Name: left and right truncation in survival data
Uploaded: 2025-01-09T15:14:17.000Z
Duration: 1 min 9 s
Channel: JoVE

Bei der Überlebensanalyse wird die Zeit ab Studienbeginn gemessen, um sicherzustellen, dass alle Teilnehmer von Zeit Null bis zu ihrem Tod oder ihrer Zensur beobachtet werden. Dies ist jedoch nicht immer machbar.
In einer Studie, in der die berufliche Exposition gegenüber einem potenziellen Karzinogen untersucht wurde, könnten beispielsweise Fabrikarbeiter zu ihrer früheren Exposition und Risikofaktoren wie Krebs befragt und dann nachverfolgt werden.
Im Idealfall ist der Zeitpunkt Null das Datum des Beschäftigungsbeginns und nicht der Zeitpunkt des Beginns der Studie.
Arbeiter, die die Fabrik vor Beginn der Studie verlassen haben, werden jedoch nicht in die Studie einbezogen. Dieses Problem wird als Linkskürzung bezeichnet.
Auf der anderen Seite tritt eine Rechtstrunkierung auf, wenn Personen ausgeschlossen werden, wenn ihre Ereigniszeit einen bestimmten Wert überschreitet, z. B. den Untersuchungszeitraum.
Das Abschneiden unterscheidet sich vom Zensieren. Bei der Kürzung sind zu einigen Themen keine Informationen verfügbar, da sie von den Daten ausgeschlossen sind. Auf der anderen Seite liefert die Zensur nur teilweise Informationen zu solchen Themen.

trunkierung bei Überlebensanalysen

Truncation in Survival Analysis

Trunkierung bei Überlebensanalysen bezieht sich auf den Ausschluss von Personen oder Ereignissen aus dem Datensatz auf der Grundlage bestimmter Kriterien, die sich auf den Zeitpunkt des Ereignisses beziehen. Dieser Ausschluss kann in zwei Hauptformen erfolgen: Linkstrunkierung und Rechtstrunkierung.

Linkstrunkierung tritt auf, wenn Personen, die das betreffende Ereignis vor einem bestimmten Zeitpunkt erlebt haben, nicht in die Studie einbezogen werden. Dies ist häufig auf einen „verspäteten Einstieg“ in die Studie zurückzuführen, bei dem nur diejenigen beobachtet werden, die bis zu einem bestimmten Einstiegszeitpunkt überleben. Beispielsweise wären in einer berufsbezogenen Studie Arbeitnehmer, die vor Beginn der Studie in Rente gegangen oder gestorben sind, nicht Teil des Datensatzes, was zu einer Verzerrung führt, die nur diejenigen umfasst, die nach dem Einstiegszeitpunkt noch gefährdet sind.

Rechtstrunkierung ist weniger üblich und tritt auf, wenn nur Personen einbezogen werden, die das Ereignis bis zu einem bestimmten Zeitpunkt erlebt haben. Dies kann in Studien geschehen, in denen das Ereignis bereits eingetreten ist und nur diejenigen mit beobachteten Ergebnissen berücksichtigt werden. Ein Beispiel wäre eine Sterblichkeitsstudie, in der nur Todesfälle innerhalb eines bestimmten Zeitraums erfasst werden und diejenigen ausgeschlossen werden, die über den Beobachtungszeitraum hinaus gelebt haben.

Der Unterschied zwischen Trunkierung und Zensur liegt in der Datenverfügbarkeit. Eine Zensur erfolgt, wenn unvollständige Informationen über den Zeitpunkt des Ereignisses vorliegen; der genaue Zeitpunkt ist möglicherweise nicht bekannt, aber es sind einige Informationen verfügbar, wie etwa die Tatsache, dass ein Ereignis bis zu einem bestimmten Zeitpunkt noch nicht eingetreten ist (Rechtszensur) oder bereits vor Beginn der Beobachtung eingetreten war (Linkszensur). Bei der Trunkierung hingegen werden für bestimmte Personen, die die Aufnahmekriterien nicht erfüllen, überhaupt keine Daten erfasst; sie werden vollständig von der Analyse ausgeschlossen.

Weitere Beispiele für Trunkierung sind Studien zu Krankheiten, bei denen nur Personen berücksichtigt werden, die nach einem bestimmten Datum diagnostiziert wurden, und Personen, die früher diagnostiziert wurden, ausgeschlossen werden (Linkstrunkierung). In ähnlicher Weise werden bei astronomischen Studien nur beobachtbare Sterne innerhalb einer bestimmten Entfernung berücksichtigt, während diejenigen, die zu weit entfernt sind, um erkannt zu werden, ausgeschlossen werden (Rechtstrunkierung).

Trunkierung bei Überlebensanalysen

Bei der Überlebensanalyse wird die Zeit ab Studienbeginn gemessen, um sicherzustellen, dass alle Teilnehmer von Zeit Null bis zu ihrem Tod oder ihrer Zensur beobachtet werden. Aber...

Education

Lehre

JoVE Core

Statistics

Statistik

Unit 1

Einheit 1

Survival Analysis

Überlebensanalyse

KEY TERMS AND CONCEPTS

SCHLÜSSELBEGRIFFE UND KONZEPTE

left and right truncation in survival data

Truncation in survival analysis describes data loss caused by the timing of an event or by when a subject can enter a study. It can happen in two forms: left truncation and right truncation. In both cases, some individuals are left out of the dataset before analysis begins.

Left truncation happens when people who had the event before a set time are not included in the study. This often occurs with delayed entry, which means a person is only observed if they survive until the entry point. For example, in an occupational study, workers who retired or died before the study started would not appear in the data. That can bias the sample toward people who are still at risk after entry.

Right truncation is less common. It occurs when only individuals who have already had the event by a certain time are included. A mortality study that records only deaths within a specific time window is one example. People who lived beyond that observation period would be excluded.

Truncation is different from censoring. Censoring means the event time is incomplete, but some information is still available. Right censoring tells us the event has not happened by a certain time, and left censoring means it happened before observation began. Truncation gives no data at all for subjects who do not meet the entry rule, so they are completely excluded from the analysis.

Other examples help show the idea. In disease studies, researchers may include only people diagnosed after a certain date, which is left truncation because earlier cases are excluded. In astronomy, right truncation can appear when only stars close enough to be seen are studied, while stars that are too far away are left out.

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truncation in survival analysis

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key terms and concepts

Learn how left truncation and right truncation affect survival data, why delayed entry matters, and how truncation differs from censoring.

Left and Right Truncation in Survival Data | JoVE K12

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JoVE Core Statistics introduces the concepts and application of the collection, analysis, presentation, and interpretation of data to students. These animated lessons provide an understanding of statistics beneficial to students from a wide range of disciplines. Additionally, the scientist-in-action videos demonstrate the application of related concepts in classical and original research experiments performed in today's laboratories worldwide

Left and Right Truncation in Survival Data

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