Oncology endpoints: An unexpected journey Waseem Jugon & Mijanur Rahman
Disclaimer The views expressed in this paper are those of the authors and do not necessarily reflect those of Roche or any other organization that may be cited for reference in this presentation
Introduction • What is oncology? • What is an endpoint? • What statistical analyses are done? • How is an endpoint interpreted? • The evolution of a programmer • Summary
What is oncology? • The term oncology means a branch of science that deals with tumours and cancers . • Cells grow out of control forming abnormal tissue growth , they may become cancerous. This is known as cell mutation and can form tumours in the body. Image Reference: http://eschooltoday.com/cancer/what-is-cancer.html
Types of cancer • Benign tumours – Non-cancerous cells that can be removed. • Malignant tumours – Cancerous tumor cells that can spread. • Solid and non-solid tumours – Non-solid tumour resulting from defective blood cells (e.g. Leukemia). – Solid tumours are excess tissues made up of cancer cells. (E.g. Breast, Lung) • Over 200 different types of cancer: – Breast, lung, bowel (colorectal) and prostate - make up over half of all new cases (approx 54%) . – The most common cancer type for men is prostate cancer. – The most common cancer type for women is breast cancer .
Evaluation of cancer therapies • Medical professionals who specialise in cancer are referred to as oncologists and can help diagnose and recommend and evaluate therapies . • RECIST - Response Evaluation Criteria in Solid Tumours – A set of rules first published in February 2000 but revised in 2008. Respond Stable Progress • The evaluations of tumours are often collected as lesions. • These can be Target or Non-Target; however the presence of New Lesions may occur at subsequent tumour assessments.
Complete Response (CR) Partial Response (PR) Progressive Disease (PD) Stable Disease (SD)
Oncology Endpoints • Defined as a measure of evaluating cancer therapies . • Primary endpoint of a study must be able to provide a valid and reproducible measure of clinical and statistical benefit . • Specified in the protocol of the clinical trial and the methods of interpreting the data of how to calculate these are contained within a statistical analysis plan . • Some endpoints may be referred to as a surrogate endpoint . – Indication to predict clinical benefit . – Accelerated approval, less expensive , Novel treatments to patients faster . “As payers seek to keep pace with groundbreaking changes in the oncology arena, it is critical that they have a solid understanding of how oncology clinical trial endpoints can or should be used to guide decisions about the care that patients receive.” Kogan, A. J, & Haren, M - Translating Cancer Trial Endpoints Into the Language of Managed Care .
Types of Oncology Endpoints Statistical Endpoint Definition Limitation Overall survival (OS) Time from randomization until death from any cause; most Requires randomized trial with lengthy • commonly used endpoint in phase 3 trials and trials for follow-up. regulatory approval and is considered the gold standard used to determine patient benefit. The reason this endpoint Can be affected by subsequent therapies • is preferred is that it is not subject to any investigator bias. Progression-free A surrogate endpoint for OS. Time from randomization to Not statistically validated as surrogate for • survival (PFS) objective tumour progression or death. Unlike time to survival in all treatment settings progression (TTP), PFS includes death from any cause as Not precisely measured subject to • well as progression. Like TTP, it is unaffected by assessment bias particularly in open- subsequent therapies. FDA prefers PFS rather than TTP as label studies regulatory endpoint. Definitions vary among studies • Time to progression A surrogate endpoint for OS. Defined as time from Frequent radiological or other • (TTP) randomization until objective tumour progression. Unlike assessments PFS, it does not include deaths, but if most deaths are not Involves balanced timing of assessments • cancer-related TTP can be acceptable endpoint. Like PFS, among treatment arms it is unaffected by subsequent therapies. Objective response A surrogate endpoint for OS. A proportion of patients with Not a direct measure of benefit rate (ORR) reduction in tumour size by a predefined amount (using • standardized criteria, such as RECIST). Directly attributable Not a comprehensive measure of drug • activity to drug effect. Only a subset of patients who benefit • Patient Reported Patient-reported outcomes, such as quality of life (QOL), Blinding often is difficult • Outcomes (PRO) complement information from traditional endpoints, Data frequently are missing or • generating the patient’s global assessment of the direct incomplete clinical benefit of a drug Clinical significance of small changes is • unknown Multiple analyses • Lack of validated instruments • Definitions are as per the FDA guidelines for Clinical Oncology endpoints
