recorded at just 6.6 to 8.5 months. In 2026, the expected overall 5-year relative survival rate for lung cancer is approximately 28% to 30%. This outcome remains highly dependent on how early the cancer is detected, e.g., for localized (Stage I), its approx. 65%, regional (Stage II/III), it's around 37%, and for metastatic (Stage IV), it’s at 10% (a five-fold increase from the 2% reported two decades ago). While the figures still look relatively dismal, this remarkable feat has only been made possible due to earlier and better diagnostics, improved surgical and radiation outcomes, and a marked understanding of the molecular profiling and use of targeted systemic and immune therapies. 

To showcase the impact on OS in this difficult-to-treat population, I will briefly mention 2 examples. Lorlatinib, an anaplastic lymphoma kinase (ALK) inhibitor, has shown  ( in a randomised phase 3 - CROWN Study),² that for patients with advanced  ALK+ NSCLC,  treated with lorlatinib, 60% remained disease-free at 5 years, 63% were progression-free, and 76%  of patients were alive at 5 years. Similarly, pembrolizumab, an immune therapy agent and a PD-1 Inhibitor, has shown (in Keynote 024 study),³   that a durable, clinically meaningful long-term OS benefit was achieved in first-line metastatic NSCLC with a PD-L1 tumour proportion score of at least 50%.  Kaplan-Meier (KM) estimates of the 5-year OS rate was 31.9% -pembrolizumab group vs 16.3% - chemotherapy group.

Multidisciplinary care is the standard of care in oncology management these days, and patient preferences and choice are also better understood and appreciated by the clinicians. What may look like a statistically significant outcome from a well-designed study may not necessarily be interpreted as clinically meaningful by patients. It is therefore a common practice to include quality of life (QoL) validated tools to evaluate the impact of an interventional study to holistically capture the statistical and clinical benefits. Decisions about various treatments, including chemotherapy, are not straightforward and often include trade-offs between their benefits, harms, and inconveniences. I had undertaken a review, with my co-authors,⁴  to find, evaluate and summarise studies quantifying the survival benefits that cancer patients judged sufficient to make chemotherapy for NSCLC worthwhile, and reported that most cancer patients (>50%) judged moderate survival benefits sufficient to make chemotherapy worthwhile, for example, absolute increases of 10% in survival rates or 6 months in life expectancies. Individual patients' preferences varied widely: benefits judged sufficient ranged from very small (e.g., survival rate of 1%) to very large (e.g., survival rate of 50%).

Knowing that OS remains the goal in Oncology, and with appreciation for how this goalpost has changed over time, it is also true that no 2 patients are going to be the same. They may present with a similar-looking clinical picture, but the actual outcome, even from the same intervention, can be very different. Apart from the many known pathologic and clinical prognostic markers, many genomic and biomarker indicators and tools have been looked at and are available in many situations, to aid the conversations on the likely benefit to be expected from a certain intervention and help formulate a prognosis on outcomes. I have published (with my coauthors),⁵  a model on how to interpret clinical data, what to take from the KM survival curves, and how to formulate this scientific data into a meaningful conversation around prognosis. We searched for randomized first-line chemotherapy trials published from January 2000 to April 2008. We recorded median time to progression (TTP) and median overall survival and extracted the following percentiles (represented scenario) from each OS curve: 90th (worst-case), 75th (lower-typical), 25th (upper-typical), and 10th (best-case). For each OS curve, we divided these percentiles (scenarios) in turn by the median to determine if a simple relationship existed between each scenario and the median. We concluded that simple multiples of an OS curve's median provided accurate estimates of typical (half to double the median), best-case (triple the median), and worst-case (one quarter of the median) life expectancy scenarios for patients starting chemotherapy for advanced NSCLC.

Now coming back to the original question, how long do I have doc!, the answer is not going to be straightforward, simple, or similar from one patient to another. This has to be carefully crafted, knowing that this information is quite critical for decision-making and future planning for the patients and their families. It must be backed by scientific evidence, should avoid point estimates, and should always be tailored across certain scenarios, providing ranges and ballpark estimates.  This can often be challenging and daunting to bring up at times, as there may be prohibitions and inhibitions that need to be overcome. At the same time, it has been shown that the majority of patients and families want to know and appreciate the truthful information to be provided, and also such conversations have shown to improve the QoL of patients and carers. While I have illustrated some examples here, prognosis of various tumours will widely vary, depending upon the stage at presentation, interventions received and various disease related (eg., size, grade, invasion, nodal or distant spread, biomarkers, genetic factors, targetable mutations and many others), as well as patient factors (like age, performance status, comorbidities, organ dysfunction and fitness to undergo various procedures and interventions etc). Many cancers, like testicular and breast, when treated early (stage 1), have a 5-yr survival close to 100%.   Overall survival for breast cancer in Australia is 93%, and for prostate cancer it's 95-97%. This contrasts with some others, like pancreas or high-grade gliomas, where less than 1 in 5 is alive 5 yrs from diagnosis. Any prognostic discussions with these patients and their families would have been so unique and individualised.

When I convey prognosis, I continually remind myself of the nuances of any such discussion, prepare myself for the tangible outcomes, and convey the information in an empathic and sympathetic manner, giving hope where it's needed, keeping a realistic attitude, hoping for the best, and preparing for the unknowns and unexpected. It is indeed an art to convey prognosis, and this art of knowing what the patient wants, how much, and what to say, timing of such discussions, and anticipating the emotional impact will carefully need to be balanced with a reasonably well-worded scientific rationale based on good evidence.