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Record 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 on OpenAlexaff
Melanie Goldfarb, Emily Christison‐Lagay, Jeff C. Rastatter, Jonathan D. Wasserman

Bibliographic record

VenueThe Journal of Clinical Endocrinology & Metabolism · 2021
Typeletter
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsEndocrinologyInternal medicineMedicineThyroid cancerThyroidCancer

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.020
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0200.018
Insufficient payload (model declined to judge)0.0040.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.383
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2021
Admission routes1
Has abstractno

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