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Enregistrement W3046179605 · doi:10.1158/1538-7445.pedca19-ia24

Abstract IA24: The lifetime impact of cancer and cancer therapy

2020· article· en· W3046179605 sur OpenAlexaboutno aff
Greg Armstrong

Notice bibliographique

RevueCancer Research · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueChildhood Cancer Survivors' Quality of Life
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineCancerQuality of life (healthcare)PopulationDiseasePediatricsMalignancyGerontologyIntensive care medicineEnvironmental healthInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Survival rates after childhood cancer have increased dramatically in the past 50 years. More than 80% of children diagnosed with a malignancy now survive five years, with most going on to become long-term survivors. This has resulted in a growing population of childhood cancer survivors in the U.S., estimated to exceed 420,000 in 2013 and to approach half a million by 2020. Unfortunately, the same curative treatments that enable long-term survival also cause toxicities that leave many survivors with a substantial burden of adverse health and quality-of-life outcomes. Survivors have a 13-fold higher mortality rate than the general population. Eighty percent of childhood cancer survivors develop at least one severe, disabling, life-threatening, or fatal chronic health condition by age 45 years, and the average survivor will experience four such conditions by age 50 years. Specifically, survivors have increased risk compared to the general population for diseases often associated with aging, such as heart disease, diminished pulmonary function, and second cancers. The substantial burden of morbidity experienced by survivors translates to a significantly reduced quality of life compared to those without a cancer history. Thus, there is a critical need to better understand which survivors have the highest risk of serious morbidity and mortality, identify those with subclinical dysfunction, and inform intervention strategies for mitigating the burden of these late effects. Unfortunately, however, as survivors age into adulthood, most are no longer followed at their primary treatment institution, but by their community primary care providers, limiting our knowledge of long-term follow and late outcomes, a similar problem to that seen when survivors of adult malignancies participate in clinical trials where systematic follow-up ends at the five-year time point. To address this knowledge gap, the Childhood Cancer Survivor Study (CCSS) was developed. The CCSS is a multi-institutional, multidisciplinary, NCI-funded collaborative resource (U24 CA55727; PI: Gregory Armstrong) established to evaluate long-term outcomes among survivors of childhood cancer, largely by self-reported outcomes. It is a retrospective cohort consisting of >25,000 five-year survivors of childhood cancer who were diagnosed between 1970-1999 at one of 31 participating centers in the U.S. and Canada. Self-reported outcomes across a spectrum of chronic health conditions, psychosocial and cognitive function, and physical function outcomes have informed over 350 publications to date enumerating risk for this aging population. The results of the CCSS have advanced knowledge of late effects among survivors of childhood cancer. CCSS investigators have demonstrated that 60-90% of adults treated for cancer during childhood develop one or more chronic health conditions. They have also shown that by age 50 years, the cumulative incidence of self-reported severe, disabling, life-threatening, or fatal health condition was 53.6% among survivors compared with 19.8% among sibling control group. Among childhood cancer survivors who reach age 35 years of age without a previous severe, disabling, life-threatening, or fatal health condition, 25.9% will experience a new severe, disabling, life-threatening or fatal condition within 10 years as compared to 6% of healthy siblings. In addition to the findings related to an increased risk of morbidity and mortality from subsequent neoplasms and cardiac disease, CCSS has shown that long-term survivors are at risk of developing a variety of adverse outcomes that include organ dysfunction (e.g., pulmonary, gonadal), impaired growth and development, impaired cognitive function, difficulties obtaining employment and insurance, and compromises in the quality of life. Recently, the CCSS provided evidence that survivors treated in more recent eras have a significant reduction in late mortality attributable to two things: fewer deaths from recurrence or progression of primary cancer but more importantly, fewer deaths from treatment-related causes such as subsequent malignancies and cardiopulmonary death. In conclusion, the now decades-long strategy of designing pediatric cancer treatment regimens with a focus on adult health and avoidance of late effects appears to have been successful. Taken along with promotion of early detection of late effects and improved treatment of late effects, this approach has now translated to extend the lifespan of many survivors of childhood cancer. Future directions include the need to: (1) assess the true impact of screening and early detection of late effects on morbidity and mortality and evaluate interventions that improve screening rates as well as alter health behaviors, (2) expand individual risk prediction for poor outcomes, (3) further understand genetic susceptibility for late effects, and (4) target studies for both primary and secondary prevention of late effects, so that we not only extend the lifespan of survivors, but their health span as well. Citation Format: Greg Armstrong. The lifetime impact of cancer and cancer therapy [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr IA24.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,017
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,038
Score d'incertitude au seuil0,128

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,017
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0040,004
Études des sciences et des technologies0,0020,001
Communication savante0,0050,002
Science ouverte0,0010,003
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0380,008

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,169
Tête enseignante GPT0,500
Écart entre enseignants0,332 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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