| Literature DB >> 26476079 |
Bryan Oronsky1, Corey A Carter2, Tony R Reid3, Jan Scicinski4, Arnold Oronsky5, Michelle Lybeck4, Scott Caroen4, Meaghan Stirn4, Neil Oronsky6, Peter Langecker7.
Abstract
Overall survival (OS) has emerged as the definitive regulatory "be-all, end-all" for the demonstration of benefit in cancer clinical trials. The reason and the rationale for why this is so are easily appreciated: literally a "test of time," OS is a seemingly unambiguous, agenda-free end point, independent of bias-prone variables such as the frequency and methods of assessment, clinical evaluation, and the definition of progression. However, by general consensus, OS is an imperfect end point for several reasons: First, it may often be impractical because of the length, cost, and the size of clinical trials. Second, OS captures the impact of subsequent therapies, both beneficial (i.e., active) and detrimental, on survival but it does not take into account the contribution of subsequent therapies by treatment arm; the postprogression period is treated as an unknown black box (no information about the potential influence of next-line therapies on the outcome) under the implicit assumption that the clinical trial treatment is the only clinical variable that matters: what OS explicitly measures is the destination, that is, the elapsed time between the date of randomization (or intention to treat) and the date of death, not the journey, that is, what transpires in-between. In long-term maintenance strategies, patients receive treatment in temporally separated but mutually interdependent and causally linked sequences that exert a "field of influence" akin to action-at-a-distance forces like gravity, electricity, and magnetism on both the tumor and each other. Hence, in this setting, a new end point, PFS2, is required to measure this field of influence. This article reviews the definition and use in clinical trials of PFS2 and makes the case for its potential applicability as a preferred end point to measure the mutual influence of individual regimens in long-term maintenance strategies with resensitizing agents in particular.Entities:
Mesh:
Substances:
Year: 2015 PMID: 26476079 PMCID: PMC4611069 DOI: 10.1016/j.neo.2015.09.001
Source DB: PubMed Journal: Neoplasia ISSN: 1476-5586 Impact factor: 5.715
Clinical End Point Key Concepts Defined
| Concept | Abbreviation | Definition |
|---|---|---|
| Progression-free survival | PFS | “The length of time during and after the treatment of a disease, such as cancer, that a patient lives with the disease that may or may not shrink but it’s increase in size does not meet the criteria of progressive disease according to the protocol criteria used” |
| “PFS deferred,” “PFS delayed,” “tandem PFS,” or “PFS version 2.0” | PFS2 | “time from randomisation to objective tumor progression on next-line treatment or death from any cause. In some cases, time on next-line therapy may be used as proxy for PFS” |
| Time to tumor progression | TTP | “The length of time from the date of diagnosis or the start of treatment for a disease until the disease starts to get worse or spread to other parts of the body.” In the context of pivotal clinical studies, this is the time from randomization to objective tumor progression |
| Time to treatment failure | TTF | “TTF is defined as a composite endpoint measuring time from randomization to discontinuation of treatment for any reason, including disease progression, treatment toxicity, and death.” |
| Duration of response | DOR | “Time from documentation of objective tumor response to objective disease progression” |
| Duration of disease control | DDC | “DDC is defined as the sum of the PFS of each sequence, except when progressive disease is observed at either reintroduction or second-therapy (DDC = PFS1 + PFS2 if treatment 2 achieved stabilization or response).” |
Figure 1Optimox study and DDC illustrated.
Figure 2AIO KRK 0207 study and TFS illustrated.
Figure 3CAIRO-3 study and PFS2 illustrated.
Figure 4ROCKET study design (clinical end point OS) illustrated.
Figure 5Action-at-a-distance illustrated. Clinical treatments may exert “fields of influence” where sequential treatments are potentially affected by the treatment administered before and/or afterwards. The concept of a clinical “field of influence” is compared with the basic magnetic field pattern.