Development and Internal Validation of a Predictive Model for Individual Cancer Risk Assessment for Thyroid Nodules

Laureano, Florentino Carral San; Alba, Juan Jesús Fernández; Heras, José Manuel Jiménez; Millán, Ana Isabel Jiménez; Fernández-Ladreda, Mariana Tomé; Ortega, María del Carmen Ayala

doi:10.4158/ep-2020-0004

Cited by 5 publications

(3 citation statements)

References 38 publications

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“…Given the limited amount of detailed information, specifically excluding high-risk characteristics, it is not well tailored for an individual patient at high risk for having thyroid cancer. In contradistinction, a calculator from Spain ( 15 ) calls for a substantial amount of specific information, including whether there is a history of autoimmune disease or a family history of thyroid cancer. The Cleveland Clinic calculator ( 16 ), which was among the earliest thyroid nodule risk calculators developed over a decade ago, serves as an example of the evolution of risk estimation.…”

Section: Clinical Calculators For Risk Stratificationsmentioning

confidence: 99%

Computer-interpretable guidelines: electronic tools to enhance the utility of thyroid nodule clinical practice guidelines and risk stratification tools

Garber,

Patkar

2023

Front. Endocrinol.

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Clinicians seeking guidance for evaluating and managing thyroid nodules currently have several resources. The principal ones are narrative clinical guidelines and clinical risk calculators. This paper will review the strengths and weaknesses of both. The paper will introduce a concept of computer interpretable guideline, a novel way of transforming narrative guidelines in to a clinical decision support tool that can provide patient specific recommendations at the point of care. The paper then describes an experience of developing an interactive web based computer interpretable guideline for thyroid nodule management, called Thyroid Nodule Management App (TNAPP). The advantages of this approach and the potential barriers for widespread adaptation are discussed.

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Section: Clinical Calculators For Risk Stratificationsmentioning

confidence: 99%

Computer-interpretable guidelines: electronic tools to enhance the utility of thyroid nodule clinical practice guidelines and risk stratification tools

Garber,

Patkar

2023

Front. Endocrinol.

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“…O protocolo para diagnóstico de nódulos tireoidianos inclui a avaliação clínica do paciente, ultrassonografia (US) e punção aspirativa por agulha fina (PAAF) (Borges et al 2022). Entretanto, mesmo que a PAAF seja considerada o método padrão ouro para a caracterização dos nódulos de tireoide, a técnica é subjetiva, apresentando de 5 a 10% de resultados falsos negativos (San Laureano et al, 2020) e 15 a 30% de resultados indeterminados, fazendo com que na maioria das vezes seja necessária a realização da ressecção do nódulo (Oczko-Wojciechowska et al, 2020;Seneldir et al, 2020;Hejaz et al 2022). Tendo em vista as dificuldades no diagnóstico preciso destes tumores, uma melhor compreensão dos mecanismos moleculares que contribuem para a carcinogênese da tireoide poderá auxiliar na conduta clínica dos pacientes com nódudos citologicamente indeterminados pela PAAF e assim permitir um diagnóstico mais acurado e eficaz (Rodrigues et al, 2019;Xia et al 2021;Chen et al 2022), evitando cirurgias desnecessárias de ressecção, além de auxiliar em novas opções de prognóstico e tratamento dos pacientes (Joo et al 2022).…”

Section: Introductionunclassified

Busca De Marcadores Moleculares Preditivos Do Acometimento De Linfonodos Em Carcinomas Papilíferos De Tireoide

et al. 2022

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O câncer de tireoide é a neoplasia que mais cresce em incidência todos os anos, sendo o carcinoma papilífero de tireoide (CPT) o subtipo mais comum. Em muitos casos estes tumores podem se tornar agressivos, ocasionando metástases linfonodais. A determinação de marcadores moleculares pela análise de expressão gênica é uma importante ferramenta para a determinação do prognóstico destes tumores. Considerando o papel dos genes NEDD9, B3GNT7, PHB, BAD, PAXIP1, PPM1D e PIK3R5 na etiologia de diversos cânceres, este estudo consistiu em verificar pela técnica de RT-qPCR se os mesmos podem ser marcadores moleculares preditivos do acometimento de linfonodos e se estão relacionados ao desenvolvimento destes tumores. No presente estudo não foi observada expressão diferencial significativa dos genes analisados entre os grupos amostrais de CPT versus MCPT (microcarcinomas) e entre os grupos de CPT linfonodo positivo versus CPT linfonodo negativo, indicando que estes genes não estão relacionados ao desenvolvimento tumoral e não podem ser considerados marcadores preditivos de metástases em linfonodos em CPT.

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“…Reportedly, a risk predictive model contributes to make corresponding decisions for treatment and management of patients with thyroid carcinoma by dividing patients into different risk groups [10,11]. Several risk models have been established for thyroid carcinoma [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Development of a Risk Predictive Model for Evaluating Immune Infiltration Status in Invasive Thyroid Carcinoma

Pang

Qin

2022

Evidence-Based Complementary and Alternative Medicine

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Aims. This study aimed to reveal the molecular characteristics and potential biomarker of immune-activated and immunosuppressive invasive thyroid carcinoma. Methods. Expression and clinical data for invasive thyroid carcinoma were obtained from the TCGA database. Tumor samples were divided into immune-activated or immunosuppressive groups based on the immune enrichment score calculated by ssGSEA. Differentially expressed genes (DEGs) between tumor vs. normal groups or between immune-activated vs. immunosuppressive groups were screened, followed by functional enrichment. Immune infiltration was evaluated using the ESTIMATE, CIBERSORTx, and EPIC algorithms, respectively. A random forest algorithm and Lasso cox analysis were used to identify gene signatures for risk model construction. Results. Totally 1171 DEGs were screened between tumor vs. normal groups, and multiple tumorigenesis-associated pathways were significantly activated in invasive thyroid carcinoma. Compared to immune-activated samples, immunosuppressive samples showed higher tumor purity, lower immune/stromal scores, and lower expression of immune markers, as well as lower infiltration abundance of CD4+ T cells and CD8+ T cells. A risk model based on a 12-immune signature (CCR7, CD1B, CD86, CSF2RB, HCK, HLA-DQA1, LTA, LTB, LYZ, NOD2, TNFRSF9, and TNFSF11) was developed to evaluate the immune infiltration status (AUC = 0.998; AUC of 0.958 and 0.979 in the two external validation datasets), which showed a higher clinical benefit and high accuracy. Immune-activated samples presented lower IC50 value for bortezomib, MG.132, staurosporine, and AZD8055, indicating sensitivity to these drugs. Conclusion. A 12-gene-based immune signature was developed to predict the immune infiltration status for invasive thyroid carcinoma patients and then to identify the subsets of invasive thyroid carcinoma patients who might benefit from immunotherapy.

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Development and Internal Validation of a Predictive Model for Individual Cancer Risk Assessment for Thyroid Nodules

Cited by 5 publications

References 38 publications

Computer-interpretable guidelines: electronic tools to enhance the utility of thyroid nodule clinical practice guidelines and risk stratification tools

Computer-interpretable guidelines: electronic tools to enhance the utility of thyroid nodule clinical practice guidelines and risk stratification tools

Busca De Marcadores Moleculares Preditivos Do Acometimento De Linfonodos Em Carcinomas Papilíferos De Tireoide

Development of a Risk Predictive Model for Evaluating Immune Infiltration Status in Invasive Thyroid Carcinoma

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