However, we continuously need to evaluate how we define and assess the impact and efficacy of a cancer treatment in patients living with the disease. Today, approaches that are more comprehensive are looking not only to extend patients’ lives, but also to help them maintain their quality of life. The positive impact that new medicines bring to patients reinforces the need to accelerate drug development, but also presents a challenge when using classical endpoints (e.g. survival). This challenge has encouraged scientists to find alternatives ways to measure the benefit of a medicine.
For serious and life threatening diseases such as cancer, combining survival assessments with other efficacy measurements that evaluate earlier and promising data could help to accelerate drug development and approvals. Health authorities occasionally consider these other measurements as ‘surrogates’ for classical survival endpoints. As our understanding of cancer has evolved, so has the importance of combining measurements to help see the broader picture.
These measurements are better known as ‘endpoints’, do you know what they mean?
Historically, we have measured the efficacy of cancer treatments in clinical trials in terms of overall survival (OS) and progression-free survival (PFS). While these continue to be meaningful measurements of success in large, late-stage clinical studies, additional exploratory endpoints are added to ensure the full picture of treatment is clear, in the spirit of assessing benefit/risk and getting drugs to patients faster.
OS measures how long a patient lives, usually from the beginning of treatment, in a clinical trial comparing two or more treatments.1
It is the ‘gold standard’ endpoint, as the longer the OS, the more time a person can spend with their family and friends, and therefore the more likely they are to make it to their next key milestone in life.
PFS measures how long a person lives without the disease worsening beyond a certain extent. We can assess PFS in terms of tumour progression, the appearance of new lesions, and/or death (due to any cause).2
For the person who has cancer, an increase in PFS can mean delayed symptoms, lessened anxiety and uncertainty associated with disease progression, and increased quality of life.2
DFS/RFS represents the length of time a person lives without any signs/symptoms of disease or relapse of their cancer after completion of initial treatment in early disease.3
This can provide an estimation of cure rates – the goal of treatment in early disease – considerably faster than OS.
We have long considered response rate and duration of response to be direct measures of a therapy’s anti-tumour activity, and we tend to use them in early and/or small clinical trials as primary endpoints, or as secondary endpoints in larger trials. Positive data in these studies could help potentially accelerate regulatory approvals.4 Each person may respond differently to a treatment, but these endpoints can indicate, for example, if a therapy could give them months or years longer with their families and loved ones.
RR is the percentage of patients whose tumour is reduced by a treatment beyond a certain amount. Similar to PFS, this could mean that the person with cancer experiences fewer symptoms associated with disease progression.4
A complete response seen in a person means that a tumour has completely disappeared following treatment. No signs of cancer are visible in scans or tests.5
DoR is the length of time that a tumour continues to respond to a treatment from first documentation of improvement to the disease worsening again.4
Cancer treatments are evolving, which means that we need new or adapted endpoints to measure efficacy more accurately or efficiently in specific settings such as early disease, blood cancers, or with new treatment modalities like immunotherapy. The ‘emerging endpoints’ work well alongside the ‘classical endpoints’.
pCR is used in early-stage disease trials to assess the efficacy of a treatment prior to surgery (‘neoadjuvant’), a quicker assessment than using PFS or OS. Achieving pCR means there are no cancer cells detectable at the time of surgery and, in many cases, this predicts that the disease will not relapse.6
When treating solid tumours with immunotherapy, we sometimes observe unconventional response patterns, which cannot be assessed successfully using the common criteria used to evaluate treatment efficacy. While iRECIST is not an endpoint, it is an adaptation to account for the apparent increase in tumour size caused by immune system cells entering the tumour (‘pseudoprogression’).7
MRD measures the ‘depth’ of response to a treatment in blood cancers. MRD can be an early predictor of PFS, and potentially accelerate drug development in slow-growing blood cancers.8 MRD uses newer, highly sensitive technologies to search for traces of certain blood cancers, where traditional tests may have not detected anything.9
We need to balance the efficacy of treatment with the overall impact of these medicines on people’s daily lives. The safety profile of a drug and its monitoring is a critical component in its development.
For a therapy to be successful, the benefit of the treatment must outweigh its side effects. Monitoring the side effects, and therefore the safety profile, of a drug is a critical component in therapeutic development.10
Treatment discontinuation is often the consequence of toxicity, burdensome side effects, or a physician’s choice to discontinue therapy.11 While not a direct assessment of treatment effectiveness, a low discontinuation rate can be a key indicator for a beneficial quality of life.
In addition to the safety or side effect data that we collect as part of all clinical trials, many additional endpoints aim to capture the overall impact of a treatment on a person. The impact of safety and tolerability in daily life, as well as symptomatic improvement, is what quality of life assessment brings.12
“What will the side effects be? Am I going to be tired all the time? How will this therapy interfere with daily life?” These types of questions have become increasingly important, and symptomatic improvement is considered a direct clinical benefit and an appropriate endpoint for drug approval.12 These endpoints are known as patient-reported outcomes (PROs), and represent the patients’ perception of their own health status or quality of life in the context of a clinical trial. There are several categories within PRO data:
HRQol relates quality of life directly with a person’s emotional or physical health – often based on a person’s own perception. For patients, this could mean they are able to carry out their usual tasks and activities, with better physical and mental wellbeing.13
PRO data on these topics are collected by surveys asking how symptoms have interfered with daily life, general activity, mood, relationships, and general enjoyment of life.12 Not being too tired to go for a short walk in the park, pick their children up, or conduct other daily activities, can make a tremendous impact.
While clinical data look at the incidence and severity of side effects, PRO data look at the overall side effect burden and how side effects, such as nausea, fatigue and pain, may affect the person day-to-day. The less frequent and bothersome these side effects are, the better tolerated a treatment will be.
References
NCI Dictionary of Cancer Terms. [online] Available from:
SI. Gutman, M. Piper, M.D. Grant, et al. [online] Available from:
NCI Dictionary of Cancer Terms. [online] Available from:
FDA. [online] Available from:
NCI Dictionary of Cancer Terms. [online] Available from:
NCI Dictionary of Cancer Terms. [online] Available from:
L. Seymour et al. Lancet Oncology. 2017; 18(3):143-152
European Medicines Agency (2014) Guideline on the use of minimal residue disease as an endpoint in chronic lymphocytic leukaemia studies. Available at:
Boldeanu F et al. Minimal Residual Disease - Generalities and Perspectives. TMJ 2011: 61; 3 – 4.
FDA. [online] Available from:
As defined in the BEST (Biomarkers, EndpointS, and other Tools) Resource Glossary, developed by FDA-NIH Biomarker Working Group. Available at:
E. Nelson et al. BMJ. 2015;350:g7818
M. Karimi and J. Brazier. Pharmacoeconomics. 2016;34(7):645-649
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