Solis Pazmino Paola, Pilatuna Eduardo, Ron Mario, Ledesma Tannya, Alvarado Benjamin, Rojas Tatiana, Pazmino Camila, Tite Belen, Figueroa Luis, Lincango Eddy, Hernandez Victor, Salazar Jorge, Garcia Cristhian, Rosero Daniela, Guerrero Jose, Ruilova Lisbeth, Imaicela Luis, Abad Hamilton, Paz-Ibarra Jose, Gonzalez Camilo, Palacios Antonio, Zanella Virgilio, Nasseri Yosef, Cohen Jason, Soto-Becerra Percy, Brito Juan P, Ponce-Ponte Oscar J
CaTaLiNA- Cancer de Tiroides en Latino América, Quito, Ecuador
Surgery Group Los Angeles, Los Angeles, California, USA.
BMJ Open. 2025 Jun 22;15(6):e093471. doi: 10.1136/bmjopen-2024-093471.
Differentiated thyroid cancer (DTC) is the most common endocrine malignancy, with a high 5-year survival rate of approximately 98%. Despite advances in diagnosis and treatment, up to 20% of patients experience recurrence, adversely affecting their quality of life. Predictive models have been developed to assess recurrence risk and guide clinical decision-making, but these models often face limitations such as retrospective design, lack of diversity in study populations and absence of external validation. The primary aim is to externally validate existing predictive models for DTC recurrence using prospective data from a diverse Latin American cohort. The secondary aim is to explore opportunities for model recalibration to improve their performance in our population.
The CaTaLiNA study is a multicentre prospective observational study conducted across 10 hospitals in five Latin American countries, including Ecuador, Peru, Uruguay and Mexico. Patients aged 18 years or older receiving treatment for DTC, such as the first thyroid surgery, active surveillance or radiofrequency ablation will be included. Recruitment will occur from November 2023 to June 2025, with follow-up extending until June 2028. Data collection will include baseline clinical, surgical and histological characteristics, treatment details and follow-up outcomes. Statistical analysis will follow the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis guidelines, using imputation strategies for missing data and evaluating calibration and discrimination of the prediction models. Calibration measures include the ratio of expected and observed events, calibration slope and calibration plot, while discrimination will be assessed using the C-index and area under the receiver operating characteristic curve.
This study protocol was approved by Comité de Ética de Investigación en Seres Humanos de la Universidad San Francisco de Quito USFQ 'CEISH-USFQ' APO-010-2023-CEIHS-USFQ Oficio No. 161-2023-CA-23030M-CEISH-USFQ. Results will be disseminated via peer-reviewed publications.
分化型甲状腺癌(DTC)是最常见的内分泌恶性肿瘤,5年生存率高达约98%。尽管在诊断和治疗方面取得了进展,但仍有高达20%的患者会复发,这对他们的生活质量产生不利影响。已经开发了预测模型来评估复发风险并指导临床决策,但这些模型往往面临局限性,如回顾性设计、研究人群缺乏多样性以及缺乏外部验证。主要目的是使用来自拉丁美洲不同队列的前瞻性数据对现有的DTC复发预测模型进行外部验证。次要目的是探索模型重新校准的机会,以提高其在我们人群中的性能。
CaTaLiNA研究是一项多中心前瞻性观察性研究,在包括厄瓜多尔、秘鲁、乌拉圭和墨西哥在内的五个拉丁美洲国家的10家医院进行。年龄在18岁及以上接受DTC治疗(如首次甲状腺手术、主动监测或射频消融)的患者将被纳入。招募将于2023年11月至2025年6月进行,随访期延长至2028年6月。数据收集将包括基线临床、手术和组织学特征、治疗细节以及随访结果。统计分析将遵循个体预后或诊断多变量预测模型的透明报告指南,使用缺失数据的插补策略,并评估预测模型的校准和区分度。校准指标包括预期事件与观察事件的比率、校准斜率和校准图,而区分度将使用C指数和受试者工作特征曲线下面积进行评估。
本研究方案已获得基多圣弗朗西斯科大学人类研究伦理委员会“CEISH-USFQ”APO-010-2023-CEIHS-USFQ第161-2023-CA-23030M-CEISH-USFQ号办公室的批准。研究结果将通过同行评审出版物进行传播。