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

Dans l’analyse de survie, le temps est mesuré à partir du début de l’étude, ce qui permet de s’assurer que tous les participants sont observés à partir du moment zéro jusqu’à leur mort ou jusqu’à ce qu’ils soient censurés. Mais ce n’est pas toujours faisable.
Par exemple, dans le cadre d’une étude portant sur l’exposition professionnelle à un agent cancérogène potentiel, les ouvriers d’usine peuvent être interrogés sur leur exposition passée et les facteurs de risque tels que le cancer, puis faire l’objet d’un suivi.
Idéalement, le temps zéro est la date de début de l’emploi plutôt que le début de l’étude.
Mais les travailleurs qui ont quitté l’usine avant le début de l’étude ne sont pas inclus dans l’étude. Ce problème est connu sous le nom de troncature à gauche.
D’autre part, la troncature à droite se produit lorsque des individus sont exclus si la durée de leur événement dépasse une valeur spécifique, telle que la période d’étude.
La troncature est différente de la censure. En troncature, aucune information n’est disponible sur certains sujets car ils sont exclus des données. D’autre part, la censure fournit des informations partielles sur ces sujets.

troncature dans l'analyse de survie

Truncation in Survival Analysis

La troncature dans l'analyse de survie fait référence à l'exclusion d'individus ou d'événements de l'ensemble de données en fonction de critères spécifiques liés au moment de l'événement. Cette exclusion peut se produire sous deux formes principales: la troncature à gauche et la troncature à droite.

La troncature à gauche se produit lorsque les individus qui ont vécu l'événement d'intérêt avant une certaine date ne sont pas inclus dans l'étude. Cela est souvent dû à une «entrée retardée» dans l'étude où seuls ceux qui survivent jusqu'à un certain point d'entrée sont observés. Par exemple, dans une étude professionnelle, les travailleurs qui ont pris leur retraite ou sont décédés avant le début de l'étude ne feraient pas partie de l'ensemble de données, ce qui entraînerait un biais qui n'inclurait que ceux qui sont toujours à risque après le point d'entrée.

La troncature à droite est moins courante et se produit lorsque seuls les individus qui ont vécu l'événement à une certaine date sont inclus. Cela peut se produire dans les études où l'événement s'est déjà produit et seules celles dont les résultats ont été observés sont prises en compte. Un exemple serait une étude de mortalité où seuls les décès survenus dans un laps de temps spécifique sont enregistrés, excluant ceux qui ont vécu au-delà de la période d'observation.

La différence entre la troncature et la censure réside dans la disponibilité des données. La censure se produit lorsque les informations sur l'heure de l'événement sont incomplètes; l'heure exacte peut ne pas être connue, mais certaines informations sont disponibles, comme le fait qu'un événement ne s'est pas produit jusqu'à un certain point (censure à droite) ou s'était déjà produit avant le début de l'observation (censure à gauche). En revanche, la troncature implique l'absence totale de données pour certains sujets qui ne répondent pas aux critères d'entrée; ils sont complètement exclus de l'analyse.

D'autres exemples de troncature incluent les études sur les maladies où seules les personnes diagnostiquées après une date spécifique sont incluses, excluant celles diagnostiquées plus tôt (troncature à gauche). De même, dans les études astronomiques, seules les étoiles observables à une certaine distance sont prises en compte, tandis que celles trop éloignées pour être détectées sont exclues (troncature à droite).

Troncature dans l'analyse de survie

Dans l’analyse de survie, le temps est mesuré à partir du début de l’étude, ce qui permet de s’assurer que tous les participants sont observés à partir du moment zéro jusqu’à leur mort ou jusqu’à ce qu’ils soient censurés. Mais...

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Unit 1

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Survival Analysis

Analyse de survie

KEY TERMS AND CONCEPTS

TERMES ET CONCEPTS CLÉS

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.

Left and Right Truncation in Survival Data

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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

statistics

JoVE Core Statistiques introduit aux étudiants les concepts suivants et leurs applications: la collection, l'analyse, la présentation, et l' interprétation des données. En parallèle, les scientifiques à l'action démontrent l’application de ces concepts dans des expériences de recherche classiques et originales réalisées dans des laboratoires du monde entier.

Left and Right Truncation in Survival Data

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