Evidence map›Paper›PMID 38001322›Full record

ArticleEndocrine2024

Prediction of classical versus non classical papillary thyroid carcinoma subtypes from cytology of nodules classified according to TIRADS.

Lorenzo Scappaticcio, Pierpaolo Trimboli, Giuseppe Bellastella, Pamela Ferrazzano, Eduardo Clery, Immacolata Cozzolino, Marco Montella, Morena Fasano, Mario Pirozzi, Sonia Ferrandes and 4 more

Abstract read
In one paragraph

Article in Endocrine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Development and validation of theAnnals of medicine and surgery (2012) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Lorenzo ScappaticcioUnit of Endocrinology and Metabolic Diseases, AOU University of Campania "Luigi Vanvitelli", Naples, Italy.
Pierpaolo TrimboliClinic of Endocrinology and Diabetology, Lugano and Mendrisio Regional Hospital, Ente Ospedaliero Cantonale, Bellinzona, Switzerland.
Giuseppe BellastellaUnit of Endocrinology and Metabolic Diseases, AOU University of Campania "Luigi Vanvitelli", Naples, Italy. giuseppe.bellastella@unicampania.it.ORCID 0000-0002-4748-321X
Pamela FerrazzanoDepartment of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.
Eduardo CleryPathology Unit, Department of Mental and Physical Health and Preventive Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy.
Immacolata CozzolinoPathology Unit, Department of Mental and Physical Health and Preventive Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy.
Marco MontellaPathology Unit, Department of Mental and Physical Health and Preventive Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy.
Morena FasanoOncology Unit, Department of Precision Medicine, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy.
Mario PirozziOncology Unit, Department of Precision Medicine, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy.
Sonia FerrandesDepartment of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.
Giovanni DocimoDepartment of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.
Fortunato CiardielloOncology Unit, Department of Precision Medicine, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy.
Renato FrancoPathology Unit, Department of Mental and Physical Health and Preventive Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy.
Katherine EspositoUnit of Endocrinology and Metabolic Diseases, AOU University of Campania "Luigi Vanvitelli", Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeOur purposes were: 1) to estimate the prediction performance (PP) of cytology in identifying papillary thyroid carcinoma (PTC) subtypes; 2) to explore how the PTC subtypes distribute among the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) categories.

methodsNodules were included if both the histology with the PTC subtype report and the cytology report with the possible PTC subtype were available. The PP was calculated by making the proportion of True positives/False positives+false negatives.

results309 cytologically "suspicious for malignancy" and "malignant" thyroid nodules with PTC histology were evaluated. ACR TI-RADS categorization for classical PTC was significantly different from non-classical PTC (p-value 0.02). For the whole cohort the PP of cytologically classical cases was 0.74, while that of cytologically non classical cases was 0.41. ACR TI-RADS categorization was not significantly different for aggressive vs non-aggressive PTC subtypes (p-value 0.1). When considering only aggressive or non-aggressive PTC subtypes, the PP of cytologically classical cases was respectively 0.86 and 0.87, while that of cytologically non classical cases was respectively 0.27 and 0.22. The PP of cytologically classical cases was 0.73 and 0.79, respectively for macroPTCs and microPTCs, while that of cytologically non classical cases was 0.55 and 0.33, respectively for macroPTCs and microPTCs.

conclusionCytology examination reliably performed in predicting classical PTC versus non classical PTC subtypes. ACR TI-RADS categorization was significantly different among classical PTC versus non classical PTC subtypes.

Indexed as

Carcinoma, PapillaryThyroid Cancer, PapillaryThyroid NeoplasmsThyroid NoduleAdultAgedBiopsy, Fine-NeedleCarcinomaCytodiagnosisFemaleHumansMaleMiddle AgedPredictive Value of TestsPTC subtypesThyroid nodulesTI-RADS

Identifiers

PMID38001322
PMCPMC11076311

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.