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

Nell'analisi della sopravvivenza, il tempo viene misurato dall'inizio dello studio, assicurando che tutti i partecipanti siano osservati dal tempo zero fino alla morte o alla censura. Ma questo non è sempre fattibile.
Ad esempio, in uno studio che esamina l'esposizione professionale a un potenziale cancerogeno, i lavoratori delle fabbriche potrebbero essere intervistati sulla loro esposizione passata e sui fattori di rischio come il cancro e quindi seguiti.
Idealmente, il tempo zero è la data di inizio del rapporto di lavoro piuttosto che quando è iniziato lo studio.
Tuttavia, i lavoratori che hanno lasciato la fabbrica prima dell'inizio dello studio non sono inclusi nello studio. Questo problema è noto come troncamento sinistro.
D'altra parte, il troncamento destro si verifica quando gli individui vengono esclusi se il loro tempo di evento supera un valore specifico, come il periodo di studio.
Il troncamento è diverso dalla censura. Nel troncamento, non sono disponibili informazioni su alcuni soggetti perché sono esclusi dai dati. D'altra parte, la censura fornisce informazioni parziali su tali argomenti.

il troncamento nell'analisi di sopravvivenza

Truncation in Survival Analysis

Con il termine troncamento nell'analisi di sopravvivenza ci si riferisce all'esclusione di individui o eventi dal set di dati in base a criteri specifici correlati al momento dell'evento. Questa esclusione può verificarsi in due forme principali: il troncamento a sinistra e il troncamento a destra.

Il troncamento a sinistra si verifica quando gli individui che hanno sperimentato l'evento di interesse prima di un certo momento non vengono inclusi nello studio. Ciò è spesso dovuto a un "ingresso ritardato" nello studio in cui vengono osservati solo coloro che sopravvivono fino a un certo punto di ingresso. Ad esempio, in uno studio occupazionale, i lavoratori che sono andati in pensione o sono morti prima dell'inizio dello studio non farebbero parte del set di dati, comportando un bias, o distorsione dei dati, per il quale si includono nello studio solo coloro che sono ancora a rischio dopo l’inizio della valutazione.

Il troncamento a destra è meno comune e si verifica quando vengono inclusi solo gli individui che hanno sperimentato l'evento entro un certo momento. Ciò può verificarsi in studi in cui l'evento si è già verificato e vengono presi in considerazione solo coloro con risultati osservati. Un esempio potrebbe essere uno studio sulla mortalità in cui vengono registrati solo i decessi entro un intervallo di tempo specifico, escludendo coloro che sono sopravvissuti oltre il periodo di osservazione.

La differenza tra troncamento e censura sta nella disponibilità dei dati. La censura si verifica quando ci sono informazioni incomplete sul momento dell'evento; il momento esatto potrebbe non essere noto, ma sono comunque disponibili alcune informazioni, come il fatto che un evento non si è verificato fino a un certo punto (censura a destra) o si era già verificato prima dell'inizio dell'osservazione (censura a sinistra). Al contrario, la troncatura non riporta alcun dato per determinati soggetti che non soddisfano i criteri di ammissione, così da essere completamente esclusi dall'analisi.

Altri esempi di troncatura includono studi sulle malattie in cui vengono inclusi solo gli individui diagnosticati dopo una data specifica, escludendo quelli diagnosticati prima (troncamento a sinistra). Analogamente, negli studi astronomici, vengono prese in considerazione solo le stelle osservabili entro una certa distanza, mentre vengono escluse quelle troppo lontane per essere rilevate (troncamento a destra).

Il Troncamento nell'Analisi di Sopravvivenza

Nell'analisi della sopravvivenza, il tempo viene misurato dall'inizio dello studio, assicurando che tutti i partecipanti siano osservati dal tempo zero fino alla morte o alla censura. Ma...

Education

Didattica

JoVE Core

Statistics

Statistica

Unit 1

Unità 1

Survival Analysis

Analisi della sopravvivenza

KEY TERMS AND CONCEPTS

TERMINI E CONCETTI CHIAVE

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

statistics

JoVE Core Statistica introduce agli studenti i concetti e i metodi di raccolta, analisi, presentazione e interpretazione dei dati. Queste video lezioni animate forniscono una comprensione della statistica che è di beneficio agli studenti di molte discipline. Inoltre, i video degli "Scienziati in azione" mostrano l'applicazione dei concetti teorici in esperimenti di ricerca tradizionali e innovativi eseguiti in laboratori internazionali.

Left and Right Truncation in Survival Data

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