Overall survival, OS for short, is the time from randomization to death from any cause in oncological clinical trials. The endpoint thus directly captures whether the survival time of the randomized treatment groups differs and is a central benchmark for the patient-relevant benefit of a cancer therapy.<\/p>\n
For OS, the starting point must be clearly defined in the protocol; in randomized trials, this is regularly randomization. Death from any cause counts as an event. Participants for whom no information on death is available by the data cut-off date are censored according to pre-specified rules. The analysis therefore relies on careful and as complete as possible follow-up of survival status. Reasons, timing, and patterns of missing information must be transparently assessed.<\/p>\n
The analysis estimates the difference between the treatment groups over time and accounts for the uncertainty of this estimate. A treatment effect should not be described by a p-value alone. Effect size, confidence interval, number and temporal distribution of events, as well as data maturity are important. In the oncology guideline, a dataset is considered mature if the event distribution allows an assessment of the treatment effect in the entire study population.<\/p>\n
The EMA calls convincingly demonstrated favorable effects on OS the most persuasive outcome of an efficacy trial from a clinical and methodological perspective. OS is frequently particularly relevant for the positive benefit-risk assessment. Nevertheless, the endpoint is not necessarily primary in every development situation. Progression-free survival, PFS for short, or disease-free survival, DFS for short, can be suitable primary endpoints depending on the disease, therapy, and objective.<\/p>\n
If PFS or DFS is analyzed primarily, OS should be reported as a secondary endpoint; conversely, if OS is primary, PFS or DFS should be reported. Differences between the endpoints must be clinically and methodologically traceable. Subsequent therapies and a crossover from the control to the investigational arm can complicate the direct interpretation of OS. Therefore, criteria for a treatment switch, the recording of subsequent therapies, and relevant analysis rules must be pre-specified in the protocol and statistical analysis plan.<\/p>\n
Overall survival is a time-to-event endpoint and not a baseline value of a study. Although its time measurement usually begins with randomization, the term describes the period until death from any cause. Baseline values, on the other hand, are characteristics collected before the start of treatment, such as tumor burden or performance status, which characterize study groups and may be accounted for in the analysis.<\/p>\n
Likewise, OS is not to be confused with the base case of a model calculation. A base case or reference case refers to a pre-defined combination of assumptions in economic or methodological modeling. OS can be used as an input parameter there, but remains a clinical endpoint from observed study data. The entry reference case and base case covers these modeling terms; here the focus is on the measurement of overall survival.<\/p>\n
The OS analysis is normally planned in the randomized population. However, early study termination or a small number of deaths can make the estimate unstable, especially if early and late events differ in their prognosis. The study team must therefore align recruitment, follow-up, and the timing of the analysis with the expected event maturity. Interim analyses and rules for early termination are pre-specified.<\/p>\n
The quality of OS data depends on consistent follow-up, even after progression or discontinuation of study treatment. Different follow-up depth between the groups, incomplete recording of deaths, and undocumented subsequent therapies can impair interpretation. In open-label studies and in the case of treatment crossover, the pre-specification of the endpoint strategy, the documentation of subsequent therapies, and sensitivity analysis are particularly important.<\/p>\n
Full-service CROs such as Mediconomics support the definition of OS in the protocol and statistical analysis plan, the organization of follow-up, and data management processes for recording survival status and subsequent therapies. This includes monitoring of data completeness, biostatistical programming of time-to-event analyses and sensitivity analyses, as well as the consistent presentation of OS, PFS, safety, and data maturity in the clinical study report.<\/p>\n
Why is OS measured from randomization?<\/strong><\/p>\n In comparative studies, randomization defines the common starting point of treatment allocation. As a result, the survival time between the randomized groups is compared in a methodologically traceable manner.<\/p>\n Is PFS the same as overall survival?<\/strong><\/p>\n No. PFS typically captures the time to objective tumor progression or death. OS exclusively captures the time to death from any cause.<\/p>\n Why must subsequent therapies be recorded?<\/strong><\/p>\n They can influence survival after progression and thus complicate the interpretation of a difference between the randomized strategies. Their documentation is important for a traceable benefit-risk assessment.<\/p>\n Overall survival, OS for short, is the time from randomization to death from any cause in oncological clinical trials. The endpoint thus directly captures whether the survival time of the randomized treatment groups differs and is a central benchmark for the patient-relevant benefit of a cancer therapy. Definition and analysis For OS, the starting point […]<\/p>\n","protected":false},"author":10,"featured_media":0,"parent":0,"template":"","meta":{"_acf_changed":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"glossary-cat":[],"class_list":["post-6697","glossary","type-glossary","status-publish","hentry"],"acf":[],"related_terms":"","external_url":"","internal_reference_id":"","_links":{"self":[{"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/glossary\/6697","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/glossary"}],"about":[{"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/types\/glossary"}],"author":[{"embeddable":true,"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/users\/10"}],"version-history":[{"count":1,"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/glossary\/6697\/revisions"}],"predecessor-version":[{"id":7440,"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/glossary\/6697\/revisions\/7440"}],"wp:attachment":[{"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/media?parent=6697"}],"wp:term":[{"taxonomy":"glossary-cat","embeddable":true,"href":"https:\/\/mediconomics.com\/en\/wp-json\/wp\/v2\/glossary-cat?post=6697"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Regulatory references<\/h2>\n
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