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Enregistrement W3202292901 · doi:10.1210/clinem/dgab711

Young Children Are not the Same as Adolescents When it Comes to Treating Thyroid Cancer

2021· letter· en· W3202292901 sur OpenAlexaff
Melanie Goldfarb, Emily Christison‐Lagay, Jeff C. Rastatter, Jonathan D. Wasserman

Notice bibliographique

RevueThe Journal of Clinical Endocrinology & Metabolism · 2021
Typeletter
Langueen
DomaineMedicine
ThématiqueThyroid Cancer Diagnosis and Treatment
Établissements canadiensSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésEndocrinologyInternal medicineMedicineThyroid cancerThyroidCancer

Résumé

récupéré en direct d'OpenAlex

Pediatric thyroid cancer is rare, limiting the ability of individual providers and treatment centers to establish an experiential picture of disease behavior based on patient and tumor characteristics. Given the highly favorable prognosis, most patients have decades of survivorship ahead of them, and balancing risks and harms of treatment with respect to long-term outcomes is paramount. Anecdotally, not all pediatric patients are equal, with differences in disease course based on age, sex, and initial response to therapy. The recent paper by Redlich et al (1) provides insight into these disparities. Using a large, multicenter cooperative German pediatric cancer registry, the authors not only validated the American Thyroid Association (ATA) postoperative risk stratification categories, but were further able to identify several patient-related factors that predicted disease recurrence/progression beyond that included in the ATA, thus providing an potential approach for dynamic risk stratification as suggested by Tuttle and colleagues (2). Nearly all patients in this cohort were treated with total thyroidectomy, central neck dissection ± lateral neck dissection, and radioactive iodine (RAI) over a 20+-year study period (1). The German pediatric cohort showed, with concrete data, what most clinicians that care for pediatric thyroid cancer patients have long believed—that younger pediatric patients, those with the most aggressive tumor features, and children with a poor response to initial therapy are least likely to achieve a sustained complete response. Moreover, in addition to the ATA risk stratification for persistent or recurrent disease, dynamic risk stratification allowed recategorization for the albeit small number of low-risk patients that failed initial therapy as well as those high-risk patients with a good response. This is an important contribution to the literature for a number of reasons. For a rare disease, the cooperative nature of the data gathered within a discipline-specific registry facilitated reporting of thyroid-specific data and outcomes in a large number of patients. Moreover, because all comers with pediatric differentiated thyroid cancer were collected in the database, there is applicability to “the real world” because not all patients were operated on or treated by high-volume thyroid surgeons/endocrinologists. The data corroborate excellent 5- and 10-year overall survival (99%), with only one death from disease, and 5- and 10-year event free survival of 84.9% and 78.1%, respectively, which is in line with previous cohorts. Moreover, it validates the utility of previous smaller, single-institution studies that have looked at dynamic risk stratification in pediatric patients (3-7). More than 50% of those with poor response to first-line therapy in the German cohort never achieved a complete response to therapy. Arguably, the most important contribution of Redlich et al (1) is their conclusion backed by solid evidence that younger pediatric patients need to be thought of, and perhaps treated differently, from adolescents. In their study, children younger than 10 years demonstrated a greater than 30% poorer event-free survival compared to older children, as well a much lower likelihood of achieving disease-free status after initial therapy. The authors also make an interesting and potentially important point, that in these youngest patients, “microcarcinoma” should likely not even be defined as a separate entity with distinct behavior. In the small-volume thyroid of a very young patient, any size tumor is somewhat substantial, and differentiated thyroid cancer in the youngest patients inherently behaves more aggressively than in older children and adolescents. Indeed, the rates of nodal and distal metastases among children with tumors smaller than 1 cm were 45.7% and 9.1%, respectively, and these rates were even higher in children younger than 10. At the same time, the authors appropriately suggest we may need to reevaluate treatment algorithms for some of the low-risk adolescent patients to avoid overtreatment. The study was limited by the heterogeneity of treatment, as most patients in this cohort were treated before the publication of standardized practice guidelines for children. Along these lines, treatment was generally more aggressive than current guidelines advocate, inasmuch as nearly all patients underwent central neck dissection and RAI therapy. Review of outcomes reflective of a less-aggressive approach for lower-risk patients, with respect to surgery and adjuvant RAI, will be an important step to establish whether indeed such patients are appropriate for less intensive initial therapy. This timely paper greatly augments existing pediatric thyroid data and prompts questions that are slated to be addressed in the updated 2022 pediatric thyroid cancer guidelines. Most notably, separating prognostication and treatment by age, advocating less intense treatment for lower-risk adolescents, and the use of dynamic risk stratification for prognostication, surveillance, and further therapy decisions. Given the rarity of the disease, future multicenter cohorts that contribute detailed, real-world, long-term data, and outcomes data reflective of contemporary treatment paradigms, will continue to help refine our understanding and treatment of pediatric thyroid cancer. American Thyroid Association radioactive iodine Disclosures: The authors have nothing to disclose. Data sharing is not applicable to this article because no data sets were generated or analyzed during the present study.

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)0,001
score de la tête « metaresearch » (Gemma)0,010
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: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil0,022

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,010
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0040,002
Communication savante0,0020,003
Science ouverte0,0010,001
Intégrité de la recherche0,0200,018
Charge utile insuffisante (le modèle a refusé de juger)0,0040,002

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 Opus0,060
Tête enseignante GPT0,383
Écart entre enseignants0,323 · 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
GenreCommentaire

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

En bref

Citations1
Publié2021
Routes d'admission1
Résumé présentnon

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Même revueThe Journal of Clinical Endocrinology & Metabolism→Même sujetThyroid Cancer Diagnosis and Treatment→Travaux en français237 207→