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. 2023 Jan 27:13:1080159.
doi: 10.3389/fendo.2022.1080159. eCollection 2022.

The TNAPP web-based algorithm improves thyroid nodule management in clinical practice: A retrospective validation study

Vincenzo Triggiani  1 , Giuseppe Lisco  1 , Giuseppina Renzulli  2 , Andrea Frasoldati  3 , Rinaldo Guglielmi  4 , Jeffrey Garber  5 , Enrico Papini  4
Affiliations

The TNAPP web-based algorithm improves thyroid nodule management in clinical practice: A retrospective validation study

Vincenzo Triggiani et al. Front Endocrinol (Lausanne). .

Abstract

Background: The detection of thyroid nodules has been increasing over time, resulting in an extensive use of fine-needle aspiration (FNA) and cytology. Tailored methods are required to improve the management of thyroid nodules, including algorithms and web-based tools.

Study aims: To assess the performance of the Thyroid Nodule App (TNAPP), a web-based, readily modifiable, interactive algorithmic tool, in improving the management of thyroid nodules.

Methods: One hundred twelve consecutive patients with 188 thyroid nodules who underwent FNA from January to December 2016 and thyroid surgery were retrospectively evaluated. Neck ultrasound images were collected from a thyroid nodule registry and re-examined to extract data to run TNAPP. Each nodule was evaluated for ultrasonographic risk and suitability for FNA. The sensitivity, specificity, positive and negative predictive values, and overall accuracy of TNAPP were calculated and compared to the diagnostic performance of the other two algorithms by the American Association of Clinical Endocrinology/American College of Endocrinology/Associazione Medici Endocrinologi (AACE/ACE/AME), which it was derived from the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS).

Results: TNAPP performed better in terms of sensitivity (>80%) and negative predictive value (68%) with an overall accuracy of 50.5%, which was similar to that found with the AACE/ACE/AME algorithm. TNAPP displayed a slightly better performance than AACE/ACE/AME and ACR TI-RADS algorithms in selectively discriminating unnecessary FNA for nodules with benign cytology (TIR 2 - Bethesda class II: TNAPP 32% vs. AACE/ACE/AME 31% vs. ACR TI-RADS 29%). The TNAPP reduced the number of missed diagnoses of thyroid nodules with suspicious and highly suspicious cytology (TIR 4 + TIR 5 - Bethesda classes V + VI: TNAPP 18% vs. AACE/ACE/AME 26% vs. ACR TI-RADS 20.5%). A total of 14 nodules that would not have been aspirated were malignant, 13 of which were microcarcinomas (92.8%).

Discussion: The TNAPP algorithm is a reliable, easy-to-learn tool that can be readily employed to improve the selection of thyroid nodules requiring cytological characterization. The rate of malignant nodules missed because of inaccurate characterization at baseline by TNAPP was lower compared to the other two algorithms and, in almost all the cases, the tumors were microcarcinomas. TNAPP's use of size >20 mm as an independent determinant for considering or recommending FNA reduced its specificity.

Conclusion: TNAPP performs well compared to AACE/ACE/AME and ACR-TIRADS algorithms. Additional retrospective and, ultimately, prospective studies are needed to confirm and guide the development of future iterations that incorporate different risk stratification systems and targets for diagnosing malignancy while reducing unnecessary FNA procedures.

Keywords: TNAPP; fine-needle aspiration (FNA); retrospective study; thyroid carcinoma; thyroid nodule; web-based algorithm.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Concordance rates between thyroid cytology (SIAPeC-IAP 2014) and histological findings dichotomized as benign or malignant (n = 188).
Figure 2
Figure 2
Histological characterization (binomial) of thyroid nodules according to the AACE/ACE/AME (A) and ACR TI-RADS (B) algorithms. AACE/ACE/AME, American Association of Clinical Endocrinology/American College of Endocrinology/Associazione Medici Endocrinologi; ACR TI-RADS, American College of Radiology Thyroid Imaging Reporting and Data System.
Figure 3
Figure 3
Cumulative concordance rates to perform or avoid FNA between the AACE/ACE/AME and TNAPP (blue) and the ACR TI-RADS and TNAPP (green). Data are illustrated by comparing rates among thyroid nodule diameters with different diameters (n = 188). AACE/ACE/AME, American Association of Clinical Endocrinology/American College of Endocrinology/Associazione Medici Endocrinologi. ACR TI-RADS, American College of Radiology Thyroid Imaging Reporting and Data System.
Figure 4
Figure 4
Distribution of avoidable thyroid biopsies after a retrospective analysis of cytological findings. AACE/ACE/AME, American Association of Clinical Endocrinology/American College of Endocrinology/Associazione Medici Endocrinologi; ACR TI-RADS, American College of Radiology Thyroid Imaging Reporting and Data System; TNAPP, Thyroid Nodule App.
Figure 5
Figure 5
Distribution of thyroid biopsies that would have been performed or avoided regarding thyroid histology after dichotomizing histological results in non-malignant (benign) and malignant. AACE/ACE/AME, American Association of Clinical Endocrinology/American College of Endocrinology/Associazione Medici Endocrinologi; ACR TI-RADS, American College of Radiology Thyroid Imaging Reporting and Data System; TNAPP, Thyroid Nodule App.
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