Novel Endpoints and The Future • OS is still considered the gold standard in terms of determining treatment benefit. Why do we need different endpoints? • OS can take many years to prove any clinical benefit. • If a surrogate endpoint can be used to gain accelerated regulatory approval, more novel therapies can reach patients faster . – PFS has been an example of a surrogate that has been used as the primary endpoint for a novel targeted therapy treatment in breast cancer. • Continuing to learn about the effect of cancer treatments
A Novel Endpoint: Pathological Complete Response (pCR) • Pathological complete response (pCR) — The Food and Drug Administration (FDA) defines pCR as no evidence of disease in the breast or lymph nodes as examined by a pathologist. • The FDA recently published a draft guidance document for the use of Pathological Complete Response (pCR) in Neoadjuvant Treatment (before surgery) of High Risk Early-Stage Breast Cancer. • FDA approval granted - major breakthrough for treatment in early breast cancer and achieve a common goal of bringing treatment to patients quicker and safer .
Understand primary endpoint data Investigator assessed PFS No New Lesions • The tumour does increase from baseline, but not by 20%. • Tumour increase is only 9.8% • Incorrectly assessed as PD
Statistical Analysis • Survival analysis - In clinical trials, the effect of an intervention is evaluated by measuring the number of patients survived after that intervention over a period of time . • Key terms in Survival Analysis – Response Rate – Median Survival – P-value – Censoring – Hazard Ratio – Odds Ratio
Kaplan - Meier Curve • Definition: The Kaplan – Meier (KM) curve is a graphical representation of a time to event analysis showing when a patient reaches a trials survival endpoint. • Can be summarised by observing the median survival . • Median survival is the measure of how long patients will live on average with a certain disease or treatment, and corresponds to the point on the KM curve where the survival probability equals 0.5. • The KM estimate describes the probability of surviving in a given length of time while considering time in many small intervals depicted as steps , occurring at the time of each new event . • Censoring - Certain situations can occur in a study such as patients refuse to remain in the study, or loss of contact with the patient etc. These are labelled as censored observations.
Kaplan - Meier Curve
Cox Regression • Definition: The Cox regression model provides us with estimates of the effect that different factors event (e.g. age, weight, sex etc.) have on the time until the end. • The hazard ratio (HR) is the relevant risk of experiencing an event being measured (e.g. death) between two groups. – HR = 1: indicates no difference – HR <1 : indicates there was a reduced risk in one of the treatment arms. – HR > 1: indicates an increased risk in one of the treatment arms.
Log Rank Test • Definition: The Log rank test is a hypothesis test and provides no direct information on how different the treatment groups are but can be used to compare the KM survival distributions between 2 groups. • This test is commonly used in clinical trials to give an indication of the efficacy of a new treatment to standard of care. • The P-value can tell us if the difference between the survival distributions is statistically significant. Odds Ratio • Definition: This is the ratio of an event happening compared to an event not happening in the sampled population.
Cox Regression – Time to event 1. Responders Nearly 60% of patients in the control arm were deemed to have had an event compared to approximately 48% in the experimental arm. 2. Time to Event The experimental arm shows an improvement of PFS by approximately 6.1 months. A P-Value calculated using a log rank test of less than 0.0001 indicates that this is statistically significant. 3. Hazard Ratio A Hazard ratio of 0.63 indicates that there is 37% lower risk of a PFS event occurring in the experimental arm compared to the control arm. 4. Truncated Analyses More patients have not experienced an event in the experimental arm.
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