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Correspondence to Author:  Luis Eduardo Ramírez Bejarano, María del Mar Meza Cabrera, Ana Milena Callejas, Carlos Andrés Carvajal, Edgar Alberto Sánchez Morales, Alfredo Saavedra Rodríguez., 

Luis Eduardo Ramírez Bejarano: Department of Pulmonology. San José University Hospital. Colombia. Popayán. Correo electrónico: luramirezb@unal.edu.co ORCID: 0000-0002-5945-5419
María del Mar Meza Cabrera: Department of chest surgery. Western Clinic. Colombia. Cali. Correo electrónico: mariadelmar1020@gmail.com ORCID: 0000-0001-8273-6529
Ana Milena Callejas: Department of Pulmonology. National Cancer Institute. Colombia. Bogota. Correo electrónico: amcallejasg@unal.edu.co ORCID: 0000-0001-7917-0616
Carlos Andrés Carvajal: Department of chest surgery. National Cancer Institute. Colombia. Bogota. Correo electrónico: ccarvajalmd@gmail.com ORCID: 0000-0001-5915-0052
Edgar Alberto Sánchez Morales: Department of Pulmonology. National University Hospital of Colombia Correo electrónico: easanchezm@unal.edu.co ORCID: 0000-0002-5518-8149
Alfredo Saavedra Rodríguez: Department of Pulmonology. National Cancer Institute. Colombia. Bogota. Correo electrónico: asaavedrar@unal.edu.co ORCID: 0000-0002-4292-803X

Abstract:

Introduction: Pulmonary nodules are a common finding in chest imaging; their evaluation rules out malignant etiology to determine further management, which may include clinical follow-up, imaging studies, or biopsy. There are multiple scales to predict malignancy, most of which were developed in patients with incidental pulmonary nodules without a cancer history, so their application in such patients has not been discussed. The objective was to evaluate 5 malignancy prediction scales in patients with a cancer history.
Materials and Methods: A cross-sectional analytical study of diagnostic tests was conducted. Data were collected retrospectively from all patients with a cancer history who underwent resection of one or more pulmonary nodules between 2012 and 2022 at the National Institute of Cancerology. Clinical history data were collected and entered into the RedCAP platform, with data reviewed by the National Institute of Cancerology’s defined oversight. Statistical analyses were performed using R software.
Results: Of the 180 patients included in the study, 61.1% were women, the average age was 56 years, and the most frequent cancer history was soft tissue sarcoma, accounting for 34.4%. In terms of etiology, 123 were malignant (68.4%), with the most common histopathological finding being metastases (57%) and 11.1% being primary lung adenocarcinoma.
Conclusion: Logistic regression analysis for calculating adjusted and unadjusted odds ratios demonstrated that the Bayesian model had the best performance in ruling out malignancy with a negative likelihood ratio (LR-) of 0.18 (p = 0.025). The nodule characteristics most correlated with malignancy were a size greater than 8 mm (OR 2.64) and the presence of more than 2 nodules (OR 2.191).

Citation:

Dr.Luis Eduardo Ramirez Bejarano. Predictive Capacity For Malignancy Of The Scales For Evaluation Of Pulmonary Nodules In Oncological Patients At The National Institute Of Cancerology Between 2012 – 2022. The Clinical Lung Cancer 2024.