A Case Report of Syndromic Multinodular Goitre in Adolescence: Exploring the Phenotype Overlap between Cowden and DICER1 Syndromes
Bibliographic record
Abstract
Abstract Background: Hereditary tumour predisposition syndromes may increase the risk for development of thyroid nodules at a young age. We present the case of an adolescent female with Cowden syndrome who had some atypical phenotypic features which overlapped with the DICER1 syndrome. Material and Methods: A 17-year-old female presented with a 3-month history of progressive right neck swelling. Fine needle cytology of the thyroid revealed a follicular neoplasm with features suggestive of follicular variant of papillary thyroid carcinoma and she underwent a hemithyroidectomy. Enlarging nodules in the remaining thyroid led to a completion thyroidectomy at 19 years of age. The patient’s past medical history included an ovarian mixed malignant germ cell tumour, pulmonary nodules and cysts, renal cysts, mucocutaneous lesions, an arachnoid cyst, and a fibrous breast lesion. Macrocephaly was noted on physical examination. Results: Based on the patient’s complex phenotype and young age, a hereditary predisposition syndrome was suspected and genetic testing of PTEN and DICER1 was undertaken. A heterozygous truncating germ-line PTEN mutation was identified, which combined with clinical findings, met criteria for the diagnosis of Cowden syndrome. Additional loss of heterozygosity of the wild-type PTEN allele was detected in the right thyroid lesion and ovarian tumour. No DICER1 mutations were identified. Conclusions: Genetic testing was crucial in elucidating this patient’s predisposition to the early development of neoplastic and non-neoplastic conditions. Our report also highlights the phenotypic overlap between the Cowden and DICER1 syndromes and illustrates the importance of recognising the variable phenotypic features of hereditary syndromes in order to enable timely implementation of appropriate care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".