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

In survival analysis, time is measured from the study start, ensuring all participants are observed from time zero until they die or are censored. But, this is not always feasible.
For instance, in a study examining occupational exposure to a potential carcinogen, factory workers might be interviewed about their past exposure and risk factors such as cancer and then followed up.
Ideally, the time zero is the employment start date rather than when the study began.
But, workers who left the factory before the study began are not included in the study. This issue is known as left truncation.
On the other hand, right truncation occurs when individuals are excluded if their event time exceeds a specific value, such as the study period.
Truncation is different from censoring. In truncation, no information is available on some subjects because they are excluded from the data. On the other hand, censoring provides partial information on such subjects.

truncatie in survivalanalyse

Truncation in Survival Analysis

Truncatie in survivalanalyse verwijst naar het uitsluiten van personen of gebeurtenissen uit de dataset op basis van specifieke criteria die verband houden met het tijdstip van de gebeurtenis. Deze uitsluiting kan in twee hoofdvormen voorkomen: linkstruncatie en rechtstruncatie.

Linkstruncatie treedt op wanneer personen die de gebeurtenis van belang vóór een bepaald tijdstip hebben ervaren, niet in de studie worden opgenomen. Dit gebeurt vaak door "vertraagde toetreding" tot de studie, waarbij alleen degenen die tot een bepaald toegangspunt overleven, worden geobserveerd. In een beroepsstudie worden bijvoorbeeld werknemers die met pensioen zijn gegaan of zijn overleden vóór de start van de studie uitgesloten van de dataset, wat kan leiden tot een vertekening waarbij alleen degenen die na het toegangspunt nog risico lopen, worden meegenomen.

Rechtstruncatie komt minder vaak voor en treedt op wanneer alleen personen worden opgenomen die de gebeurtenis vóór een bepaald tijdstip hebben ervaren. Dit gebeurt bijvoorbeeld in studies waarin de gebeurtenis al heeft plaatsgevonden en alleen degenen met waargenomen uitkomsten worden meegenomen. Een voorbeeld is een mortaliteitsstudie waarbij uitsluitend sterfgevallen binnen een specifiek tijdsbestek worden geregistreerd, terwijl personen die na de observatieperiode nog leefden, worden uitgesloten.

Het verschil tussen truncatie en censuur ligt in de beschikbaarheid van gegevens. Bij censuur is er sprake van onvolledige informatie over het tijdstip van de gebeurtenis; de exacte tijd is mogelijk niet bekend, maar er is wel enige informatie beschikbaar, zoals dat een gebeurtenis tot een bepaald moment niet heeft plaatsgevonden (rechtercensuur) of al had plaatsgevonden voordat de observatie begon (linkercensuur). Truncatie daarentegen houdt in dat er helemaal geen gegevens beschikbaar zijn voor bepaalde proefpersonen die niet aan de toelatingscriteria voldoen; zij worden volledig uitgesloten van de analyse.

Andere voorbeelden van truncatie zijn studies naar ziekten waarbij alleen personen die na een specifieke datum zijn gediagnosticeerd worden opgenomen, terwijl degenen die eerder zijn gediagnosticeerd worden uitgesloten (linker truncatie). Evenzo worden in astronomische studies alleen waarneembare sterren binnen een bepaalde afstand meegenomen, terwijl sterren die te ver weg zijn om te worden waargenomen, worden uitgesloten (rechter truncatie).

Truncatie in survivalanalyse

In survival analysis, time is measured from the study start, ensuring all participants are observed from time zero until they die or are censored. But, ...

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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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Left and Right Truncation in Survival Data

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